• 12.3 billion ACH (Automated Clearing House) payments worth approximately $24 trillion. FedACH is a nationwide system, developed and operated by Minneapolis staff on behalf of the entire Federal Reserve System, which provides the electronic exchange of debits and credits.
• $10.8 billion of currency deposits from financial institutions, destroyed $2.8 billion of worn and torn currency and shipped $12.6 billion of currency to financial institutions.
• 178,000 transactions for the 56 million investors who hold $177 billion in U.S. Savings Bonds and answered 577,000 calls and written inquiries from investors as the Treasury Retail Securities site for the Federal Reserve System.
• 250,000 customer support calls handled and 26,000 credentials issued for Federal Reserve payment and information services as one of two national Customer Contact Centers.
• 312,500 calls answered and 324,600 tickets created by the National Service Desk; Minneapolis is one of two sites that provide front line IT support for the Federal Reserve System.

The Bank has consistently achieved outstanding operating results, and 2012 was no exception. We managed our expenses effectively, maintained a strong internal control environment and met most operating metrics. The accompanying “2012 by the Numbers” highlights the scope of some of the Bank’s operations and the importance of excellence in conducting our operations. In a variety of areas, such as the FedACH, the Customer Contact Center and the National Service Desk, we have operational responsibilities that support the System more broadly. In a similar vein, as the Federal Reserve Treasury Retail Securities site, we support the Bureau of the Public Debt’s retail program by servicing electronic and paper U.S. Savings Bonds, and Treasury marketable securities. Managing these consolidated operational responsibilities requires effective coordination and collaboration with stakeholders beyond our Bank.

Technological change creates opportunities for greater efficiency, and the System continues to refine, reorganize and consolidate its operations to take full advantage of these opportunities. We are engaged in several multiyear IT initiatives, including the consolidation of our server and network infrastructure, the upgrade of our desktop computers and the strengthening of our information security infrastructure. Change also continues in the Bank’s FedACH and Treasury Retail Securities operations as a result of technology advances, marketplace dynamics and evolving business plans.

For the System’s supervision and regulation area, assuming expanded responsibility pursuant to the Dodd-Frank Act as systemic risk regulator, supervisor of thrift holding companies and supervisor of systemically important financial market utilities has required significant additional resources. Evolving regulatory and supervisory frameworks require increased emphasis on the analysis and review of financial organizations’ risk profiles. In this regard, the Bank has engaged in a multiyear initiative to strengthen the analytical and technical skills of staff in order to address these new demands.

The Bank’s Office of Minority and Women Inclusion established under Section 342 of the Dodd-Frank Act continues its work to ensure equal opportunity and racial, ethnic and gender diversity in our workforce and senior management, and the participation of minority- and women-owned businesses in our procurement activities. These efforts reinforce the Bank’s long-standing and ongoing commitment to diversity and inclusion in our workforce and suppliers.

Another area of ongoing emphasis is the Bank’s outreach efforts. We continue to work with communities, nonprofit organizations, lenders, educators and others in the district and across the nation to encourage financial and economic literacy, address housing problems, promote equal access to credit and advance economic and community development. In 2012, we expanded our outreach activities in the district; at the national level, one particularly notable event was the Indian Country Summit held in Washington, D.C.

In 2012, we expanded our contributions at the System level to policy discussions in a variety of areas, including monetary policy, supervision and regulation, and financial services. We also assumed a new responsibility as the System’s Enterprise Content Management Support Office and will implement technology that will enable System users to better capture, store, preserve and deliver content and documents.

Looking forward, the System and the Bank will be commemorating 100 years of service with the signing of the Federal Reserve Act in December 1913 and the chartering of Reserve Banks in 1914. As we look to the future, our employees’ unwavering commitment to our core values will allow us to successfully address challenges and achieve the System’s mission to foster the stability, integrity and efficiency of the nation’s monetary, financial and payments systems.

James M. Lyon
First Vice President

[PDF, off-site via Board of Governors]

November Interview

Current Monetary Stance

Clement: Perhaps we could start with your current view on how the Fed should be setting its monetary policy.

Kocherlakota: In thinking about that question, bear in mind that two goals have been assigned to us by Congress when we—and by “we,” I mean members of the Federal Open Market Committee—make monetary policy. One is to promote price stability, and the other is to promote maximum employment. And we face limitations on what our tools can accomplish. Monetary policy impacts the economy with a lag of one to two years. So we’re aiming to achieve those goals over a one- to two-year time frame.

Now, what does this mean quantitatively? Well, the Fed has a target of 2 percent inflation over the longer run. And right now most FOMC participants are forecasting that personal consumption expenditure inflation, which is the Fed’s preferred measure of inflation, will run at or below 2 percent over the next year or two.¹ Over that same time frame, unemployment is predicted to be elevated relative to where it’s going to be in the long run, again, based on our FOMC participants forecast.

So, right now we have inflation forecast at or below our 2 percent target over the next year or two and unemployment high relative to where we want to be in the longer run, expect it to be in the longer run.

By providing more monetary stimulus, the FOMC can facilitate a faster transition of unemployment to its long-run lower level while keeping inflation close to target. I think there’s a question of how we can do that. And that’s what the proposal that I made in Ironwood [Michigan, in September 2012] is designed to accomplish.²

Clement: Could you restate the liftoff plan you proposed in Ironwood?

Kocherlakota: Sure. The liftoff plan is to sustain low interest rates—that is, we’ll keep the fed funds rate extraordinarily low—at least until unemployment falls below 5 1/2 percent, as long as the medium-term outlook for inflation remains within a quarter of a percentage point of 2 percent, the long-run target. “Medium term” meaning—I’m very precise on this in the speech—but it basically means a two-years-ahead outlook for inflation.

Clement: Those are the numerical thresholds.

Kocherlakota: Those are the thresholds. Generally, people would be thinking about the thresholds of 2 1/4 percent and 5 1/2 percent. And these are thresholds in that you’re committing to keeping interest rates low as long as you remain within those zones.

After hitting one of the thresholds, you’re not making any commitment about what’s going to happen. There’s going to be a policy conversation. I would say it’s a return to business as usual, frankly. It’s the point at which we’d have a serious discussion about the trade-offs we face, et cetera.

But in that zone defined by the thresholds, you keep interest rates low.

Clement: Why have you provided explicit economic conditions, you call them “thresholds,” rather than the calendar dates the Fed has relied on more traditionally?

Kocherlakota: Well “traditionally”...[laughter]. Boy, things become traditions very rapidly.³

But, joking aside, that’s a good question: What was the benefit of this proposal as opposed to saying “the FOMC will keep interest rates low until, say, mid-2016.” Right now the Committee is saying mid-2015.⁴ Let’s say we extend it to mid-2016.

Well, I think that change in the date would be confusing. And the reason it’s confusing is that people don’t know if the FOMC changed the date because it thinks conditions are worse, or because the FOMC is simply providing more accommodation given the same conditions.

Clement: So it’s ambiguous about the state of the economy.

Kocherlakota: It’s ambiguous about the state of the economy, exactly. If people think it’s because we have information about the state of the economy that they don’t have, and we convey to them that that information tells us the economy is going to be bad, then this will not necessarily be a stimulative policy; it could actually be the opposite of that.

The other thing is that we’re making no commitments. Whenever we use a date, we’re very careful to say it’s not a commitment. We said this is what we anticipate will be true. That gives rise to a lot of ambiguity and speculation about “the Fed might raise rates before 2016, maybe raise the rates after that.” We’re not really conveying much information. These thresholds, on the other hand, I think deliver exactly the kind of information we want to provide. That is, they set forth the conditions we will need to see before we would even begin to consider raising rates.

Choosing Threshold Numbers

Clement: Can we talk about the numbers themselves, especially the inflation figure? Your liftoff plan raises the possibility of exceeding the Fed’s long-term inflation target of 2 percent that was made very explicit quite recently. And you say, “Perhaps we can raise inflation a bit higher than that.” I think that raises a concern about how seriously the public should take targets that the FOMC sets.

Kocherlakota: I think this is a great question. The FOMC, the way it states the target in its long-run goals and strategy statement is that over the longer run, inflation should be at 2 percent. It then also says it’s going to follow a balanced approach to the two mandate objectives of maximum employment and price stability.

What does this mean? Let’s suppose we didn’t have a maximum employment mandate. We only had the price stability mandate. That would indicate that we should try to keep inflation close to 2 percent. But if you look around the world at inflation-targeting banks, they are often willing to allow for small deviations, over the medium term, between where inflation goes and their longer-run inflation target.

Why is that? It’s because they don’t want to cause undue damage to the real economy by tightening too much or by providing too much accommodation if they’re trying to get the rate of inflation up. That by itself would argue for some deviation. That is, even if you just had a single mandate, you might well be thinking about the real economy in trying to set monetary policy.

Now, obviously, the existence of the second mandate pushes even more toward allowing for some deviation. Having a balanced approach to the two mandates means that you should be willing to allow inflation to be above its 2 percent target in order to facilitate a faster transition of unemployment back to its lower, more desirable longer-run levels.

Clement: Why not bring it up to 3 percent if that will bring unemployment down more quickly? Why did you decide on a quarter percentage point above 2 percent?

Kocherlakota: I set it at a quarter percentage point because, actually, given how high unemployment is, I think it’s unlikely we could ever get the medium-term inflation outlook to be as high as 2 1/4 percent, frankly.

We have our long-run goal of 2 percent, and if we have as much slack as we do in the economy that’s pushing downward on wages relative to where people think they’re going to be in the longer run, it’s hard for that inflation outlook to get up to 2 1/4 percent. We could say 3 percent, but I don’t think we’d get to 3 percent. So, I think 2 1/4 percent is allowing as much leeway as we really need.

Clement: What about the second figure, for the rate of unemployment? The liftoff plan specifies a threshold of 5 1/2 percent. How did you arrive at that figure?

Kocherlakota: So that number...I think I got the reaction to that number I wanted to have. People were shocked at the idea that the Fed would keep rates low for that long. That’s exactly the reaction I wanted to have. I wanted to surprise people with that number because if you want a policy to be truly stimulative relative to the current policy stance, to be actually helpful, you have to be surprising people with what you were saying on that dimension.

I think there is a question about why not a lower number than 5 1/2 percent. The answer to that is, then I did start to worry about the tensions with the 2 1/4 percent. Over a longer time horizon, you have to start to think about whether the Committee would be willing to have the inflation outlook go even higher than 2 1/4 percent to get unemployment even lower than 5 1/2 percent.

Given the Committee’s thinking, typically, about how it views its longer-run objectives, the 2 1/4 percent/5 1/2 percent numbers were consistent with how I thought the Committee would behave in the future, basically. And you don’t want to lay out something that seems implausible for the Committee to deliver on.

Thresholds, Not Triggers

Clement: You said that these are “thresholds,” not “triggers.” Would you explain that distinction?

Kocherlakota: If I said 5 1/2 percent was an unemployment “trigger,” I’d mean that we would automatically raise the fed funds rate as soon as the unemployment rate fell below 5 1/2 percent. Similarly, if I said 2 1/4 percent was an inflation “trigger,” I’d mean that we would automatically raise the fed funds rate as soon as the inflation outlook rose above 2 1/4 percent.

By using the term “threshold,” I’m trying to communicate that the policy commitment is one-sided. The public does have a guarantee that we won’t raise interest rates until the unemployment rate falls below 5 1/2 percent, as long as the medium-term inflation outlook stays below 2 1/4 percent. But we have not said we will necessarily raise the fed funds rate when those conditions aren’t met. We’ve only said that we will have a serious policy conversation about raising the fed funds rate at that point.

Clement: I guess that leads to a follow-up question. In your Ironwood speech, you also said that if a threshold is reached, the FOMC would have a “delicate cost-benefit calculation to make.” And that conversation would be a “challenging one.”

Kocherlakota: Well, we hope not; if the world is good to us, no. But I think you can imagine circumstances in which it would be. I’ll talk about the unemployment threshold, for example. Suppose unemployment fell below 5.5 percent to 5.3 or 5.2 percent, while your outlook for inflation is still at 1.6 percent. Certainly, we’ve had shocks to the economy, changes in the economy, where that configuration doesn’t seem impossible.

Would you necessarily raise the fed funds rate at that stage? I wouldn’t see a need for it myself. Others might have a different view. I think, then, that’s the sense in which you’d want to have a dialogue about how exactly you want to balance the two mandates against each other.

I think my vision, Doug, was that as long as we’re in this zone defined by the two thresholds, I didn’t really see a tension between the two mandates. I think being a quarter percentage point above 2 percent—that’s within range of the target even if I were just thinking about that mandate by itself. And unemployment being anywhere above 5 1/2 percent I thought about as being too high. So neither mandate was forcing me to raise interest rates in that zone. Once I got out of that zone being defined by the two thresholds, then I think it’s less clear how the Committee would reach its decisions. You’d have to start to think about how you’re weighing the two mandates against each other.

Are Objectives Complements or Trade-Offs?

Clement: In past speeches, you’ve referred to each objective in the dual mandate as complementary to the other. But here you talk about the potential for tension between them, a trade-off, like the Phillips curve. How do you reconcile that seeming discrepancy? Are the objectives complementary or alternatives, trade-offs?

Kocherlakota: I think that it depends on the nature of the shocks that hit the economy. The FOMC has said that it typically sees the two mandates as being complementary.⁵ That’s because it sees most shocks to the economy as being shocks to the demand for goods and services, not the supply of goods and services. Downward shocks to demand lead to downward pressures in both employment and prices. To keep inflation close to target after such a shock, you’d need to ease monetary policy. But by doing so, you’d automatically be mitigating the adverse consequences of the shock for employment. It’s in this sense that the two mandates are typically complementary. And that is exactly why I would suggest that right now we do not have a tension between the two mandates.

Perception that Your Views Have Dramatically Shifted

Clement: We’ve talked a lot about your Ironwood proposal. Let me ask you about public reaction to your position. People were surprised, a bit shocked really, in the sense that you seemed to have changed your view quite significantly, and fairly quickly. In speeches as recent as April 2012, and in various interviews, you had strongly advocated a position of tighter monetary policy. But in Ironwood, your view had changed to a position of easing policy, providing more monetary accommodation.

Did that public reaction surprise you? And I guess more importantly, how do you respond to that perception that your view had shifted significantly?

Kocherlakota: In some ways, yes, I was surprised.

I was surprised by the reaction in the sense that I felt I was putting a lot of weight on the price stability mandate by suggesting that even an inflation outlook—medium-term outlook, two-year outlook—that is a quarter percentage point higher than 2 percent should be viewed as a cause for concern. I’m not saying we’re going to raise rates at that point, just to be clear. But I’m saying it’s a time to consider raising rates.

I felt that I was actually being highly respectful of the price stability mandate, and properly so. With that said, I think it is true that to suggest that unemployment could get as low as 5 1/2 percent without pushing inflation above 2 1/4 percent, that was a change in my thinking relative to where I was in April. That change in my thinking came just because of the data on inflation and reading a ton of work that had been done on the factors generating high unemployment.

Evolution of Views

Clement: Why don’t we move to that process, then, and discuss how and why your views evolved from 2011.

Kocherlakota: Sure. In its January 2012 long-run goals and strategy statement, the FOMC said that its goal over the longer run is to maintain 2 percent inflation.⁶ In the beginning of this year, I was concerned that the stance of monetary policy was sufficiently accommodative that it would push us noticeably above that over the next year or two. A lot of that thinking was driven by what I saw in the labor market and my concerns about structural impediments to decreases in unemployment, to the (pre-crisis) levels of, say, 2007.

Clement: What do you mean by “structural impediments”?

Kocherlakota: That’s a good question. I think one aspect of it has been the issue of whether or not the kinds of workers are available that firms want to hire. So “job mismatch,” as it’s called—that’s one aspect of it.

Another aspect, though, is that firms will cut back on hiring if they are very worried about increases in the future costs of workers—increases that could be driven by future taxation or future regulation. Trying to mitigate that kind of fall in employment using monetary policy will lead to inflation.

Clement: Monetary policy can’t have an impact on structural impediments?

Kocherlakota: It’s that the trade-offs between inflation and unemployment become ones that are much less desirable. It would take a lot bigger increase in inflation to generate a desired fall in unemployment.

Clement: What changed your perception of the importance of structural unemployment?

Kocherlakota: I gave a speech about structural unemployment in August 2010 in which I pointed to the shift in the “Beveridge curve.”⁷ This is a plot of unemployment and vacancies over time. It has shifted outward, meaning that, roughly speaking, it looks like firms are having a surprisingly hard time filling their job openings given how many people are looking for jobs. There are other interpretations of this, though, as there always are in economics. So, I laid out my concerns about that shift in August 2010. That shift is still there in the data.

But what’s changed since August 2010 is that there’s been a lot of research trying to parse out what is responsible for this shift. That work goes through a number of factors. It’s summarized in a paper that Professor Edward Lazear gave at the Kansas City Fed’s Jackson Hole Conference earlier this year [2012].⁸ As a Fed president, I was already aware of a lot of that work because much of it has been done within the [Federal Reserve] System.

What this work usually does is look, factor by factor, at how much unemployment is caused by each structural factor. Generally, the answer is not a lot. You can get to maybe a percentage point, or point and a half, of the increase in unemployment since 2007, due to structural factors, something like that.

Those studies were very important in shaping my thinking. Another thing that happened was that inflation over the course of 2012 came in considerably lower than I had anticipated. Both of those things mattered in shaping how I thought about inflation going forward.

I should be clear—it’s not that I used to think structural factors were the sole source of elevated unemployment, and now I think they don’t matter. It’s more nuanced—the evolution of the data has led me to put less weight on structural factors than I did earlier in 2012.

Changing and Conflicting FOMC Views

Clement: You’ve clearly changed your view over time. Other Fed leaders have as well. This past Friday [Nov. 13, 2012], and earlier, different Fed presidents and FOMC participants were changing and clarifying their positions. Several of them voiced support for thresholds. Others are strongly opposed to thresholds and/or greater quantitative easing.

Does FOMC credibility suffer when its members shift their positions or when there’s public discord among them? And does it raise concerns, do you think, that policy won’t be consistent over time, which in itself can undermine policy effectiveness?

Kocherlakota: I think that there’s no problem as long as participants are clear about how their policy recommendations/choices will allow the FOMC to achieve its desired outcomes, and that we all have a collective understanding of what those desired outcomes are.

It’s true that different participants may have different views about the level of structural employment, for example. That’s why you have 19 people in a meeting room—to bring those different visions to bear.

But the essence of what ensures credibility and consistency is that we’re all working together, on the same page, to achieve those objectives of keeping inflation at 2 percent and promoting maximum employment. If everyone’s working toward that, then I don’t think there’s any reason for the public to worry about inconsistency.

Clement: But conflicting participants’ public statements from one FOMC meeting to the next—is that a concern?

Kocherlakota: Again, I’d say that there’s no problem if some participants stand up and say, “I think inflation’s going to run up above 2 percent if we keep on this same path, and we should be scaling back on monetary accommodation,” or others say, “Boy, I think inflation’s going to be running at 1 percent; we have to be adding accommodation.” Or they’re talking about the employment mandate in the same way. This is showing that we all have the same objectives. We’re all working toward the same goals.

There would be a problem if we were trying to achieve different goals than the ones we’ve stated as our long-run objectives. But it could well be that we’re led to different views about how to achieve those goals, because we have different views about what factors are affecting the economy. And that’s life. I mean, that’s why we have 19 people at the table. But those 19 people should be on the same page about what we’re trying to achieve as a committee.

Risks to State-Contingent Thresholds?

Clement: Obviously, one of the concerns about greater monetary accommodation is possibly fueling inflation. I gather you don’t agree with that concern.

Are there other possible risks to state-contingent forward guidance? And maybe we should talk about that term “forward guidance” later.

Kocherlakota: I have a great set of policy advisers here in Minneapolis, and we’ve talked a lot about the potential costs of a state-contingent forward guidance policy. It’s very hard for us to come up with anything, given that you’re laying out inflation protections and unemployment thresholds—you protect yourself on both sides. It’s been hard for us to come up with anything on that dimension.

Now, I guess people wonder about the effectiveness of laying out forward guidance along these lines. Will it help stimulate the economy? And I think the Fed is always engaged in forward guidance. Suppose for example...

Explaining Forward Guidance

Clement: Let me step back a bit.

Kocherlakota: Sure.

Clement: This is really about explaining the term “forward guidance.” The last slide of your Ironwood speech says: “The Fed should clearly communicate its intention to pursue policies that are fully supportive of much higher levels of economic activity.” Would such a statement be considered “forward guidance”—a very deliberate strategy to manage public expectations about future policy? How would you explain “forward guidance”?

Kocherlakota: I think forward guidance is an attempt to use words today to describe what your actions are likely to be in the future.

Clement: And how does that, in and of itself, stimulate the economy?

Kocherlakota: Let me give an example, and just for the sake of simplicity, I’ll use a trigger statement rather than a threshold statement—not “we’ll consider taking a certain action,” but rather “we will pull the trigger.”

One possibility is to say to the public, “We’re going to raise rates above their current extraordinarily low level as soon as unemployment gets to 7 percent.”

The other possibility is to say, “We’re going to raise rates when unemployment hits 5 1/2 percent.”

Those are the two possibilities. The first plan for interest rates tells the public that the FOMC is going to start to choke economic activity as soon as unemployment hits 7 percent. After all, that’s the whole point of raising rates—to dampen down economic activity. The other possibility is that they’ll wait to an unemployment rate of 5 1/2 percent before beginning to dampen down economic activity.

Upon hearing those two different plans for interest rates, people should have different expectations for what the paths of economic activity and unemployment are going to be. And, in particular, between the 7 percent plan and the 5 1/2 percent plan, the second suggests that times are going to be better for them in general, going forward. It means that individuals don’t need to save as much for bad times ahead. That’s the basic point of providing such forward guidance, to convey the expectation that because times will be better in the future, individuals don’t need to save as much and therefore can spend more now.

Clement: That’s what stimulates economic activity.

Kocherlakota: That’s what stimulates economic activity. I think it’s really important to understand that we are always engaged in forward guidance. If we were to raise interest rates at the next meeting by 25 basis points, a rise in one-day interest rates by a quarter percentage point, that would have enormous consequences for markets and the way people are thinking about spending, et cetera.

Why is that? Not because they think that quarter-percentage-point move really has any impact on their decision-making right now. It’s because it tells them something about what we’re going to do in the future. It’s the path of what they think is going to happen based on that.

We were always engaged in forward guidance, using our interest rate moves combined with our words. Now we’re using words alone. That’s the only difference.

Support for Forward Guidance

Clement: So, you’ve long supported the idea of forward guidance, simply as inherent to monetary policy.

Kocherlakota: Yes.

Clement: But now you’re changing your view about the type of forward guidance that should be provided—from guidance through words regarding calendar dates to words regarding economic thresholds.

Kocherlakota: I’ve always been sympathetic to the threshold idea since President [Charles] Evans of the Chicago Fed first laid it out in September of 2011.⁹ And I think that any economist would say that the idea of using economic conditionality as a way to express a likely plan of attack in the future is preferable to using calendar dates.

But I would say two things about President Evans’ plan. I didn’t necessarily like his numbers, and so I’ve come to my own choice of what I think the numbers should be. And, as I’ve described earlier in our conversation about the evolution of my thinking on the stance of policy overall, I now see a need for stimulus that I did not see in September 2011.

Quantitative Easing

Clement: You mentioned quantitative easing earlier. How effective has it been, and is forward guidance an alternative to QE or do they work in concert? What’s the nature of that relationship?

Kocherlakota: In a speech at Jackson Hole this past August, Chairman [Ben] Bernanke provided an excellent assessment of the effectiveness of quantitative easing.¹⁰ I think what you take away from his remarks is that, directionally, quantitative easing has the impact of pushing down on longer-term interest rates. And that should be directionally stimulative to the economy because by pushing down on market interest rates, people are led to think, “Hmm, maybe I shouldn’t be buying those assets that are paying such a low yield. I should spend money instead.”

With that said, these impacts are very complicated compared to forward guidance. Forward guidance is a much more typical way for us to do monetary policy. It’s basically telling the public about the path of future short-term interest rates. How we’re able to influence longer-term interest rates using QE—well, it’s actually much more sophisticated to see how that works, in terms of the economic mechanisms involved.

The benchmark thinking about QE, actually, was done by Neil Wallace and later by Gauti Eggertsson and Mike Woodford, following up on Neil’s work.¹¹ And that baseline economic modeling would say these kinds of interventions should have no impact on yields and no impact on the economy at all.

Now, the empirical work that I mentioned has validated that there does seem to be an impact on yields. What that means in terms of the impact on economic activity, I’m still sorting through, to be honest. As of now, I would say that I think quantitative easing works in the right direction, but gauging the actual magnitude of its impact remains challenging.

Really, forward guidance is the more traditional tool for monetary policy, and quantitative easing is more unconventional. But with all that said, they work together very well. In particular, being clear about when we’re likely to start raising rates gives very important information about how long we’re likely to hold any assets we purchase. That’s critical in how effective they’re going to be in terms of stimulating the economy. If we buy assets and hold them for a day, they are not having any impact on the economy. If we buy assets and hold them for three years, yes, they can start to have an impact on the economy.

Other Policy Options

Clement: Other economists have proposed intentional policies to raise the rate of inflation, basically to make spending in the future more expensive and thereby encourage stimulative spending now. Is this idea consistent with a liftoff plan that could raise the potential inflation rate to 2 1/4 percent?

Kocherlakota: As long as unemployment is remaining above 5 1/2 percent, it’s going to be very challenging to actually deliver on the rates of inflation that some observers have mentioned. You see people talking about 3, 4, 5, 6 percent. If unemployment is above 5 1/2 percent—well, this depends on your view of structural unemployment, of course—but given the FOMC’s forecast that it expects long-run unemployment to fall to between 5 and 6 percent, and that unemployment rate to be consistent with our long-run target of 2 percent inflation, it’s going to be very challenging to generate high inflation, 3 to 4 percent kind of numbers, as long as unemployment stays above 5 1/2 percent.

Basically, given current measures of structural unemployment and long-term inflation expectations, we can’t get a medium-term inflation outlook of 3 percent or 4 percent unless the unemployment rate has fallen noticeably below 5 percent. I don’t think such a monetary policy is believable. In other words, I’m confident that if unemployment starts to get that low, the FOMC would want to tighten to rein in inflation well before the medium-term outlook rose to 3 percent.

Raising Consumption Taxes

Clement: You’ve spoken in past speeches regarding the idea of raising future consumption taxes, a proposal essentially intended to make future spending more costly and thereby encourage current spending.¹² Is that idea, a fiscal policy really, consistent with a liftoff plan idea? And in fact, is there a need to coordinate monetary policy with fiscal policy, assuming there’s a possibility of doing that?

Kocherlakota: I think what we have seen in Japan and in the United States is that when you get to the zero lower bound for interest rates, it’s more challenging for the monetary authority to provide stimulus. Typically, that’s why the interest rate is at zero; we’d like to push it down further and can’t.

That should be a signal to the fiscal authority to be more interventionist in the economy than it would otherwise be. The consumption tax idea that I’ve talked about is certainly not my idea alone. Bob Hall and Susan Woodward have talked about this, and Martin Feldstein has. And there’s the work done here on it by Juan Pablo Nicolini with some co-authors.¹³ That idea seems like an eminently sensible way to stimulate the economy using fiscal policy.

And there are other ideas, too, but my point is mainly that the monetary authority, which I think plays a very useful role in stabilizing the economy typically, when the economy faces the zero lower bound, it doesn’t mean central banks are out of weapons. They do still have tools. But it does mean that they’re not going to be as effective as they typically would be. And I think that should be a signal to the fiscal authority. I don’t know if you want to call that coordination, but I’d like to think they’re watching what we’re doing with interest rates, and they should be helping us out at that point.

What I mean by helping us out is they should be taking steps to enable us—we’re going to have a harder time achieving our congressionally mandated goals of 2 percent inflation and low unemployment. They should be providing policy support of some kind to allow us to better achieve those objectives, which they clearly think of as being important. That’s why they set them out for us.

Out of Policy Tools?

Clement: Some observers noted that when Vice Chair Janet Yellen gave her speech recently in support of thresholds...¹⁴

Kocherlakota: It was an excellent speech.

Clement: It was; it really was... But some economists noted that stock markets barely moved after the speech. And they suggested that that seemed to indicate that perhaps the Fed had no more power, no more “dry powder,” in a sense. As one blogger put it, “If the economy stumbles, will the Fed pull a new trick out of its policy bag, or is that bag finally empty?”

Kocherlakota: I’ll say two things; one I just mentioned. I think that the Fed’s tool kit is not as—we would prefer to reduce interest rates further; I think that would be the most natural way for us to try to stimulate the economy, to achieve our objectives. We would like to lower interest rates further than the zero we’re currently at. With that said, we still do have tools.

Vice Chair Yellen used a threshold of 6 1/2 percent in her speech. I don’t think that the stock market reaction to 6 1/2 percent reveals much about how it would react to 5 1/2 percent.

A Collective Outlook

Clement: One other question occurred to me. In a speech that you gave in Great Falls in October, you said your proposed operational definition of price stability hinges on the Committee’s formulating and communicating a quantitative collective outlook.¹⁵ Do you see that as a possibility?

Kocherlakota: Certainly, conversations continue on that kind of topic. I think Vice Chair Yellen made clear in her speech that that’s something we continue to talk about. I think it would be very valuable for us to formulate a collective vision of how we’re doing. That’s essentially what that would be: a collective vision of how we’re doing in terms of our goals. Does the Committee think inflation is going to be at 2 percent over the next two years? If not, why aren’t they doing something about it? Do they think unemployment is going to be higher than its long-run values over the next two years? If so, why aren’t they doing something about it?

I think having a collective sense of that, in a quantitative way, would lead to more accountability on the part of the FOMC.

December Interview

What Led to FOMC Threshold Adoption?

Clement: Well, a lot has happened since our last conversation.

Kocherlakota: Yes, indeed.

Clement: And first and foremost, at its December 2012 meeting, the FOMC as a whole adopted thresholds for inflation and unemployment. The numbers are different from those you laid out in your Ironwood speech, but the strategy is consistent. Do you view this as a change in policy or as a change in communication, a recasting of forward guidance?

Kocherlakota: I think it is a change in communication. If you go back to the October statement, it said that the FOMC anticipated keeping interest rates extraordinarily low at least through mid-2015. And now, instead, the FOMC has replaced that date with thresholds for unemployment and inflation, saying that it anticipates that it’ll keep interest rates extraordinarily low until unemployment falls below 6 1/2 percent as long as what I’m going to call the medium-term outlook for inflation—one to two years out—that medium-term outlook remains below 2 1/2 percent.

Now, there’s a sense in which that’s an equivalent level of accommodation to the mid-2015 date. It’s equivalent in the sense that right now I would say the Committee roughly expects that we will get to 6 1/2 percent unemployment around mid-2015. The statement has that rough equivalence in it. Going forward, I would anticipate we would drop any reference to dates at all and only maintain this language about the thresholds.¹⁶

Now, the beauty of thresholds, as the Chairman noted in his press conference, is that even when they stay fixed, the level of accommodation, of monetary policy stimulus associated with them, varies with the state of the economy. He used the language “automatic stabilizer,” which I think is very apt.¹⁷

So if things were to worsen for some reason, if conditions were to evolve less favorably than we expect in 2013 or 2014, well, then, it’s going to take longer, and people are going to realize it’s going to take us longer to get to 6 1/2 percent unemployment than we think right now. And that means interest rates are going to stay low for longer.

On the other hand, if conditions evolve more favorably than we expect in 2013, 2014, we’re going to get to 6 1/2 percent unemployment. People will start to learn: We’re going to get to 6 1/2 percent unemployment more rapidly than anticipated. And they’ll learn that interest rates are going to be raised sooner than they had anticipated.

I think that’s the benefit, even though it’s roughly the same level of accommodation right now. You can leave these numbers fixed, and the level of stimulus is varying automatically with the evolution of the economy in a way that we would like.

Clement: So people will be focused on the state of the economy rather than the calendar.

Kocherlakota: Yes. The calendar date relies on the Fed’s forecast, and that’s going to be changing over time. With this new approach, we tell the public how we’re looking at the economy and they form the forecast about when we’re likely to get there. Then that shapes their thinking about our policy. It’s just a very healthy way of communicating. I think it enhances transparency, accountability and effectiveness of policy.

Clement: What led to threshold adoption by the full FOMC? Could you trace the FOMC’s evolution in terms of moving to communicating policy through explicit economic conditions rather than calendar dates?

Kocherlakota: So, in December of 2008, the Committee lowered interest rates to their current level, with the fed funds rate being targeted to a zero to 25 basis point band, about as low as it can go.¹⁸ I believe it was in March of ’09 when the Committee said that it anticipated keeping rates extraordinarily low for an extended period.¹⁹ This is an attempt to provide some guidance to say it’s not just this meeting, it’s not the next meeting, where you might expect interest rates to rise.

In August of 2011, the Committee became more concrete about that, switching from talking about an “extended period” to instead saying that the fed funds rate would stay extraordinarily low at least through mid-2013.²⁰ And then there was some evolution in the date after that.

I would say that there was some unhappiness with the date almost immediately. And, right after that August meeting, President Evans offered a different approach, to formulating in terms of thresholds.²¹ There was a lot of analysis of that approach after he made his suggestion.

Basically, you want to put some thought into it that it’s going to work the way you want it to. The way you can do that is through model-based analysis, study, et cetera, and that was what was going on over that time frame.

Clement: I think the Chairman noted in his press conference that this was a difficult change to explain, and a press conference allowed an opportunity...

Kocherlakota: Yes, well, we have a press conference every two meetings. I’ve expressed the belief in the past that the FOMC should consider having a press conference after every meeting. Certainly, I think that this kind of change in communication is sufficiently rich and complicated that a press conference is vital.

Are the Numbers Too High?

Clement: The thresholds that were set out by the FOMC are 6 1/2 percent for unemployment and 2 1/2 percent for inflation. Those are somewhat higher than the numbers you mentioned in your Ironwood speech. Are you concerned that the FOMC thresholds are higher than yours?

Kocherlakota: On the inflation front, I suggested an inflation threshold of 2 1/4 percent and the Committee went to 2 1/2 percent. As I suggested in my speech, I saw this conversation about what the appropriate inflation threshold should be as being very much an ongoing one. I would say my thinking was still evolving. I’m comfortable with 2 1/2 percent as the outcome of the Committee discussion. There’s always a give and take in a committee, and we ended up with 2 1/2 percent. So I guess I think that’s an appropriate place to be.

Clement: And unemployment?

Kocherlakota: I’m more concerned about the unemployment threshold. I think that we have left an opportunity out there for improvement by setting it as high as we did. I think the public is left thinking that the Committee could well be planning to retard the pace of economic recovery while the unemployment rate remains noticeably above our long-run estimates.

This dampens current stimulus because people think that times are not going to be as good as they could be if we had more aggressive policy, more stimulative policy, so they’ll believe they have to save now for worse times ahead. That dampens the amount of stimulus we’re going to provide today. So, I would have preferred 5 1/2 percent.

That opportunity is not one that’s foreclosed to us. What I mean by that is, in terms of the inflation threshold, I think it would be very challenging for us to lower that now that we’ve set it where it is. We’ve made a commitment essentially that, barring unusual circumstances, we’re not going to start to raise rates as long as the inflation outlook remains below 2 1/2 percent. If you now lower that to 2 1/4 percent, you change the nature of that commitment.

It’s different with lowering the unemployment threshold. If we were to raise it, we’d face the same problem, but lowering it is perfectly in keeping with what we’ve said so far. I worry that we’ll come to a point where we’re going to want to do this later anyway—that is, lower the unemployment threshold—and we’ll have lost all the stimulus we could have provided in the intervening period by lowering it ahead of time. So I would have preferred us to go to the threshold I mentioned in Ironwood: 5 1/2 percent.

Clement: You spoke before about wanting to shock or surprise the public, in a sense, with the threshold numbers.

Kocherlakota: Yes, yes.

Clement: Would a lower unemployment number have done that?

Kocherlakota: Yes, I believe so. Based on the reaction to my Ironwood talk, I think the answer is yes to that [laughter].

No, more seriously, I think that the equivalence we talked about earlier between our earlier communication of mid-2015 and the 6 1/2 percent unemployment rate meant that while there’s an automatic stabilizer gain that we’ve talked through, there’s no gain really in the anticipated path of stimulus. With 5 1/2 percent, you’d get that gain.

Now, I don’t want to be too negative. I mean I’m very heartened by the switch in our basic communication framework. I think it was the right move. And as I said, I think our communication leaves open the possibility of improving policy by lowering the unemployment threshold. But that is an opportunity for improvement that is out there for the Committee, I think.

“Targets?”

Clement: I’d like to raise a question about confusion of terms. In media reports following the press conference on December 12 and at the press conference itself, the media used the term “target” in relation to what the Chairman clearly referred to as thresholds.

You’ve taken great pains to distinguish “thresholds” from “triggers,” but it seems there’s still confusion as to whether these numbers for inflation and unemployment are “targets,” implying that the Fed is aiming for inflation at 2 1/2 percent and unemployment at 6 1/2 percent, as the word “target” implies. Can you clarify that point?

Kocherlakota: I can try [laughter]. Let me talk first about the inflation threshold. Our long-run objective—our target—for inflation is 2 percent. So what is this 2 1/2 percent about? I view it as a safeguard, a guardrail—protection against what I see as being an unlikely risk of unduly high inflation.

Over the past 15 years, the medium-term outlook for PCE inflation, personal consumption expenditure inflation, has never risen above 2.3 percent. That’s been true even though the unemployment rate actually fell below 5 percent. Even though we had such high resource utilization in the economy that the unemployment rate fell below 5 percent at times during that 15 years, that wasn’t sufficient pressure on prices to drive the medium-term PCE inflation outlook above 2.3 percent.

Given how much slack we have currently, how are we going to get to a medium-term outlook of 2 1/2 percent as long as longer-term inflation expectations stay well anchored? So I just view the inflation threshold as really being a protection. I’m not saying we shouldn’t have it in there. We should always be making policy with an eye toward protecting the economy against unlikely adverse outcomes. But it’s only that—a protection to say our medium-term outlook is never going to get that far out of whack, to the point where people should be starting to worry about our commitment to the 2 percent long-run target, which is really the key thing.

Clement: OK, so, as you said, it’s a “guardrail,” something that you’re not likely to hit, but just in case...

Kocherlakota: Right, just in case.

Now, in terms of the unemployment threshold, I guess I understand the possibility of confusion in the sense that I articulated earlier. I thought it would be better policy to set the unemployment rate threshold lower. If we think the long-run unemployment rate is going to settle down between 5.2 percent and 6 percent, why would we begin to raise rates when the unemployment rate is as high as 6.4 percent so that it’s remaining clearly elevated above our target, the long-run goal for unemployment? Well, “goal” is too strong a term; it’s the place where we think unemployment is going to settle down, long term.

Clement: Right, what the FOMC participants expect will happen.

Kocherlakota: Now, the only reason I can see where we’d want to raise rates is if we’re worried about inflation. That’s why we have the inflation safeguard in there.

So, I understand the possible confusion on the unemployment threshold. I think if you set it at 5 1/2 percent, you won’t have that confusion anymore. I think it’s clearly smack dab in the middle of where the Committee sees the unemployment rate settling down to in the long run.

Initial Public Reaction

Clement: Critics of this new FOMC policy have already suggested that thresholds are going to have too little impact, as evidenced by the fact that the stock markets didn’t move very much after it was announced, long-term Treasuries rose just a bit and I think expected inflation increased only slightly.

Another critic said that if markets have already discounted the impact of monetary easing on unemployment, that’s an indication that “the expectations effect won’t work.” And other critics are concerned that inflation has just been unleashed, that thresholds will do too much in terms of fueling inflationary expectations beyond the control of monetary policy.

What’s your sense of this initial public reaction to the December 12 announcement, which was intended to stimulate economic activity?

Kocherlakota: I think that the behavior of inflation expectations is pretty much in keeping with what I would have anticipated. I think, under current conditions, we have a lot of room to influence economic activity without generating inflation that’s noticeably above 2 percent.

Where does that room come from? It comes from the relationship between resource utilization, unemployment and inflation. As of now, that relationship is relatively flat, meaning that monetary stimulus can achieve desired reductions in the unemployment rate without generating big movements in inflation. This is the Phillips curve, which in some quarters has a bad reputation, but that’s how I think of the relationship that emerges at any given moment in time that’s traced out between resource utilization and inflation.

So I am not surprised by inflation expectations not rising that high. As I pointed out earlier, in the past 15 years, even though unemployment’s fallen below 5 percent, we still did not have an inflation outlook that was noticeably above 2 percent.

Now, there’s talk by many observers that monetary easing can’t lower the unemployment rate. I think that the issue, really, is the opposite. The issue is, does the public think that the Fed can increase the unemployment rate by raising interest rates? I would submit the answer to that is yes. If that’s true, shouldn’t we let the public know that we don’t plan on fostering unemployment through our policy actions until such time as unemployment has normalized?

That’s what I think this policy is about: letting the public know that we’re not going to get in the way of the economic recovery by raising rates, until such time as the recovery is closer to being complete.

Let me say a couple of things about inflation. I think there’s this vision out there—this was one of the reactions to my 5 1/2 percent number in Ironwood—that somehow we have to raise rates before we get to full employment. We have to do it. Otherwise, we’re going to have inflation unleashed.

Clement: “Taking away the punch bowl just when the party [is] really warming up,” as the Fed has been said to do.²²

Kocherlakota: But this is dependent on the set of shocks that are affecting the economy. That’s what shapes the appropriate level of monetary policy: How adverse are the shocks that are hitting the economy? If the shocks are adverse enough, then you might need a lot of monetary stimulus in order to offset them so as to keep inflation at 2 percent instead of falling too low.

Clement: Hoping to keep it as high as 2 percent, avoiding deflation.

Kocherlakota: As high as 2 percent—and to keep unemployment from being too high. If you say you’re always going to be raising rates before you get to full employment, you’re defeating yourself. You’re tying your hands behind your back.

What determines where we should be in terms of monetary policy is that we want to be doing our best to mitigate and offset the shocks that face the economy so as to achieve our objectives: the long-run objective of 2 percent inflation and keeping unemployment low in the face of shocks.

Personally, as somebody who’s been termed an inflation “hawk,” a central banker who worries a lot about inflation, I think thresholds are fantastic news. That’s true for two reasons.

First, suppose the pace of recovery were to quicken over the next few months, and we saw a significant decline in unemployment and significant upticks in inflationary pressures associated with that. That would be the good-news scenario, so to speak. Would the Committee have been willing to move the mid-2015 date in quickly?

I think there would have been a lot of concerns about doing so. I think there would have been a concern in the Committee that we would have unraveled all the accommodation in one fell swoop if we start to move that date in. What would we be communicating? I think it would be very challenging for us.

Now, with thresholds, even if we do nothing, a fall in the unemployment rate, or an increase in inflationary pressures, automatically brings forward that first day of tightening. The automatic nature of policy is beneficial if you’re worried that inflation could be going too high.

The other thing is, I think it’s really good for accountability. I think the Committee has never really clearly marked out a true worry zone for inflation. We haven’t said we’re going to raise rates when the outlook gets above 2 1/2 percent. For example, I’ll say for myself that if unemployment was 11 percent and the outlook for inflation was at 2 1/2 percent, I might not want to raise rates at that stage.

But, with that said, we’ve marked out what is clearly a worry zone. And given the history that I’ve reviewed about the medium-term inflation outlook, it is a worry zone. It’s very different from what we’ve seen in the past.

Future Moves

Clement: You’ve just used the word “automatic” a number of times. That leads me to wonder about future policy moves given that the policy steps taken at the December meeting—the boost in long-term asset purchases as well as more explicit forward guidance—were quite significant.

Do you think the FOMC is likely to make further large changes in policy over the next couple of years, or will it simply be a matter of monitoring economic activity relative to the thresholds? In other words, is monetary policy essentially on autopilot now? In your view, are thresholds “automatic stabilizers,” as the Chairman said at the press conference?

Kocherlakota: I think that the FOMC statement does build a lot of “automaticity,” if that is a word, into monetary policy.

But as I’ve said, I also think that the statement gives us the freedom to do more—for example, by lowering the unemployment threshold.

I really do think this is, I hesitate to use the term “gold standard,” but it’s really leading edge in terms of central bank communication methods right now. I think we should take a lot of pride in that. I’ve certainly been surprised by things in the past, but I don’t see us making changes in our basic communication framework going forward. Nonetheless, I think that communication framework certainly leaves open the possibility of changes in policy.

Consensus Statement?

Clement: Coming back to a question I asked in our first conversation, about a consensus FOMC statement on inflation expectations and unemployment expectations. According to recent statements by some FOMC members, it seems that not all foresee the likelihood of, or see the value in, a consensus statement. Do you still consider it a useful thing?

Kocherlakota: Oh, I think we’re going to have a consensus statement. Let me be clear by what I mean by that though. I think the Chairman answered this question in his press conference. He said specifically that we’re going to have to go through the intellectual exercise. Actually, I have it right here: “In terms of inflation forecasts, what the Committee will do on a regular basis is include in its statement its views of where inflation is likely to be...”

That’s exactly what I had in mind. “For example,” he continued, “currently we already say that, you know, we expect inflation to run at or below the Committee’s objective in the longer term. The intellectual exercise we’ll be doing is asking ourselves, if we maintain low rates along the lines suggested by this policy, would we expect inflation to cross the threshold or reach that—reach that level?”

That’s it. That’s exactly what I had in mind by a consensus outlook: The Committee offers guidance about it, and has to, given the formulation of policy. So, I’m comfortable where we ended up on that, given what the Chairman said.

Note

Endnotes

References

Bernanke, Ben S. 2012. Monetary Policy since the Onset of the Crisis. Speech at the Federal Reserve Bank of Kansas City Economic Policy Symposium, Jackson Hole, Wyo., Aug. 31.

Correia, Isabel, Emmanuel Farhi, Juan Pablo Nicolini and Pedro Teles. 2012. Unconventional Fiscal Policy at the Zero Bound. Working Paper 698. Federal Reserve Bank of Minneapolis.

Eggertsson, Gauti, and Michael Woodford. 2003. The Zero Bound on Interest Rates and Optimal Monetary Policy. Brookings Papers on Economic Activity 34 (1): 139-235.

Evans, Charles. 2011. The Fed’s Dual Mandate Responsibilities and Challenges Facing U.S. Monetary Policy. Speech at the European Economics and Financial Centre, London, Sept. 7.

Feldstein, Martin. 2002. Commentary: Is There a Role for Discretionary Fiscal Policy? Commentary at Rethinking Stabilization Policy, a Symposium Sponsored by the Federal Reserve Bank of Kansas City, Jackson Hole, Wyo., Aug. 29-31.

Kocherlakota, Narayana. 2010a. Inside the FOMC. Speech in Marquette, Mich. Aug. 17.

Kocherlakota, Narayana. 2010b. Monetary Policy Actions and Fiscal Policy Substitutes. Speech at the National Tax Association’s 103rd Annual Conference on Taxation, Chicago, Nov. 18.

Kocherlakota, Narayana. 2012a. Planning for Liftoff. Speech at Gogebic Community College, Ironwood, Mich., Sept. 20.

Kocherlakota, Narayana. 2012b. More Thoughts on a Liftoff Plan. Speech at Annual Helena Branch Board of Directors Meeting and Community Luncheon, Oct. 10.

Lazear, Edward P., and James R. Spletzer. 2012. The United States Labor Market: Status Quo or a New Normal? Paper presented at the Federal Reserve Bank of Kansas City Economic Policy Symposium, Jackson Hole, Wyo.

Wallace, Neil. 1981. A Modigliani-Miller Theorem for Open-Market Operations. American Economic Review 71: 267-74.

Woodward, Susan, and Robert Hall. 2008. Measuring the Effect of Infrastructure Spending on GDP. Financial Crisis and Recession blog, Dec. 11.

Yellen, Janet L. 2012. Revolution and Evolution in Central Bank Communications. Speech at the Haas School of Business, University of California, Berkeley, Berkeley, Calif., Nov. 13.

The first journey is my own. Early in 2012, I suggested in public remarks that the Federal Open Market Committee might need to raise the fed funds rate considerably earlier than it was currently contemplating. Several months later, in September 2012, I gave a speech in Ironwood, Mich., recommending that the FOMC should commit to keeping the fed funds rate extraordinarily low until the unemployment rate fell below 5.5 percent, as long as the medium-term inflation outlook stayed sufficiently close to the Federal Reserve’s long-run 2 percent target and longer-term inflation expectations continued to be well anchored. (My proposal was closely related to one advanced by Charles Evans, president of the Federal Reserve Bank of Chicago, about a year previously.) The annual report provides details about why I favored the Ironwood proposal at the end of 2012, as opposed to my prior recommendations.

The second (and much more important) policy journey is that of the FOMC itself. In its January 2012 policy statement, the FOMC said that it

“...currently anticipates that economic conditions—including low rates of resource utilization and a subdued outlook for inflation over the medium run—are likely to warrant exceptionally low levels for the federal funds rate at least through late 2014.”

With this statement, the Committee gave information to the public about how long it intended to maintain the fed funds rate at extraordinarily low levels. But in its December 2012 policy statement, the FOMC switched to a different kind of communication. Instead of saying how long it expected the fed funds rate to remain low, it described economic conditions that would need to prevail before it would consider raising the fed funds rate. More specifically, the Committee announced that it

“...currently anticipates that this exceptionally low range for the federal funds rate will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent, inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee’s 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored.”

The annual report provides my thoughts about the significance of this change in Committee communications.

The report has a somewhat unusual structure. It consists of edited versions of two distinct interviews with me, conducted by Doug Clement of the Federal Reserve Bank of Minneapolis. The first took place in November 2012, after my Ironwood speech but before the Committee’s change in communications. Consequently, it focuses more on my policy journey. The second interview took place in December 2012, about a week after the Committee’s change in communications. It’s more informative about the other monetary policy journey, the FOMC’s.

But it would be a mistake to draw too sharp a distinction between these two journeys. My Ironwood proposal and the Committee’s new communication strategy have much in common. They both frame communication about the future course of policy in terms of quantitative goals—specific macroeconomic objectives the FOMC is seeking to achieve. I see this results-oriented approach to monetary policy as especially valuable in light of current U.S. macroeconomic conditions. But I believe it will likely continue to be valuable long into the future.

Narayana Kocherlakota
President

In “Financial Frictions and Fluctuations in Volatility,” a Minneapolis Fed staff report published in July, economists Cristina Arellano and Patrick Kehoe of the Minneapolis Fed and Yan Bai of the University of Rochester develop a model that can convincingly generate several central macroeconomic patterns seen in U.S. data during the Great Recession. In particular, the economists explore the financial and microeconomic underpinnings of sharp declines in employment and economic output between 2007 and 2009, accompanied by relatively stable labor productivity. In almost all recessions, productivity and output both decline, but in the most recent downturn, productivity was nearly unchanged. What economic mechanisms account for this anomaly?

One clue that informs their investigation is the severe credit contraction during the recent U.S. financial crisis. Another clue, at the micro level, is the large increase in dispersion of growth rates among firms—that is to say, growth at some companies suffered very little during the crisis, while other firms contracted dramatically. Even during normal times, companies grow at different rates, of course, but during the 2007-09 recession, the range between the highest and lowest growth rates nearly doubled.

These observations are building blocks for a quantitative model with heterogeneous firms (for which growth rates can differ) and financial frictions (meaning that credit markets don’t function smoothly). The economists’ goal is to create a model in which increasing volatility at the firm level leads to higher dispersion in firms’ growth rates along with declines in both aggregate labor and economic output, but stable labor productivity. Their aim, in short, is to better understand the U.S. economy during the recent recession by building a model that can replicate its behavior between 2007 and 2009.

Central to the model: Risk, and firms hedging against it by trimming financial obligations wherever feasible—specifically, by hiring fewer inputs. “They key idea in the model,” write the economists, “is that hiring inputs to produce output is a risky endeavor.”

Firms receive revenue from selling their output only after they have already paid for inputs, such as employees, necessary to produce that output. Hiring labor (or buying materials or purchasing machinery) therefore entails risk, since demand for a firm’s output may fall after the input expenditure is incurred. If financial markets were “complete,” as economists say, firms could protect themselves against that event by borrowing against future profits; but in this model, financial market frictions mean that firms must bear the risk themselves.

“This risk has real consequences if, when firms cannot meet their financial obligations, they must experience a costly default,” observe the economists. “In such an environment, an increase in uncertainty arising from an increase in the volatility of idiosyncratic shocks leads firms to pull back on their hiring of inputs.” (Though the word “hiring” suggests employees only, here it applies to other inputs as well: raw materials, capital equipment and the like.)

If we build it, will it work?

The economists proceed in stages. First, they build a “benchmark” model. Then they calibrate and quantify it to gauge how well it matches real U.S. data. They create two alternatives to their benchmark model to pinpoint whether the results are driven by both factors (imperfect financial markets and volatility shocks) or just one. Lastly, they extend their model with refinements that bring it closer to how economists believe economies truly work.

The model has three key pieces:

1. Firms hire inputs before knowing how much demand they’ll experience for their output.
2. Financial markets don’t necessarily provide firms with credit, and they’re especially averse when the economy is volatile; as a result, firms default if they’re unable to pay their debts.
3. Since firms pay a fixed cost to start their operations, they make positive profits in the future to cover those fixed costs; the cost of default is the loss of future expected profits.

These three essential parts mean that firms trade off expected risk and return whenever they choose their inputs. Hiring more inputs enables them to make more profit as long as they don’t default. But because more hiring raises their financial obligations, it also increases the chance of defaulting. It’s a tough choice, and becomes more so when the broader economy is looking uncertain—or, in the idiom of economics, “when the variance of idiosyncratic shocks increases.”

The model includes identical households, heterogeneous firms and financial intermediaries. Households buy goods produced by firms, but the demand for each good is subject to idiosyncratic demand shocks. The volatility of these demand shocks varies over time, and this is the source of aggregate fluctuations in the model. 

Firms are the guinea pigs in this model. They differ from one another, and they face not only volatile demand for their products, but imperfect or incomplete financial markets that don’t allow them to insure against fluctuations in that demand. Thus, they may sink or swim based in large part on those fluctuations, as well as their hiring decisions. If they default on their debts, they fail: They “exit the market.”

Benchmark and beyond

The benchmark model is calibrated to the U.S. economy with standard values for such variables as interest rates, annual sales growth for firms and the like. The economists test the model with these parameters by checking whether it can match U.S. data accurately; it does—with, for example, the fraction of labor employed by new firms at 1.8 in both data and model, and the liability-to-sales ratio at 5.5 in the data versus 5.6 from the model. A near-perfect fit.

Then they see how it responds to “impulses”—that is, how the model’s mechanism reacts to a sudden increase in demand volatility. In this test, just as in the actual U.S. economy during the recent crisis, the model’s output and labor (that is, employment) drop strongly when volatility increases, but labor productivity (defined as the ratio of gross domestic product to aggregate employment) increases slightly at first and then stabilizes. “The overall response,” the economists write, referring to labor productivity, “is fairly flat compared to the responses of output and labor.”

In addition, wages fall about 1.4 percent after the volatility shock and then continue a slow decline, and the interest rate drops just a bit initially and remains slightly depressed. The benchmark, in short, works well as a representation of the U.S. economy during the financial crisis, at least for one-time shocks in demand volatility.

They then build two alternate versions of the benchmark to investigate whether this success is due primarily to its inclusion of incomplete financial markets or to its volatility shocks. This investigation finds that “both financial frictions and the source of the shocks—volatility instead of productivity—are critical to our benchmark model’s results” (emphasis added). In other words, neither financial frictions by themselves, nor just volatility shocks, are able to generate economic responses that resemble the real world during the Great Recession.

Real world testing

But the fundamental question is, how well can this model account not for a theoretical one-time volatility shock, but for a series of shocks like those experienced in the real economy during the Great Recession? The answer: very well. “We show that our model can account for much,” the economists write.

To reach that conclusion, they first find the volatility shock sequence that generates dispersion among firms’ sales growth rates similar to that actually measured in U.S. data between late 2007 and the third quarter of 2009. The data reveal nearly a doubling in this range of growth rates, from 17 percent to 31 percent. The economists feed that shock sequence into their model and see what happens to macroeconomic output, labor and productivity.

Given how crude the model is—in the sense of leaving out countless aspects of an actual national economy—it does a remarkable job of generating results similar to real world figures. “The model generates a decline in output of 6.5 percent, whereas in the data output declines 9.7 percent,” they find. And it “produces about an 8 percent decline in labor, whereas in the data labor declines about 10 percent.”

While not dead on, the model’s results are quite close, suggesting that the mechanisms at its heart are what drive the actual economy, through good times and bad. When the economists summarize the overall results, they conclude that the model “can explain 67 percent of the overall contraction of output and 73 percent of the contraction in labor during the Great Recession.” The model produces a fairly flat productivity profile for the recession, while in real data, productivity first falls and then rises modestly. But “both in the model and in the data, productivity at the end of this event is essentially unchanged … even though output has fallen 10 percent.”

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Refinement

The economists explore several dimensions of, and refinements to, their model. One is to alter the model by introducing “sticky wages,” the idea that in the real world, most prices don’t change instantly. A gallon of gasoline may rise or fall in price several times a day or week, but wages, automobiles and even items on a restaurant menu take a while to adjust to trends in the economy—to a broad recession or to a rise in the cost of health care, steel or eggs. This factors into the model, since in the benchmark version of the model, wages fall when volatility increases, and such response dampens the labor adjustment firms make.

And indeed, by making the model’s input prices less responsive to volatility, the economists find that sticky prices “diminish offsetting equilibrium effects.” The charts on page 35 show their results. They compare real wage trends in the data, the benchmark model and the sticky real wage model for the entire span of the Great Recession and show that while they drop by about 2 percent in the data and over 8 percent in the benchmark model, “in the sticky real wage economy, real wages drop about the same as in the data.” Sticky real wages also amplify the output and employment effects of increased volatility.

Thus, Arellano, Bai and Kehoe’s model, with key features and additional enhancements, does a striking job of duplicating patterns seen in the U.S. economy in recent years. “Hence,” they conclude, “we think of the model as a promising parable for the Great Recession of 2007-2009.”

Since the days of Adam Smith, international trade and long-run growth have engrossed economists. Global trade, after all, is the exchange of goods and services—at the core of economics—writ large. And long-term growth is how countries do (or do not) permanently raise their standards of living.

Several giants in economics have made important contributions to one of these fields or the other, but very few have had an enduring and transformational influence on both. Among the latter is Harvard’s Elhanan Helpman, one of the world’s foremost authorities on international trade and economic growth, and a leading figure in several other areas, including political economy.

In 2010, the prestigious Nemmers Prize in Economics, awarded biennially to recognize “work of lasting significance,” was given to Helpman “for fundamental contributions to the understanding of modern international economics and the effects of political institutions on trade policy and economic growth.” (Five of the previous eight Nemmers Prize recipients later received the Nobel Prize.)

It was in the early 1980s that he helped develop “new trade theory,” a fundamental concept that explained what traditional comparative advantage theory could not: The vast majority of international trade takes place among quite similar countries and sectors. He later developed key insight into the ways modern firms organize production not at a single factory but in multiple stages, sites and nations—leading to global trade flows never envisioned by earlier economists.

In addition, with Gene Grossman of Princeton, Helpman pioneered the extension of “new growth theory”—the idea that information, ideas and technology (not just capital and labor) are central determinants of economic growth—into settings with international trade. They explored the importance of international research and development, and spillovers thereof, to technological innovation and growth itself.

More recently, Helpman has investigated the role of institutions—legal regimes, education systems and the like—in both growth and the political systems that determine trade policy. Currently, he is studying why economic inequality often accompanies greater trade flows across borders—contrary to predictions of traditional trade theory—but then diminishes.

In the following interview, he describes the history and current frontiers of his pathbreaking research, sharing insights gained through decades of research into the riddles of economic growth and global trade.

Helpman: So, what would you like to talk about?

Region: In truth, I’m a bit overwhelmed by all the fields in which you’ve worked, but perhaps we could focus on three that I think are among your primary areas: new growth theory, new trade theory and trade (and policy) related to market structure. That’s a lot to cover, but if we have time, perhaps we’ll be able to visit a few other topics.

New Growth Theory

Region: As you know, Paul Romer, Bob Lucas and others pioneered what was later termed “new,” or “endogenous,” growth theory, emphasizing increasing returns associated with new knowledge, ideas, technology and spillovers. You extended this new growth theory into settings with international trade, often with Gene Grossman, looking at the importance of research and development and spillovers from industrial research.

Could you tell us, why are R&D spillovers central to economic growth?

Helpman: In the previous episode of growth theory, the view was taken, following [Robert] Solow, that economic growth is driven mostly by capital accumulation. Some of Solow’s students also discussed the accumulation of human capital, which Lucas essentially then extended and turned into a major view of economic growth.

However, at the same time, there were a number of people who worked on the impact of research and development. Zvi Griliches, for example, worked on it from a microeconomic perspective rather than from a macroeconomic perspective. They developed the concept of R&D capital stocks and the type of externalities that they generate. Moreover, they estimated these external effects.

Region: They developed spillover estimates that early on?

Helpman: They did, yes, and the typical estimate was that the social rate of return on R&D could be twice as high as the private return. So when Gene Grossman and I entered the field, we had this in the background. We knew that there were R&D spillovers, and we knew that the social rate of return was high. Then the question that Paul Romer and other people asked was, to what extent can you explain growth with investment in research and development, rather than assume, as Solow had done, that the rate of technical change is exogenous? Because if you could tie growth to the rate of technical change, obviously, you potentially could explain a lot of aggregate growth.

Region: Which is what made it “endogenous” growth?

Helpman: Endogenous, correct. I mean, at some level in economics, almost everything is endogenous; it only depends on how far back you want to stand. You can ask the question, OK, research and development is endogenous, but it depends on the economics environment, which is treated as exogenous. If, however, you are willing to take one step back, you realize that some elements of this economics environment, such as the patent system, are in fact endogenous too.

In any case, Gene Grossman and I thought that this is very important for links across countries. In other words, that if research and development affects the growth rate of a country, then it may also impact the growth rate of its trade partners. Our idea was to explore channels of cross-country influence and try to understand the interdependence of the growth rates of different countries.

Region: This was your “quality ladders” paper?

Helpman: Well, the quality ladder was just a model. We actually wrote an earlier paper, less known than the others, I think it was in ’89, which was very specific in many details. So when we wrote the quality ladder paper, we already had a better view of the world, and we could write something more appealing.

And, of course, there was the work of Paul Romer that we could build on. Our aim was to integrate this view of the growth process into a worldwide system in order to explore these interdependencies across countries. So when we wrote, later, the book, we showed that the same mechanisms work, whether you explain growth by quality ladders or by extending product variety.

From a macroeconomic perspective, these two alternative views are pretty good substitutes. For some issues, they are not. For example, if you want to measure the deviation of what the market generates from what is the best for society, these two views will give you somewhat different answers. But from a perspective on how the growth process behaves, they provide very similar results.

Region: The book you refer to is Innovation and Growth in the Global Economy?

Helpman: Yes, Innovation and Growth.

Region: Still considered the main reference on trade and endogenous growth, over 20 years after its publication.

Empirical Impact Of R&D, Human Capital And Institutions 

Region: Earlier you mentioned Griliches’ empirical estimates. Though you’re mainly a theorist, you too have studied the empirical impact of R&D—both domestic and international—on productivity and therefore growth. I think your first empirical work on this was in 1995 with David Coe. And you later extended that with Coe and Alexander Hoffmaister to look at human capital and institutions.

Would you summarize your findings from that work? Which variables—R&D, human capital, institutions—have the most significant impact on productivity? And what does that suggest for policy?

Helpman: Well, I’m a little shy about policy recommendations. But I can talk about the findings; it’s easier. Yes, so, our first empirical paper on R&D spillovers, international R&D spillovers I should say, is the paper we wrote in ’95. We wrote a couple of other papers as well. In ’97, Coe, Hoffmaister and I had a paper; then [Tamim] Bayoumi, Coe and I wrote another later on.

In the 1995 paper, essentially, we asked the following question—we know how Griliches has estimated R&D spillovers across firms; there also existed estimates of spillovers across industries—so we asked the question, can we estimate spillovers across countries?

We computed productivity growth in a variety of OECD [Organisation for Economic Co-operation and Development] countries in this particular paper. We constructed R&D capital stocks for countries, rather than for industries, which is what Griliches had done. Then we estimated the impact of the R&D capital stocks of various countries on their trade partners’ productivity levels.

And we found substantial spillovers across countries. Importantly, in those data, these spillovers were related to the trade relations between the countries. And we showed that you gain more from the country that does more R&D if you trade with this country more. This produced a direct link between R&D investment in different countries and how trading partners benefit from it.

In the ’97 paper with Coe and Hoffmaister, we looked at developing countries because the ’95 paper was about industrialized countries. The developing countries don’t do much R&D. The overwhelming majority of R&D is done in industrialized countries, and this was certainly true in the data set we used at the time.

So we asked the following question: If you look at developing countries, they trade with industrialized countries. Do they gain from R&D spillovers in the industrialized countries, and how does that gain depend on their trade structure with these industrialized countries? We showed empirically that the less-developed countries also benefited from R&D spillovers. And the more they trade with industrialized countries that engage heavily in R&D, the more they gain.

The exercise Bayoumi, Coe and I then did is also quite interesting. The International Monetary Fund had an econometric model for its midterm projections. We integrated the equations that Coe and I had estimated previously into this IMF econometric model. Then we could simulate it using our specification of the relationship between R&D levels and productivity levels across countries. In this way, we could essentially decompose the growth process. How much of it is driven by capital accumulation? How much is driven by productivity growth due to R&D?

One of the important findings—which analytically is almost obvious, but many people miss it—is that, if you have a process that raises productivity, such as R&D investment, then this also induces capital accumulation. So then, the contribution of R&D to growth comes not only from the direct productivity improvement, but also through the induced accumulation of capital. When you simulate the full-fledged model with these features, you get a very clear decomposition. You can see how much is attributable to each one.

With this, we could handle a relatively large number of countries in all different regions of the world, and [run some] interesting simulations. We could ask, for example, if all the industrialized countries raise their investment in R&D by an additional half percent of gross domestic product, who is going to benefit from it? Well, you find that the industrialized countries benefit from it a lot, but the less-developed countries benefit from it also a lot.

It was still the case that the industrialized countries would benefit more, so in some way it broadened the gap between the industrialized and the less-developed countries. Nevertheless, all of them moved up significantly.

This was quite fascinating—both the research itself and the implications we found in these simulations.

Of course, I’ve also been involved in an attempt to understand how institutions affect growth, and in the more recent paper, we looked at the role of institutions in enhancing the contribution of R&D to growth. And we’ve found that they’re quite important. For example, patent protection is an important tool. Countries that have better patent protection systems benefit more from R&D investment and also from R&D invested in other countries.

R&D, Institutions And International Spillovers

Region: What’s your general sense then, from this entire body of both theoretical work and empirical research, of the importance of international R&D spillovers and institutions in contributing to economic growth?

Helpman: My sense is that institutions are very important. Of course, there has been a lot of work by other scholars on the subject, and my contribution is at the margin, to some extent. But you know, institutions impact growth through a variety of channels; R&D investment is just one of them. It is relatively less-researched than some of the others.

Let me make some general remarks on this subject. If you look at the empirical work on institutions and growth, or institutions on economic performance more broadly, then I think we, many of us, have become convinced that there exists a robust relationship between the quality of institutions and economic performance.

However, most of the empirical work is based on a broad-brush sweep. And it’s hard to identify from that precise mechanisms through which institutions affect performance. There are, of course, exceptions to the rule. Generally speaking, we have these robust correlations, which in fact some people dispute, too, but let’s agree that these are robust correlations.

The more important understanding that will have clear policy implications requires studies of specific mechanisms and how they work through the system in order to translate features of institutions into features of economic performance. For example, think about correlations that tell you that different legal systems have a different effect on income per capita. And suppose that you’re convinced that one system is better than another.

Region: That perhaps the British legal system is better for economic growth than, say, the French system.

Helpman: Right. But if you don’t understand what features of the British system feed into better performance, through which channels and in what dimensions of performance, it’s very hard to think about the design of policies. So, this is an area where we need a much more detailed understanding in order to be able to actually translate these broad correlations into concrete policy recommendations.

Current Developments In Growth Theory

Region: Perhaps that leads to a question about current research developments. The world economy and theory itself have changed a great deal since the research of the early 1990s, so it’s probably a misnomer to still call it new growth theory.

Helpman: Oh, right, it’s not “new” anymore.

Region: Indeed. So, what current directions in growth theory, then, do you consider most promising? Which avenues should be pursued?

Helpman: There really hasn’t been that much work on economic growth lately. A lot of work, for example, has tried to identify distortions in resource allocation, mostly empirical research. And there has been work like that of Daron Acemoglu on induced technical change.

But altogether, there hasn’t been a big change in the view of the profession on economic growth. Frankly speaking, despite the fact that many papers have been published dealing with various aspects of this subject, there has been no major change in the view of the growth process.

An End To Growth?

Region: Curiously, that lack of change in the view of the growth process brings to mind a recent paper by Robert Gordon on stagnation in economic growth itself. He argues that a number of factors suggest that the rates of economic growth seen in the United States specifically over the past 250 years are not likely to be seen again. Does that seem plausible to you?

Helpman: No. I mean this is his own personal judgment, right, and that’s fine. Essentially, he talks there about technologies that I would term “general-purpose technologies,” which is a subject on which people worked in the past. Again, there hasn’t been much work recently, but in the ’90s, there was quite a bit of work on this.

So, what’s a general-purpose technology? It is a type of technology on which other technological developments build. And it usually induces more specific technical change and the development of inputs that build on this technology for further production.

Region: His examples are steam engines and locomotives, I believe, electricity and …

Helpman: Yes, the steam engine was a general-purpose technology; electricity was a general-purpose technology. The microprocessor was a general-purpose technology. So there are technologies like this, which appear from time to time. And sometimes at the beginning they cause some havoc …

Region: An end to the buggy whip industry, say.

Helpman: Right. But then eventually, they trigger a process of development and growth that can be very fast and can last very long. Therefore, it is true that a number of these general-purpose technologies were big contributors to growth. But there was at least one more recently, the microprocessor.

Moreover, I don’t see how we can predict how many of these technologies will emerge in the future. So, one person can believe that we won’t see anything new in the near future. Another person may think that we will. I don’t think we have the capability actually to predict these developments. It’s easier to predict what will happen once the general-purpose technology emerges. That’s not entirely easy either, but at least you have something to build on in terms of predictive power.

But how do you predict that somebody will come up with a great idea that will trigger a completely new process of technological development? I don’t think that we can do it.

New Trade Theory

Region: Let me ask about new trade theory. Of course, new growth theory relates to your work on new trade theory. In the 1980s, new trade theory expanded upon neoclassical trade theory, comparative advantage based on factor proportions, labor productivity. You and Paul Krugman were the foremost leaders in developing this new work, bringing [Edward] Chamberlin’s theory into the mix.

What inadequacies in traditional theory required better answers? And how did new trade theory address those weaknesses?

Helpman: When I was a student, the type of trade theory that was taught in colleges was essentially based on Ricardo’s 1817 insight, Heckscher’s 1919 insights and then Ohlin’s work, especially as formulated by [Paul] Samuelson later on.

This view of trade emphasized sectoral trade flows. So, one country exports electronics and imports food, and another country exports chemicals and imports cars. This was the view of trade.

The whole research program was focused on how to identify features of economies that would allow you to predict sectoral trade flows. In those years, there was actually relatively little emphasis on Ricardian forces, which deal with relative productivity differences across sectors, across countries, and there was much more emphasis on differences across countries in factor composition.

In parallel, some work tried to deal with industrial organization issues in trade. One of my teachers, Richard Caves, had done at one time quite a bit of work on it, but the theory of industrial organization and trade was very slim. More generally, there was little integration of that theory with the empirical work in trade.

Two interesting developments in the 1970s triggered the new trade theory. One was the book by Herb Grubel and Peter Lloyd in which they collected a lot of detailed data and documented that a lot of trade is not across sectors, but rather within sectors. Moreover, that in many countries, this is the great majority of trade.

So, if you take the trade flows and decompose them into, say, the fraction that is exchanging [within sectors] cars for cars, or electronics for electronics, versus [across sectors] electronics for cars, then you find that in many countries, 70 percent—sometimes more and sometimes less—would have been what we call intra-industry trade, rather than across industries.

Region: So, for instance, looking at trade flows between the United States, Japan and Germany in, say, cars.

Helpman: Yes. You export cars, you import cars; you export electronics, you import electronics. So, Grubel and Lloyd did a great service by devising an index, which allowed a decomposition that showed the relative magnitudes of these trade flows.

The other observation that also started to surface at the time was that when you looked at trade flows across countries, the majority of trade was across the industrialized countries. And these are countries with similar factor compositions. There were obviously differences, but they were much smaller than the differences in factor composition between the industrialized and the less-developed countries. Nevertheless, the amount of trade between developed and developing countries was much smaller than among the developed countries.

This raised an obvious question. If you take a view of the world that trade is driven by [factor composition] differences across countries, why then do we have so much trade across countries that look pretty similar?

Some other empirical studies raised various issues, like the work of Béla Balassa on the formation of the European Common Market. But this would take too much time to explain.

These were the empirical developments. Then, on the theoretical front, monopolistic competition was introduced forcefully by both Michael Spence in his work, which was primarily about industrial organization, and [Avinash] Dixit and [Joseph] Stiglitz in their famous 1977 paper. These studies pointed out a way to think about monopolistic competition in general equilibrium. And trade is all—or, at least then, was all—about general equilibrium.

So combining these new analytical tools with the empirical observations enabled scholars to approach these empirical puzzles with new tools. And this is how the new trade theory developed. At some level, you know, the answers are pretty simple …

Region: Well, simple in retrospect, perhaps.

Helpman: [Laughs.] Well, yes, yes. There were people like Béla Balassa who actually had the right insight. I mean, he didn’t write down the model, but when he looked at the data and he saw this, he told a story that is not that different from what the models told.

Region: I read your conversation with Daniel Trefler, in which you describe the process of writing your 1981 Journal of International Economics paper—a landmark paper, as he said. Arriving at those “simple” answers sounded very difficult.

Helpman: Yes, indeed. It wasn’t easy at all. It was very hard actually. It’s very difficult to write down a detailed economic model that describes new phenomena in a convincing way. It’s very difficult.

Nevertheless, we have to do it, because this not only imposes a discipline on how we think about the problem, but there are typically unintended consequences of model building. You build a model to explain a phenomenon, but the model then has other types of predictions, and you ask yourself, are these other predictions consistent with the evidence? If they are not consistent with the evidence, then maybe there is something wrong with this model.

Generally speaking, I think this is one of the nicer things that have happened in economics in the last few decades: this interplay between theory and empirical findings. There used to be—in trade, this was definitely the case—a pretty sharp division between empirical work and theoretical work. And these new questions, and the construction of models to handle them, brought theory and empirical work much closer together.

These new models looked at product differentiation within industries. And they looked mainly at manufacturing. Today there is substantial trading in services, but at that time, it was negligible. Manufactured products are what countries used to trade. And in manufacturing industries, product differentiation is everywhere.

Region: So you look at trade flows of, say, Chevrolets and BMWs, for instance. Both cars …

Helpman: Right, both cars.

Region: But very different.

Helpman: Yes, they are different cars. And countries produce different cars. And, you know, countries produce different electronic equipment, and they produce different chemicals. And they trade them.

The first obvious conclusion you reach is that if one country produces different brands of a product from its trade partner, then they’re going to exchange these brands and then you’ll get intra-industry trade. This may beef up the trade volume across quite similar countries to an extent that you wouldn’t be able to predict if you wanted to use differences in factor proportions across countries as drivers of trade.

So, these models provided some nice predictions that could be brought to the data. They provided indices you could look at, and they started a new research program, which has been sustained to this very day with the more recent revolution in trade research.

New Trade Theory And Multinationals

Region: Let’s move to that. It seemed to me that your 1984 paper was one of the first to develop a theory of trade and multinationals. And then firm-level data became available toward the end of the ’80s, early ’90s, that pointed out the importance of understanding how firms differ in their levels of trade involvement. Within the same industry, some firms trade a lot internationally while others don’t.

In addition, your paper “Trade, FDI and the Organization of Firms” points out that new research is looking at the structure of industries and providing what you call “new explanations for trade structure and patterns of FDI and new sources of comparative advantage.”

What are those theoretical refinements—the new new trade theory, if you will? And what are the new explanations they offer?

Helpman: In the 1990s, a lot of effort went into the integration of trade and growth. In parallel, a lot of excellent empirical work was being done. Part of it actually focused on the more traditional explanations based on differences across countries in factor proportions. This started with the work of [Edward] Leamer in the mid ’80s and some of his co-authors and continued with Trefler in a famous 1995 paper and a variety of papers that followed. This was one line of research.

There was another line of research that evolved. Andy Bernard, for example, from Dartmouth, was a big contributor to this one. This work started to look at firm-level data sets.

In the older new trade theory—that’s a funny term, no?—in the older new trade theory, there were firms, obviously, but we didn’t pay much attention to the differences across firms within an industry, basically. It’s not that we didn’t know there was a size distribution of firms in every industry, but the questions that we asked didn’t seem to require this added complexity in order to answer them. Therefore, we assumed all these firms were, basically, symmetric.

Now, the important thing about the empirical work in the 1990s that used firm-level data sets is that they identified systematic relationships between firm characteristics and their involvement in foreign trade. The key observation was that if you look across these data sets, then you find that only a fraction of firms in every industry exports, and it’s not a large fraction, actually.

But this is not a random sample of firms in the industry. This is a skewed sample. In particular, the bigger and more productive firms engage in foreign trade, and the others don’t. Moreover, those that export still serve the domestic market with a large share of their output.

Thus, we accumulated some insights into what you might call stylized facts about the relationship between trade and firm characteristics. And this is what triggered a reevaluation of the old new trade theory, which was then developed further, by Marc Melitz primarily but by other people as well, into the new new trade theory. The interesting thing here was that Melitz’ paper—which essentially provided a theoretical explanation of these stylized facts—triggered a huge literature. And it triggered a huge literature in more than one way, one of them related to the multinational issue.

Parallel to this, there was an independent development that allowed a new approach to multinationals, namely, the one based on contractual frictions. This is an interesting story because the work by [Sanford] Grossman and [Oliver] Hart on contractual frictions is from 1986. Then there was a paper by Hart and [John] Moore in 1990.

Evidently, Hart’s work had been around for a while. However, it had not been integrated into international trade. And parallel to Marc Melitz’ contribution, research was being built on these contractual frictions, particularly by Pol Antràs. Melitz’ paper and Antràs’ paper actually were published in the same year, but they dealt with very different issues.

Eventually, these two branches were integrated. As a result, we have a very comprehensive and detailed model of international trade where you can think simultaneously about the choices of firms to export, to engage in foreign direct investment, how this is related to the degree of heterogeneity of productivity within industries, how it is related to the severity of contractual frictions.

So it opens new windows, which are quite fascinating. And this research program that continues to this very day led to much better empirical work, more-refined theory; it has been a fantastic period for people working in this area.

Region: You chose your field well.

Helpman: One gets lucky from time to time. [Laughs.]

Trade And Inequality

Region: I’d like to ask you about trade and inequality. Conventional trade theory, since Heckscher-Ohlin at least, has argued that trade should result in greater income and wage equality among nations and workers. But empirical studies generally haven’t borne that out. They find an inverse relationship.

Recently, with Oleg Itskhoki and Stephen Redding, you’ve done a great deal of work on the impact of trade on inequality and come up with an interesting explanation for this seeming anomaly, showing that trade seems to increase inequality initially, in contradiction to traditional theory, but eventually decreases it.

Essentially you argue for an inverted U-shaped curve between wage inequality and openness to trade, reminiscent of a Kuznets curve but for trade liberalization. Would you summarize that work and perhaps refer to your work on wage inequality in Brazil?

Helpman: Let me step back a little bit. Most of the work on trade and inequality in the neoclassical tradition was focused on inequality across different inputs. So, for example, skilled workers versus unskilled workers, or capital versus labor, and the like. There was a lot of interest in this issue with the rise in the college wage premium in the United States, which people then found happened also in other countries, including less-developed countries.

Region: So, the idea of skilled-biased technological change.

Helpman: Yes, the conclusion was that skilled-biased technological change drove wage inequality. Because if you wanted to use a trade explanation, then you should have seen opposite movements in inequality between skilled and unskilled workers in countries at different levels of development. This was one line of inquiry and debate in the literature on the impact of trade on inequality.

The other interesting thing that happened was that labor economists who worked on these issues also identified another source of inequality. They called it “residual” wage inequality, which is to say, if you look at wage structures and clean up wage differences across people for differences in their observed characteristics, such as education and experience, there is a residual wage difference, and wages are still quite unequal across people. In fact, it’s a big component of wage inequality.

Our aim in this research project, which has lasted now for a number of years, was to try to see the extent to which one can explain this inequality in residual wages by trade. It wasn’t an easy task, obviously, but the key theoretical insight came from the observation that once you have heterogeneity in firm productivities within industries, you might be able to translate this also into inequality in wages that different firms pay.

You know, it’s not obvious that bigger and more productive firms have to pay higher wages, although empirically this is true. You can write down a model in which this doesn’t happen. Now, I was interested in the question of how do different countries respond to trade when they have different labor market frictions? This is partly related to some readings of what happened in Europe in terms of labor market policies.

Region: Sure. Greater rigidity in European labor markets has been considered a source of economic underperformance in many respects.

Helpman: We tried to combine these insights, labor market frictions on the one hand and trade and firm heterogeneity on the other, and the question is, can we generate a link between trade and unequal wages paid by different firms when there are labor market frictions?

We managed eventually, after significant effort, to build a model that has this feature but also maintains all the features that have been observed in the data sets previously. It was really interesting that the prediction of this model was that if you start from a very closed economy and you reduce trade frictions, then initially inequality is going to rise. However, once the economy is open enough, in a well-defined way, then additional reductions in trade friction reduce the inequality. Now, it is not clear that this is a general phenomenon, but our analytical model generated it.

Region: So, it’s an inverted U curve.

Helpman: Yes, it’s an inverted U shape, and the driving force there is the following. If, within an industry, you have firms with different productivity levels, they make different strategic decisions about how to organize their production and how to integrate into foreign markets.

What happens is the bigger, more productive firms export, as we observe in the data. But the key point here is the following: Look at two firms with very close productivity levels. And say the one with lower productivity chooses not to export because this is what maximizes its profits, and the one with a somewhat higher productivity level (even if just marginally higher) chooses to export.

The exporter is going to respond in a discontinuous way; it will perform a big jump. Why is this? Because to export, it has to cover the fixed cost of penetrating a foreign market. Therefore, it will be significantly larger than the firm with the slightly lower productivity level. Now, if you have a mechanism—as we do in our model—in which firms screen workers and then bargain over wages, which results in a positive correlation between wages and firm productivity, then you’re going to have a big jump in wages when the firm goes from nonexporting to exporting.

This generates inequality, but now, it depends where this jump takes place. If the jump takes place very close to autarky, so just a tiny number of firms in the country export, then when you remove the barriers so that more firms export, this is going to raise inequality.

But if it’s a nation where almost all the firms export, yes, then the inequality is not so large because the firms with the significantly lower wages employ very few people. So now, when you liberalize trade again, and you expand the range of firms that export, you actually reduce inequality.

Region: And, empirically, you found that Brazil’s trade liberalization experience was consistent with the model’s prediction.

Helpman: Right. In this paper on Brazil, we wanted to see to what extent this type of model fits the data. To assess a model like this, you need very detailed data, what we call matched employer/employee data. These are data where you know in which firm every person works. In addition, you need to know the wages of every worker, their education, their experience. You need to know if the firm exports, doesn’t export. Very detailed data. So we have this huge data set from Brazil on which we estimated the model, and then when we simulate the model we get the inverted U shape.

Reaching A Lay Audience

Region: Let me ask just one more question. In 2004, you wrote a wonderful book for a lay audience, The Mystery of Economic Growth. Then in 2011, Understanding Global Trade. Both books provide concise, lucid descriptions, in nontechnical language, of the historical and current research in each area, growth theory and trade theory.

I’m curious to know why, after years of deeply technical research—work that has expanded frontiers of both areas—you’ve chosen recently to write for a lay audience. Why did you decide, twice, to devote a substantial amount of time to each book? The opportunity cost of working on those two books was enormous, given the research time you sacrificed. Why did you consider it important to reach the lay audience as opposed to continuing to work with your colleagues to further expand the frontiers of research in either growth or trade theory?

Helpman: You know, maybe I made the wrong cost/benefit calculation. [Laughs.]

Region: I certainly don’t think so.

Helpman: I just had the urge to do it, frankly speaking. It came from the fact that very few people outside the profession—or even in the profession who were not close to this research line—really understood or knew about the importance of the research that has been done.

So it started with growth theory, yes? I was engaged in work on growth for a long time, and at the Canadian Institute for Economic Research, we have had a group that worked on this subject. But each time I talked to people from other fields in economics and certainly to people outside economics, they knew relatively little about the subject.

And by that time, I felt that we had a good enough understanding of this research that we could explain it actually in nontechnical terms. It is not always possible and it usually takes a long time, for whatever reason. I don’t know exactly why. It’s just something about how our brains work that over time we gain a better understanding of things, even if we are not working on them, necessarily. But obviously, you keep thinking about these issues time and again. You try to explain them to other people.

I felt that the topic was obviously very important—economic growth—and I felt that I should be able to explain at least the major issues to people who don’t have a Ph.D. in economics, basically, or who have an economics Ph.D. but work in labor economics markets or economic development or whatever. So I don’t know, I developed this urge to do it, and I sat down and did it.

Region: And did it again, seven years later.

Helpman: Yes, it was the same. However, I would not have done it on the trade book if we had not had these wonderful 10 years of research where we had an explosion of new insights. Again, I felt the work had become more and more technical, on both the theoretical side and the empirical side. Nevertheless, the insights are not that complicated actually, so we should be able to explain these things to interested parties. And, well, I decided to do it.

Region: I’m very glad you did.

Helpman: Well, actually, I’m glad I did it too. It took a lot of time obviously and, you know, we don’t have too much time. [Laughs.]

Region: Very true, and I’ve used more than my share of yours. Thank you so much.

Helpman: You’re very welcome. Good to meet you.

Over the course of my three-year tenure as president of the Federal Reserve Bank of Minneapolis, I have given many talks across the Ninth District. Often, during the course of those talks, I have described how I obtain the economic information that helps inform my policymaking. I do this because I believe that it is important for people to know how their policymakers receive information that helps them make policy. As well, this process of information gathering reinforces the point that the Federal Reserve System is grounded in regional representation from across the country. Indeed, that’s why our central bank is a “system” and not just one monolithic operation in Washington. So for this column, I will describe the information-gathering efforts that I employ and then conclude by discussing my decision to make those efforts public.

First, it would not surprise you to learn that Federal Reserve policymakers have large amounts of data at their disposal. Indeed, that is an understatement. There is no end to data on all aspects of the economy, from inflation to employment to manufacturing and trade, and hundreds of data points in between. Nonetheless, these data do not tell the whole story that I need as a policymaker. Some data can be weeks or months old at the time a decision needs to be made. In addition, as important and revealing as data are, there is still much to learn from people making decisions on the ground. For example, what are businesses’ hiring plans? What are expectations for future sales? What about price pressures? What are banks experiencing in terms of loan demand?

Those questions and many others provide answers that help bring data to life and inform the choices that I have to make. But who answers those questions? How do we gather such information? The sources are many and reflect the broad and varied constituency of the Ninth District. First, there is our board of directors. In my previous column, for the September 2012 Region, I described the role of the directors in some detail, so I will only stress here the important role they play in relaying economic information. For every meeting, a subset of the directors is charged with answering questions about the condition of the general economy and also about their particular industry. They do this not only by relaying information pertinent to their own companies, but also based on many phone calls and conversations with colleagues in their industries.

In addition to the board of directors, I meet twice a year with three advisory councils, for a total of six meetings. These meetings are held expressly for the purpose of gathering information about the Ninth District economy. These councils represent small business and labor, agriculture and community financial institutions. Who sits on these councils? The answer is as varied as any town’s Main Street and rural highways: Ranchers, farmers, owners of retail shops, credit unions, labor representatives and small manufacturers, among many others, are represented in these meetings. By the way, information about the board of directors and these advisory councils, including the members, is available at minneapolisfed.org.

Beyond these more formal channels of communication, my travels around the Ninth District give me another way to get useful input. Whenever I give a speech outside the Twin Cities, I schedule meetings with local business owners and bankers, as well as with organizations that serve consumer groups, especially those that provide services to low- and moderate-income communities and households. I am always grateful for the time that these busy people take from their schedules to discuss their views about the economy and the choices facing businesses and individuals. I always come away with more insight than I had before.          

Finally, just as I go out to the district to meet with people and to learn from them, others come to the Bank to visit with me. These people might be representatives from industries, consumer groups, labor groups, neighborhood coalitions and even representatives from other countries.

All told, I meet with a wide variety of people with insights from throughout the economy. So who are these people? Well, as I indicated earlier, you can visit our website to see who sits on our board of directors and on our advisory councils. As to those other groups I meet with throughout the Ninth District and at the Bank, you can see for yourself who they are, as they are now listed on our public website. Earlier this year I began posting my schedule online. In part, this move was a matter of transparency—that is, just as I think it is important for people to understand how I receive economic information, they should also know who gives me that information. But equally important, I publish my schedule because it reinforces the connections that I have with many segments of the Ninth District economy. As I often tell people when I give talks, it is these connections—this two-way communication with people in local economies—that ensure that the American people have input into monetary policy.

To get the most current read on the economy, the Philadelphia Fed established the Real-Time Data Research Center. Along with forecasts and economic research, the center collects and makes available the most up-to-date economic data. While its primary audience is economists and policymakers, the site is useful for anyone curious about the state of the economy. Of particular interest is the center’s real-time business conditions index, which is updated every few days as new data are released.

Abstract

Banks are prone to panic-induced runs due to their traditional structure of short-term, unconditional liabilities and long-term, illiquid assets. To avoid systemic crises caused by such panics, governments tend to bail out failing banks. Traditional banking systems thus impose external costs. Three major theoretical benefits are often used to justify a banking system that relies on short-term debt despite these costs: (1) maturity transformation, (2) efficient monitoring of bank managers and (3) facilitation of financial transactions. In a previous paper, we argued that the first two justifications, while seemingly compelling, actually suggest financial arrangements very different from our current system. In this paper, we examine the third justification, that a banking system reliant on short-term debt is essential for the facilitation of transactions. We find, in fact, that this reliance is more costly than generally recognized and, moreover, that socially beneficial financial transactions can and should be provided at less cost and risk by both restricting and broadening the payments system. Transactions should be restricted to institutions that continuously mark to market the value of their assets and issue equity claims to owners. Such accounts should also be broadened to include financial vehicles that are readily available, thanks to advances in information and communication technologies, and possibly quite different from current banks.

Introduction¹

The financial crisis of 2007-08 and consequent Great Recession generated substantial discussion and debate over future banking regulation. Largely absent, however, has been a careful reexamination of whether the beneficial services provided by traditional banks outweigh the inherent financial fragilities of those banks and their associated costs to society.

Three major benefits are usually said to justify traditional bank reliance on short-term debt, the source of their inherent fragility. In a previous article, we assessed—and found wanting—two of these proposed rationales: (1) the benefit of maturity transformation, or creation of long-term financial assets from shorter-term assets and (2) the benefit of efficient monitoring of bank managers, through appropriate alignment of investor incentives. (See Chari and Phelan 2012a.)

Here we discuss the third justification, that traditional banks are beneficial and necessary because they provide payments services essential to the efficient function of modern economies. We conclude that while this rationale was compelling in an earlier historical era—prior to modern advances in information and communication technology that facilitate transactions of all sorts—the necessary services can now be provided through existing financial vehicles that do not rely on traditionally structured, inherently fragile banks.

We begin by briefly reviewing the structural source of traditional bank fragility and proceed to consideration of the necessity of banks, despite this fragility. We then address the main topic of this paper: the argument that banks as currently structured are necessary because their demand deposits facilitate financial transactions. We conclude that the current structure of banks is unduly costly to society and that essential payments services can, with modern information and communication technologies, be provided with less fragile and more efficient financial institutions.

The inherent fragility of banks

In what sense are banks and similar financial institutions fragile? Our previous paper discusses this question in detail; here we provide a synopsis, referring interested readers to the earlier discussion.

The assets of financial institutions are, by and large, financial assets, and claims on them are primarily financial liabilities. Their financial assets consist mainly of conditional promises to deliver dollars at future dates. These assets, such as home mortgages, are often long term and illiquid. Their financial liabilities consist mostly of a variety of obligations to deliver dollars at particular dates, under certain circumstances. Banks in particular have liabilities that are mostly short term and unconditional, such as demand deposits and certificates of deposit.

This reliance on short-term debt makes banks fragile in that they are particularly vulnerable to the risks of insolvency and the possibility of confidence crises. Since bank assets are much longer term and illiquid than their liabilities and because the value of these assets fluctuates, a bank’s net worth also fluctuates a great deal.

The illiquidity of banks’ assets and the demandable structure of their liabilities thus expose banks to crises of confidence. Since a bank typically will not be able to meet the demands of all depositors within a short period of time should they all choose to withdraw, banks are vulnerable to self-fulfilling panics in which depositors withdraw their funds simply because they believe other depositors will do so. This panic is an entirely rational response even if the bank is solvent (though illiquid).

Governments have a strong incentive to intervene to bail out debt holders of banks in order to prevent the entire financial system from failing. Paradoxically, expectations of such bailouts can increase the incidence and depth of financial crises. Once depositors believe that their deposits will be protected in the event of systemic failure, they have less incentive to monitor bank managers, who, in turn, have increased incentive to take on risk, knowing their failures are implicitly insured by taxpayers.

In this way, expectations of bailouts can lead financial systems to rely excessively—from a social perspective—on short-term debt to fund long-term assets. Fragile banking systems thus impose external costs, and regulation may therefore be socially desirable.

Are banks necessary?

The fragility of the banking system together with the reality that such fragility may well lead to occasional massive bailouts compel us to ask why societies would choose regulatory systems that allow financial institutions to fund illiquid assets whose value can fluctuate rapidly with short-term debt and demand deposits.

One could perhaps argue that banks were necessary prior to the electronic information age because no other forms of financial intermediation were feasible. With the advent of high-speed computers and modern communications, however, alternative financial institutions can provide similar services with far less potential for crises. We discuss such alternatives later in this paper.

We now examine the possible social benefits of a financial system in which illiquid assets with volatile values are funded by demand deposits and short-term debt. This cost-benefit analysis facilitates the design of a better regulatory system for banks, clearly a matter of considerable importance.

The previous paper examined two of the three major theoretical justifications for the reliance of the banking system on short-term debt: (1) demand deposits allow banks to engage in socially useful maturity transformation and (2) demand deposits allow for efficient monitoring of bank managers. This paper considers the third major justification: (3) demand deposits facilitate financial transactions.

To anticipate our conclusion, we believe that while all three justifications are compelling, they point us to a financial system very different from the one currently in place. The first two justifications suggest that it is important to have institutions that finance long-term assets with short-term debt, but we have argued that the assets that are so funded should not have close substitutes in publicly traded markets. In this paper, we will argue two main points regarding the usefulness of banks in facilitating transactions. First, we argue that regardless of technology, the social benefit to using banks to facilitate transactions is lower than the private benefit, thus potentially explaining why the historical ubiquity of bank-facilitated transactions does not imply their efficiency. Second, we argue that the necessity of bank-facilitated transactions is much less obvious than it was a century ago, before advances in information and communication technologies allowed us to create very different institutions than we currently have to facilitate transactions.

Our analysis will suggest a framework for thinking about regulatory policy for institutions that facilitate payments. The economic case for regulating such institutions is convincing, given that the failure of the payments system imposes significant external costs. We argue that institutions that facilitate payments should primarily issue equity-like claims such as those issued by standard mutual funds. Current practice hopelessly conflates these two economic cases into a single institution called “banks” and exposes the economy to unnecessary risks and recurrent costly bailouts.

Assessment of the transactions facilitation view

The most obvious service that banks provide now, and have offered throughout their ubiquitous existence, is payments services. Historically, banks have allowed individuals and firms to pay for goods and services through their provision of bank checks and other widely accepted claims. Therefore, those individuals and firms haven’t had to resort to costly barter or specie trade.

Here, we raise the possibility that banks exist because they provide a privately useful function—the facilitation of transactions in a form that pays households interest—but the social usefulness is less than the private usefulness.

The starting point of our assessment involves the central bank and monetary policy. The central bank creates money, which, for simplicity, we will call “cash.” Cash typically earns no interest. Our first key point is that, to the extent that monetary policy is conducted so as to keep inflation—and thus the (nominal) interest rate—inefficiently high, private agents have strong incentives to develop private payments systems to economize on the use of cash. Interest-bearing demand deposits (checking accounts) at banks are one example of such a private payments system. Because of the interest received in such accounts, households and firms will find it advantageous to switch from cash to these private deposits as their means of payment. Clearly, then, there would be private benefits to the introduction of payments systems like checking accounts.

But do these private benefits imply equivalent social benefits? If one household’s use of demand deposits imposed no costs on other households, the answer would be yes. But if use of such demand deposits does indeed impose costs on other households, the net social benefit of demand deposits will be lower and can, in fact, be negative. In the appendix, we present an example economy where these net social benefits from demand deposits are indeed negative, even though each household finds it in its interest to use them (since the private benefits are positive). In Chari and Phelan (2012b), we present a more general model where the net social benefits from interest-bearing means of payments can be either positive or negative, but are nevertheless always less than the private benefits.

The reason one household’s use of demand deposits imposes costs on other households is as follows: Introducing bank-provided payments leads to an expansion of the “means-of-payment” supply, now defined to include both cash and the amount of demand deposits. This higher means-of-payment supply leads to higher prices in the aggregate economy, which reduces the purchasing power of other households’ deposits and cash—but individual firms or households do not take this into account when they choose to use demand deposits over cash. This pecuniary externality (that is, an external cost imposed through prices rather than real resources) can cause households to use deposits instead of cash in cases where they wouldn’t, had they internalized this cost imposed on other households, and this externality implies that net social benefits of demand deposits are lower than net private benefits.

With net private benefits of banking exceeding net social benefits, it is clear that the banking system will be inefficiently large. In the model presented in the appendix, because the net social benefits are negative, not only is the banking system inefficiently large, the optimal size of banks is zero.

The model in the appendix is but a simple example, and the implications from it seem unrealistic. However, we would argue that recent developments in communication technologies and financial innovations may in fact make the model’s implications more than just a hypothetical scenario.

Historically, communication costs and limited development of financial markets have led to the use of systems in which only a fraction of a household’s financial wealth could be used for payments. With improvements in communication and financial markets, however, we can conceive of a world in which each individual can instantaneously access all of his or her financial wealth to make payments. We can also imagine a world in which settlement of transactions is instantaneous. In this world, cash becomes unnecessary, and precisely because cash is unnecessary, there is little or no need for payments systems that arise from the need to economize on cash, that is, arise because monetary policy is setting the inflation rate too high.

In the 1800s, it would have been inconceivable to pay for groceries, for example, by using a debit card associated with one’s mutual fund or stock portfolio (and in doing so, stocks were immediately sold, and the grocery received its settlement while the shopper was still at the counter). But today, this scenario is not far-fetched. In a world with virtually costless communication, banks as specialized providers of transactions services would simply be obsolete. These observations lead us to conclude that the actual importance of banks in the payments system is likely small today and will likely become even smaller in the near future. This is the third and final key point in our assessment of the transactions facilitation view.

What should “banks” look like, if not the traditional but fragile demand-deposit bank? As mentioned in the introduction, alternative financial institutions can provide similar services to the transactions facilitation services that traditional banks offer with far less potential for crises. One such example is the open-end mutual fund. These funds do not owe their shareholders a fixed dollar amount, but instead only the value of their percentage of the fund on the day the shareholder wishes to withdraw. If an unexpected surge of withdrawals occurs, the fund simply sells a sufficient quantity of the fund’s assets and gives the proceeds to the withdrawing shareholders. After this, the remaining shareholders still hold exactly the same assets per share as before. No shareholder gains by being earlier in line than other shareholders. Therefore, a belief that a run will occur cannot cause a run for a mutual fund—the self-fulfilling nature of runs that afflicts banks with demand deposits is thus avoided.

Implications for policy

Banks have been a durable part of the economic landscape for many centuries, and economic theory does explain why it might be efficient to set up institutions that fund long-term assets with short-term debt. Theory also illustrates that it might be optimal for private agents, but undesirable for society at large, to establish such institutions. These competing lessons from economic theory also provide guidance for regulation of such institutions.

As discussed in the earlier paper, both the
maturity transformation and the efficient monitoring views suggest that, given the costs imposed by crises and attendant bailouts, it may be desirable to allow financial institutions to issue short-term debt only if their assets do not have close publicly traded substitutes. Further, to minimize the incentive of governments to bail out institutions if a crisis occurs, such institutions should be separated from the payments system.

Any regulatory system must also take seriously the central role that banks have long played in the payments system. We have argued that this role may well be an artifact of a bygone era. Advances in information and communication technology make it feasible to access a wide array of assets, from stocks in public firms to portfolios of home equity loans, to undertake transactions. We have also argued that payments systems that require the use of demand deposits expose the economy to confidence crises and that it is possible to devise payments systems that do not require the use of debt-like claims, but instead use equity-like claims for transactions purposes.

These considerations suggest that the payments system should be both restricted and broadened. Transactions accounts should be restricted to institutions that mark the value of their assets to market continuously and that issue mutual-fund-like equity claims to owners. Such accounts should be broadened to institutions that are possibly very different from modern-day banks to include institutions such as stock and bond mutual fund companies.

We emphasize that the money market mutual fund as currently structured resembles a bank more than it does a mutual fund and therefore should not be allowed to issue transactions accounts. So, for example, Vanguard’s money market mutual fund (as currently structured) would no longer be allowed to serve as a transactions account, but Vanguard’s 500 Index Fund would.

The framework for regulatory policy implied by our analysis would lead to a banking system that is radically different from the one we currently have. Institutions that issue large amounts of short-term debt relative to their assets would be regulated and required to hold relatively little of their assets in publicly traded securities. The liabilities of such institutions would not serve as means of payment. The payments system would consist of institutions that issue equity claims.

Economic theory tells us that we do need banks. Theory also points us to constructive ways in which we can reform the financial system to make it more efficient and to ensure that crises that affect particular financial institutions do not spill over into the rest of the economy.

Endnotes

References

Chari, V. V., and Christopher Phelan. 2012a. What Assets Should Banks Be Allowed to Hold? Economic Policy Paper 12-3, (May) Federal Reserve Bank of Minneapolis.

Chari, V. V., and Christopher Phelan. 2012b. On the Social Usefulness of Fractional Reserve Banking. Working paper. University of Minnesota.

The benefits of government infrastructure projects in developing countries are obvious: Irrigation systems increase crop yields; schools produce educated, productive citizens; health clinics and sewage treatment plants enhance wellbeing. What isn’t so evident—in large part because it’s difficult to measure—is what happens when people flock to an area to take advantage of these benefits. New infrastructure may raise incomes and improve quality of life, but it may also put pressure on other community resources such as housing or transportation.

To measure the “congestion” effects from migration, economists typically use land prices as a proxy; new arrivals invariably drive up rents. But reliable price data simply aren’t available in many parts of the world. Recent research by Taryn Dinkelman, an economist at Dartmouth College, and Sam Schulhofer-Wohl, a senior research economist with the Minneapolis Fed, demonstrates an alternative method for gauging often overlooked migration effects in less-developed countries.

In “Migration, Congestion Externalities, and the Evaluation of Spatial Investments,” the economists use population growth as a yardstick for congestion and find that the impact of migration can be considerable, especially in areas where land is not priced. Rural South Africa is a case in point; in studying the consequences of an electrification project in that country, Dinkelman and Schulhofer-Wohl estimate that congestion effects, including crowded settlements and schools, cut the project’s per capita benefits in half.

If you build it …

The notion that congestion can diminish the benefits of location-specific infrastructure programs is well established, although migration effects have received less attention than direct, positive outcomes of those programs, such as higher incomes and improved health. A new public amenity like a hospital or a water treatment plant will continue to draw people until crowding of other shared public resources becomes so severe that in-migration ceases. “That intuition is pretty well understood in economics,” Schulhofer-Wohl said in an interview. “The challenge is how to measure that effect.”

To investigate the welfare impact of migration, the economists develop a model in which infrastructure upgrades in a rural area induce people to move there from the city. The government-funded facility raises local incomes (by allowing women to work outside the home, for example), but also increases the population—and demand for other public goods such as subsidized housing, schools and bus service.

Unlike standard analytical methods, the model doesn’t rely on land prices to estimate the impact of migration on welfare. Instead, the model looks at income and population data to determine the net effect of infrastructure improvements. “The existing methods work if there is a land market and you can observe the prices,” Schulhofer-Wohl said. “What we contribute is how to analyze these programs if either there’s a land market but you can’t observe the prices, or there isn’t a land market.”

That is the case in many rural areas of developing countries, including Dinkelman’s native country of South Africa. Large expanses of that country are state owned or communally held and are allocated based on tribal or family ties.

To put their model to the test—and illustrate the importance of migration in assessing the worth of infrastructure projects—the researchers analyze a government electrification project in KwaZulu-Natal (KZN), a South African province with high unemployment and no land market. The project extended electrical service to about 200,000 households in the late 1990s, and the primary impacts on labor market outcomes were documented by Dinkelman in a 2011 paper.¹

Welfare drain

Electrification in KZN increased employment, raising average incomes; but it also led to dramatic population increases in comparison with communities that didn’t receive electrical hookups. One outcome of population gain was crowded schools; student-teacher ratios rose by two-thirds relative to villages that remained off the grid.

To calculate the net per capita welfare impact—the degree to which congestion effects offset income gains—the economists feed into their model summary income and Census data gleaned from over 1,800 rural KZN communities. The output of the model is the monetary value of the project to residents, measured as a fraction of monthly income. It turns out that when congestion effects are accounted for, roughly half of that value—the per capita welfare gain from the electrification project—disappears (see chart). Thus, the study “provides the first empirical evidence from a developing-country context that congestion effects exist and can be quantitatively large,” the researchers write.

Large Chart

The model also shows that migration undercuts the benefits of infrastructure projects the most in places like rural South Africa that lack a functioning land market. Without rising land prices to signal increasing congestion, people keep moving into the rural area, consuming more communal land and other public goods and reducing welfare gains for all—an outcome that the researchers view as a version of a tragedy of the commons. Migration exacts a lower toll in areas with land markets because congestion is less severe, and landowners benefit from higher rents.

Accounting for mobility

Dinkelman and Schulhofer-Wohl see “broad relevance” for their model in gauging the costs and benefits of infrastructure projects in developing countries, where people are becoming increasingly mobile. In some cases, the net benefits of such programs may be less than supposed, because of resulting strains on public resources that are slow to respond to population inflows.

In areas without land markets or reliable price data, a means of quantifying congestion effects could help planners mitigate welfare losses—by spreading out projects, for example, or simultaneously expanding other public services such as schools or health clinics.

“Our hope is that people will use our work as a building block to be able to account for migration in evaluating these programs,” Schulhofer-Wohl said.

—Phil Davies

1 Dinkelman, Taryn. 2011. “The effects of rural electrification on employment: New evidence from South Africa.” American Economic Review 101 (7): 3078-3108.

Reprinted with permission from voxeu.org

Economists have long been worried about income inequality and its effects on welfare. For instance, workers with a college degree earn on average much more than those who did not complete high school. This disparity translates into large differences in consumption levels and hence welfare (see, for instance, Heathcote, Storesletten and Violante 2010). We argue, however, that these welfare differences are dwarfed by the differences in longevity between individuals in different socioeconomic groups, and mainly by differences in longevity between individuals of different educational levels.

In recent research (Pijoan-Mas and Ríos-Rull 2012), we use the Health and Retirement Study (HRS) to document the expected longevities at age 50 of different population subgroups of white men and white women. In particular, we look at the different expected longevities by educational groups, wealth quintiles, labor market status and marital status.

Main results

Figure 1 shows that the most important differences are linked to education, which turns out to be much more important than wealth. At age 50, a college-educated white man can be expected to live 6.1 more years than a high school dropout; in contrast, a white man in the top quintile of the wealth distribution is expected to live 3.8 more years than a white man in the bottom quintile. Very similar differentials hold for women.

Large Image

In addition, we find that a white man fully attached to the labor market (as a full-time worker or as an unemployed worker actively looking for a job) is expected to live 3.4 more years than an inactive individual; and a married white man can be expected to live 2.5 more years than an unmarried one. The differentials for women are substantially smaller, but still large.

To obtain these differentials, we did not compute life expectancies. Instead, we estimated a hazard model for survival, with the socioeconomic characteristic of interest and (self-assessed) health status as stochastic endogenous covariates. Then we used these estimates to compute expected life durations at age 50 for each group. Our methodology allows us to bypass the two problems associated with the use of life expectancy. The first problem is that people’s socioeconomic characteristics evolve over the life cycle (except for education) and hence so do the relevant mortality rates. For instance, one-third of white women who are married at age 50 become divorced or widowed before age 70. The second problem is that mortality rates tend to decline over time, and this may happen at different rates for people in different socioeconomic groups.

Decomposition

When we look at these longevity differences in more detail, we learn that they must be due to factors that evolve slowly with age. In particular, we use our estimates to decompose the differentials in expected longevity into three components:

1. differences in health among socioeconomic types already present at age 50,
2. different evolution of health conditional on socioeconomic status, and
3. different mortality rates by individuals with identical health but different socioeconomic status.

Large Image

Large Image

Time trends

We obtained our results with the pooled HRS data, which range from 1992 to 2010. The large temporal span of the HRS can be used to obtain some information about how these differentials in expected longevity have evolved over time. Previous estimates document large increases in life expectancy differences between education groups (see, for instance, Preston and Elo 1995; Meara, Richards and Cutler 2008; and Olshansky et al. 2012). Consistently, we find that the differentials for education have increased, between 1992 and 2008, by 1.8 years for men and 1.7 years for women. In addition, we also document important increases for wealth (1.4 years for men, 0.7 years for women), for labor market attachment (0.7 years and 0.6 years) and for marital status (1.0 years and 1.5 years).

These large increases happened during a time period when there was a sizable increase in income and wealth inequality. Although we do not want to make any causal statement, it is hard to avoid thinking that the increase in income inequality lurks behind the increase in the socioeconomic gradient of longevity. If so, we should conclude that the upsurge of income inequality in recent decades has had welfare implications much stronger than previously thought. Our results also show, however, that education seems to matter more than wealth. Therefore, it might very well be that the increase in the socioeconomic gradient of longevity is also tightly related to selection: Over the years, the pool of less-educated or unmarried people has become worse off in terms of their ability to survive.

References

Heathcote, Jonathan, Kjetil Storesletten and Giovanni Violante. 2010. “The macroeconomic implications of rising wage inequality in the United States.” Journal of Political Economy 118 (4): 681-722.

Meara, Ellen R., Seth Richards and David M. Cutler. 2008. “The gap gets bigger: Changes in mortality and life expectancy, by education, 1981-2000.” Health Affairs 27 (2): 350-60.

Olshansky, S. Jay, Toni Antonucci, Lisa Berkman, Robert H. Binstock, Axel Boersch-Supan, John T. Cacioppo, Bruce A. Carnes, Laura L. Carstensen, Linda P. Fried, Dana P. Goldman, James Jackson, Martin Kohli, John Rother, Yuhui Zheng and John Rowe. 2012. “Differences in life expectancy due to race and educational differences are widening, and many may not catch up.” Health Affairs 31 (8): 1803-13.

Pijoan-Mas, Josep, and Victor Ríos-Rull . 2012. “Heterogeneity in expected longevities.” CEPR Discussion Paper 9123.

Preston, Samuel H., and Irma T. Elo. 1995. “Are educational differentials in adult mortality increasing in the United States?” Journal of Aging and Health 7 (4): 476-96.

In “Financial Frictions and Fluctuations in Volatility,” a Minneapolis Fed staff report published in July, economists Cristina Arellano and Patrick Kehoe of the Minneapolis Fed and Yan Bai of the University of Rochester develop a model that can convincingly generate several central macroeconomic patterns seen in U.S. data during the Great Recession. In particular, the economists explore the financial and microeconomic underpinnings of sharp declines in employment and economic output between 2007 and 2009, accompanied by relatively stable labor productivity. In almost all recessions, productivity and output both decline, but in the most recent downturn, productivity was nearly unchanged. What economic mechanisms account for this anomaly?

One clue that informs their investigation is the severe credit contraction during the recent U.S. financial crisis. Another clue, at the micro level, is the large increase in dispersion of growth rates among firms—that is to say, growth at some companies suffered very little during the crisis, while other firms contracted dramatically. Even during normal times, companies grow at different rates, of course, but during the 2007-09 recession, the range between the highest and lowest growth rates nearly doubled.

These observations are building blocks for a quantitative model with heterogeneous firms (for which growth rates can differ) and financial frictions (meaning that credit markets don’t function smoothly). The economists’ goal is to create a model in which increasing volatility at the firm level leads to higher dispersion in firms’ growth rates along with declines in both aggregate labor and economic output, but stable labor productivity. Their aim, in short, is to better understand the U.S. economy during the recent recession by building a model that can replicate its behavior between 2007 and 2009.

Central to the model: Risk, and firms hedging against it by trimming financial obligations wherever feasible—specifically, by hiring fewer inputs. “They key idea in the model,” write the economists, “is that hiring inputs to produce output is a risky endeavor.”

Firms receive revenue from selling their output only after they have already paid for inputs, such as employees, necessary to produce that output. Hiring labor (or buying materials or purchasing machinery) therefore entails risk, since demand for a firm’s output may fall after the input expenditure is incurred. If financial markets were “complete,” as economists say, firms could protect themselves against that event by borrowing against future profits; but in this model, financial market frictions mean that firms must bear the risk themselves.

“This risk has real consequences if, when firms cannot meet their financial obligations, they must experience a costly default,” observe the economists. “In such an environment, an increase in uncertainty arising from an increase in the volatility of idiosyncratic shocks leads firms to pull back on their hiring of inputs.” (Though the word “hiring” suggests employees only, here it applies to other inputs as well: raw materials, capital equipment and the like.)

If we build it, will it work?

The economists proceed in stages. First, they build a “benchmark” model. Then they calibrate and quantify it to gauge how well it matches real U.S. data. They create two alternatives to their benchmark model to pinpoint whether the results are driven by both factors (imperfect financial markets and volatility shocks) or just one. Lastly, they extend their model with refinements that bring it closer to how economists believe economies truly work.

The model has three key pieces:

1. Firms hire inputs before knowing how much demand they’ll experience for their output.
2. Financial markets don’t necessarily provide firms with credit, and they’re especially averse when the economy is volatile; as a result, firms default if they’re unable to pay their debts.
3. Since firms pay a fixed cost to start their operations, they make positive profits in the future to cover those fixed costs; the cost of default is the loss of future expected profits.

These three essential parts mean that firms trade off expected risk and return whenever they choose their inputs. Hiring more inputs enables them to make more profit as long as they don’t default. But because more hiring raises their financial obligations, it also increases the chance of defaulting. It’s a tough choice, and becomes more so when the broader economy is looking uncertain—or, in the idiom of economics, “when the variance of idiosyncratic shocks increases.”

The model includes identical households, heterogeneous firms and financial intermediaries. Households buy goods produced by firms, but the demand for each good is subject to idiosyncratic demand shocks. The volatility of these demand shocks varies over time, and this is the source of aggregate fluctuations in the model. 

Firms are the guinea pigs in this model. They differ from one another, and they face not only volatile demand for their products, but imperfect or incomplete financial markets that don’t allow them to insure against fluctuations in that demand. Thus, they may sink or swim based in large part on those fluctuations, as well as their hiring decisions. If they default on their debts, they fail: They “exit the market.”

Benchmark and beyond

The benchmark model is calibrated to the U.S. economy with standard values for such variables as interest rates, annual sales growth for firms and the like. The economists test the model with these parameters by checking whether it can match U.S. data accurately; it does—with, for example, the fraction of labor employed by new firms at 1.8 in both data and model, and the liability-to-sales ratio at 5.5 in the data versus 5.6 from the model. A near-perfect fit.

Then they see how it responds to “impulses”—that is, how the model’s mechanism reacts to a sudden increase in demand volatility. In this test, just as in the actual U.S. economy during the recent crisis, the model’s output and labor (that is, employment) drop strongly when volatility increases, but labor productivity (defined as the ratio of gross domestic product to aggregate employment) increases slightly at first and then stabilizes. “The overall response,” the economists write, referring to labor productivity, “is fairly flat compared to the responses of output and labor.”

In addition, wages fall about 1.4 percent after the volatility shock and then continue a slow decline, and the interest rate drops just a bit initially and remains slightly depressed. The benchmark, in short, works well as a representation of the U.S. economy during the financial crisis, at least for one-time shocks in demand volatility.

They then build two alternate versions of the benchmark to investigate whether this success is due primarily to its inclusion of incomplete financial markets or to its volatility shocks. This investigation finds that “both financial frictions and the source of the shocks—volatility instead of productivity—are critical to our benchmark model’s results” (emphasis added). In other words, neither financial frictions by themselves, nor just volatility shocks, are able to generate economic responses that resemble the real world during the Great Recession.

Real world testing

But the fundamental question is, how well can this model account not for a theoretical one-time volatility shock, but for a series of shocks like those experienced in the real economy during the Great Recession? The answer: very well. “We show that our model can account for much,” the economists write.

To reach that conclusion, they first find the volatility shock sequence that generates dispersion among firms’ sales growth rates similar to that actually measured in U.S. data between late 2007 and the third quarter of 2009. The data reveal nearly a doubling in this range of growth rates, from 17 percent to 31 percent. The economists feed that shock sequence into their model and see what happens to macroeconomic output, labor and productivity.

Given how crude the model is—in the sense of leaving out countless aspects of an actual national economy—it does a remarkable job of generating results similar to real world figures. “The model generates a decline in output of 6.5 percent, whereas in the data output declines 9.7 percent,” they find. And it “produces about an 8 percent decline in labor, whereas in the data labor declines about 10 percent.”

While not dead on, the model’s results are quite close, suggesting that the mechanisms at its heart are what drive the actual economy, through good times and bad. When the economists summarize the overall results, they conclude that the model “can explain 67 percent of the overall contraction of output and 73 percent of the contraction in labor during the Great Recession.” The model produces a fairly flat productivity profile for the recession, while in real data, productivity first falls and then rises modestly. But “both in the model and in the data, productivity at the end of this event is essentially unchanged … even though output has fallen 10 percent.”

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Refinement

The economists explore several dimensions of, and refinements to, their model. One is to alter the model by introducing “sticky wages,” the idea that in the real world, most prices don’t change instantly. A gallon of gasoline may rise or fall in price several times a day or week, but wages, automobiles and even items on a restaurant menu take a while to adjust to trends in the economy—to a broad recession or to a rise in the cost of health care, steel or eggs. This factors into the model, since in the benchmark version of the model, wages fall when volatility increases, and such response dampens the labor adjustment firms make.

And indeed, by making the model’s input prices less responsive to volatility, the economists find that sticky prices “diminish offsetting equilibrium effects.” The charts on page 35 show their results. They compare real wage trends in the data, the benchmark model and the sticky real wage model for the entire span of the Great Recession and show that while they drop by about 2 percent in the data and over 8 percent in the benchmark model, “in the sticky real wage economy, real wages drop about the same as in the data.” Sticky real wages also amplify the output and employment effects of increased volatility.

Thus, Arellano, Bai and Kehoe’s model, with key features and additional enhancements, does a striking job of duplicating patterns seen in the U.S. economy in recent years. “Hence,” they conclude, “we think of the model as a promising parable for the Great Recession of 2007-2009.”

Mary Brainerd
Chair, Board of Directors
Federal Reserve Bank of Minneapolis

Good evening, everyone. My name is Mary Brainerd, and I would like to thank you all very much for being here this evening. I have the pleasure of standing before you in my capacity as the chair of the board of directors of the Federal Reserve Bank of Minneapolis. It’s a treat to be here tonight, and rather unique for me and for the entire board of directors. As you’ve just heard, we’re here to kick off a tour of the Bakken oil patch and to learn more about how the rapid development of the oil industry in recent years is reshaping the area’s economy. And I have to say, after hearing so many stories about the Bakken, I can’t wait to get a firsthand look.

I am going to take just a moment to tell you a bit more about my role on the board of directors, and also the role of my colleagues, and then I am going to introduce the president of the Federal Reserve Bank of Minneapolis, Narayana Kocherlakota. But first I want to add that in my day job, I am the president and CEO of HealthPartners, a Minneapolis-based nonprofit health care organization.

So, you may be wondering what a health services professional is doing on the board of directors of a regional Federal Reserve bank. I admit, when I was first informed that I was a candidate for the board, I had the same question myself. However, I soon realized that it made perfect sense. For example, I am joined on the board by a manufacturer of agricultural implements, a provider of social services, a leader in the development of water technology, and providers of financial services, to name just a few. Recent chairs of the board of directors have included a window manufacturer and representatives of labor organizations. Members of the bank’s board of directors have represented every sector of the Ninth District’s economy from the natural resources industry of Montana to the shipping industry of the Great Lakes, and everything in between, and from towns large and small.

So when you consider that one of the main roles of the Federal Reserve is to monitor economic conditions across the country, it does makes sense that people from diverse industries from the Upper Midwest should sit on the board of directors of a Federal Reserve bank. In addition, this expertise proves valuable to the board as we also provide oversight for bank operations; for example, I was privileged to be on the team that selected Narayana as president. As Narayana will describe in a moment, one of the great strengths of our regionalized central bank system is precisely that it requires such representative input. And I would add that it has been an honor and a privilege to serve on the board, and I’m sure all of my colleagues would agree, along with those in the room who have previously served on the board.

I could go on about the role of the directors, and I would be happy to take any questions at the end of Narayana’s remarks, but now I would like to introduce Narayana Kocherlakota, president of the Federal Reserve Bank of Minneapolis. His official biography is impressive: He is one of the top macroeconomists in the field today, and he has numerous journal publications to prove it. He has taught at Northwestern University, the University of Iowa, Stanford, and the University of Minnesota, where he served as chair of the economics department. He earned his Ph.D. in economics from the University of Chicago and his bachelor’s in mathematics from Princeton. He became the 12th president of the Federal Reserve Bank of Minneapolis in 2009 at the ripe old age of 45.

However, as impressive as all of that is, one of the things that strikes me most about Narayana is his ability to take complex ideas or problems and explain them in such a way that, well, a health services professional can understand them. Maybe this is the teacher in him, but whatever the reason, we are lucky to have someone like Narayana at the helm of the Minneapolis Fed these days. With so much attention on the Federal Reserve and its role in the economy, we need a good communicator who is willing to take the time to explain and to interpret economic events.

You’ll see what I mean in a moment. Ladies and gentlemen, please welcome Narayana Kocherlakota.

Narayana Kocherlakota
President
Federal Reserve Bank of Minneapolis

Thank you very much, Mary, for that introduction. And like Mary, I would also like to thank all of you for joining us here this evening as we begin our tour of the Bakken oil patch. This is my second visit in about a year. I was here last September for a similar tour and learned so much that I urged our entire board of directors to come out here too. They didn’t need much urging: One of our directors, Howard Dahl from Fargo, whom many of you know, has been telling us so much about this land of milk and honey that it was easy to persuade the rest of the board that they should see it for themselves. Having had a good preview last year, I know that everyone will be impressed, and not only with the drilling sites and crew camps, but also with all of the truck traffic that we will encounter as we approach Williston. At one point during my last trip, I was attending a meeting in Sidney, Montana, and we were waiting for a speaker from Williston. He called to say that he would be late, because of traffic. Now, I haven’t spent much time in western North Dakota, but my guess is that this is not something that I would have heard five years ago! More seriously—as we think about the tremendous economic returns that this area is experiencing, it’s important for us to keep in mind too that there are certainly some costs associated with generating those returns. And I’m sure we’ll hear more about those benefits and costs tomorrow.

So you’ve heard from Mary, and I’ve mentioned Howard. Let me begin by making quick introductions of the rest of the members of our board. As you listen to my intros, you might find it useful to keep in mind that the Minneapolis Federal Reserve district includes the states of Montana, North and South Dakota, Minnesota, and parts of Wisconsin and Michigan. Without further ado, then, here are the directors:

Mary Brainerd, president and CEO of HealthPartners, as you know, is our chair.

Randy Hogan, chairman and CEO of Pentair in Minneapolis, is our deputy chair.

And MayKao Hang is president and CEO of the Amherst H. Wilder Foundation in St. Paul.

Those three directors are what we call Class C directors, which means that they are appointed by the Board of Governors in Washington, D.C., to represent the public.

And then we have Howard Dahl, president and CEO of Amity Technology in Fargo.

Bill Shorma, president of Rush-Co/Strategic Rail Services in Springfield, South Dakota.

And Larry Simkins, chairman, president, and CEO  of the Washington Companies in Missoula, Montana.

Those three are what’s known as Class B directors. Like the Class C directors, Class B directors are representatives of the public. However, they are not chosen by the Board of Governors in Washington. Instead, they are elected by banks in the Minneapolis Federal Reserve district who are members of the Federal Reserve System.

And you’ve probably already guessed that our next group of three directors is termed Class A. These directors are elected by member banks in our district to represent those banks. And our Class A directors are:

Julie Causey, chair of Western Bank in St. Paul.
Ken Palmer, chairman, president, and CEO of Range Financial Corporation and Range Bank in Negaunee, Michigan, which is in the Upper Peninsula. And, finally, Dick Westra, president and CEO of Dacotah Bank in Aberdeen, South Dakota.

Also present today is Jake Marvin, chairman and CEO of Marvin Windows, and our former board chair who served our board for six years ending last December.

I would like to publicly thank all of these people for their public service. Being a board director is a job that demands much and returns little beyond the fulfillment associated with important public service. And this event is a great illustration of what I’m talking about. Like all of you, these are busy people with important responsibilities back home, so for them to take time from their schedules to tour a region of our district speaks volumes about their commitment. I should also mention that we are joined by members of our bank senior management team as well as other bank staff today. While I won’t take the time to introduce each of them, suffice it to say that this too is a group of highly dedicated public servants. They provide outstanding leadership and support to the Federal Reserve Bank of Minneapolis and the Federal Reserve System. I do want to particularly acknowledge Barb Pierce and Patti Lorenzen for their tremendous help in setting up the logistics for this visit. We are also quite fortunate to have two expert local tour guides for tomorrow: Loren Kopseng and Ron Ness. Before I go on, let me remind you that the following views are my own, and not necessarily those of others in the Federal Reserve.

As Mary described in her remarks, one of the strengths of the Federal Reserve System that Congress designed nearly 100 years ago, in 1913, is its system of regional banks and branches that ensures representation from citizens in towns and cities throughout the country, including relatively small communities like Springfield, Aberdeen and Negaunee. What I’m going to do in the remainder of my remarks is describe the decentralized nature of the Federal Reserve, especially as it pertains to monetary policy, and then discuss the role of the directors. After that, I will be happy to take your questions on these subjects or other issues on your mind this evening. In addition, as Mary noted, if you would like to direct a question to her about her role on the board of directors, she also stands ready.

So, to begin, the Federal Reserve Bank of Minneapolis is one of 12 regional Reserve banks that, along with the Board of Governors in Washington, D.C., make up the Federal Reserve System. Our bank represents the ninth of the 12 Federal Reserve districts, and, by area, we’re the second largest. As I mentioned earlier, our district also includes the Dakotas, Minnesota, northwestern Wisconsin and the Upper Peninsula of Michigan.

What do we do at the Federal Reserve Bank? Well, within the Federal Reserve we have clever ways of describing the work we do; for example, we use the highly technical term “three-legged stool” to describe our primary roles. Those three legs include payment services, supervision and regulation of financial institutions, and monetary policy. Very briefly, that first leg means that the Federal Reserve Bank of Minneapolis, along with the other 11 Federal Reserve banks, works to ensure the smooth movement of funds between banks, savings and loans, and credit unions through a nationwide electronic payments system. As for the second leg, the Federal Reserve Bank of Minneapolis supports the Federal Reserve System in ensuring a safe, sound and accessible banking system, and stable financial markets through supervision and regulation of the nation’s banking, financial and payments systems. This means that we implement rules and regulations as mandated by Congress. In doing so, we work with other federal and state agencies and regulators to promote safety and soundness in the operations of the financial services industry.

Obviously, I could spend a great deal of time speaking about those two responsibilities, especially supervision and regulation, which has grown in prominence since the financial crisis and the passage of the Dodd-Frank Act. However, I want to move now to the third leg of the stool, monetary policy, as this role is the one that most directly impacts the lives of Americans and is also where the role of our directors is most prominent.

Monetary policy is established by the Federal Open Market Committee, or FOMC. The FOMC meets at least eight times per year and consists of the seven governors of the Federal Reserve Board in Washington, the president of the Federal Reserve Bank of New York, and a group of four other Reserve bank presidents that rotates annually. For example, I was on the FOMC in 2011 and will be a member of the Committee again in 2014. However, all 12 Reserve Bank presidents—whether they vote or not—participate in FOMC deliberations. This is an important point, as it highlights the decentralized nature of the Federal Reserve’s policymaking. All of the presidents bring their perspectives on the economy to every meeting, and those perspectives are shaped, in part, by what we learn from our local districts. Our directors play a big role in that information-gathering process. At every board of directors meeting, a number of directors are charged with answering questions about trends in the economy. For example, are firms planning to hire? What are their capital expenditure projections? Are input prices changing? What are firms’ expectations for growth in the near and medium term? Our directors don’t just answer those questions from the perspective of their own companies; rather, they contact a number of businesses in their regions and industries to gauge broader business sentiment.

This type of information is very valuable to policymakers. As you might imagine, the Federal Reserve is very good at aggregating and analyzing data, but data often lag and do not give a complete description of what is currently happening in the economy. The information that I receive from our directors is important in helping me complete that economic picture. I should also note that the Federal Reserve Bank of Minneapolis has three advisory councils to seek further input from citizens in our district. These councils have members from the agricultural industry, small business and labor, and the financial services industry. As well, we have a branch office based in Helena (Mont.), and we receive valuable economic intelligence from the members of that branch’s board of directors.

So I have described the Federal Reserve’s decentralized structure, especially as it pertains to monetary policymaking, and I have also begun to explain the directors’ role by illustrating how they contribute to that policymaking. Now I would like to briefly describe some of the other roles of the directors. Directors, as you would imagine, do more than just provide economic intelligence—in particular, they also provide oversight of bank management. In some respects, this is similar to any board of directors. For example, through committees and board deliberations, directors review and approve the bank’s annual budget, review the bank’s annual performance, and oversee the internal audit program and the bank’s control environment. This oversight helps ensure that Federal Reserve banks are run as effectively and efficiently as possible. I know that I speak for all of our management team when I say that we benefit on an ongoing basis from the collective wisdom that gathers in our board room.

I began these remarks by introducing our board and describing the various classifications under which they serve. Those classes—A, B and C—may seem rather mundane, but they are really quite meaningful. Again, Congress had a good idea about how the Federal Reserve should be structured when it formed the System a century ago, and it has stood the test of time. That first group I mentioned, the Class C directors who serve to represent the public, are appointed by the Board of Governors in Washington, D.C. That last point is key because it ensures that the Board of Governors, which is appointed by the president and approved by the Senate, has a say in the makeup of our board of directors. So in that respect, our local board of directors has a direct connection to the federal government in Washington, which is important. The second group, the Class B directors, are also chosen to represent the public, but they are elected by member banks from each district. This too is important because it ensures that the public is represented by directors who are chosen locally, and not by Washington. In this way, the framers of the Federal Reserve Act carefully balanced national and local interests in the composition of bank boards of directors.

The last group, the Class A directors, who are elected by member banks to represent those banks, are the ones that have received some attention of late. Since the financial crisis and the extraordinary measures that the Federal Reserve has taken to prevent the collapse of our financial system, some have questioned whether it is appropriate for bankers to sit on the boards of Federal Reserve banks. Isn’t it wrong, these critics say, to give bankers power over those who are supposed to supervise them? It would be wrong if that were the case, but members of the board of directors—bankers or not—have no say in how Federal Reserve banks conduct their supervisory operations. Supervisory matters are handled directly between bank staff and the Board of Governors in Washington, D.C. Supervisory matters are not a part of the business of the board of directors.

However, what is a part of board business is the important information that bankers relate about credit conditions in the economy, about issues pertaining to the payments system and about general business conditions. This is precisely the kind of information that policymakers need to do their job, whether under extraordinary or normal economic conditions.

Our board of directors and our senior management team have made this trip out to western North Dakota to learn more about what makes your economy tick. But I’m glad, too, to have had this opportunity to tell you a little about our board of directors—a group of dedicated public servants whose role is often misunderstood by many. Now, I am sure that you have a number of questions. Mary and I look forward to doing our best in answering them. Thank you very much for your time.

In the United States, where inflation remains low but unemployment stubbornly high, policymakers eagerly seek to boost economic activity. To that end, Congress and the Obama administration have wrestled over numerous expansionary fiscal policies. Several have been implemented, but with limited success.

The Fed, for its part, has nudged the fed funds rate toward zero—since December 2008 and counting—until it can go no further. The goal is to encourage business investing and consumer spending by minimizing the cost of borrowing.

Since hitting the zero bound, the Fed has tried nontraditional policy tools to stimulate the economy. The three major tools are the large-scale asset purchase programs, the maturity extension program and the Fed’s new forward guidance policy.^1/ All three are designed to bring down long-term interest rates and thereby stimulate household and business spending.

A better path?

The economics profession (let alone policymakers) has yet to reach a consensus—or concession—on the correct policy avenue to pursue.

A recent paper, “Unconventional Fiscal Policy at the Zero Bound”, by Juan Pablo Nicolini of the Minneapolis Fed, with Isabel Correia, Emmanuel Farhi and Pedro Teles, proposes a novel fiscal strategy. The four economists lay out a series of fiscal policy measures that would relieve the zero bound faced by monetary policymakers caught in the liquidity trap. It’s this constraint, the impossibility of forcing nominal interest rates below zero, that undermines the Fed’s standard policy intervention of lowering borrowing costs by injecting still more liquidity into credit markets.

The economists’ fiscal policy proposal generates negative real interest rates that will stimulate investing and spending. And it will do so, the paper illustrates, effectively and efficiently—avoiding the harmful consequences of the more conventional fiscal policies advocated by some economists and the possibly long-term inflationary pressure that alternative monetary policy steps might create.

Creating inflation with taxes

It’s a promising scenario, but as the economists acknowledge, their strategy of a tax policy that neutralizes the effects of the zero bound constraint is “unconventional.” Explaining it requires careful technical description—it’s a 50-page paper—but the central idea is fairly intuitive.

To encourage consumers and firms to engage in normal economic activity when the economy is stuck and nominal interest rates are at zero requires negative real interest rates. And “the only way to achieve negative real interest rates,” note the economists, “is to generate inflation.” (Recall Irving Fisher’s eponymous equation: The nominal rate equals the real interest rate plus inflation.) This will make holding on to money costly; the longer cash sits in your wallet, your savings account or under your mattress, the less it will buy. Purchasing power will relentlessly dissipate. To avoid poverty, people will spend and businesses invest.

However, caution the economists, generating inflation for producer prices is inefficient; it would create economywide distortions that reallocate resources wastefully and result in lower economic output than would otherwise be possible. Instead, “the idea is to induce inflation in consumer prices while keeping producer price inflation at zero,” they write (emphasis added). “The result is negative real interest rates, and yet the distortions associated with producer price inflation are altogether avoided. This can be achieved by simultaneously adjusting consumption and labor taxes.”

The strategy, then, is to raise tax rates on consumption and lower them on labor. But what’s critical is that these changes continue over time. So the consumption tax rise isn’t just a one-time hike, but an enduring upward trend. (Indeed, one way to implement this would be to initially reduce consumption taxes and slowly bring them up; the key thing is that consumers face consumption costs that will be more expensive in the future than they are today.)

So, to reiterate, the hike and cut are ongoing: Rates climb over time on consumption and fall steadily on labor. The consumption tax, because it rises over time, effectively increases the price of purchasing something a year from now, making it advantageous to spend now—boosting economic activity.

Why cut labor taxes? Ongoing consumption tax hikes mean that workers have to put in more labor hours to pay for the constantly rising cost of products and services; that would alter labor decisions inefficiently. To prevent that distortion, labor tax rates must decline in mirror image to the rising consumption tax rates and, by effectively increasing take-home pay, balance out the increasing cost of consumer goods.

Changing consumption tax rates also distort investing decisions, generating temporary underinvestment in capital. To avoid this, a temporary investment tax credit or short-term capital income tax cut is also essential.

Reality check

The economists point out that others have raised similar ideas. In 2002, Harvard’s Martin Feldstein suggested that to escape its own persistent liquidity trap, Japan could raise its consumption tax rate and reduce income tax rates. In 2008, economists Robert Hall and Susan Woodford proposed sales tax holidays at the state level.^2/

Both proposals hinged on the same fulcrum: Future consumption taxes must be higher than current taxes. The Hall-Woodford sales tax holiday proposal, for instance, would lower the tax immediately to zero and commit to increase it in the future, thereby encouraging consumers to spend now and thus spur the economy.

But this research paper is the first with a model that formalizes the concept and includes the additional taxes necessary for its efficient implementation. The greater part of the paper is devoted to the model’s mathematical structure and specification, and then its elaboration in alterative economic environments (when lump-sum taxes aren’t possible, for example, or idiosyncratic shocks occur).

The economists go further, measuring outcomes under a variety of tax rate scenarios to see if the necessary tax rate changes would be reasonable in scale, not just a theoretician’s pipe dream. And the plan does, indeed, seem practical.

To implement this plan under one feasible scenario, they calculate, tax rates on consumption that are 5 percent in the midst of the liquidity trap would increase over five quarters (15 months) to 14 percent. Simultaneously, labor income taxes would decline from 28 percent to 21 percent. A 9 percent investment subsidy would be implemented immediately and slowly unwind to zero.

Benefits and caveats

Such policies would yield substantial economic benefits relative to the stagnant status quo. Assuming prices and wages are somewhat rigid or “sticky,” meaning that they don’t change instantly, the unconventional fiscal policy would generate a 1 percent increase in consumption over 10 quarters and a 0.2 percent permanent increase. If some price or wage flexibility exists, increases would be greater still; flexible prices and rigid wages would result in increases of over 4 percent temporarily and nearly 1 percent permanently. In the world of economics, these are substantial gains, especially in the moribund landscape of a liquidity trap.

Other appealing features of this strategy: It’s revenue neutral—though it alters tax rates, it requires no net tax increase to implement. And it’s “time consistent”—an economist’s way of saying that policymakers won’t be tempted to change it later to achieve a better outcome.

In closing, the economists caution that this strategy does crucially hinge on the willingness to implement a policy of flexible taxes. But “after witnessing the policy response to the recent crisis in the United States and elsewhere,” they observe, “it is hard to argue for lack of flexibility of any fiscal policy.” Recent examples in the United Kingdom, the United States and Spain demonstrate that, faced with a recession that seems unending, policymakers will adopt promising policies—no matter how unconventional they may first appear.

1/ For a more complete description, see remarks by Chairman Ben Bernanke, “Monetary Policy since the Onset of the Crisis,” Aug. 31, 2012, at the Federal Reserve Bank of Kansas City Economic Symposium in Jackson Hole, Wyo. Also see the Board of Governors Maturity Extension Program and Reinvestment Policy page at Monetary Policy since the Onset of the Crisis. The Federal Open Market Committee provides forward guidance in its meeting statements. The Sept. 13, 2012, statement, for example, says, “To support continued progress toward maximum employment and price stability, the Committee expects that a highly accommodative stance of monetary policy will remain appropriate for a considerable time after the economic recovery strengthens. In particular, the Committee also decided today to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that exceptionally low levels for the federal funds rate are likely to be warranted at least through mid-2015.”

2/ Minneapolis Fed President Narayana Kocherlakota discussed related ideas in a 2010 speech, based on work by Nicolini and his co-authors.

What is the value of higher education?

This spring the Minneapolis Fed held its 24th Annual Student Essay Contest, which is open to all high school students in the Ninth Federal Reserve District. The contest drew 320 essays from schools throughout the district. The winning essay is published here. Other top essays can be found under the Student Resources section of the Community & Education tab.

Thirty finalists each received $100. The third-place winner received an additional $200, and the second-place winner an additional $300. The first-place winner, Matthew McFarland of the Blake School in Minneapolis, received an additional $400 and a paid summer internship at the Minneapolis Fed.

There are plenty of factors to weigh in making decisions about what to do after high school graduation. Family and social expectations are important, but the decision is fundamentally an economic one. Higher education is a major investment. How to weigh the costs and benefits is different for everyone, but the decision has tremendous significance for individuals and for society as a whole. Entrants in this year’s essay contest were asked to evaluate such decisions using economic principles.

Theoretical research to date is inconclusive in the sense that integration could lead to either divergence or convergence of cycles. Much depends on the source of the overall, or aggregate, fluctuations, suggests theory. If the negative shock is to a national banking sector and its efficiency, then problems in one country will likely spread to others, as global banks will also likely pull funds from unaffected countries. In other words, if Citibank Europe goes down, it’s likely that operations of Citibank U.S. will be negatively affected.

But if the crisis is a negative shock to a specific nation’s “real” economy (that is, a nonfinancial sector), then that crisis could actually lead to a divergence in international growth, since banks will tend to pull credit from affected nations and send more of it to untroubled economies, where it’s likely to provide higher returns. So, if Volkswagen is a customer of Citibank Europe and Volkswagen gets into trouble, then Citibank will devote more funds to U.S. firms, improving conditions in the United States.

The issue is quite relevant from the policy perspective. A better understanding of the mechanisms at work could clarify the potential impact on the United States of a euro-area meltdown or aid developing countries in understanding whether more financial integration with the rest of the world is desirable.

To bring greater clarity to the “ambiguous, and sometimes conflicting, answers” from the empirical and theoretical literature, Fabrizio Perri of the Minneapolis Fed, with economists Sebnem Kalemli-Ozcan and Elias Papaioannou, has written “Global Banks and Crisis Transmission,” National Bureau of Economic Research Working Paper 18209, July 2012, and forthcoming in the Journal of International Economics^1/ . Their paper takes on two tasks: It analyzes relevant data, and it then creates a model to help explain what the data reveal. In so doing, it tells a consistent and compelling story of the relationships between global financial integration, co-movement in business cycles and banking crises. The study is not the final word on these matters, of course, but it will undoubtedly lead future research in fruitful directions.

Key empirical findings

The economists begin by analyzing a unique database: quarterly data on country-pair bank links from 20 developed nations between 1978 and 2009. The three-decade period is one of international financial calm, by and large, punctuated by several financial crises, particularly that of 2007-09. A critical feature of the data set is that it provides information about indirect banking links as well as direct ties, thereby permitting measurement of the importance of financial exposure between countries through banks in offshore accounts in, for example, the Cayman Islands. Their statistical analysis—running regressions of relevant variables—reveals three central findings:

• When financial markets are calm, the association between banking links and business cycles is significantly negative—consistent with the study mentioned earlier.
• In periods of financial crisis, this negative correlation approaches zero. This suggests that “a financial crisis is an event that induces co-movement” among countries that share financial links, thereby muting the usual negative association.
• During the 2007-09 financial crisis (though not in other crises  in the period studied), there was  a positive association between business cycle synchronization and exposure to the U.S. financial system. But curiously, indirect links through the Cayman Islands were a powerful explanatory factor in this financial contagion. “The positive correlation between output synchronization and financial linkages to the U.S. emerges only when, on top of direct links to the U.S., we also consider indirect links via the Cayman Islands, the main off-shore financial center of the U.S. economy.”

These findings provide a logical bridge between two separate bodies of research on financial integration: one that looks at business cycles and another that focuses on financial contagion. Financial crises spread contagiously from one country to another through bank connections, it appears, and this creates greater business cycle co-movement among countries that are tightly connected financially. During the recent crisis, many observers believed that the U.S. credit shock spread internationally via bank networks, but empirical evidence for the idea was largely absent. That evidence now exists.

In part, the quality of the study’s data set is what allows the economists to provide this elusive confirmation. Its depth and structure enable them to distinguish the effect of financial connections between individual country pairs from the impact of large shocks common to all nations. With its greater historical range, a better measure of financial integration and solid panel data, the researchers can isolate the specific importance of bilateral financial links.

A model with credit shocks

The second part of the paper is devoted to building a model of international business cycles with banking and then running it quantitatively, to see if, with reasonable parameters, it can generate patterns seen in actual data. The idea is to create a mathematical representation of the economic mechanisms that may be at work in an integrated financial world. If this model can faithfully replicate real-world results, then those mechanisms—and the theory behind them—may in fact be a reasonable explanation, during crisis and calm, of the impact of global banks on national economies.

The economists create an international business cycle model in which global banks allocate funds between, on one hand, households and others who save and, on the other hand, firms and other borrowers who invest those funds—the process referred to as “financial intermediation.” In this model, both banking shocks and productivity shocks can cause economic fluctuations. As the economists write, the model serves two purposes: “to precisely spell a causal link between financial integration and business cycle synchronization” and “to show that our empirical findings can be used to identify sources of output fluctuations, and thus to shed light on the causes of the triggering and spreading of the 2007-2009 crisis.”

They calibrate the model with standard real-world parameters for factors like depreciation rates and capital’s share of output, but also for less standard variables like the degree of financial integration between pairs of countries, the costs incurred by banks in intermediating funds and banks’ share of portfolios devoted to risky assets.

Testing: One, two, three …

With the model built, the economists see how it performs. First they show that when run with both banking shocks and productivity shocks, the model generates plausible business cycles and, indeed, helps explain some features that standard models (without credit shocks) have trouble with. Standard models without credit shocks can’t generate realistic values, for example, for changes in employment relative to gross domestic product or international correlations in consumption.

Then they give it the real test: checking its quantitative results against the empirical results from the first part of their paper. The primary test is to run the same regression equation on the model’s artificial data as they ran earlier with the empirical (real-world) data. If roughly the same relationships appear in both, the model is a good fit and the mechanisms it contains hold explanatory power.

In specific, they compare results for synchronization of GDP growth among countries—business cycle co-movement. During tranquil times, the data show a synchronization coefficient ranging from -0.302 to -0.220. The model generates a coefficient of -0.35—the correct sign (negative) and a close numerical match. During crisis periods, the data’s output coefficient ranged from 0.123 to 0.264. The model: 0.25—an excellent fit.

“The comparison between coefficients,” they write, “suggests that the relation between financial integration and output co-movement implied by our model is statistically close to the one we estimate in the data.” Both model and actual data indicate that when financial times are calm, greater bilateral financial integration leads to diverging business cycles, but when crises hit, this negative relationship is muted, as credit shocks transmit through international banking ties and business cycles synchronize more closely.

Lessons and future research

The model suggests that financial integration is a crucial determinant of synchronization of business cycles. When compared with the statistical relationship seen in real-world data, the model’s estimates are quite close. “Although this does not formally prove that financial integration is indeed a causal driver of international business cycle integration,” the economists observe, “it shows that this hypothesis is entirely consistent with the data patterns.”

A second lesson from their model is that credit shocks are crucial in explaining the tendency for nations with close banking ties to contract simultaneously during crises. “This leads us quite naturally to conclude that indeed large credit shocks to financial intermediaries could have been the underlying source of the global contraction in economic activity that took place during the 2007-2009 global crisis.”

The model also suggests an obvious direction for future research, say the economists: “the analysis of the effectiveness and desirability of policies geared toward reducing capital losses of the financial/banking sector, like the 2008 bailout.” The model indicates that capital losses to banks strongly affect domestic and international economic output; in the future, policymakers might therefore consider measures to prevent or buffer such shocks, or to mitigate their transmission to the broader economy.

1/ See “ Not-So-Great Expectations,” Region, December 2011, on related research by Perri.

Interview conducted July 25, 2012

Financial Incentives and Medical Practice

Region: I’d like to start with a few questions regarding your research on incentives and health care. Your 2008 Quarterly Journal of Economics study of tort reform and birth outcomes with your husband, Bentley MacLeod, and your 2011 paper together that broadened this “joint and several liability” research beyond childbirth procedures suggested that economic incentives play a crucial role in both the U.S. tort system and medical practice.

Could you tell us more about this work on the complex and sometimes conflicting financial incentives in health care and how it might relate (if at all) to your June 2012 NBER paper on physician-induced antibiotic use in China …

Currie: Yes, it’s all very closely related, actually …

Region: And for that matter, perhaps also to your much earlier American Economic Review paper with Jonathan Gruber and Michael Fischer on physician payments, which found that increasing Medicaid/private fee ratios significantly decreased infant mortality rates.

Would you tell us more about this body of work?

Currie: Sure. Physician incentives are extremely important for the health care system, and everyone—or at least all health economists—thinks that financial incentives can distort people’s decisions. But it’s very hard to pin that down. There’s a lot of literature on things like small area variations in use of medical care saying that utilization rates are much lower in Minnesota than they are in Florida, for instance, but people don’t live longer in Florida, even though they get extra care.

Region: The Dartmouth research.

Currie: Yes. It’s argued that these variations show there’s waste or inappropriate utilization, but that’s not a very direct way to go at it. The QJE piece on C-sections was looking at a specific argument about why doctors might be doing too much, which is that they’re afraid of legal liability. It’s very common for people to say doctors do too much because they’re afraid of being sued if they don’t. But there’s a really obvious alternative hypothesis, which is that doctors do too much because the more they do, the more they get paid.

Region: Sure. Incentives work.

Currie: Yet no one ever says that, so in our paper, we look at how people respond to changes in the liability environment. One of the things we realized while we were doing it is that for something like childbirth, the doctor often doesn’t really face any financial liability because if you have jurisdiction with Joint and Several Liability (JSL), people are going to go for the deep pocket. The deep pocket is not the doctor; the deep pocket is the hospital.

If you actually go and read these cases, sometimes they seem very strange. You have a C-section; something goes terribly wrong. And instead of talking about what went wrong in the surgery, they’re spending all of their time saying, “Well, the nurse should have done this or that.” The reason for that is that the nurse is an employee of the hospital, while the doctor is an independent contractor. So if you want to nail the hospital, the deep pocket, you have to show that the nurse was negligent.

The upshot of our study is that different types of tort reforms have quite different effects. We found that if you put caps on damages, you actually got more C-sections, not less. People found that counterintuitive because their belief was the reason the doctors are doing C-sections is to avoid liability.

Region: The conventional wisdom, right?

Currie: Yes, but on the other hand, if you’re doing too many C-sections and causing surgical complications, then putting caps on damages makes you do more and not fewer.

JSL reforms, which had been largely neglected, are interesting from an economic standpoint because they get you away from this deep pockets regime to one where you’re going to sue the hospital and the doctor. So it increases the doctor’s legal liability if they do something wrong.

Region: So the new JSL regime apportions liability among concerned parties, not simply to the deepest pocket.

Currie: That’s right. And it reduced C-sections. So our results point to the idea that the reason we have so many C-sections is that doctors make twice as much money doing them, which is the same thing we had found in an earlier study of Medicaid fees where we were looking at the differential [in payment] between doing a C-section or doing a normal delivery. When that differential increased, the rate of C-sections went up for the Medicaid people. So it’s consistent with that.

In the more recent paper about JSL, we were trying to look more broadly at what happened to accident rates. We’re looking at accidental deaths, and most accidental deaths are actually among the elderly. Many of them are trip-and-fall cases: Somebody leaves something lying around or doesn’t fix the handrail, and an elderly person falls and dies. And again, we found that going away from the common law regime that encouraged going after deep pockets to a legal regime where everybody is responsible for the damage that they cause reduced accident rates.

Region: So there, too, the economic incentives mattered. And then there’s the Chinese study—a totally different culture, a very different health care system.

Currie: Well, yes, but economists think that people are the same everywhere, right? In some fundamental sense.

In China, you don’t go to the doctor, you go to the hospital. Everybody’s treated on an outpatient basis. Also in China, hospitals are financed largely from drug sales. There’s a very strong incentive to sell people drugs. Our study was an experimental audit where we sent people complaining of vague symptoms suggestive of mild colds or flu to clinics and then kept track of what medicines they were prescribed.

The results were really kind of hair-raising in the sense that none of the people we sent in should have gotten antibiotics, but I think 60 percent of them got antibiotic prescriptions. Most of them got more than one antibiotic prescription, and many of them were getting very sophisticated, expensive antibiotics that you’re not supposed to use for trivial infections because they’re supposed to be saved for more dangerous sorts of infections.

Region: And you had three or four variations in that study, with, for instance, patients offering gifts to the doctor or clearly stating that the doctor’s recommendation would not influence what they would actually do.

Currie: Yes, in our initial study, our people [the “patients”] just presented with these symptoms, and the experimental treatment was that they would say, “I saw on the Internet that you shouldn’t give antibiotics for a cough or cold.” That simple intervention reduced antibiotic prescriptions by 20 percent. But other researchers said to us, “Well, that doesn’t really establish why the doctors are prescribing the drugs. Maybe they’re prescribing the drugs because they think that’s what the patients want.”

We wanted to get at that mechanism, and so in our second experiment, we had a number of different treatments. The results of the gift treatment were very striking. The person comes in and gives this really trivial gift. We have a picture of it. It’s this funny pen with a little “Hello Kitty” or something on it. The “patient” also makes a little speech about how much they respect doctors, which perhaps is the real gift involved. In this experiment, the doctors who receive the pen are less likely to prescribe antibiotics, and they also spend a longer time with the patient and generally are more attentive. They do respond to that small gift. And so, we thought, that shows that the doctor doesn’t think that the antibiotics are what the patient wants because if it was, then they would be responding to the gift by doing more of what the patient wants instead of less.

Region: It makes one think about the impact of far more significant gifts from the manufacturers, often through pharmaceutical reps.

Currie: Oh, yes, there’s a huge literature on that. It’s very interesting. If you Google “pen and pharmaceuticals” or “pen and doctor,” you come up with all of this literature where people are arguing about whether physicians can be influenced by a trivial gift like a pen, which pharmaceutical companies give out all the time, along with little memo pads or things like that.

Region: Let alone funding medical conferences and the like.

Currie: That’s right; everybody realizes that, yes, conference funding could influence people, and so that’s bad. But there are lots of people who’ve written in very respected publications saying, “It’s ridiculous to think that doctors’ behavior could be influenced by these trivial things.” I suppose the same people would say, “Oh, you can’t learn anything from a study about these Chinese doctors because they’re poor, or maybe a pen means more to them,” or something. I don’t think so. I think it’s just human nature to want to reciprocate.

Health Insurance and Health Care

Region: With several colleagues, over a number of years, you’ve examined the impact of public health insurance, such as Medicaid, especially in the context of managed care, and the effect of expanding public health insurance on health care utilization and health status. You’ve also looked at the interaction between private and public provision of health care.

Two studies in particular caught my eye—your 2011 work with Douglas Almond and Emilia Simeonova of the expiration of Hill-Burton requirements in Florida and your 2007 piece with Anna Aizer and Enrico Moretti on Medicaid managed care in California.

What does this research, those two and the others you’ve done, tell us about the incentives, market structures and public institutions that are most conducive to provision of quality health care at a reasonable cost?

Currie: Yes, that’s a good question. I think both of those papers show that providers are incredibly responsive to incentives and that they typically find the least costly way to deal with mandates. Maybe they also say something about unintended consequences of laws. The Hill-Burton study looked at this old law …

Region: Enacted in 1946.

Currie: Yes, but it went on for some period of time, and hospitals that got money under Hill-Burton were required for 20 years to devote 3 percent of their revenues to indigent care. We show in our study that the hospitals did do that: They were spending 3 percent of their revenues on indigent care. But the other thing—and this is consistent with some work that Mark Duggan did in California—was that we looked at who they choose to serve [Duggan, Mark. 2000. “Hospital Ownership and Public Medical Spending.” Quarterly Journal of Economics 115 (November): 1343-74].

The hospitals seemed to have looked around and said, “OK, what class of patients are the best people to serve, given that we have to serve a bunch of indigent people?” And they picked pregnant women. Most pregnant women are healthy. They typically have a short stay, so you don’t have this huge right tail of expenses.

But they don’t look around and say, “Oh, let’s get elderly diabetics,” right, who might have a huge right tail, or kidney dialysis people. So we were looking at what happened when these mandates expired. Many hospitals just closed their maternity units. They were like, “OK, we can get out of that business.” In our data, we were able to follow the same women over time, and we saw women being shifted from one hospital to another either because the maternity service closed or because the hospital would no longer take Medicaid.

I think that’s the most striking thing, is how rapidly the hospitals responded and how much they can change their service mix to try and attract the type of patients that are profitable. Also, it doesn’t really make very much difference whether they’re private hospitals or public hospitals or for profit or not.

Region: Yes, that surprised me a bit. You might expect different reactions from private versus public providers. And your 2007 study?

Currie: On Medicaid managed care. The whole argument about managed care is that if you have a patient and you have a capitated payment for that patient, then you should want to be providing preventive care to them so that you minimize your costs down the road.

I think the problem with that argument from the point of view of Medicaid is that there’s so much churning of patients on and off Medicaid that the company looks at you and instead of saying, “I should provide you good preventive care,” they say, “There’s a good chance you’ll be gone in a couple years and not my problem, so I want to give you as little as possible.”

Added to that, in this particular case, was the fact that in California, they had carve-outs out of the managed care contracts. Carve-outs are things that don’t have to be covered by the capitated payment. It turned out they had a carve-out for neonatal intensive care, which sounds fair on the face of it because neonatal intensive care is very expensive, and so maybe it is unfair to the plan to expect it to be covered by the one capitated payment if they happen to get a very sick infant. But that meant that Medicaid managed care plans had zero incentive to try to prevent very sick infants because if the infant was sick, the cost of care would go back to the state program.

Impact of the Affordable Care Act

Region: In this context, it was roughly a month ago that the Supreme Court issued its ruling on the Affordable Care Act. Given this ruling, what is your sense of the impact of the reform bill on health care in the United States, specifically child health?

Will this part of the “invisible safety net,” as your book calls it, become more secure than it now is? Or does the decision’s limit on federal powers over Medicaid expansion by states mute that effectiveness?

Currie: There are a bunch of different issues with respect to children. The original legislation focused on extending Medicaid to low-income, able-bodied adults. That mostly didn’t affect children because poor children are already covered up to age 19, and in a lot of states, the children are covered up to 200 percent or even 300 percent of the poverty level. There might have been an indirect effect on children through the workings of the whole system in that if hospitals ended up being more stable or being more able to offer indigent care or something like that, then perhaps there would have been a spillover onto children.

The Supreme Court ruling could have several potential effects on children. One is that if states choose not to participate in the Medicaid expansion for adults, then hospitals are in big trouble. In the negotiations over this bill, hospitals agreed to give back money to Medicare on the understanding that there were going to be many more people who had health insurance, including Medicaid, so that the burden of providing indigent care would be reduced. Hospitals anticipated that they would do at least as well or better under the ACA than they had been doing before.

Now, with the ruling, in a big state like Texas, for example, if the hospitals are getting less for Medicare and they don’t get the people coming in with health insurance, then they’re in big trouble. Hospitals may have been not very profitable for a long time, so reducing their revenues further could have negative effects on the provision of indigent care or care to existing Medicaid patients, including children. So that’s one way.

But then a more direct threat, I would say, to children is that a number of states seem to be interpreting the ruling as saying that the federal government can’t boss them around when it comes to Medicaid and they can change the provisions of the program however they like. Maine has already thrown many thousands of 19-year-olds off their Medicaid program. There was also a headline today saying that 14 states were restricting the services covered under the Medicaid program.

States have many things they have to cover, and then there are a bunch of things that are optional. States have always had the right to cut back on the optional things. But it may be that they’re taking this Supreme Court ruling to mean that they can challenge the federal government’s ability to mandate what must be covered. And if that’s true, then you could have essentially a rollback in many states of the Medicaid coverage that children have. That would be really bad for kids. So the really scary part about the Supreme Court ruling is that it could have the effect of undoing a lot of the Medicaid expansions for infants and children that happened from the ’80s basically through the middle of the ’90s.

And my research suggests that would be really bad.

Labor Markets in U.S. Health Care

Region: I’d like to ask about your paper on hospital staffing and market structure in California, Cut to the Bone? Very intriguing work. Could you summarize that study briefly and tell us what bearing it might have for the future of labor markets in the U.S. health care industry?

Currie: We were looking at the big hospital chains. One of the things that have been going on in the hospital market is that big chains like Tenet or HCA have been taking over hospitals. We wanted to see how they reorganized the hospitals when they took them over. What we found was that they tended to change the way that the hospital was staffed.

Although there is a large literature arguing that there is monopsony in the market for nurses, we did not see any effect on nurse wages or employment levels when a hospital was taken over by a chain. But nurses were expected to work harder after the takeovers, in that they ended up with more patients per nurse. We couldn’t, in that paper, show that there were direct effects on health, but it seems likely that there might be because many of the things that go wrong in hospitals have to do not really so much with doctors, but with the quality of the nursing care that people get.

Region: Do you have any sense of what impact, therefore, current consolidation trends in the United States might have on labor markets in health care? Of course, there’s huge demand for nurses now, and there are many nursing strikes.

Currie: There is a high demand for nurses, but the quality of the nurse labor force may fall over time if wages stay constant while the effort that is demanded rises. Also, a lot of schools that used to train RNs in four-year programs no longer do that; the nurses are being trained in community colleges with two-year degrees. So you’re getting a different sort of person doing it.

Region: Less human capital.

Currie: Exactly.

Women in Economics

Region: As you well know, women are underrepresented in economics, from undergraduate to professional levels. This is a broad question, but what are the impediments, trends and possible means of addressing this inequality?

Your research on mentoring is of particular interest here, of course. Your findings on the CeMENT program established by the Amercian Economic Association’s Committee on the Status of Women in the Economics Profession (CSWEP) suggested that mentoring could indeed have an impact on professional development.

Have you or others been able to follow up on the results reported in 2010, which I believe covered CeMENT participants from 2004 to 2008, with a look at how those and the January 2010 cohort have fared?

Currie: One of the main impediments to women in economics is the same impediment for women in STEM [science, technology, engineering and mathematics] fields generally, and that is an underrepresentation in math historically. Now perhaps that’s going to go away. I understand that for girls in high schools, test scores are now exceeding boys’ test scores in math as well as in reading, whereas before it used to be the reverse.

So women have been catching up. But when they go to college, they still tend not to go into STEM fields and not to take mathematics. These days, if you don’t have any math background, it’s virtually hopeless to try to do an economics Ph.D. program. You can’t even get off the starting block. I think that’s one issue.

Another issue is the whole work/family thing. The problem there is more societal than it is with academic employers. There are problems with academic employers, and people think that universities could do more, but by and large, a university is an incredibly flexible workplace compared to most other workplaces. … Many departments really do kind of bend over backwards to help people manage their work/family issues.

Personally, I found that the major challenges had to do with [my children’s] schools. Schools are always expecting you to show up in the middle of the day and on very short notice, which is odd given that they are largely staffed by working women themselves. They put pressure on mothers who are not able or willing to, say, show up with cupcakes on short notice.

And it’s always the mom who is supposed to do that. If you’re a dad and you do anything at the school, then you’re a hero, whereas if you’re a mom and you don’t show up at least a couple of times a year, then you’re just a bad mother. That kind of societal expectation is I think much more oppressive than most of what I experienced from my employers.

Region: And trends for women in economics?

Currie: Well, the trends are, I think, slow—very slow—improvement over time. It takes an awfully long time for people to go through graduate school and go through the hierarchy and become full professors somewhere.

Region: It’s a long pipeline.

Currie: Yes, it is. I think role models are important too. I know some women don’t believe that, but personally, you know, when [Harvard economist] Claudia Goldin visited when I was a graduate student, that was tremendously influential for me. I am not sure that Claudia herself believes in role models, but she was a tremendous role model for me. I think the lack of successful role models has been an issue, though that has certainly changed with, for example, the recent female Clark medalists, Susan Athey, Esther Duflo and Amy Finkelstein. [See the interviews with Goldin and Duflo in the September 2004 and December 2011 Region, respectively.

Now, the mentoring aspect is interesting in part because it’s such a small intervention. What we do in CeMENT is to bring young female academics together for a couple of days at the end of the AEA convention. Women who apply are first grouped according to field, and then we randomly assign them to be in the treatment or the control group. At the meeting, the women from each field who are in the treatment group meet with a senior mentor and a junior mentor. And they are supposed to submit a piece of work, which everybody in their group reads and discusses with them. Other sessions deal with work/life balance, the tenure process, grant writing, the publication process and other issues as well.

What we found in the initial evaluation was that there did seem to be a positive effect of being in the program in terms of publications and grants. Maybe you could say it was directly because of the intervention. You know, you bring a piece of work, people look at it and then you’re more likely to get your piece of work published.

We are following up people over time. We don’t survey them, but we look for their CVs online and see how they’re doing. I guess I’ll probably be doing that for the foreseeable future, trying to track down these cohorts every couple of years. Some of the anecdotal evidence was really very interesting about who benefits and why they benefited from it. Some women felt very isolated. They often had no other woman to talk to. If they felt they had problems that their male colleagues wouldn’t understand…

Region: Cupcake expectations.

Currie:Yes, cupcakes. Then they would ask other members of their group about that. Also, when they graduate, some people are better connected than others, you know. One of the benefits of coming from an elite program is that you know people who also came from an elite program, so you tend to be better connected in the profession. If you don’t have that advantage, you may not have any kind of group. We saw that people who were not as connected to begin with, or who had no women in their departments, seemed to rely on the group they were assigned to as a sort of peer group to discuss issues with and to get advice.

The mentors don’t actually get contacted a whole lot, but they often do get contacted for advice about the really big things like, “I’m putting together my tenure package. Should I include this or that?” Or “What should I say when they ask me about letter writers?” So it seems like people gained access to an unbiased senior person who could help them when it really counted.

I don’t know if it will ultimately play out in terms of a difference in tenure rates, for example, which is the hope, because it is a quite small intervention. But I think it has had some positive effects already.

Early Childhood Education

Region: As you know, the Minneapolis Fed has long been interested in the economic impact of early childhood education, and we were honored to have you participate in our 2003 conference. [See “The ABCs of Early Childhood Development” in the December 2003 Region.] At that time, you presented a paper on the “black box” of Head Start—what we knew at that time about what does and doesn’t work in the Head Start program.

Your research suggested that more expensive programs were more effective in terms of gains in reading and vocabulary, and that spending should focus more on children and less on programs for parents and community development.

What have we learned since then about the impact of Head Start, specifically, and other ECE programs, more generally?

Currie: Well, one thing is that I was very happy to learn that my initial results seemed to hold up.

Region: Always reassuring.

Currie: There’s a paper by David Deming, which uses the same research design as my early work on Head Start. [Deming, David. 2009. “Early Childhood Intervention and Life-Cycle Skill Development: Evidence from Head Start.” American Economic Journal: Applied Economics 1 (July): 111-34.

But in the NLSY [National Longitudinal Study of Youth] data you can now follow the children for much longer. He looks at outcomes when they’re teenagers and finds generally positive effects. There’s another paper by Pedro Carniero and Rita Ginja looking at Head Start using a somewhat different research strategy, which finds positive effects on mental health outcomes. The focus on mental health in that paper is certainly an important new direction for research on early childhood. I have been surprised in my work on the longer-term effects of mental health problems in childhood by how big the effects are relative to the effects of physical health problems. [Carneiro, Pedro, and Rita Ginja. 2009. “Preventing Behavior Problems in Childhood and Adolescence: Evidence from Head Start.” University College London.

I think a lot of the early childhood research focus has shifted to this possible link between health and educational outcomes. For example, there is the question of whether kids are suffering from low birth weight or things related to low birth weight, and maybe that’s what’s leading them to end up in special education. What are the things that cause that? That’s something I’ve been spending time on, trying to look at whether pollution or stress or other things during pregnancy might have an impact on health at birth, which would then lead to poorer educational outcomes.

Fetal Origins of Inequality

Region: That certainly leads to your research on fetal origins, so perhaps we could talk about that. Since your work with Rosemary Hyson in 1999, if not earlier, you’ve been exploring the long-term relationship between health and economic outcomes.

In your 2011 Ely lecture to the AEA, you reviewed much of this research on determinants of health at birth and their link to adult outcomes, with new evidence about in utero exposure to pollution. And you shed further light on mechanisms underlying perpetuation of poverty.

Recently, you’ve explored the economic side of the fetal origins hypothesis. And you’ve been looking at early disease environments and their long-term effects on both mothers and children.

Could you briefly review the fetal origins hypothesis and how economists have expanded its reach—to test scores, education and income as well as health?

Currie: I think the phrase itself was coined by David Barker, a physician who was interested in whether there was a biological mechanism such that if the fetus was starved in utero it would be more likely to be obese or more likely to have heart disease or diabetes, things related to that in later life. The idea is that you are sort of training the fetus to think this is a hungry environment so that they should be really thrifty with food. An infant programmed in this way would then be more likely to gain a lot of weight later on and to have diseases related to obesity. So that was specifically what the fetal origin hypothesis was about.

I believe Thalidomide was the first thing that really shocked people and showed that if you give drugs to the woman, that it could have an effect on the fetus. People were also working on the Dutch “Hunger Winter” prior to Barker, looking into whether being literally starved in utero had long-term effects.

So economists have taken that idea and run with it. Economic studies are examining a wide range of things that might affect fetal health and asking whether they have long-term consequences. I think there’s pretty broad acceptance now of the idea that all kinds of things that happen when people are in utero seem to have a long-term effect.

One of the things I talked about in my Ely lecture was what mechanism might underlie the long term effects, and I raised the idea of “epigenetic” changes as one possibility. The way I like to think about that is you have the gene, which only changes very slowly when you have mutations. But then kind of on top of the gene you have the epigenome, which determines which parts of the gene are expressed. And that can change within one generation. There are animal experiments that do things like change the diet of guinea pigs and all the baby guinea pigs come out a different color. It can be pretty dramatic.

Region: So, far different, and far quicker, than natural selection.

Currie: Yes, it’s a different mechanism, and it makes some sense from an evolutionary perspective because it’s a way for populations to change rapidly when it’s necessary. The idea is that the fetal period might be particularly important because these epigenetic switches are being set one way or another. And then once they’re set, it’s more difficult to change them later on.

I think we haven’t really been able to look at all of the implications of that given the limitations of the data. We don’t have very much data where we can follow people from, say, in utero to some later period. But, that’s where the frontier is, trying to do that kind of research and make those linkages. What I’ve been able to do is to categorize a whole set of things that have systematic impacts on the fetus. I’m really happy I didn’t know any of these things when I was pregnant.

Region: How old are your kids?

Currie: My kids are 12 and 15, so I didn’t learn about any of this until afterwards. I would have been a nervous wreck!

I think a really interesting thing about the fetal origins hypothesis for public policy is that if it’s really important what happens to the fetus, and some people think that maybe the first trimester is the most important or the most vulnerable period, then you’re talking about women who might not even know that they’re pregnant. It really means you should be targeting a whole different population than, say, 15 years ago, when we thought, oh, we need to be targeting preschool kids instead of kids once they reach school age. Now we’re kind of pushing it back. Then it was, “We need to be playing Mozart to infants.” Now the implication is that we’ve got to reach these mothers before they even get pregnant if we really want to improve conditions.

Epigenetics implies that it does not make sense to talk about nature versus nurture. If nature is the gene and nurture is the thing that sets the switches, then the outcome depends on both of those things. So you can’t really talk about nature or nurture in most situations. It has to be some combination of both.

Region: It just struck me that that contrasts a bit from your early childhood education finding that you don’t want to focus program spending on mothers or parents. Focus on the kids, not on the moms.

Currie: That’s true enough. I guess a cynical view would be, “Well, if they’ve already had their kids, then there’s no point, right? Quit worrying about them.” But many moms who have one young child are likely to have another, so maybe that would be a good way to target them. But in a different way than they get targeted now.

The NBER Summer Institiute

Region: One more question, about your work as director of the NBER’s Program on Families and Children. You’ve pulled together a number of papers that will be presented here in Cambridge tomorrow. What key themes are you hoping will be covered at that session? And therefore, what themes are you perhaps hoping to encourage in future economic research? I don’t know if that’s how you choose papers but …

Currie: Well, the way I choose papers is that people submit them, and we had an awful lot of papers submitted this time, and then we just pick the ones that seemed best.

But, indeed, some themes do seem to be emerging. One thing that is interesting—and I’m starting to do a little bit of work like this myself—is thinking about children in developing countries. Things we’re looking at here in the United States, like the effects of in utero exposure to pollution on child health and economic outcomes, involve problems that are much worse in developing countries.

So if we can find an effect here … for instance, my E-ZPass paper suggested that the incidence of low birth weight was 8 percent higher for pregnant women who are subjected to large amounts of auto exhaust because they live near highway toll plazas. If that is true here, then what must be the effect in Beijing? It must be even bigger than that.

Region: Right, or other sorts of pollution that you’ve looked at: toxic releases or factory closings/openings, for instance.

Currie: Yes. So one thing I’m excited about is that people are starting to think about these issues in developing countries. I think it’s really important in a sense that if there are children in developing countries who are damaged from the start because of the conditions they’re exposed to in utero, or in early childhood, then that would definitely be a drag on development.

And conversely, another thing I was thinking about is that you can have this kind of perverse selection effect. Suppose conditions get better and children who would have died now survive; if those children are nevertheless unhealthy, then you could have mean health decline over the short term with development.

Region: The human capital and health care costs associated with that would be enormous.

Currie: Right. So I think these are really important issues in developing countries, and they’re starting to be addressed. So, tomorrow, we have a number of papers looking at Indonesia, Colombia and India as well as one looking at the relationship between family size and children’s education across a large number of developing countries.

Another of tomorrow’s papers that’s directly relevant to the discussion we have been having is by Bruce Meyer and Laura Wherry about Medicaid expansions to teenagers. As I was saying, there were Medicaid expansions in the ’90s. Their study shows that black children who gained insurance coverage as pre-teens has lower future mortality rates.

And there is more work on Head Start. Marianne Bitler, Thurston Domina and Hillary Hoynes are presenting a paper looking at distributional impacts of Head Start. Interestingly, they find larger effects for Hispanic children than other groups, which is something I had also found.

Region: It’ll clearly be a very interesting program tomorrow. Thank you so much.

In this Research Digest, the Region reviews three examples of such work, recent studies by Minneapolis Fed economists and their colleagues on distinct aspects of the Great Recession. The first digest looks at international synchronization (or lack thereof) of economic cycles and the factors that may cause nations to climb or plummet in concert; the second explores interactions between financial frictions and firm-level volatility, and whether a model built around these phenomena might explain economic patterns seen in U.S. data between 2007 and 2009. And the third examines policy alternatives to pull an economy out of the doldrums when in the midst of what monetary economists refer to as a “liquidity trap”—when interest rates have reached the zero bound.

Abstract

Fifty-eight years ago, Arnold Harberger estimated that the costs of monopoly, which resulted from misallocation of resources across industries, were trivial. Others showed that the same was true for tariffs. This research soon led to the consensus that monopoly costs are of little significance—a consensus that persists to this day.

This paper reports on a new literature that takes a different approach to the costs of monopoly. It examines the costs of monopoly and tariffs within industries. In particular, it examines the histories of industries in which a monopoly is destroyed (or tariffs greatly reduced) and the industry transitions quickly from monopoly to competition. If there are costs of monopoly and high tariffs within industries, it should be possible to see those costs whittled away as the monopoly is destroyed.

In contrast to the prevailing consensus, this new research has identified significant costs of monopoly. Monopoly (and high tariffs) is shown to significantly lower productivity within establishments. It also leads to misallocation within industries: Resources are transferred from high- to low-productivity establishments.

From these histories, a common theme (or theory) emerges as to why monopoly is costly. When a monopoly is created, “rents” are created. Conflict emerges among shareholders, managers and employees of the monopoly as they negotiate how to divide these rents. Mechanisms are set up to split the rents. These mechanisms are often means to reduce competition among members of the monopoly. Although the mechanisms divide rents, they also destroy them (by leading to low productivity and misallocation).

Introduction¹

In standard economic theory, monopoly leads to a welfare loss. This loss stems from a misallocation of resources across industries: Too few goods are produced by the monopolist; too many in other industries. Economic theory had long suggested that this welfare loss exacted high costs from the economy. But modern understanding took a turn when, in a landmark 1954 paper,² Arnold Harberger analyzed the quantitative significance of monopoly costs in the United States. Were these costs as high as conventional economic theory suggested? The clear but surprising answer that Harberger provided was no.

Harberger estimated that, contrary to his expectation and to standard theory, the costs of monopoly were quite trivial. “We come to the conclusion that monopoly misallocations entail a welfare loss of no more than a thirteenth of a per cent of the national income. Or, in present values, no more than about $1.40 per capita,” he wrote. “I must confess that I was amazed at this result. ... Monopoly does not seem to affect aggregate welfare very seriously through its effect on resource allocation” (Harberger 1954, pp. 85, 86, 87).

Other economists extended Harberger’s work to estimate costs associated with tariffs, and here, too, the costs were trivial. A consensus quickly developed that Harberger’s conclusion was indeed valid.

Recently, a new literature has taken a different approach to understanding the costs of monopoly. Looking within industries, it examines the histories of industries in which a monopoly is destroyed and the industry transitions quickly from monopoly to competition, as well as the histories of industries that rapidly moved the opposite way, from competition to monopoly. If there are costs of monopoly, those costs should be whittled away as the monopoly is destroyed. Likewise, if an industry is monopolized, costs should be created. In both cases, costs should be apparent when comparing the industry before and after monopolization.

Several industries have been studied with this method, including transportation in the United States and U.S. manufacturing of sugar, iron ore and cement. The historical records of these disparate industries show that there are costs of monopoly and tariffs within industries. In these industries, this new literature has shown that monopoly led to, among other costs, the following:

1. Low productivity at each factory. That is, for any given amount of inputs, monopoly meant that less output was produced than under competition.
2. Misallocation of resources between high- and low-productivity factories. That is, monopoly led to resources (capital, labor, etc.) being transferred from productive factories to unproductive factories. Again, this misallocation occurs within an industry and is different from the misallocation that Harberger studied.

In sharp contrast to Harberger’s finding, these studies show that the welfare costs associated with monopoly and tariffs are not small. The consequence of cases (1) and (2) above is that industry output could have been produced with fewer inputs. One way to measure the loss, then, is to calculate the value of the “wasted” inputs. The histories of these industries show that as monopoly was destroyed in each, productivity at each factory soared. Doubling of productivities in a few years was common. The value of the wasted inputs was as much as 20 percent to 30 percent of industry value added.

A common theme (or theory) emerges from the histories as to why monopoly led to these costs. When a monopoly is created, “rents” are created. (In this usage, “rent” is the difference between what a factor of production is actually paid and what it would need to be paid to remain in use; as such, it is a measure of that factor’s monopoly power.) Conflict emerges among shareholders, managers and employees of the monopoly as they negotiate how to divide these rents among themselves—or, more colloquially, how to “split the spoils.” Mechanisms are set up to split the rents. Although they divide rents, they also destroy them (by leading to low productivity and to misallocation).

As used in this paper, the term “monopoly” means more than the strict definition: an industry with a single producer. One industry mentioned later in the paper was a cartel for 40 years. Conflict over rents emerged between groups in the cartel, firms, workers and managers. In some industries, there were high tariffs (and other forms of protection). This high protection led to strong incentives among groups in the domestic industry to form monopolies. Firms attempted to collude, and workers formed industrywide unions (i.e., monopolies). So, the statement that “tariffs led to large welfare losses” means that tariffs led to incentives to form monopolies and then to actual monopolies, and these monopolies then led to large welfare losses.

A body of literature in the 1960s and 1970s argued that the costs of monopoly and tariffs were not trivial, saying (in essence) that there were costs within industries. This theoretical literature, and why it did little to dent the “Harberger consensus,” is briefly reviewed in Minneapolis Fed Staff Report 468, on which this policy paper is based. In this policy paper, I discuss historical studies that look at the collapse of monopoly. I describe how the monopolies emerged and how they were destroyed. Then I discuss the mechanisms that were used to split rents and why these mechanisms led to welfare losses.

Monopoly: Its Creation and Destruction

When a monopoly is created, the government often has a hand in the process. This is the case in most of the industries studied, to greater or lesser degrees. In U.S. sugar manufacturing, the government played a central role in creating monopoly. During the Great Depression, sugar manufacturers were permitted, indeed encouraged, by U.S. law to form a cartel.

Many U.S. cartels were created during the Depression (as part of the New Deal), but the New Deal sugar cartel survived much longer than most. For 40 years, from 1934 to 1974, the industry was repeatedly able to renew the U.S. laws that enabled it to operate as a cartel. Soaring world sugar prices in 1974 resulted in the cartel losing political support, and the laws permitting it to operate as a cartel were not renewed.

To describe the government’s role in creating monopoly in the other industries, a useful approach is to first sketch a very simple model. Consider an industry where transportation costs are large relative to production costs. If the domestic price is initially set equal to the cost of domestic production, then domestic producers will have a strong incentive to push their price up to the sum of foreign production cost plus the cost of transportation (or tariff) involved in bringing the foreign product to domestic markets.

The incentive to do so is great in this “industry” because, by assumption, transport costs are large relative to production costs. A very large tariff will be an incentive to increase prices, just as a large transportation cost would.

If the transportation or tariff cost is large, assume that groups will make investments to form monopolies. Firms will attempt to collude, and workers to form strong unions. Some groups may succeed. If later on protection is cut, the incentives to make these investments will fall, and the monopolies will weaken (or disappear). This same logic applies if, rather than a transportation cost advantage, local firms have a production cost advantage.

This simple abstraction is a good representation of both the iron ore and cement manufacturing industries. In the early 1950s, U.S. producers had production cost advantages over foreign producers, and the industries received significant protection. Groups invested in creating monopolies. At various times, firms in these industries were charged with trying to collude. The U.S. government investigated the industries for antitrust violations. It is unnecessary to enter into the argument as to how effective collusion was; there is little doubt that very strong, industrywide unions emerged in these industries. Although antitrust laws in the United States made firm collusion difficult, building monopoly unions was easier. Collective bargaining laws enacted by the U.S. government allowed unions to organize all workers in an industry and not be bound by antitrust laws.

The monopolies in these industries—in particular, the strong monopoly unions—lasted for many decades in the post–World War II period. The monopoly unions were able to provide very high wages. For example, by the 1970s, cement workers were paid as much as U.S. autoworkers (who were the highest-paid manufacturing workers). The unions also had very stringent work rules (as described later on).

In the 1980s, the monopolies in these industries weakened or were dissolved. The union in the cement industry dissolved. In the iron ore industry, the union did not disappear, but lost much of its clout. For example, work rules became much less stringent, and plant managers had more control over how to structure plant operations.

Why the weakening of the monopolies in the 1980s? Foreign producers were now threatening to enter local markets. Brazil offered to sell iron ore in Chicago and Cleveland, the heart of the U.S. market, at half the local price. Firms around the world offered to sell cement on the West Coast and Gulf of Mexico at half the U.S. prices.

How could foreign firms offer to sell at such discounts? There are two proximate reasons. First, transportation costs greatly decreased (relative to production costs) in the postwar period. This, by itself, would have meant a weakened incentive for continued investment in keeping monopoly. But, second, the production cost advantage of U.S. producers decreased. This development was, of course, to be expected, as the whole purpose of creating strong unions was to increase wages (and hence costs). The monopolies also led to lower productivity, increasing costs further. But what was striking is that U.S. producers were at a production cost disadvantage.

An obvious question is: Why did the unions (and other groups discussed later on) push wages so high and lower productivity to the point where foreign producers could offer such steep discounts? At least three possibilities come to mind. First, the groups realized that wage demands and work rules would lead to the demise of monopoly, but that this strategy was the best. Second, the groups realized that wage demands and work rules would lead to the possibility of foreign entry, but they expected more government protection than they were able to receive. Many calls for protection were made, and some protection was given, but it was not enough. Third, perhaps the outcome (foreign entry) was not expected. Although I do not know which story best describes the events, the story itself is not important for the issue at hand. The main point is that there are significant costs of monopoly and tariffs.

Monopoly: Splitting the Spoils (and Destroying Them as Well)

During the period when monopolies in these industries were strong, groups set up mechanisms to split rents. Here I discuss some of the mechanisms used and how they led to the destruction of rents—in particular, to low productivity and misallocation. When monopoly was weakened in these industries, the mechanisms were abandoned, leading to large productivity gains in establishments and to resources being reallocated from low- to high-productivity producers.

One mechanism used to split rents was competition-reducing rules. Here I discuss two types that were used: quotas and work rules.

Quotas
In the U.S. sugar industry, the New Deal cartel included factory owners, factory workers, farmers, farm workers and others. As the cartel was established, each of these groups sought to secure (for themselves) as large a share of rents as possible. A major mechanism to split rents was quotas. In the cartel, firms were given quotas—the right to sell a certain amount of sugar each year.

Incumbent farmers also sought, and were successful in acquiring, quotas—the right to grow sugar beet crops on a given number of acres each year. Without these quotas for incumbent farmers, nothing stopped firms from moving the locations of their factories or even using different farmers in the same location. Just as firms in the cartel used firm quotas to limit competition, incumbent farmers wanted quotas to limit competition among themselves (and from other farmers). Without these quotas, there was no way to ensure that incumbent farmers would receive a share of the monopoly profits.

As is often the case, these quota rights (both those of the firms and those of the farmers) could not be sold. Although the allocation of quotas for acres in 1934 was “efficient,” over time there was a change in the comparative advantage of locations in manufacturing sugar. Hence, there emerged a significant misallocation of resources between factories, with low-productivity factories producing too much sugar and high-productivity factories too little.

I can estimate the magnitude of the welfare loss due to these mechanisms to split rents (the quotas), that is, from the misallocation of resources within the industry. Recall the introduction to this paper, which mentioned that one way to measure welfare loss is to calculate the value of wasted inputs in producing industry output. The estimates indicate that the losses were roughly 20 percent to 30 percent of industry profits.

Work Rules
In the iron ore and cement industries, those who were in a position to gain from the large transportation costs into local markets, and the protection offered by tariffs, were the factory owners, factory workers and even the local governments (e.g., townships) where factories were located. What mechanisms were used to acquire rents? Local townships placed significant taxes on the production of iron ore and cement. Workers formed very strong unions. Although claims of collusion within both industries have been made, these claims are harder to document than the taxes and union contracts that emerged in these industries.

A major mechanism to split rents was the work rules in union contracts. Among other things, work rules were a way to limit competition among workers. They were structured so that managers could not play workers off each other.

Union contracts split the tasks in plants into groups or categories. Workers were then assigned to one of these groups or categories, that is, given the right to complete tasks in that category. Only the workers in this group could complete the tasks assigned to the group. Very often these distinctions among workers were arbitrary in that a worker in a particular category was able, but not allowed, to complete tasks in many other categories.

These types of work rules dividing work among members of the union are most often called job classification systems. They are similar to the quotas discussed earlier. In particular, work rules are a way to limit competition between workers, just as quotas limited competition between farmers. They ensure that groups of workers receive a share of the monopoly profits. But they also destroy profit.

What is the quantitative significance of work rules? In the 1980s, when the work rules in the iron ore and cement industries were made much less stringent, labor productivity doubled in a few years. Other productivities increased as well. If these increases in productivity can be tied in large part to the relaxing of work rules, then obviously these are big welfare gains.

We can estimate the magnitude of this welfare loss due to these mechanisms to split rents (the work rules), that is, from the low productivity in establishments. Again, one way to measure the welfare loss is by the value of the wasted inputs. With these work rules, machines were down longer than necessary. The energy that was being consumed elsewhere in the plant when output was not produced was a wasted input. Capital was also wasted, as work rules meant that disabled machinery took longer to repair than was necessary.

Labor input was wasted as well. For example, a machine operator could not hold a tool for a repair person (who would need to bring in another repair person for such tasks). The value of this wasted input was the opportunity cost of the machine worker’s time multiplied by the amount of time involved. A rough estimate suggests a dead-weight-loss-to-industry-value-added ratio of 16 percent to 17 percent. (See Staff Report 468, pp. 14-15, for details of this calculation.)

Using a dead-weight loss for the wasted capital and energy of a few percentage points (possibly more) of value added, together with the wasted labor estimate of 16 percent to 17 percent of value added, gives an estimate of over 20 percent in total.

Splitting the Spoils: Other Industries, Other Countries and a U.S. Cost Estimate

In other industries as well those just discussed, and in other countries, work rules have likely led to the same type of misallocation—with low-productivity plants producing too much output and high-productivity plants too little. However, I cannot be sure of their quantitative significance because no studies like those described in the preceding section have been completed for these industries.

Many U.S. industries had significant market power after World War II, first by virtue of the devastation that many countries faced as a result of the war and later because of government protection of U.S. manufacturing. Monopolies emerged; in particular, the postwar years saw the emergence of industrywide unions in the auto, steel, paper, tire, airplane and chemical industries, to name a few.

What mechanisms were used to split rents? The job classification systems discussed earlier are prevalent throughout manufacturing (though for the most part are less stringent today than a few decades ago). Some observers of these industries hold the view that work rules led to low productivity in plants.

Stringent work rules likely led to low productivity in establishments in many manufacturing industries. In some, they led to other types of distortions and losses not seen in the cement and iron ore industries. As I suggested earlier, work rules in these industries likely led to misallocation—resources being transferred from high- to low-productivity plants. High wages (and stringent work rules) have likely led to another type of misallocation in industries: a change of technology (in order to escape the wages and work rules).

A similar phenomenon—that is, monopolists splitting (and destroying) rents—occurs in other countries. In Britain, job classification systems (referred to as “job demarcation rules”) are widespread. Demarcation rules are also used in France. In both countries, research suggests that these rules lead to reduced productivity.

I finish this section with a back-of-the-envelope estimate for the within-industry costs of monopoly and tariffs for the United States. This will enable a preliminary stab at the question, are these welfare losses similar in magnitude to Harberger’s losses (0.1 percent of value added), or can I conclude that they may well be significantly larger?

Industries that are known to have strong unions and rigid work rules include mining, utilities, construction, transportation (in particular, airlines and railroads) and parts of manufacturing, in particular, durable manufacturing (steel, airplanes, autos). Assume that work rules had similar negative impacts on productivity in those industries as they did on the industries discussed in detail earlier—again, about 20 percent of industry value added.

Adding together the total value added of these industries thus affected (just over 25 percent of total gross domestic product in 1977) enables an estimate of welfare losses from monopolies and tariffs of roughly 5 percent of GDP (=20 percent loss of 25 percent GDP share). (Further calculation details are in Staff Report 468.) Again, this calculation is obviously extremely crude, but it does suggest that the losses may well be orders of magnitude larger than Harberger’s estimated losses.

Costs of Monopoly: Summary and Observations

Research on the theoretical and quantitative significance of monopoly costs has evolved considerably since the mid-1950s, when Harberger’s influential paper suggested—in contrast to the prevailing view among economists—that in the United States, the costs of monopoly resulting from resource misallocation across industries were actually quite insignificant.

This paper reviews a new stream of research that uses a different approach to analyzing the costs of monopoly. It examines the costs of monopoly and tariffs within industries rather than across them. In particular, it examines the histories of industries in which a monopoly is destroyed (or tariffs greatly reduced) and the industry transitions quickly from monopoly to competition.

Over considerable time spans and a wide range of industries, this research finds that monopoly exacts high costs in two ways: (1) through misallocation of economic resources between high- and low-productivity factories and (2) by decreased productivity at each factory. The historical studies call the Harberger consensus into question. At least in the industries studied thus far, monopoly and tariffs have led to significant welfare losses, on the order of 20 percent of value added.

A common thread runs through these histories, one that suggests a theory. When a monopoly is created, rents are generated. But the distribution of these rents—splitting the spoils—causes conflict among shareholders, managers and employees of the monopoly. These parties devise mechanisms to split the spoils, but the mechanisms often lead, paradoxically, to the destruction of rents.

The implications of this theory of monopoly costs, and of the empirical findings of high costs, deserve serious consideration by policymakers as they design and enforce antitrust measures. Government policies themselves, such as tariffs and other forms of protection, are an important source of monopoly. This review of recent research indicates that the costs of such protectionist policies are considerable and should be fully recognized and appreciated. Furthermore, policy reforms to minimize these costs should be carefully considered.

As for future economic research, a key question is to understand why mechanisms (such as work rules) are used to split rents when they also self-destructively wipe out rents. Why can’t members of the monopoly structure contracts that avoid such large wasted resources? Differences in information? The inability of parties to commit to future actions? Such reasons may well be why mechanisms intended to split rents also destroy them.

Endnotes

1 The author thanks Tasso Adamopoulos, John Asker, Doug Clement, Tom Holmes, Pete Klenow, Sam Kortum, David Lagakos, Justin Pierce, Todd Schoellman and Arilton Teixeira. See a more complete version of this policy paper.

References

2 Harberger, Arnold C. 1954. “Monopoly and Resource Allocation.” American Economic Review 44(2): 77–87.

Matthew McFarland
The Blake School
Minneapolis, Minnesota

In evaluating the beneficial externalities that justify government support for higher education, society must look beyond the economic benefits, such as increased productivity. Individuals who have invested in higher education develop stronger civic and communal values. Education strongly encourages political activity, public awareness, community involvement, personal and familial health, reduction in crime and acceptance of basic democratic values. These behaviors occur because investment in human capital increases the opportunity cost of inefficient time and resource allocation. Government investment in education is not only an investment in the economy; it is also an investment in the strength of the democracy itself.

The economics behind the higher rates of civic activity resulting from education can be explained by examining the costs and benefits of socialization. Glaeser, Ponzetto and Shleifer (2007) state, “A primary aim of education is socialization” (p. 79). Fundamentally, education imparts stronger communication and social interaction skills. An individual capable of effective communication increases his/her potential contributions to a group effort and the group’s potential as a whole. As communication becomes easier, the cost of collaboration decreases. The opportunity cost of rejecting cooperation also increases with communication proficiency. The well educated spur their peers to participate in politics by using their developed persuasion/communication skills. Educated individuals are drawn toward collaboration because a group of efficient communicators is more effective than the sum of the individual parts (due to specialization). These individuals understand the necessity of cooperation to effect political change (see Glaeser, Ponzetto and Shleifer 2007).

The effects of education on democratic activity are clear. Dee (2003) states that college entrance correlates to an increase in voting by almost 30 percent above the average. He finds that education increases the rate of newspaper readership and significantly raises support for free speech. Glaeser, Ponzetto and Shleifer (2007) show that college graduates are overwhelmingly more likely to join groups and organizations. Dee (2003) and Glaeser, Ponzetto and Shleifer (2007) demonstrate that college graduates are more likely to “volunteer” to combat local problems (20 percent and 29 percent, respectively). Wolfe and Zuvekas (1995) state that, after income, education is the “primary determinant of donations” (p. 8) to charitable causes. Their research finds that college graduates dedicated twice as many hours toward volunteering as did high school graduates. Educated individuals pursue these civic behaviors because their stronger social interaction skills increase the benefits and decrease the costs of social interaction.

Beyond direct civic values, education reduces crime and promotes healthy lifestyle choices. A report issued in 2000 by the Joint Economic Committee of the U.S. Congress (Saxton 2000) states that the average crime rate in the top 15 “most educated” states was 20 percent lower than the same rate in the 15 “least educated” states. The report concludes, “Education has a greater effect on crime reduction than the higher income that is associated with superior educational attainment” (pp. 10-11). The high costs, both direct and indirect, accompanying the legal consequences of criminal activity discourage individuals with higher education from participating in illegal behaviors.

Wolfe and Zuvekas (1995) document additional benefits of education. They indicate that education positively affects the individual’s life expectancy and health. They propose that these health improvements arise from better information about nutrition, healthy activities and use of health services, along with a decline in health-harming activities. This claim is supported by their quantitative conclusion that additional years of schooling decrease the amount of cigarettes consumed, reduce the likelihood of heavy drinking and increase the average amount of exercise. Wolfe and Zuvekas (1995) also realize that children of more-educated parents tend to experience lower rates of infant mortality and low-weight births. Education helps individuals recognize the benefits of healthy behavior and the costs of unhealthy habits, positively affecting the health of the individuals and those closely associated with them.

Higher education, by increasing an individual’s marginal productivity, raises the opportunity cost of nonoptimal choices. This higher cost induces individuals to make better choices, which generates beneficial externalities that are highly desirable in a democratic society. Higher education produces individuals who effectively cooperate to accomplish their political aims. These individuals are politically invested, active in their communities, charitably oriented, healthier and law-abiding. Utility-maximizing, educated individuals will avoid costly behavior while realizing the benefits of civic participation.

The presence of these beneficial externalities indicates that the free market alone will fail to produce the optimal supply of individuals with higher education. Government policy should aim to increase the number of educated individuals by reducing the costs of higher education through subsidies. The government currently subsidizes higher education through student loan programs and scholarship opportunities. Such subsidies are currently under attack for their “inefficiency.” Before reducing funding for student loan programs, voters and policy officials must understand that cuts in funding will reduce the presence of the externalities brought about through higher education. Cutting subsidies could weaken the vitality of our democratic society. Before slashing these valuable aids, the “inefficiencies” of education subsidies must be weighed against the political virility, community health and civic values they bring about.

References

Dee, Thomas S. 2003. “Are There Civic Returns to Education?” National Bureau of Economic Research Working Paper 9588.

Glaeser, Edward L., Giacomo A. M. Ponzetto and Andrei Shleifer. 2007. “Why Does Democracy Need Education?” Journal of Economic Growth 12 (2): 77-99.

Saxton, Jim. 2000. “Investment in Education: Private and Public Returns.” Washington, D.C.: Joint Economic Committee, U.S. Congress.

The Federal Reserve Bank of Atlanta’s Inflation Project is a one-stop shop for anyone who wants to know about price stability. Its most comprehensive tool is the inflation dashboard, which collects 30 data series that measure an array of prices as well as money and credit, condensing them into six broad indexes. The project also hosts the Atlanta Fed’s own forward-looking survey of inflation expectations, along with a price index for goods whose prices are “sticky,” that is, change infrequently. Finally, the site contains a market-based measure of the chances of deflation—when prices in general fall—which can happen during recessions and cause further economic damage.

Still seem overwhelming? A short video tutorial walks visitors through the site and makes it easy to use. Compare prices at The Inflation Project.

• 11.9 billion ACH (Automated Clearing House) payments worth approximately $22.4 trillion. FedACH is a nationwide system, developed and operated by Minneapolis staff on behalf of the entire Federal Reserve System, which provides the electronic exchange of debits and credits.
• $10.9 billion of currency deposits from financial institutions, destroyed $819 million of worn and torn currency, and shipped $12.6 billion of currency to financial institutions.
• Tenders, account maintenance, forms and other customer transactions for 149,000 active Legacy Treasury Direct accounts for individuals holding Treasury securities totaling $23 billion, and 1.7 million savings bond purchase requests worth $1.5 billion, as the Treasury Retail Securities site for the Federal Reserve System.

[PDF, off-site via Board of Governors]

For 2011, the Bank posted strong operating results. Expenses were below budget and operating metrics were achieved. The accompanying “2011 by the Numbers” highlights the scope of some of the Bank’s operations. Over the past decade, this “By the Numbers” summary of some of our key operational activities has changed enormously. In my 2007 letter, I noted that during 2006, the Bank had processed 769 million checks worth $851 billion. By 2010, this activity and the several hundred employees involved in it were gone, as the System completed its conversion of check processing from physical handling of the paper items to electronic processing of digital images of the items and the consolidation of this physical processing activity from 45 offices to just one. In less than a decade, we have seen a complete transformation of the check processing business made possible by the System’s leadership to put check images on the same legal footing as the original items.

This dynamic of technological change creating opportunities for greater efficiency and the System reorganizing and consolidating its operations to take full advantage of these opportunities is evident across our operations. In information technology, we are engaged in a multiyear effort to consolidate our server farms and networks Systemwide to achieve greater efficiency. As 2011 began, the U.S. Treasury’s Bureau of the Public Debt was in the process of selecting between the Minneapolis Fed and the Pittsburgh Branch of the Cleveland Fed to be the sole surviving site for conducting retail securities operations as fiscal agent for the Treasury. At one time, all 12 Reserve Banks conducted this work in their districts for the Treasury. Technology has allowed consolidation and significant operational savings. In February, the Treasury announced its selection of Minneapolis as the surviving site. We completed this consolidation in 2011 on schedule and on budget.

For the System’s supervision and regulation area, assuming expanded responsibility pursuant to the Dodd-Frank Act as systemic risk regulator, supervisor of thrift holding companies and supervisor of systemically important financial market utilities requires significant additional resources. Evolving regulatory and supervisory frameworks require increased emphasis on the analysis and review of financial organizations’ risk profiles. In this regard, the Bank is strengthening the analytical and technical skills of staff in order to address these new demands.

In 2011, there were a number of opportunities for the Bank to leverage its expertise and expand its System responsibilities. The Bank’s legal function assumed a new responsibility for System work on employee data privacy. The Bank’s information technology function is partnering with the Chicago Fed to lead an initiative to evaluate content management technology and is working with the Board of Governors’ supervision and regulation function on a broad document management framework and on supervision and regulation’s specific document management tool selection.

Another area of greater emphasis in 2011 and going forward is the Bank’s outreach efforts. To address this priority, the Bank hired a senior vice president responsible for outreach and community affairs as a member of the management committee. She oversees our efforts to facilitate interaction and provide analytical support on issues ranging from the inner city to rural areas and to American Indian reservations. She is also coordinating our efforts to strengthen and broaden our dialogue with business owners, bankers, community leaders and community groups. As part of these efforts, we are continuously evaluating our activities and communications with the goal of enhancing transparency, understanding and accessibility.

Last year, we established an Office of Minority and Women Inclusion consistent with Section 342 of the Dodd-Frank Act. While the office is new, its objectives, which include promoting inclusion of minorities and women across all levels of our workforce, ensuring participation of minority- and women-owned businesses in our procurement activities and fostering financial literacy, reflect long-standing priorities of the Bank. The annual report of the OMWI director, published each March, will provide us a new channel to communicate our activities and results.

Going forward, the Bank will continue to seek opportunities to leverage its strengths in making important System contributions while at the same time pursuing financial and operational strategies directed at ensuring that all System objectives are met efficiently and with high quality. The Bank will continue its focus on academic research in applied economics and is expanding its capabilities related to selected public policy issue-oriented research.

The Bank’s continued success in addressing challenges is a result of our employees’ strong commitment to excellence and the Bank’s core values. As we look to the future, this unwavering commitment to our core values and to acting in the public interest, as well as our commitment to excellence, will allow us to successfully meet future challenges.

James M. Lyon
First Vice President