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September 2003

Price Signals

Economist Pete Klenow analyzes price differences—over time, among products and across countries—to shed light on some of economics' most contentious issues

Douglas Clement
Editor

It would be difficult to find two questions of macroeconomic theory more central to the conduct of economic policy today than these:

• Why are some nations poorer than others?
• Do changes in money supply affect economic output?

The first question is at the heart of disputes over globalization, trade policy and international aid. The second is crucial to debates about employment, inflation and interest rates. And although these problems are related only indirectly to one another, they share two characteristics: (1) Solid answers to them are essential to sound policy; and (2) such answers have been hard to find, though economists have worked on them for decades.

Fortunately, insights into both macroeconomic questions are now being discovered through a rather unexpected method—the ingenious application of price theory, a traditional domain of microeconomics.

In recent work, Minneapolis Fed senior economist Peter Klenow examines international differences in the price ratios of investment goods to consumption goods and finds that traditional theories of underdevelopment aren't supported by the data. The facts suggest that the strong correlation between levels of investment and levels of income—often seen as a major causal relationship—is a bit of a chimera. A closer look reveals that at domestic prices there's actually very little correlation between investment rates and income levels. To the extent that savings and investment rates are important in explaining differences in development, that implies that the heart of the problem lies not in inadequate savings, as usually proposed, but in inefficient use of those savings. The right question, in other words, isn't why do some nations save so little, but rather why do they get so little from what money they do save?

And in separate research, Klenow looks at how prices change when monetary policy changes. Here, too, he finds that the evidence is at odds with much conventional theory. Many economists today rely on macroeconomic models in which changes in monetary policy can affect economic output—expanding the money supply by reducing the federal funds rate, for instance, can boost quantities of products demanded by consumers because not all prices adjust quickly. (With more money in their hands, and prices stuck for a while, goes the theory, people will demand more “sticky-price” products.)

But Klenow finds that the price and quantity changes predicted by such sticky-price models following monetary “shocks” don't meet the reality test—that is, the model's predictions don't match the actual data. So either the models are flawed, the way economists usually measure monetary shocks is flawed or both, argues Klenow.

Klenow's exploration of price behavior in these very different contexts is bringing new clarity to persistent questions. And such insights aside, the most intriguing aspect of his work is how it uses elementary price theory—and micro-level data—to delve into the broadest and most fundamental issues of economic growth and transformation, bridging the customary—if artificial—divide between micro and macroeconomics.

Prices and prosperity

What causes underdevelopment? Why are some countries rich and others poor? There are many reasons, no doubt, only some of them economic. (See the review of The Elusive Quest for Growth.) But for their part, economists have focused on three sources for the variations among countries: physical capital, human capital and total factor productivity. The last, TFP, is sort of a black box that seems to include everything that the other two factors don't. Human capital means levels of education and training of a country's population, the acquired skills that people can apply toward economic development. And physical capital is machinery, equipment and tangible infrastructure: the trucks, roads and factories that produce and deliver economic goods.

While TFP and human capital ultimately may prove to be most significant in explaining different levels of economic development, noted Klenow in a recent interview, economists have given more attention to physical capital. “It's 20 percent of the story, not 100 percent, but it's definitely more than 20 percent of the literature,” he observed. (The disproportion may be due to the fact that physical capital was identified early on as a growth factor as well as the fact that it's fairly easy to measure and, therefore, to study.)

And in looking at physical capital, economists have traditionally argued that the main reason some nations have more of it than others is their very different savings levels. “The central problem in the theory of development,” wrote W. Arthur Lewis, a Nobel laureate considered the pioneer of development economics, “is to understand the process by which a community which was previously saving 4 or 5 percent of its national income or less, converts itself into an economy where voluntary saving is running at about 12 to 15 percent of national income or more.”

Without adequate savings, nations have little to invest in physical capital and so little ability to develop. For over 50 years, therefore, economists have analyzed impediments to saving, including high dependency rates (high ratios of young and old people to those of working age) or a fundamental inability to produce more than subsistence levels of food and shelter.

Other economists have looked more directly at investment per se, rather than savings. Chari, Kehoe and McGrattan, in a 1997 Minneapolis Fed staff report (“The Poverty of Nations: A Quantitative Investigation”), for example, argue that disincentives to investment arising from corruption or bureaucratic inefficiency, say, represent distortions in investment-output ratios. “Distortions of these kinds typically raise the prices of investment goods relative to those of consumption goods,” they wrote. “Indeed, in the data, investment goods prices are low in rich countries and high in poor countries.”

Klenow, working with Chang-Tai Hsieh of Princeton University, takes a closer look at the data in a May 2003 National Bureau of Economic Research working paper, “Relative Prices and Relative Prosperity.”

When economists examine the relationship between income levels and investment rates across countries, note Hsieh and Klenow, they typically value the quantities bought in each country at “international” prices—that is, at the average prices prevailing across countries. That choice is critical.

Economists use the concept of purchasing-power parity (PPP) to arrive at international prices. The idea is that exchange rates don't fully reflect the differences in standards of living among nations, so taking the price of a commodity in one country and doing a simple exchange rate translation into another country's currency doesn't necessarily give you a good sense of the cost of that commodity in that other country. A tuna sandwich in Tokyo costs more than it does in Topeka, simply because the cost of living is higher in Japan, regardless of the exchange rate (or the relative scarcity of tuna, for that matter). PPPs are meant to deal with these differences, attempting to provide a proper basis for comparing living standards among nations.

“A PPP is the rate of currency conversion that equalizes purchasing power of different currencies,” according to the Bureau of Labor Statistics. “[It] has the dimensions of an exchange rate as well as a price index.” In effect, PPPs are like a cost-of-living index across nations—applying the same measuring stick to all countries by adjusting for standards of living—just as the consumer price index allows economists to see how price levels change over time for the same shopping basket of goods and services.

While PPP prices are essential for some purposes, they're misleading for others. “If you want to compare purchasing power of incomes in different countries, PPP prices are helpful,” said Klenow. “But they're not necessarily a good guide to why investment rates differ across countries.” Understanding investment rate variation among nations calls for an analysis of domestic prices, not international prices, argue Hsieh and Klenow, because most people base their purchasing decisions on the domestic prices they face in the home market. (Domestic and international prices might be the same for some products, but not all.)

In making their argument, Hsieh and Klenow first confirm that there is a close association between investment rates and per capita income when measured in PPP prices. (For statistics buffs: the Pearson correlation coefficient is 0.50.) When measured this way, wealthy countries show an investment rate two to three times higher than poor nations.

But the correlation virtually disappears when looking at investment rates at domestic prices. (The correlation coefficient drops to 0.05.) “When evaluated at domestic prices, richer countries have only modestly higher investment rates than poorer countries do,” they wrote. “At domestic prices, poor countries like Mali and Kenya do not invest much less than rich countries such as the U.S. or Norway.”

This, they point out, contradicts the long-held notion that poor countries are poor because of inadequate savings compared to rich countries, so all the hypotheses behind those alleged paltry savings rates lose their importance. “This evidence undermines explanations involving discount rates, subsistence consumption, low-savings traps, and the taxation of capital income,” they wrote.

The problem, argue the economists, lies instead in the much higher price of investment relative to consumption (at domestic prices) in poor countries compared to rich. So saving and investing a given fraction of local income does not buy as much equipment for businesspeople in Kenya as in Norway.

And that leads to their second surprising discovery: The reason for the high relative price of investment in poor countries isn't that investment goods are notably more expensive in poor nations compared to rich countries, according to the data. “Computers in Mali cost roughly the same as in the United States,” noted Hsieh and Klenow.

The explanation is that consumption goods—haircuts and taxi cabs, for instance—are far less expensive in poor nations than in rich countries. “What is responsible for the high relative price of capital in Mali is that nontradable services are much cheaper in Mali than in the U.S.” And this finding undercuts theories of underdevelopment related to investment distortions. The problem, argue Hsieh and Klenow, isn't that investment goods prices are deformed by tariffs, taxes or corruption, but rather that “consumption is cheap in poor countries, making investment expensive and lowering PPP investment rates.”

“Our results imply that the covariation of physical capital investment rates and income arises from a deeper productivity puzzle,” they concluded. “The challenge is not just to explain lower overall productivity in poor countries, but to explain low productivity in investment goods production relative to consumption goods production.”

If Hsieh and Klenow have thus cast a large shadow over conventional explanations for international differences in development and begun to shed light on other possibilities, it's apparent that their contribution is due in part to a willingness to look beneath the macroeconomic surface. For five decades at least, economists have taken for granted the idea that investment and savings rates correlate directly with national income levels. Klenow wasn't content. “The data sets out there are really easy to use if you don't ask a lot of questions,” he said. “Looking into the details made us see things that we hadn't really seen people talk about before.”

Sticky prices

Klenow brings similar curiosity and technique to bear on a pivotal question regarding the effectiveness of monetary policy: Is money neutral?

Two and a half centuries ago, British philosopher David Hume argued that increases in money supply affect economic output.

“[I]n every kingdom into which money begins to flow in greater abundance than formerly, everything takes a new face: labour and industry gain life; the merchant becomes more enterprising; the manufacturer more diligent and skilful [sic]. ...”

It was the first formal statement of what economists would later call the non-neutrality of money, meaning that changes in a country's quantity of money will also affect the quantity of various goods and services produced by a nation, at least in the near term.

The theory is based on the idea that putting more money into an economy will prompt people to spend more. Increasing demand will induce suppliers to hire more employees and provide more goods. So in the short run, an increase in money supply will result in an increase in output and employment.

This can only happen, though, if prices don't jump immediately with the increase in demand. And that might be possible because of “sticky prices”—the theory that prices of goods and services don't adjust instantly. Wages might be sticky, for example, because of labor contracts. And business owners might want to avoid the expense of reprinting restaurant menus or product catalogs, so other prices will be slow to adjust.

Arguing that prices adjust more slowly than output after a money supply increase, Hume wrote, “It is easy to trace the money in its progress through the whole commonwealth; where we shall find, that it must first quicken the diligence of every individual, before it encrease [sic] the price of labour.”

But many economists have argued that Hume (and his modern supporters) was wrong: Money is neutral. According to this school of thought, prices are actually quite flexible, and so both demand and supply curves shift quickly in response to increases in money supply. A new equilibrium will be established—with higher prices, but the same quantities demanded and produced. Output and employment won't change when money supply grows or shrinks (at least not when those money supply changes are expected).

These are the arguments of the rational expectations school, led by Robert Lucas, the University of Chicago economist who has powerfully challenged the concept of sticky prices and the alleged non-neutrality of money since the 1970s. In his 1995 Nobel award lecture, “Monetary Neutrality,” Lucas observed that new facts had been revealed through the application of mathematical rigor, statistical power and dynamic equilibrium models—techniques that were unknown in Hume's day.

“I think the fact is that this is just too difficult a problem for an economist equipped with only verbal methods,” Lucas noted, “even someone of Hume's remarkable powers.” Aided by more powerful methodology, Lucas and others have made a strong case that changes in monetary policy (if anticipated) can change prices, but not output or employment, because on the whole, people act rationally, markets perform efficiently, and prices adjust quickly. “Anticipated monetary expansions” have inflation effects, argued Lucas, “but they are not associated with the kind of stimulus to employment and production that Hume described.” (Unanticipated monetary changes, on the other hand, could have short-terms effects. Still, said Lucas, “none of the specific models ... can now be viewed as a satisfactory theory of business cycles.”)

Economic journals are filled with debate over monetary neutrality, but the argument is far more than theoretical. When the Federal Reserve's Open Market Committee discusses monetary policy, its decisions about discount rates and federal funds rates are predicated on assumptions about the likely impact of its actions. If the FOMC lowers the federal funds rate, leading to an increase in the money supply—or if it does the opposite—will it affect output and employment, or just prices?

Klenow engages the debate by testing whether the standard macroeconomic model used by sticky-price proponents accurately predicts the effect of monetary policy changes. And to do so, he exploits the fact that products differ in degree of stickiness—gasoline prices change quickly, for example, while prices of books and pharmaceuticals change slowly.

In a winter 2003 Quarterly Review article with Mark Bils at the University of Rochester and Oleksiy Kryvtsov at the University of Minnesota, Klenow takes a standard sticky-price model, alters it to accommodate multiple consumer goods with varying levels of stickiness and then looks at predictions generated when this model economy experiences a 1 percent increase in money supply (“Sticky Prices and Monetary Policy Shocks”).

The model predicts that roughly two months after the money supply increases, prices of flexible-price goods will increase over 1 percent while prices of sticky-price goods will rise just 0.2 percent. Quantities of flexible-price goods consumed will decline by 0.1 percent, according to the model, while consumption of sticky-price goods will increase about 0.7 percent.

The quantity effect diminishes over time. The model projects that a little more than a year after the 1 percent money supply increase, sticky-price goods will have joined their flexible-price cousins in experiencing about a 1 percent price rise. And quantities consumed of both types of goods will, after this 13-month lag, reach the same levels as before. In other words, the money supply increase will affect prices and quantities of flexible-price goods more quickly and dramatically than those of sticky-price goods, and over time, prices for both will rise 1 percent and quantities will be unchanged.

The reality test

With these model predictions in hand, the economists then look at reality: What do the data say about price and quantity changes for flexible- and sticky-price goods following a money supply change? Sticky-price theory suggests (and the model predicted) that prices of flexible-price goods should rise initially, more so than for goods with more rigid prices.

Bils, Klenow and Kryvtsov look at price and quantity behavior for goods and services that represent about two-thirds of overall consumer spending (housing, atypically sticky in both price and quantity, is intentionally excluded from their calculations). Their data, from the U.S. Bureau of Economic Analysis, span the years from 1959 to 2000. The purpose of the exercise, of course, is to see how these data appear to react to changes in monetary policy, so the economists try out several different measures of monetary policy: the federal funds rate, nonborrowed reserves and the ratio of nonborrowed to total reserves.

The first measure, though, is enough to tell their story. Using a 1 percentage point drop in the fed funds rate—the same expansionary monetary policy step used for their sticky-price model projections—they find that prices for flexible-price goods decline by almost 1 percent after two months—the opposite direction from the model's prediction. “Prices for flexible goods actually decrease relative to prices for sticky goods in the first eight months after the [fed funds rate decrease],” noted the economists. “We see no impact ... on the relative quantity consumed for the first year. ... Neither the initial nor subsequent responses match those predicted by the model.”

The findings are “robust,” as economists like to say: Altering a few details of the experiment doesn't change the basic results. Looking at prices from just the last 18 years rather than the four-decade data set, for instance, changes little. And the findings are consistent when they examine responses to the other measures of monetary policy change. Regardless of the monetary policy variable measured, or the time span examined, a change in money supply appears to have an anomalous impact on the prices and quantities of goods—sticky-price goods and flexible-price goods seem to move in ways they shouldn't, according to standard sticky-price theory.

It's a striking discovery, but the implications are ambiguous. Perhaps the sticky-price model they've used—standard issue for monetary economists—doesn't accurately describe how price stickiness works in response to monetary policy changes. Or maybe the measures they've used to represent changes in monetary policy—again, standard issue—are inadequate. And of course, it could be that both interpretations are valid. “Put more succinctly,” they concluded, “we reject the joint hypothesis of sticky-price models and these popular means of identifying monetary policy” shocks.

Does this mean that Hume was, indeed, wrong? Is money neutral, after all? Klenow is careful to emphasize that rejecting a given theory doesn't prove its converse. More to the point, Klenow's work doesn't repudiate sticky-price theory. It simply demonstrates that the model and measures most commonly used to represent and test the theory need work. “We're actually not taking a stand on whether or not money is neutral,” said Klenow. “We're not bringing anything to the table in terms of direct evidence or logic on that question. ... Our view is simply that we need to do more theorizing about how money can affect output.”

The bigger picture

In his graduate work at Stanford University, a professorship at the University of Chicago's Graduate School of Business and the last three years at the Minneapolis Fed, Klenow has written papers on the sources of industrial innovation, the relationship between education and economic growth, and the impact of trade liberalization on product varieties, among other topics. The central theme, he points out, is the importance of technology and productivity, especially for economic growth and development.

His work on sticky prices is thematically distinct, but it illustrates Klenow's underlying creative process and methodology. “Sticky Prices and Monetary Policy Shocks” developed out of an earlier piece of Bils-Klenow research into product quality changes over time, and how quality is or isn't reflected in prices. “So I wanted to know exactly how they calculate prices for the consumer price index, to what extent they adjust for quality and how,” said Klenow. He spent uncounted hours pursuing that exact truth at the Bureau of Labor Statistics in Washington, D.C.

“The end product,” he said (neglecting to mention his highly regarded American Economic Review paper on quality and prices): “I'm now a supplemental employee of the Bureau of Labor Statistics,” holding aloft his coveted BLS identity badge. “So I get to access all these internal documents, get to find out exactly what they do, and in excruciating detail.”

That level of detail is essential to Klenow, because he's unwilling to accept data at face value. “I happen to be a macroeconomist. That's my audience and motivation,” he noted. “But my dad and three brothers are accountants, so I guess I have that kind of background: Exactly how are these numbers put together? Once I start pushing in that direction I've been able to see some of the details of measurement that shed light on the macro questions.” (California-raised Klenow has just moved closer to his accounting roots, leaving the Minneapolis Fed to join the highly ranked economics department at Stanford University.)

Bringing the data to bear

The hallmark of Klenow's work, then, is not a narrow focus on a particular area of economics, but rather an intense curiosity about data and the deep lessons they can tell about the broader economy. He lays the substance of econometrics over the framework of economic theory—sometimes modifying theory in the process—and thereby strengthens ties between micro and macroeconomics.

“I'm looking at micro data and seeing what it has to say about macro,” observed Klenow. “Our core assumption in economics is rationality at the individual level—firms try to maximize profits; households try to maximize happiness. Our theories operate at that individual level. So our models of the macroeconomy should be consistent with the micro data we observe.”

And the end product of the research is not only a firmer grasp on the reality of development gaps or mechanisms of monetary policy, but the opportunity to improve them—to facilitate the stability of economies and the growth of nations. “I really like that idea of bringing the data to bear,” said Klenow. “To say, here are different hypotheses, the data tell us something about them. Then we can use that in the future to better understand what's going on, and to make better policy.”

See also: What's sticky, what's not and why?

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