Emi Nakamura, Clark Medalist 2019
American Economic Association Honors and Awards Committee
Emi Nakamura is an empirical macroeconomist who has greatly increased our understanding of price-setting by firms and the effects of monetary and fiscal policies. Nakamura’s distinctive approach is notable for its creativity in suggesting new sources of data to address long-standing questions in macroeconomics. The datasets she uses are more disaggregated, or higher-frequency, or extending over a longer historical period, than the postwar, quarterly, aggregate time series that have been the basis for most prior work on these topics in empirical macroeconomics. Her work has required painstaking analysis of data sources not previously exploited, and at the same time displays a sophisticated understanding of the alternative theoretical models that the data can be used to distinguish.
Nakamura is best known for her use of microeconomic data on individual product prices to draw conclusions about the empirical validity of models of price-setting used in the macroeconomic literature; this has been a critical issue for analysis of the short-run effects of monetary policy. Studies of the adjustment of individual prices—in particular, measures of the average time that prices are observed to remain unchanged—have long been a key source of evidence regarding the importance of price rigidity. However, until very recently most evidence of this kind came from studies of a very small number of markets, so that the question of how typical these specific prices were remained an important limitation. The availability of new data sets that allow changes in the prices of a very large number of goods to be tracked simultaneously has radically transformed this literature over the past fifteen years, and Nakamura, together with her frequent co-author Jón Steinsson, has played a leading role in this development.
In their most-cited paper, “Five Facts About Prices: A Re-Evaluation of Menu Cost Models” (QJE 2008), Nakamura and Steinsson study the BLS data on individual prices used to construct the published consumer and producer price indices for the U.S. economy, documenting a variety of facts about changes in individual prices that can then be compared to the implications of a popular theoretical model of price adjustment, the “menu cost” model. They give particular attention to the average frequency of price changes, an important issue in the numerical calibration of quantitative models of the effects of monetary policy. While past studies using other sources had concluded that the median time between price changes in the U.S. economy was nearly a year, the first work using the BLS microdata (by Mark Bils and Pete Klenow) had argued that the BLS data underlying the CPI showed that prices actually changed much more frequently (a median duration of prices only a little over 4 months). Bils and Klenow actually did not use the BLS micro dataset, but rather an extract from it for the period between 1995 and 1997 that reported average frequencies of price changes at a very disaggregated level. Nakamura and Steinsson instead obtained access to the actual micro data used by the BLS, which has all the price observations collected by the BLS and for the period from 1988 to 2005.
Revisiting Bils and Klenow’s conclusion using their superior dataset, Nakamura and Steinsson show that one’s conclusions about the frequency of price changes in the CPI data depend on the method used to distinguish sales from changes in “regular prices.” They also study the changes in individual wholesale prices and consumer prices. They find both that changes in regular prices occur much less often than price changes that include sales (they find a median duration of 8-11 months for regular prices, depending on the precise method used to classify price changes), and that producer prices (for which there is less of a need to filter out “sales”) also change quite infrequently. A first reason why this paper is so influential is that it gives very convincing microeconomic evidence for much more substantial “stickiness” of individual prices than the surprising results of Bils and Klenow had implied. The paper is also valuable for documenting features of the data on individual price changes that can be used to test the realism of specific models of price adjustment. Nakamura and Steinsson stress two features of the data that are contrary to the predictions of a popular class of models of price adjustment (“menu-cost” or “S-s” models): clear seasonality in the frequency of price adjustments, and the failure of the hazard function for price changes to increase in the time since the last change in price.
The ability of a “menu-cost” model to account for the quantitative characteristics of the micro data on price changes is considered further in “Monetary Non-Neutrality in a Multi-Sector Menu Cost Model” (QJE 2010, also with Steinsson). Prior numerical analyses of the implications of menu-cost models (such as the influential paper by Golosov and Lucas) had assumed that all goods in the economy were subject to menu costs of the same size (in addition to being produced with the same technology), with the parameters common to all goods being assigned numerical values to match statistics for the set of all price changes (such as the overall frequency of change in prices and the average absolute size of price changes). But one of the facts documented by Nakamura and Steinsson in “Five Facts” is that there is tremendous heterogeneity across sectors of the U.S. economy in the frequency of non-sale price changes.
In the “Monetary Non-Neutrality” paper, they calibrate a multi-sector menu-cost model to also match the distribution across sectors of both the frequency of price changes and the average size of price changes. They find that the real effects of a monetary disturbance are three times as large in their multi-sector model as in a one-sector model (like that of Golosov and Lucas) calibrated to the mean frequency of price change of all firms. Indeed, whereas Golosov and Lucas argue that price rigidity is not an empirically plausible explanation for the observed effects of monetary disturbances, if one takes account of the micro evidence on the frequency of price adjustments, Nakamura and Steinsson show that their calibrated multi-sector model (with nominal shocks of the magnitude observed for the U.S. economy) predicts output fluctuations that would account for nearly a quarter of the U.S. business cycle. This would be roughly in line with the fraction of GDP variability that is attributed to monetary disturbances in atheoretical vector-autoregression studies. The paper’s emphasis on the importance of taking account of sectoral heterogeneity when parameterizing the degree of price stickiness has been highly influential.
More recently, Nakamura and Steinsson have devoted considerable effort to extending the BLS micro-level data set on consumer prices back to 1977. This labor-intensive, multiyear data-construction project is of interest because the extended database now includes the period in the late 1970s and early 1980s when inflation was much higher and more volatile than it has been since 1988. The first paper making use of the extended data set is with Patrick Sun and Daniel Villar, “The Elusive Costs of Inflation: Price Dispersion During the U.S. Great Inflation” (QJE, forthcoming). The paper considers how the firms’ adjustment of their prices to changing market conditions differs in a higher-inflation environment. The authors find that “regular” (i.e., non-sale) prices were adjusted more frequently in the earlier (higher-inflation) part of their data set, and by about the amount that would be predicted by a model of optimal price adjustment considering a fixed cost (a “menu cost”) of adjusting the firm’s price. They conclude from this that it is important, when assessing the welfare costs expected to follow from choosing a permanently higher rate of inflation, to take account of the increased frequency of price adjustments that should be expected to occur, keeping prices from being as far out of line with current conditions as would otherwise be expected in a more inflationary environment.
The paper also seeks to measure the degree to which there is greater dispersion in the prices of similar products in a higher-inflation environment. Some common models of price adjustment imply that there should be: given staggering of the times at which different firms’ prices happen to be reconsidered, the price that is optimally chosen would vary depending on the rate at which prices in general increase from week to week. If so, this should be an important source of increased distortion of the allocation of resources in a higher-inflation environment. Measurement of the degree of dispersion in the prices of genuinely identical goods is difficult, since different prices for different firms’ goods might reflect heterogeneity of the goods, so that they would have different prices even with fully flexible prices.
For this reason, the authors propose instead to look at the how the average size of price changes (when prices are adjusted) differs between high- and low-inflation periods; the idea is that if prices are adjusted to their currently optimal level whenever they are changed, the size of the price changes that are observed indicates how far prices have drifted from their optimal level just before they are adjusted. They find that the average size of price increases, when they occur, is about the same (a 7 percent increase on average) in their pre-1988 sample as in their post- 1988 sample. Again, they interpret this as evidence that the timing of price changes adjusts endogenously when the rate of inflation increases, in such a way as to reduce the distortions created by inflation relative to what one would expect if the timing of price adjustments were independent of the degree to which a given firm’s prices have gotten out of line with current market conditions. The authors conclude that the welfare costs of chronically higher inflation may not be as large as welfare calculations based on sticky-price models with an exogenous frequency of price adjustment would suggest. The paper is simultaneously an important contribution to policy debates about the costs of inflation; to our understanding of historical facts about price adjustment in the US; and to the empirical basis for assessing the realism of alternative theoretical models of price-setting.
Another area in which Emi Nakamura has had a significant impact is in the study of the effects of government spending shocks, a classic issue in macroeconomics that has been of renewed interest following the widespread use of fiscal stimulus measures by governments in response to the global financial crisis. Estimates of the size of the government spending multiplier have been quite dispersed and remain highly controversial. Nakamura’s work with Jón Steinsson in “Fiscal Stimulus in a Monetary Union: Evidence from U.S. Regions” (AER 2014) brought new data and a fresh identification approach to an important debate.
An important problem in estimating the fiscal multiplier is the difficulty of finding truly exogenous changes in government spending. Researchers have for a long time argued that changes in military purchases are a plausible candidate for exogenous variations in government spending. However, there have not been large variations in aggregate military spending since the Korean War, so that aggregate military spending is of limited use for identifying the government spending multiplier for the U.S. economy of the past 50 years. An important insight of Nakamura and Steinsson’s paper is that while in the aggregate there may not have been large variation in U.S. military spending, there has been sizeable variation in regional military spending, and those regional variations can thus be used to estimate a government spending multiplier. Another important problem with previous studies is that the output effects of government spending should very likely (according to standard theory) depend on the nature of the monetary policy reaction. Some have argued that typical studies under-estimate the multiplier by failing to take account of the extent to which output effects are reduced by the typical monetary response to output booms resulting from government purchases outside of deep recessions, even though the likely response during a deep recession would (arguably) be quite different. Nakamura and Steinsson’s strategy sidesteps this problem, since the monetary policy reaction is common to all states, and so should not be a factor in explaining the differential effects on output across states.
A further complication in estimating government spending multipliers is that their size depends on how changes in government spending are financed. Previous studies have struggled with how to take into account financing considerations. An advantage of Nakamura and Steinsson’s empirical strategy is that regional military spending is financed by federal taxation and thus regions that receive a large chunk of military spending will not have tax structures that are different from regions that do not receive military spending. Thus, considering variations in regional military spending and relating it to regional output variations should provide a much more reliable estimate of the government spending multiplier than previous studies.
The paper offers much more than a clever instrument for measuring the multiplier effect of government purchases. The authors point out that the multiplier estimated for the effect of relatively higher purchases in one state on relative economic activity in that state need not be the same as the multiplier for the effect on national GDP of a nation-wide increase in government purchases (the central issue for debates about the effectiveness of “fiscal stimulus” as a response to recession), because of spillovers between states of the effects of increased purchases in any given state. These spillovers occur not only because increased income in one state leads to increased purchases from out-of-state suppliers, while the national economy is less open, but also because increased relative government spending in one state is not financed by increased relative taxation of that state’s residents, while increased national spending will require increased revenue to be raised from US taxpayers in aggregate. Steinsson and Nakamura address the likely magnitude of the difference between the two multipliers by developing and analyzing a quantitative multi-region New Keynesian general-equilibrium model and asking what the national multiplier would be in the case of a model parameterization that can account for their estimated relative state-level effects. The paper provides an excellent example of work that combines non-structural empirical work with careful model-based analysis of what can be learned from the estimates and makes a substantial contribution to an applied literature of considerable importance for macroeconomic policy.
Nakamura has also made important contributions to empirical analysis of the effects of monetary policy. “High Frequency Identification of Monetary Non-Neutrality: The Information Effect’’ (QJE, 2018, also with Steinsson) studies interest-rate changes in a thirty-minute window around 106 scheduled Federal Reserve announcements between January 2000 and March 2014. As is standard in related literature, financial-market changes observed during this thirty-minute window are attributed to information released in the Federal Reserve announcement. However, unlike some earlier proponents of such “high-frequency identification” of shocks to monetary policy, Nakamura and Steinsson recognize that the news revealed need not only represent a change in expected monetary policy for given economic fundamentals; it could also contain news about the state of the economy that the Fed is aware of but the markets might not have been aware of yet, or news about how the Fed interprets the current state of the economy differently than markets had believed prior to the announcement. The paper’s contribution is to draw inferences about monetary non-neutrality while allowing for the possible presence of such information effects, and to build and estimate a theoretical model that can explain the observed effects of Fed announcements.
This problem motivates the development of a model in which Fed announcements can have both an information effect and a pure monetary policy shock, allowing estimation of how big each component in the observed Fed announcements is. The results of this estimation suggest that the proposed model can explain well the observed effects of Fed announcement shocks; that about two-thirds of the announcement shock represents news about future economic fundamentals, and hence that only one-third represents a pure monetary policy shock; and that, despite the great importance of the information effect, the observed responses to Fed announcements are consistent with a high degree of monetary non-neutrality in the U.S. economy. These are important results about fundamental questions in monetary economics, and the paper represents a significant improvement upon prior methodology.
While Nakamura’s most characteristic contributions have been to empirical research, her work is always guided by a sophisticated understanding of the structure of theoretical models, and some of her contributions are primarily theoretical. An important example is her paper “The Power of Forward Guidance Revisited” (AER 2016, with Steinsson and Alisdair McKay). This paper addresses a question about monetary policy that has been a focus of considerable interest in light of central-bank responses to the recent financial crisis both in the US and elsewhere, namely, the extent to which central-bank commitments about future policy (possibly indicating that interest rates should remain at their current level for years into the future) can be an effective way of influencing financial conditions and stimulating aggregate demand, even in the absence of any change in the current level of short-term interest rates.
Simple New Keynesian DSGE models imply that advance commitments to maintain a highly accommodative policy in the future should have a substantial stimulative effect; in fact, in the case of a commitment to low interest rates extending several years into the future, the models predict an immediate effect on both economic activity and inflation that is so strong as to make it difficult to regard this as a realistic prediction—and one that is certainly not consistent with the more modest effects of actual experiments with forward guidance. This has been called “the forward guidance puzzle.” Nakamura and her co-authors argue that the unrealistic implication of the simple New Keynesian models results from the feature that each agent has a single intertemporal budget constraint, as a result of assuming complete financial markets and no borrowing constraints. They analyze the effects of a long-horizon commitment to a fixed nominal interest rate in a model that instead allows for the existence of uninsurable income risk and borrowing constraints and find that while the effects of expectations about monetary policy at shorter horizons are similar to those predicted by the simpler model, the predicted effects of a long-lasting commitment to a fixed nominal interest rate are much weaker. Essentially, they find that in the case of a household with a significant probability of having a point in time over the next several quarters at which its borrowing constraint binds, expectations about monetary policy farther in the future than the time at which the constraint binds do not affect its current ability to spend, and this substantially reduces the predicted effects on current aggregate demand of commitments about policy years in the future.
Their alternative model thus implies that forward guidance is a less powerful tool for getting out of a sharp contraction than simpler models would imply, though it hardly implies that it is irrelevant. The paper is both a contribution to an important policy debate and a useful methodological contribution to the literature on the application of New Keynesian models to assess alternative monetary policies. It has stimulated an active recent literature on “heterogeneous-agent New Keynesian models,” which explores the implications for other aspects of macroeconomic dynamics of introducing income heterogeneity and borrowing constraints.
Nakamura has recently published a JEP article on “Identification in Macroeconomics,” with Steinsson and a new working paper on the role of women’s labor force participation in the slow recovery from recessions observed over the last few decades. The former is an interesting generalization of the approach discussed above in her fiscal policy paper and also in the price-setting papers: using cross-section variation to identify macroeconomic phenomena and disciplining the aggregate implications with careful structural modeling. This approach is common to several of Nakamura’s most influential papers and is methodologically eclectic. It takes advantage of advances in the availability of new and larger data sets to explore cross-section variation, while also recognizing that this alone does not deliver the macroeconomic implications that are of interest to her. The macro implications require modeling of aggregation that takes into account the heterogeneity in the micro data, and equilibrium considerations. Moreover, the macro models have implications for the cross section that are testable and provide additional discipline and ability to distinguish competing macro hypotheses. This approach has also been applied in several of her recent papers on the wealth effect from housing, delivering significantly different implications from work focusing only on the micro data.
The working paper “Women, Wealth Effects, and Slow Recoveries” (with Fukui and Steinsson) on slow recoveries from business cycle downturns documents that the slow recovery phenomenon coincides with the convergence of female’s labor force participation to that of males. That is, as female labor force participation rose during the mid and late-20th century, employment recovered quickly from downturns as women entered the labor force in higher numbers during recoveries. However, as female labor force participation has risen and converged towards men’s, that dynamic has faded. The paper argues that this effect alone accounts for 70 percent of the slowing of economic recoveries. This is an interesting “opposite number” of another labor market finding: that firms adjust faster during downturns, as they adjust to long-run trends more when they are firing. This result suggests a similar finding during upturns, when there is capacity to draw new workers into the labor market.
Prior recognition for Nakamura’s accomplishments includes a CAREER Award from the NSF (2011), a Sloan Research Fellowship (2014), the Elaine Bennett Research Prize from the AEA (2014), being named a member of “Generation Next: Top 25 Economists Under 45” by the IMF (2014), and being named one of the decade’s top eight young economists by the Economist (2018). She serves as a Co-editor of the AER, on the CBO’s Panel of Economic Advisers, the AEA Committee on National Statistics, and the BLS Technical Advisory Committee; these appointments testify to the role she has quickly gained in the profession as an expert on issues relating to data construction. Her contributions to the general methodology of empirical macroeconomics, and to the empirical basis for analyses of the effects of monetary and fiscal policies, make Emi Nakamura an outstanding candidate for this year’s John Bates Clark Medal.
The best young economists
Our pick of the decade’s eight best young economists
They mostly want to change the world, not just fathom it
From The Economist, Dec 18th 2018
“The solution in Vietnam”, said William DePuy, an American general in 1966, “is more bombs, more shells, more napalm.” But where exactly to drop it all? To help guide the bombing, the Pentagon’s whizz kids calculated the threat posed by different hamlets to the American-backed government in South Vietnam. Fed with data capturing 169 criteria, their computer crunched the numbers into overall scores, which were then converted into letter grades: from a to e. The lower the grade, the heavier the bombing.
Almost 50 years later, these grades caught the eye of Melissa Dell, an economist at Harvard University. Those letters, she realised, created an unusually clean test of DePuy’s solution. A village scoring 1.5 and another scoring 1.49 would be almost equally insecure. But the first would get a d and the second an e, thus qualifying for heavier bombing. To judge the effectiveness of the onslaught, then, a researcher need only compare the two. Simple.
Or not. Inconveniently, the scores had not survived: only the letter grades (and the 169 indicators underlying them, preserved because of an ibm lawsuit). To resurrect the algorithm that linked the two, Ms Dell embarked on what she calls a “treasure hunt”. She stumbled on an old journal article which suggested the army had removed hundreds of musty records waiting to be catalogued by the National Archives. She tracked those files to Fort McNair where a military historian dug out the matrices she needed to reverse engineer the algorithm.
That kind of tenacity is one reason why Ms Dell, who is still in her 30s, is among the best economists of her generation. We arrived at that conclusion based on an investigative strategy somewhat less sophisticated than those for which she is celebrated: we asked around, seeking recommendations from senior members of the profession. They named over 60 promising young scholars. We narrowed that list down to eight economists who we think represent the future of the discipline: Ms Dell and her Harvard colleagues Isaiah Andrews, Nathaniel Hendren and Stefanie Stantcheva; Parag Pathak and Heidi Williams of the Massachusetts Institute of Technology (mit); Emi Nakamura of the University of California, Berkeley and Amir Sufi of the University of Chicago Booth School of Business. Taken together, they display an impressive combination of clever empiricism and serious-minded wonkery. They represent much of what’s right with economics as well as the acumen of top American universities in scooping up talent.
This is the fourth time we have assembled such a list, and a pattern emerges. The first group, from 1988, was dominated by brilliant theorists who brought new analytical approaches to bear on long-standing policy questions. Back then, theorists were treated like the “Mozarts” of the profession, according to one member of that generation. Two of these maestros have since been to Stockholm to collect Nobel prizes: Paul Krugman in 2008 and Jean Tirole in 2014.
In those days, empirical work enjoyed less prestige. As Edward Leamer of the University of California, Los Angeles noted earlier in the 1980s, “Hardly anyone takes data analyses seriously. Or perhaps more accurately, hardly anyone takes anyone else’s data analyses seriously.” It was easy for economists to proclaim a seemingly significant finding if they tweaked their statistical tests enough.
By 1998 theory was giving way to a new empiricism. One member of the cohort we chose that year, Harvard’s Michael Kremer, was arguing that randomised trials could revolutionise education, much as they had revolutionised medicine. Another, Caroline Hoxby of Stanford, showcased the creative potential of a “quasi-experimental” technique: the instrumental variable. She wanted to know whether competition for pupils improved school quality. But this was hard to gauge, because quality could also affect competition. To untie this knot, she employed an unlikely third factor—rivers—as an “instrument”. Places densely reticulated by rivers tend to be divided into many school districts, resulting in fiercer competition between them. If these locales also have better schools, it is presumably because of that competition. It is not because better schools cause more rivers.
This cohort’s Mozart—the empiricist with, if anything, “too many notes”—was Steven Levitt of the University of Chicago. In his view, “Economics is a science with excellent tools for gaining answers but a serious shortage of interesting questions,” as Stephen Dubner, a journalist, once put it. In pursuit of more compelling questions, he roamed freely, carrying his tools into unconventional and even quirky areas of research (penalty kicks, sumo and “The Weakest Link”, a game show). The result was “Freakonomics”, a bestseller written with Mr Dubner, and a phalanx of imitators.
Ten years later, many of our picks of 2008 also excelled in empirical work. Esther Duflo of mit institutionalised the randomised trials that Mr Kremer helped pioneer. Jesse Shapiro of Brown University—still under 40, but we are not allowing double dipping—delighted in some of the same empirical virtuosity as Mr Levitt.
The work exemplified by these two waves of economists (and many others) amounted to a “credibility revolution” in the discipline, wrote Joshua Angrist and Jörn-Steffen Pischke, authors of the revolutionary movement’s textbook, “Mostly Harmless Econometrics”. Like many revolutions, this one was founded on a change in the mode of production: the introduction of personal computers and digitisation, which brought large bodies of data into economists’ laps.
Like all revolutions, this one was followed by a backlash. The critics lodged three related objections. The first was a neglect of theory: the new empiricists were not always particularly interested in testing formal models of how the world worked. Their experiments or cleverly chosen instruments might show what caused what, but they could not always explain why. Their failure to distinguish mechanisms cast doubt on how general their findings might be. Like jamming musicians who never write anything down, they could not know if their best grooves would return in new settings.
The second objection was a lack of seriousness. “Freakonomics” had encouraged an emerging generation of economists to trivialise their subject, their critics alleged, somewhat unfairly. “Many young economists are going for the cute and the clever at the expense of working on hard and important foundational problems,” complained James Heckman, a Nobel laureate, in 2005.
The new empiricists were also accused of looking for keys under lampposts. Some showed more allegiance to their preferred investigative tools than to the subject or question under investigation. That left them little reason to return to the same question, unless they found more neat data or a new oblique approach. This hit-and-run approach makes some scholars nervous, since even a perfectly designed one-off experiment can deliver a “false positive”.
Where does that leave today’s bright young things? This year’s cohort has certainly picked up its predecessors’ empirical virtuosity. Their papers are full of the neat tricks that enlivened the credibility revolution. Mr Pathak and his co-authors have compared pupils who only just made it into elite public schools with others who only just missed out, rather as Ms Dell compared villages on either side of the Pentagon’s bombing thresholds. The study showed that the top schools achieve top-tier results by the simple contrivance of admitting the best students, not necessarily by providing the best education. Ms Dell and her co-author showed that bombing stiffened villages’ resistance rather than breaking their resolve.
Ms Williams has exploited a number of institutional kinks in the American patent system to study medical innovation. Some patent examiners, for example, are known to be harder to impress than others. That allowed her to compare genes that were patented by lenient examiners with largely similar genes denied patents by their stricter colleagues. She and her co-author found that patents did not, as some claimed, inhibit follow-on research by other firms. This suggested that patent-holders were happy to let others use their intellectual property (for a fee).
Our economists of 2018 also show great doggedness in unearthing and refining new data. Ms Dell is interested in the economic consequences of America’s decision to “purge” managers from Japan’s biggest companies after 1945. To this end she is helping develop new computer-vision tools that will digitise musty, irregular tables of information from that time.
For a paper called “Dancing with the Stars”, which shows how inventors gain from interactions with each other. Ms Stantcheva and colleagues painstakingly linked some 800,000 people in a roster of European inventors to their employers, their location and their co-inventors in order to find out what sorts of propinquity were most propitious. Mr Hendren has joined forces with Harvard’s Raj Chetty (another of our alumni of 2008) to exploit an enormous cross-generational set of data from America’s census bureau. The data link 20m 30-somethings with their parents, who can be identified because they once claimed their offspring as dependents on their tax forms. The link has allowed Mr Hendren to study the transmission of inequality from one generation to the next.
The 2018 cohort’s combination of clever methods and dogged snuffling out of data comes along with a rejection of some of the more frolicsome manifestations of earlier new empiricists. Many of them display an admirable millennial earnestness. They are mostly tackling subjects that are both in line with long-standing economic concerns and of grave public importance. Ms Williams seeks a more rigorous understanding of technological progress in medicine and health care, which many commentators casually assert was the largest factor in improving people’s lives over the past century. Ms Dell is interested in the effects of economic institutions, such as the forced labour used in Peruvian silver mines before 1812. The lingering consequences of that colonial exploitation are visible, she says, in the stunted growth of Peruvian schoolchildren even today.
Ms Stantcheva studies tax, perhaps the least cute subject in the canon. As well as investigating the public opinions and values that shape today’s tax systems, she also studies taxation’s indirect and long-term consequences. Taxation can, for example, inhibit investments in training or scare off the inventors who drive innovation. On the other hand, successful professionals often have to work hard as a signal of their ability to their bosses, who cannot observe their aptitude directly. That rat race, she points out, limits their scope to slack off even in the face of high top rates of tax. With Thomas Piketty of the Paris School of Economics (the most obvious omission from our list in 2008) and another co-author, she has explored how tax rates affect rich people’s incentives to work, to underreport income, and to bargain for higher pay at the expense of their colleagues and shareholders. When that third incentive predominates, top rates as high as 80% might be justified.
Mr Hendren’s work on the market’s failures to provide health insurance was, he says, “ripped from the headlines” of the Obamacare debate. His more recent research on social mobility is almost as topical. The son of a black millionaire, he has found, has a 2-3% chance of being in prison. Among white men only those with parents earning $35,000 or less have odds of incarceration that high. Black disadvantage is not confined to bad neighbourhoods. Mr Hendren and his co-authors have discovered that black boys have lower rates of upward mobility than white boys in 99% of America’s localities. Young black women, on the other hand, typically earn a little more than white women with similarly poor parents. This research with Mr Chetty should inform a broad swathe of thinking about race in America.
Crisis? What crisis?
In short, our picks of 2018 are looking for the intellectual keys to important social puzzles; they are willing to move lampposts, turn on headlights or light candles to find them.
Mr Pathak provides a good example of this question-driven, issues-first approach. In his work on school choice he began by examining the matching algorithms that many American cities use to decide which pupils can attend oversubscribed schools. Previous systems encouraged parents who were in the know to rank less competitive “safety schools” above their true favourites. Mr Pathak’s research has helped promote mechanisms that allow parents to be honest.
Now that these improved formulae have caught on, Mr Pathak’s algorithmic expertise is less urgently required. A different kind of economist, committed to the algorithms more than the schools, might have dropped education for problems tractable to similar approaches in other fields. But Mr Pathak is exploring other ways to improve school quality instead.
This habit of sticking with big questions should make this generation of scholars less vulnerable to the curse of false positives. But this is not the only way in which the new crop is helping to clean up the academic literature. One rule of thumb when reading journals is that dull results that nonetheless reach publication are probably true, but that striking, eminently publishable stories should be taken with a pinch of salt. Mr Andrews’s quantitative work on these problems seeks to weigh out the appropriate salt per unit of splashiness. According to his calculations, studies showing that the minimum wage significantly hurts employment are three times more likely to be published than studies finding a negligible impact. Knowing the size of this bias, he and his co-author can then correct for it. They calculate that minimum wages probably damage employment only half as much as published studies alone would suggest.
Mr Andrews has also scrutinised the instrumental variables that featured so heavily in the credibility revolution. To work well, an instrument (such as the river networks Ms Hoxby used as a proxy for school competition) should be tightly linked to the explanatory factor under examination. Often the link is weaker than economists would like, and their efforts to allow for this may be less adequate than they suppose. Mr Andrews and his co-authors have reassessed the reliability of 17 articles published in the profession’s leading journal, suggesting better ways for economists to handle the instruments they use. “No econometrician has generated more widespread excitement than him in a very long time,” according to Edward Glaeser of Harvard (one of our 1998 batch).
So how have these question-driven economists tackled the biggest economic question of the past decade: the global financial crisis? That disaster posed a problem for quasi-experimental empirical methods, which work better for data-rich microeconomics than for macroeconomics, where the data are less plentiful. The scope for macroeconomic experimentation is also limited. On April Fools’ Day an economist circulated an abstract purportedly co-written by Ben Bernanke and Janet Yellen in which the former central bankers revealed they had raised and lowered interest rates randomly during their stints in office in a covert experiment known only to themselves. In reality, as Ms Nakamura points out, the Federal Reserve employs hundreds of phds to make sure its decisions are as responsive to the economy (and therefore non-random) as possible.
None of today’s bright young macroeconomists have reinvented their sub-discipline in the wake of the Great Recession in the way that John Maynard Keynes did after the Great Depression (although Keynes was already 52 when he published “The General Theory”). If they had they would have drawn more attention from the nominators of this list.
Yet, unlike our batch in 2008, this year’s group does contain two economists who have carried the credibility revolution some way into macroeconomics. Ms Nakamura, who writes many of her papers with Jon Steinsson, also at Berkeley, has used micro methods to answer macro questions. Working with the Bureau of Labour Statistics she has unpacked America’s inflation index, examining the prices for everything from health care to Cheerios entangled within it. Whereas macroeconomists typically look at quarterly national data, her work cuts up time and space much more finely. She has divided America into its 50 states and the passage of time into minutes. This has let her shed light on fiscal stimulus and the impact of monetary policy as seen through the half-hour window in which financial markets digest surprising nuances from Fed meetings.
One of her most provocative papers is also the simplest. She and her co-authors argue that America’s slow recovery from its recent recessions is not the result of a profound “secular stagnation” as posited by Larry Summers (one of our 1998 picks). Rather it reflects the fact that the rise in the number of working women, rapid for several decades after the war, has since slowed. In the past, the influx of women put overall employment on a strong upward trajectory. Thus after a recession, the economy had to create a lot of jobs to catch up with the rising trend. In more recent decades, employment trends have flattened. Thus even a relatively jobless recovery will restore the economy to its underlying path.
Our final pick, Mr Sufi, is, like Ms Nakamura, exploiting voluminous data unavailable to scholars of previous downturns to understand the Great Recession. Had America merely suffered from an asset bubble in housing (like the dotcom bubble of the 1990s) or a lending mishap (like the savings and loan crisis of the 1980s), it could have weathered the storm, he feels. But high levels of household debt made the spending fall unusually severe and the policy response (a banking rescue and low interest rates) surprisingly ineffective. Mr Sufi and Atif Mian of Princeton University find evidence for their macro-view in a micro-map of debt, spending and unemployment across America’s counties. The households of California’s Monterey county, for example, had debts worth 3.9 times their incomes on the eve of the crisis. Spending cutbacks in counties like this accounted for 65% of the jobs lost in America from 2007 to 2009, they estimate. The Obama administration’s failure to provide more debt relief for homeowners with negative equity was the biggest policy mistake of the Great Recession, they say.
Because they want to change the world, not just delight in its perversity, many of these economists engage closely with policy. Ms Stantcheva now sits on France’s equivalent of the council of economic advisers. Mr Sufi is pushing for mortgage payments to be linked to a local house-price index, falling when the index does, but allowing the lenders a small slice of the homeowners’ gains if the market rises. He and Mr Mian have also proposed linking student-loan repayments to the unemployment rate of recent graduates.
Intriguingly, this concern for real-world outcomes is pushing some of these young economists back towards theory. In recommending a policy reform, an economist is saying that it serves some objective better than the status quo. That objective needs a theoretical rationale. A goal like improving well-being might seem bland and unexceptionable. But most policies hurt some people while helping others. How should society weigh the hurt against the help?
Ms Stantcheva and Emmanuel Saez, of the University of California, Berkeley, have proposed a theoretical framework that accommodates different answers to that question (utilitarian, libertarian, Rawlsian, and so on). Meanwhile Mr Hendren has calculated that the American tax system is implicitly willing to impose $1.5-2 of hurt on rich people to provide $1 of help to the poor. That provides one possible benchmark for evaluating new policies.
Engaging with policy can take a toll. “I’ve testified in about 15 different school-committee meetings,” says Mr Pathak. “I’ve had families shouting at me.” But it is also stimulating, he adds, not just because it helps people, but also because it enriches research. “Testifying in school-committee meetings is one of the richest sources of research ideas I’ve ever had.”
When Thomas Menino, Boston’s long-serving former mayor, expressed concern that the city’s policy of busing kids to their school of choice across the city was undermining the sense of community around some schools, Mr Pathak looked into “walk zones”, which reserve systems some places for children living within walking distance. Seemingly innocuous details of such schemes turned out to have far-reaching effects. The theoretical subtleties he uncovered proved to be “incredibly rich”, Mr Pathak says, keeping him fruitfully busy for a couple of years on something that “there’s no way we would have looked at…without interacting with Boston and the mayor.” By answering practical questions rigorously, economists can both make themselves useful and be spurred in interesting new directions.
The importance of fingerwork
Mozart’s first biographer claimed that the child prodigy composed his music feverishly in his mind, without ever coming to the “klavier”. Many people came to believe that he could compose whole masterpieces while walking after dinner, travelling in a carriage or “in the quiet repose of the night”.
More recent musicology casts doubt on this account. Much of Mozart’s work was sketched out, or even improvised, on a keyboard; he is thought to have done little composition without one.
The theorists of the 1980s resembled the mythical Mozart of the popular imagination, completing beautiful deductive theories with their minds, before seeing how they played in the real world. The best young economists of today more closely resemble the less magical Mozart described by later scholars. Just as he walked back and forth between his compositional sketches and his piano, they move back and forth between their theoretical notation and their empirical instruments, searching for the keys to knowledge.