この問題を克服するための1つのアプローチは、20世紀の戦時の軍事支出に対する米国の生産量の反応を研究することです（Ramey and Shapiro 1989、Ramey 2011、Barro and Redlick 2011、Hall 2009）。ここでの考えは、これらの戦争は当時の米国経済の状態とはほとんど関係のない地政学的要因によって引き起こされたということです。ただし、大規模な戦争はほとんどありません。また、戦争はしばしば愛国心の高まりと経済に直接影響を与える可能性のある経済活動の規制を伴います。そして、水をさらに混乱させるために、戦争の資金を調達するために同時に増税される範囲に大きなばらつきがあります。これらの理由から、私たちがこれらの戦争から学ぶことができることはあまりありません。
軍事費の地域差を使用して乗数を特定する
これらの問題は、政府支出の疑似ランダム変動の他のソースの探求を動機付けます。最近の研究では、私たちのアプローチは、米国における軍事支出の地域差を活用することでした（Nakamura and Steinsson 2011）。米国が軍事力増強に着手すると、一部の州では他の州よりも支出が増加する傾向があるという事実を利用しています。たとえば、米国の総軍事支出がGDPの1％増加すると、カリフォルニアの軍事支出は平均でカリフォルニアのGDPの約3％増加しますが、イリノイの軍事支出はイリノイのGDPの約0.5％しか増加しません。カリフォルニアのような州はイリノイのような州に比べてひどく行動しているため、米国はベトナム戦争のような軍事力の蓄積に着手しないという仮定の下で、これらの蓄積に関連する地域の変動を使用して、支出の相対的増加の効果を推定することができます相対出力。私たちの結論は、
州の相対的な支出がGDPの1％増加すると、相対的な州のGDPは1.5％増加するということです。
他の多くの著者が最近、同様の相対的な乗数を推定するために、支出における他の国の変動のソースを悪用しました。たとえば、Shoag（2011）は、州の年金制度への棚ぼた返還に関連する支出の増加を研究しています。 Acconcia et al（2011）は、政治腐敗の証拠によって引き起こされたマフィアに対する法的に強制された取り締まりに関連したイタリアの州レベルの支出の削減を研究しています。 Chodorow-Reich et al（2011）、Clemens and Miran（2011）、Cohen et al（2011）、Fishback and Kachanovskaya（2011）、およびWilson（2011）の研究も参照してください。これらの論文の大部分は、相対的な支出に対する相対的な支出の影響を見積もっており、これは我々が見積もったものと同程度かそれよりも大きかった-1.5から2.5の間の乗数。
1.5の乗数は大きすぎて本当ではありませんか？
一見したところ、これらの乗数は非常に大きく（たとえば、Barro and Redlick 2011およびRamey 2011の推定と比較して）、したがって追加の財政刺激策の支持者にとって好ましいように見えるかもしれません。ただし、これらの実験結果を解釈する際には注意が必要です。
地域の消費ショックに対する国家政策の反応と総支出ショックに対するこの違いは、実質的に、政府の支出乗数が比較的緩和的な金融および税政策の反応を条件としていることを意味します。これは、おそらくBarro and Redlick（2011）およびRamey（2011）の乗数推定値よりも乗数推定値が高い理由を説明している可能性があります。
A major question facing many governments in the rich world today is whether we should try to stimulate the economy by increasing government spending. The professional opinion of economists regarding this question is sharply divided. While many economists believe that increases in government spending can have large ‘multiplier’ effects – ie increase output by more than the increase in spending – many others are sceptical of this and some even believe that increases in government spending may harm the recovery.
A major reason for this disagreement is that it is notoriously hard to construct convincing empirical evidence on the effects of fiscal stimulus. The empirical challenge is a familiar one; correlation does not imply causation. In the case of fiscal stimulus, the simple-minded approach of seeing whether output is high in periods of high government spending doesn’t work since governments tend to systematically increase spending when output is low for some other reason, eg because of a financial crisis. The simple correlation will then ‘confound’ the effects of government spending with the effects of other factors. What is needed is some sort of ‘natural experiment’, ie pseudo-random variation in government spending.
One approach to overcoming this problem is to study how US output has responded to wartime military spending in the 20th century (Ramey and Shapiro 1989, Ramey 2011, Barro and Redlick 2011, Hall 2009). The idea here is that these wars were caused by geopolitical factors that were largely unrelated to the state of the US economy at the time. However, large wars are few and far between. Also, wars often involve a surge of patriotism and controls on economic activity that can directly impact the economy. And to muddle the water even further, there is a large degree of variation in the extent to which taxes are raised contemporaneously to finance the war. For these reasons there is only so much we can learn from these wars.
Using regional variation in military spending to identify the multiplier
These issues motivate the quest for other sources of pseudo-random variation in government spending. In recent work, our approach has been to exploit regional variation in military spending in the US (Nakamura and Steinsson 2011). We use the fact that when the US embarks upon a military buildup, there is a systematic tendency for spending to increase more in some states than others. For example, when aggregate military spending in the US rises by 1% of GDP, military spending in California on average rises by about 3% of California GDP, while military spending in Illinois rises by only about 0.5% of Illinois GDP. Under the assumption that the US doesn’t embark upon military buildups like the Vietnam War because states like California are doing badly relative to states like Illinois, we can use regional variation associated with these buildups to estimate the effect of a relative increase in spending on relative output. Our conclusion is that when relative spending in a state increases by 1% of GDP, relative state GDP rises by 1.5%.
A number of other authors have recently exploited other sources of sub-national variation in spending to estimate similar relative multipliers. For example, Shoag (2011) studies increases in spending associated with windfall returns to state pension plans; and Acconcia et al (2011) study reductions in provincial-level spending in Italy associated with legally mandated crackdowns on the mafia that were triggered by evidence of political corruption. See also studies by Chodorow-Reich et al (2011), Clemens and Miran (2011), Cohen et al (2011), Fishback and Kachanovskaya (2011), and Wilson (2011). Most of these papers have estimated effects of relative spending on relative output that are of a similar magnitude to those we estimate or somewhat larger – multipliers between 1.5 and 2.5.
Are multipliers of 1.5 too large to be true?
At first glance, these multiplier numbers may seem quite large (eg relative to the estimates of Barro and Redlick 2011 and Ramey 2011) and thus favourable to advocates of additional fiscal stimulus. However, some care is required in interpreting these empirical results.
One difference between our estimates and older evidence based on aggregate data is that in our setting, the region getting the spending is not paying for it. Could this be the reason why we are getting such a high multiplier estimate? Neoclassical models would actually suggest the opposite. The reason is that the negative wealth shock that accompanies an aggregate government spending shock causes an increase in labour supply. The fact that no such wealth shock occurs in our setting should thus lower the multiplier, not raise it.
Another important difference is that when spending increases in California relative to Illinois, national government policy is held fixed across these states. For example, the Fed is not able to respond by raising interest rates in California relative to Illinois, and Congress does not respond by raising tax rates in California relative to Illinois.
In sharp contrast, monetary and tax policy is not constant in response to aggregate government spending shocks. “Normal” monetary policy – eg the policy practiced by the Fed under the leadership of Paul Volcker and Alan Greenspan – is to ‘lean against the wind’ quite aggressively by raising real interest rates – or decreasing them by less– in response to aggregate government-spending shocks. The tax policy response to aggregate government-spending shocks varies more over time. During the Korean War, taxes were raised by a large amount. This is less true for more recent military buildups.
This difference between the response of national policy to a regional spending shock and an aggregate spending shock implies that the government spending multiplier we estimate, in effect, is conditioning on a relatively accommodative monetary and tax policy response. This likely explains why our multiplier estimate is higher than those of, eg Barro and Redlick (2011) and Ramey (2011).
Do we need additional stimulus today?
So, what does our analysis imply about the effects of additional stimulus today? One lesson that our analysis illustrates is that there is no ‘single multiplier,’ but rather the multiplier is highly sensitive to the stance of monetary and tax policy (see also Woodford 2011 on this point). An important special feature of the current situation in many economies is that nominal interest rates are very close to their lower bound of zero. This constraint implies that nominal interest rates are likely higher at the moment than the monetary authorities in these countries would like them to be. This means that these central banks are unlikely to respond to fiscal stimulus by raising rates the way they would in normal times. In other words, monetary policy is likely to be more accommodative in response to fiscal stimulus today than in normal times.
It turns out that our analysis is particularly well suited to help us draw inference about this situation. As we discuss above, we know from the fact that the US is a monetary and fiscal union that the Fed can’t differentially increase interest rates in one region versus another and that Congress doesn’t raise tax rates in one region relative to another. This pins down an important ‘moving part’ when it comes to interpreting our estimate of the fiscal multiplier.
For estimates based on aggregate variation in spending, it is much less clear what the monetary and tax policy response was at the time and it is therefore much harder to interpret these estimates and much harder to distinguish between the Neoclassical and the New Keynesian view of how government spending affects the economy.
The fact that we can pin down relative policies allows us to show that our estimates are much more consistent with New Keynesian models in which ‘aggregate demand’ shocks – such as government spending shocks – have large effects on output when monetary policy is sufficiently accommodative than they are with the plain-vanilla Neoclassical model. In particular, our results support the view that aggregate fiscal stimulus should have large output multipliers when the economy is at the zero lower bound.
Barro, R. J., and C. J. Redlick (2011) “Macroeconomic Effects from Government Purchases and Taxes,” Quarterly Journal of Economics, 126(1), 51-102.
Chodorow-Reich, G., L. Feiveson, Z. Liscow, and W. G. Woolston (2011) “Does State Fiscal Relief During Recessions Increase Employment? Evidence from the American Recovery and Reinvestment Act,” Working Paper, University of California at Berkeley.
Clemens, J., and S. Miran (2011) “The Effects of State Budget Cuts on Employment and Income,” Working Paper, Harvard University.
Cohen, L., J. Coval, and C. Mallow (2011) “Do Powerful Politicians Cause Corporate Downsizing?,” Journal of Political Economy, forthcoming.
Fishback, P., and V. Kachanovskaya (2010) “In Search of the Multiplier for Federal Spending in the States During the New Deal,” NBER Working Paper No. 16561.
Hall, R.E. (2009) “By How Much Does GDP Rise if the Government Buys More Output?,” Brookings Papers on Economic Activity, 2009(2), 183-249.
Ramey, V. A. (2011) “Identifying Government Spending Shocks It's All in the Timing,” Quarterly Journal of Economics, 126(1), 1-50.
Ramey, V. A., and M. D. Shapiro (1998) “Costly Capital Reallocation and the Effects of Government Spending,” Carnegie-Rochester Conference Series on Public Policy, 48(1), 145-194.
Serrato, J. C. S., and P. Wingender (2011) “Estimating Local Fiscal Multipliers,” Working Paper, University of California at Berkeley.
Shoag, D. (2011) “The Impact of Government Spending Shocks Evidence on the Multiplier from State Pension Plan Returns,” Working Paper, Harvard University.
Wilson, D. J. (2011) “Fiscal Spending Jobs Multipliers Evidence from the 2009 American Recovery and Reinvestment Act,” Working Paper, Federal Reserve Bank of San Francisco.
Woodford, M. (2011) “Simple Analytics of the Government Expenditure Multiplier,” American Economic Journal Macroeconomics, 3(1), 1-35.
Nakamura, Emi; Steinsson, Jon (2014). "Fiscal stimulus in a monetary union: Evidence from US regions". The American Economic Review. 104 (3): 753–792. JSTOR42920719. uses regional variation in US military spending to estimate an "open economy multiplier" of 1.5. This empirical evidence "indicates that demand shocks can have large effects on output", particularly at the zero lower bound.[12]
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.
Nakamura, Emi; Steinsson, Jon (2008). "Five facts about prices: A reevaluation of menu cost models". The Quarterly Journal of Economics. 123 (4): 1415–1464. JSTOR40506213. This paper analyzes detailed microeconomic price data and describes firms' price-setting behavior to test the menu cost model of price stickiness. They find mixed evidence: some facts in the data are consistent with the menu cost model, but others are not.
Nakamura, Emi; Steinsson, Jon; Sun, Patrick; Villar, Daniel (2018). "The Elusive Costs of Inflation: Price Dispersion during the U.S. Great Inflation"(PDF). Quarterly Journal of Economics. 133(4): 1933–1908. attempts to measure the costs of inflation. In the commonly used New Keynesian macroeconomic models, the social costs of inflation arise from inefficient price dispersion: higher inflation implies higher price dispersion. Nakamura et al. digitize price data from the era of high inflation in the US in the 1970s and 1980s to test this hypothesis. They find "no evidence that the absolute size of price changes rose during the Great Inflation", and conclude that "This suggests that the standard New Keynesian analysis of the welfare costs of inflation is wrong and its implications for the optimal inflation rate need to be reassessed".
American Economic Association Honors and Awards Committee April 2019
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.
Photographer: Graham Morrison, Bloomberg/American Economic Association
The John Bates Clark medal is arguably the most exclusive award in the field of economics. It’s given to only one economist each year — unlike the Nobel prize, which often is shared among several (though the Clark medal is only for Americans). And one must be under age 40 to receive it. This year’s prize goes to Emi Nakamura of the University of California-Berkeley, an undisputed star in the field of macroeconomics.
Unlike the Nobel, it’s rare for a macroeconomist to get the Clark medal. Arguably the last winner whose research dealt mainly with the business cycle was Lawrence Summers, who received the prize all the way back in 1993. For at least the past two decades, macroeconomics has tended to be a discipline ruled by consensus and by incremental innovations, with few standout geniuses. Nakamura is a rare exception.
Nakamura is one of the leaders in the field of New Keynesian economics. This school of thought, which has become the dominant paradigm at central banks around the world, holds that recessions happen because companies are unable to adjust their prices in response to events like a financial crisis or a big rise in interest rates. Without the ability to adjust prices, the theory goes, companies cut their output and lay off workers instead. In a 2008 paper with frequent co-author and husband Jon Steinsson, Nakamura showed that even very small amounts of this so-called price stickiness can generate large recessions, and make the economy very sensitive to changes in monetary policy.
Exactly why companies can’t adjust prices, however, remains something of a mystery. Nakamura’s research has helped to shed light on this question. Another 2008 paper with Steinsson helped to establish that price stickiness probably results from multiple factors.
But despite her status as one of the leading lights of New Keynesian economics, Nakamura has spent much of her career challenging the idea. In a recent paperwith Steinsson, she showed that interest rate cuts tend to boost expectations of future growth without raising expected inflation much — in contradiction of what standard New Keynesian models (and the intuition of many macroeconomists) would predict. In another paper the two economists questioned the assumption of many New Keynesian models that inflation causes as much harm to the economy as unemployment.
The biggest failure of standard New Keynesian models is that they assume a central bank always has the ability to fight recessions by lowering interest rates. The recent Great Recession exposed the limits of this tool because nominal interest rates can’t go much below zero. Some economists have suggested that in lieu of cutting rates, central banks could use forward guidance — that is, promising to keep rates lower for longer even after the recession ends — to much the same effect. But together with Alisdair McKay and Steinsson, Nakamura showed that theories that predict big effects for forward guidance are highly unrealistic.
If interest rate cuts and forward guidance fail, what can be done to fight recessions? One of the most potent weapons might be fiscal stimulus via government spending programs. In 2011, as the U.S. was struggling to get its economy growing again and politicians were debating whether to enact deep budget cuts, Nakamura and Steinsson came out with the first version of a papermeasuring the effects of stimulus. Looking at differences in military procurement across states, the economists measured how changes in local government spending boosted local economies. Their conclusion — that each dollar of government spending stimulated about 50 cents of additional private economic activity — was influential both within the economics profession and outside of it.
But macroeconomics being the inexact science that it is, even very well-done papers like Nakamura and Steinsson’s can’t prove beyond a shadow of a doubt that stimulus works. That’s why macroeconomists often have to act like detectives, gathering shreds of statistical evidence from a variety of sources and aggregating them into a coherent picture. In a recent survey paper, Nakamura and Steinsson discuss statistical approaches that macroeconomists can use to be more confident that the correlations they observe really represent causation.
Thus, over the past decade, Nakamura has contributed a vast amount to economists’ understanding of the theory and evidence regarding business cycles. Even this list doesn’t really provide a full summary of her contributions — for example, in a recent paper with Masao Fukui and Steinsson, she showed evidence that women’s entry into the labor force hasn’t crowded out men very much. She has also done work on the economics of housing, exchange rates, distortions in Chinese economic data, the impact of uncertainty on the business cycle, and the relationships between retailers and wholesalers. In an age of hyper-specialization, Nakamura stands out as a virtuoso.
Macroeconomics is an inherently difficult subject, where theory and data are both extremely limited and progress tends to proceed in small increments rather than leaps and bounds. But the contributions of Emi Nakamura show that there are still top minds working in macroeconomics. The world will be better off as a result.
(Corrects second paragraph to indicate that Lawrence Summers was the last macroeconomist to win to John Bates Clark Medal.)
This column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.
Her research focuses on empirical issues in macroeconomics, including price stickiness, the impact of fiscal shocks, and measurement errors in official statistics. In particularly influential work, she showed that many measured price changes are due to temporary sales, scheduled far in advance, rather than happening as dynamic responses to economic conditions.[8]
She is married to fellow economist Jon Steinsson,[9] and is the daughter of economists Alice Nakamura and Masao Nakamura[10][11] and the granddaughter of economist Guy Orcutt.
Nakamura, Emi; Steinsson, Jon (2008). "Five facts about prices: A reevaluation of menu cost models". The Quarterly Journal of Economics. 123 (4): 1415–1464. JSTOR40506213. This paper analyzes detailed microeconomic price data and describes firms' price-setting behavior to test the menu cost model of price stickiness. They find mixed evidence: some facts in the data are consistent with the menu cost model, but others are not.
Nakamura, Emi; Steinsson, Jon; Sun, Patrick; Villar, Daniel (2018). "The Elusive Costs of Inflation: Price Dispersion during the U.S. Great Inflation"(PDF). Quarterly Journal of Economics. 133(4): 1933–1908. attempts to measure the costs of inflation. In the commonly used New Keynesian macroeconomic models, the social costs of inflation arise from inefficient price dispersion: higher inflation implies higher price dispersion. Nakamura et al. digitize price data from the era of high inflation in the US in the 1970s and 1980s to test this hypothesis. They find "no evidence that the absolute size of price changes rose during the Great Inflation", and conclude that "This suggests that the standard New Keynesian analysis of the welfare costs of inflation is wrong and its implications for the optimal inflation rate need to be reassessed".
Nakamura, Emi (2018). "High-Frequency Identification of Monetary Non-Neutrality: The Information Effect"(PDF). Quarterly Journal of Economics. 133(3): 1283–1330. demonstrates changes in financial market expectations of real variables (the real interest rate, and economy growth) in the thirty-minute window after Federal Reserve rate announcements.
McKay, Alisdair; Nakamura, Emi; Steinsson, Jon (2016). "The Power of Forward Guidance Revisited"(PDF). American Economic Review. 106(10): 3133–3158. argues that the effects of forward guidance are likely to be substantially reduced if financial markets are incomplete: specifically, if agents face borrowing constraints and uninsurable income risk.
Nakamura, Emi; Steinsson, Jon (2010). "Monetary non-neutrality in a multisector menu cost model". The Quarterly Journal of Economics. 125 (3): 961–1013. JSTOR27867504.
Nakamura, Emi; Zerom, D (2010). "Accounting for incomplete pass-through". The Review of Economic Studies. 77 (3): 1192–1230. JSTOR40835861.
Nakamura, Emi; Steinsson, Jon (2014). "Fiscal stimulus in a monetary union: Evidence from US regions". The American Economic Review. 104 (3): 753–792. JSTOR42920719. uses regional variation in US military spending to estimate an "open economy multiplier" of 1.5. This empirical evidence "indicates that demand shocks can have large effects on output", particularly at the zero lower bound.[12]
政府支出の乗数を推定する際のさらなる複雑さは、その大きさが政府支出の変化に対する資金調達の仕方に左右されるということです。これまでの研究では、資金調達上の考慮事項をどのように考慮に入れるかという問題がありました。Nakamura and Steinssonの実証的戦略の利点は、地域の軍事支出が連邦税によって賄われているため、軍事支出の大部分を受け取る地域は軍事支出を受け取らない地域とは異なる税構造を持たないことです。したがって、地域の軍事支出の変動を考慮し、それを地域の生産高変動と関連付けることで、以前の研究よりもはるかに信頼性の高い政府支出倍率の推定値が得られるはずです。
Emi Nakamura, Clark Medalist 2019 https://www.aeaweb.org/about-aea/honors-awards/bates-clark/emi-nakamura https://2.bp.blogspot.com/-0a5PqWCOxk0/XMqP9y_pYPI/AAAAAAABidU/gHmIK1X9dNYr_99ynOWeoIEDCPy0qT4LACLcBGAs/s1600/IMG_4833.JPG
Emi Nakamura(米国籍)の論考はマンキューマクロ入門篇でも言及されている。邦訳第4版。 http://nam-students.blogspot.com/2017/11/9th-ed.html マンキュー マクロ経済学 第４版 9th ed https://www.amazon.co.jp/dp/4492315047 入門篇、旧第３版からの変更点はまえがき(vii)に詳しい。 新第９章のケース・スタデイ「乗数の推定における地域デー夕の利用」(348頁)で新たに参照されたのは 以下の論文。 エミ・ナカムラとジョン・スタインソン Fiscal Stimulus in a Monetary Union: Evidence from US Regions By Emi Nakamura and Jon Steinsson http://www.columbia.edu/~en2198/papers/fiscal.pdf 軍事予算の乗数効果を扱った異色の論考。 メニューコストなど価格理論が有名。
3 Comments:
89 名無しさん＠お腹いっぱい。[] 2019/05/02(木) 15:37:37.26 ID:1OTmPLgY
Emi Nakamura(アメリカ国籍) 2019年クラーク賞受賞
Emi Nakamura, Clark Medalist 2019
https://www.aeaweb.org/about-aea/honors-awards/bates-clark/emi-nakamura
https://2.bp.blogspot.com/-0a5PqWCOxk0/XMqP9y_pYPI/AAAAAAABidU/gHmIK1X9dNYr_99ynOWeoIEDCPy0qT4LACLcBGAs/s1600/IMG_4833.JPG
Emi Nakamura(米国籍)の論考はマンキューマクロ入門篇でも言及されている。邦訳第4版。
http://nam-students.blogspot.com/2017/11/9th-ed.html
マンキュー マクロ経済学 第４版 9th ed
https://www.amazon.co.jp/dp/4492315047
入門篇、旧第３版からの変更点はまえがき(vii)に詳しい。
新第９章のケース・スタデイ「乗数の推定における地域デー夕の利用」(348頁)で新たに参照されたのは
以下の論文。
エミ・ナカムラとジョン・スタインソン
Fiscal Stimulus in a Monetary Union: Evidence from US Regions
By Emi Nakamura and Jon Steinsson
http://www.columbia.edu/~en2198/papers/fiscal.pdf
軍事予算の乗数効果を扱った異色の論考。
メニューコストなど価格理論が有名。
参考
2015年インタビュー
https://www.aeaweb.org/content/file?id=1158
母親(もまた高名な経済学者)のインタビュー
https://en.wikipedia.org/wiki/Alice_Nakamura
Nobel Symposium Emi Nakamura Monetary policy: Conventional and unconvent...
2018年 33:21
https://youtu.be/srbcIgNXPVM
「世界のナカムラ」が切り開く低金利時代の経済学：日経ビジネス電子版
https://business.nikkei.com/atcl/seminar/19/00030/062100027/?n_cid=nbponb_twbn
「世界のナカムラ」が切り開く低金利時代の経済学
日本にルーツ、気鋭のマクロ経済学者が権威ある賞を受賞
広野 彩子2019年6月25日
全2547文字
米連邦準備理事会（FRB）が6月19日、米連邦公開市場委員会（FOMC）の会合後に公表した声明文の表現を改めたことから、米国では早期利下げの見方が強まっている。中央銀行が将来の金融政策の方針を前もって表明する「フォワードガイダンス」は日本を含めた中銀が採用している。だが、ある気鋭の経済学者はその効果に懐疑的である。
「フォワードガイダンスは米国や日本で近年、極めて重要な政策になっている。だが低金利の中でさらに利下げを表明したところで、人々の景気の先行き見通しを変えて消費をこれ以上刺激することは難しい。効果は小さなものにとどまるだろう。低金利下では、長期的には政府負債の増大につながるものの、非伝統的な金融政策とともに財政刺激政策を考慮することが重要」――。こう指摘するのは、金融政策や価格の硬直性などを実証研究する米カリフォルニア大学バークレー校の中村恵美（Emi Nakamura）教授である。カナダ国籍と米国籍を持つ日系二世だ。
中村恵美（Emi Nakamura）
米カリフォルニア大学バークレー校教授
1980年10月生まれ。2001年、米プリンストン大学で経済学を学び、最優等で卒業、米ハーバード大学大学院でロバート・バロー教授らに師事、2007年に経済学で博士号取得（Ph.D.）。米コロンビア経営大学院で助教授、准教授、教授を経て2018年から現職。経済学者の夫と子供2人、38歳。
中村教授はこのほど、40歳以下の米国の経済学者に与えられる「ジョン・ベーツ・クラーク賞」を受賞した。同賞は、ノーベル経済学賞の登竜門といわれ、過去には故人のポール・サミュエルソンやミルトン・フリードマンをはじめ、現在も活躍するロバート・ソロー教授やポール・クルーグマン教授、ジョセフ・スティグリッツ教授ら、のちにノーベル経済学賞を受賞した著名な経済学者が受賞者に名を連ねる。
金利がゼロより下がらない状況の中、非伝統的な金融政策が多くの国で採用されてきたが、その正当性は理論モデルで担保されていると考えられてきた。最も典型的なものがフォワードガイダンスだ。「フォワードガイダンスはニューケインジアンと呼ばれる我々世代の研究者が提案したもの」と、東京大学大学院経済学研究科の渡辺努教授はいう。「しかしその理論モデルがよって立つ仮定の吟味が不十分だった。実際、フォワードガイダンスは当初考えられていたほどの効果を発揮しておらず、仮定が正しくなかったことを示している。中村教授らは仮定を丁寧に見直すことで、ゼロ金利下の金融政策の議論に大きな影響を及ぼした」。
またこれまで注目を浴びた研究の一つに、夫であるアイスランド人のジョン・スタインソン米カリフォルニア大学バークレー校教授と発表した論文がある。米国州政府を国とみなし、合衆国を通貨連盟に見立てながら、各州のGDP（域内総生産）と軍事支出の解析を通じて低金利の先進国における財政刺激策の有効性を検証したもので、冒頭のコメントの裏付けの1つともなる知見を提供している。
次ページ「マクロ経済学の仮説を疑え」
「世界のナカムラ」が切り開く低金利時代の経済学 (2ページ目)：日経ビジネス電子版
https://business.nikkei.com/atcl/seminar/19/00030/062100027/?P=2
「世界のナカムラ」が切り開く低金利時代の経済学
日本にルーツ、気鋭のマクロ経済学者が権威ある賞を受賞
広野 彩子2019年6月25日
全2547文字
「マクロ経済学の仮説を疑え」
中村教授の研究が際立っているのは、個別製品の実際の価格改定の頻度など、これまでマクロ経済の分析では使われることの珍しかった現実の生データを入手し、地道に分析し続けてきた点にある。フォワードガイダンスの検証のみならず、「物価は変わりにくい」「デフレは悪い」といった、過去のマクロ経済学者が当然として受け入れてきた仮定を疑い、実証研究を積み重ねながら挑んできたのだ。
上記2つの疑問に対する現在の中村教授の答えは以下。マクロ的な物価は変動しにくいか？ 「科学的根拠から、やはりしにくいことが分かった」。「デフレ」は悪いことか？ 「価格が下落している時に名目金利がゼロ近くになっていると、実質金利がかなり高くなってしまう。それが消費者の需要減につながり、景気後退につながり得る」。
「中村教授と（夫である）スタインソン教授による一連の研究は、その後の研究にとって標準、ベンチマークとなっている」と、阿部修人・一橋大学経済研究所教授は評する。東大の渡辺教授は「中村教授らの真骨頂は、マクロ経済学で当たり前とみなされてきた仮定をデータで検証しようとしてきた独自の視点と研究のセンス」という。
「中央銀行の役割は価格を安定させることで、その理屈は理論モデルに基づく。だが理屈がよって立つ仮定が正しいかどうかの確認はできていなかった。また物価安定が損なわれた時、理論モデルが想定するような悪いことが本当に起きるのかどうかもわかっていなかった。基礎的なことが理解できていないので、日本のデフレについて『デフレでもいいじゃないか』と言う人が現れても学者はきちんと反論できない。中村教授らは、これまで確認を怠ってきた重要な事項について、実際のデータを駆使しながら迫り、大きな成果を挙げた」（渡辺教授）。
つまり中村教授らの研究は、2008年のリーマン危機以降すっかり勢いをなくしていたマクロ経済学に、科学的根拠に基づく研究手法を取り入れることによって、新風を吹き込んできたのだ。
父方の祖父は生前、東京・台東区で豆腐店を経営
中村教授は「学者一家」の生まれ。父親は慶應義塾大学卒で元東芝のエンジニアであった経済学者、中村政男カナダ・ブリティッシュ・コロンビア大学名誉教授。母親は米国人経済学者アリス・ナカムラ・カナダ・アルバータ大学教授。兄のケン・ナカムラ氏が米カリフォルニア大学サンフランシスコ校准教授の神経学者だ。
「子供のころ、よく母に経済学会に連れていかれ、いろいろな経済学者と知り合った。家では常にデータで解明することの重要性を両親が議論していたので、かなり影響を受けたと思う」と本人は話す。
日常的に使うのは英語だ。とはいえ父方の祖父は生前、東京・台東区で豆腐店を営み、幼少期の夏を日本で過ごした。幼稚園から小学校まで毎夏来日しては1カ月間、同区の竹町小学校（現・平成小学校）に通い、日本の小学校の掃除当番や給食など、日本ならではのカリキュラムを楽しんだという。
また最近の研究では、米国において、過去には女性の景気回復時における労働市場への参入スピードが男性より速かったのが、近年は女性も男性と同じような動きをすることになったため、雇用回復全体も遅くなったとする研究や、転職頻度が景気とどう関係するかに注目する研究など、労働市場に関する研究にも意欲的に取り組んでいる。
マクロ経済学に新風を巻き起こしている「世界のナカムラ」の研究が、先行き不透明な先進国の金融・経済政策に一石を投じる日もそう遠くはないかもしれない。
2020/02/20
安い外国製品に頼るなら
フィリップス曲線が対応しなくなるのは当たり前
いつまでも頼れるわけではない
世界レベルの統計ならフィリップス曲線は有効だ
主流派のグローバリズム前提の議論は底が浅い
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