In this paper we develop a block bootstrap approach to out-of-sample inference when real-time data are used to produce forecasts. In particular, we establish its first-order asymptotic validity for
West-type (1996) tests of predictive ability in the presence of regular data revisions. This allows the user to conduct asymptotically valid inference without having to estimate the asymptotic variances
derived in Clark and McCracken’s (2009) extension of West (1996) when data are subject to revision. Monte Carlo experiments indicate that the bootstrap can provide satisfactory finite sample size and power even in modest sample sizes. We conclude with an application to inflation forecasting that adapts the results in Ang et al. (2007) to the presence of real-time data.
As a result of the BoJ's large-scale asset purchases, the consolidated Japanese government borrows mostly at the floating rate from households and invests in longer-duration risky assets to earn an extra 3% of GDP. We quantify the impact of Japan's low-rate policies on its government and households. Because of the duration mismatch on the government balance sheet, the government's fiscal space expands when real rates decline, allowing the government to keep its promises to older Japanese households. A typical younger Japanese household does not have enough duration in its portfolio to continue to finance its spending plan and will be worse off. Low-rate policies tax younger, poorer and less financially sophisticated households.
We present a ranking of journals geared toward measuring the policy relevance of research. We compute simple impact factors that count only citations made in central bank publications, such as their working paper series. Whereas this ranking confirms the policy relevance of the major general interest journals in the field of economics, the major finance journals fare less favourably. Journals specialising in monetary economics, international economics and financial intermediation feature highly, but surprisingly not those specialising in econometrics. The ranking is topped by the Brookings Papers on Economic Activity, followed by the Quarterly Journal of Economics and the Journal of Monetary Economics, the American Economic Journal: Macroeconomics, and the Journal of Political Economy.
We study a simple model where a single good can be produced using a diminishing-returns technology (Malthus) and a constant-returns technology (Solow). The economy's output exhibits three stages: (i) stagnation, (ii) transition with increasing growth, and (iii) constant growth in the long run. We map the Malthus technology to agriculture and show that the share of agricultural employment is sufficient to determine the onset of economic transition. Using data on the share, we estimate the onset of transition for the U.S. and Western Europe without using output data. Our model implies that output growth during the transition is a first-order autoregressive process and that the rate of decline in the share of agricultural employment is a sufficient statistic to describe the output growth. Quantitatively, while there is no a priori reason why agricultural employment would pin down output dynamics over two centuries, the autoregressive coefficient on the output growth process is practically the same as the one implied by the rate of decline in the share of agricultural employment.
This paper studies differences in health care usage and health outcomes between low- and high-income individuals. Using data from the Medical Expenditure Panel Survey (MEPS) I find that early in life the rich spend significantly more on health care, whereas from middle to very old age medical spending of the poor surpasses that of the rich by 25%. In addition, low-income individuals are less likely to incur any medical expenditures in a given year, yet, when they do, their expenses are more likely to be extreme. To account for these facts, I develop and estimate a life-cycle model of two types of health capital: physical and preventive. Physical health capital determines survival probabilities, whereas preventive health capital governs the endogenous distribution of shocks to physical health capital, thereby controlling the life expectancy. Moreover, I incorporate important features of the U.S. health care system such as private health insurance, Medicaid, and Medicare. In the model, from the very early ages the rich spend more in preventive health to expand their life expectancy, which leads to milder health shocks (and lower curative medical expenditures) for them in old age compared to the poor. Public insurance—which is designed to insure large expenditures—amplifies these differences by hampering the incentives of the poor to invest in preventive health. I use the model to examine a counterfactual economy with universal health insurance in which 75% of preventive medical spending is reimbursed. My results suggest that policies encouraging the use of health care by the poor early in life produce significant welfare gains, even when fully accounting for the increase in taxes required to pay for them.
This paper investigates patterns in real wage growth in 2022 to determine whether wages have kept up with rising price levels, and how this differs among labor market participants. Using the CPS for wages and imputing expenditure data from the CEX, we measure separately nominal wage growth and inflation rates at the micro level. We find that there is more heterogeneity in the former, meaning that when we combine them, an individual’s real wage growth is primarily driven by their nominal wage growth. In 2022, 57% of individuals experienced negative real wage growth, with older and less educated workers, as well as job-stayers, being hit the hardest. Conversely, younger and highly educated workers, as well as job-switchers, had higher real wage growth.
We study the multidimensional sorting of males and females in the U.S. marriage market over the past decade using a model of targeted search. We find strong vertical sorting on income and education, and horizontal sorting on race. We find that women put significant effort into targeting men at the top of the desirability scale, while men put less effort and target women with similar characteristics. We find no improvement in quality of matching and no noticeable changes in sorting patterns or individual search behavior, despite rapid improvement in search technology. Finally, we find that targeted search substantially reduces income inequality across married couples, even when compared with random matching, by producing a large number of matches between low income and high income individuals.
We revisit the measurement of the sources and consequences of job displacement using Canadian job separation records. To circumvent administrative data limitations, conventional approaches address selection by identifying displacement effects through mass-layoff separations, which are interpreted as involuntary. We refine this procedure and find that only a quarter of mass-layoff separations are indeed layoffs. Isolating mass-layoff separations that reflect involuntary displacement, we find twice the earnings losses relative to existing estimates. We uncover heterogeneity in losses for separations with different reason and timing, ranging from 15 percent for quits after a mass layoff to 60 percent for layoffs before it.
We calculate impulse response functions from regime-switching models where the driving variable can respond to the shock. Two methods used to estimate the impulse responses in these models are generalized impulse response functions and local projections. Local projections depend on the observed switches in the data, while generalized impulse response functions rely on correctly specifying regime process. Using Monte Carlos with different misspecifications, we determine under what conditions either method is preferred. We then extend model-average impulse responses to this nonlinear environment and show that they generally perform better than either generalized impulse response functions and local projections. Finally, we apply these findings to the empirical estimation of regime-dependent fiscal multipliers and find multipliers less than one and generally small differences across different states of slack.
We investigate the role financial conditions play in the composition of U.S. growth-at-risk. We document that, by a wide margin, growth-at-risk is investment-at-risk. That is, if financial conditions indicate U.S. real GDP growth will be in the lower tail of its conditional distribution, we know that the main contributor is a decline in investment. Consumption contributes under extreme financial stress. Government spending and net exports do not play a role.
We investigate whether the losses from an increase in trade costs (protectionism) are equal to the gains from a symmetric decrease in trade costs (liberalization). We incorporate dynamics through capital accumulation into a standard Armington trade model and show that the welfare changes are asymmetric: Losses from protectionism are smaller than the gains from liberalization. In contrast, standard static trade models imply that the losses equal the gains. The intuition for asymmetry in our model is that, following protectionism, the economy can coast off of previously accumulated capital stock, so higher trade costs do not imply large losses immediately. We develop an accounting device to decompose the source of welfare asymmetries into three time-varying contributions: share of income allocated to consumption, measured productivity, and capital stock. Asymmetry in capital accumulation is the largest contributing factor, and measured productivity is the smallest.
Many prominent studies in macroeconomics, labor, and trade use panel data on regions to identify the local effects of aggregate shocks. These studies construct regional-exposure instruments as an observed aggregate shock times an observed regional exposure to that shock. We argue that the most economically plausible source of identification in these settings is uncorrelatedness of observed and unobserved aggregate shocks. Even when the regression estimator is consistent, we show that inference is complicated by cross-regional residual correlations induced by unobserved aggregate shocks. We suggest two-way clustering, two-way heteroskedasticity- and autocorrelation-consistent standard errors, and randomization inference as options to solve this inference problem. We also develop a feasible optimal instrument to improve efficiency. In an application to the estimation of regional fiscal multipliers, we show that the standard practice of clustering by region generates confidence intervals that are too small. When we construct confidence intervals with robust methods, we can no longer reject multipliers close to zero at the 95% level. The feasible optimal instrument more than doubles statistical power; however, we still cannot reject low multipliers. Our results underscore that the precision promised by regional data may disappear with correct inference.
We estimate the local, spillover and aggregate causal effects of government transfers on personal income. We identify exogenous changes in federal transfers to residents at the state-level using legislated social security cost-of-living adjustments between 1952 and 1974. Each effect is measured as a multiplier: the change in personal income in response to a one unit change in transfers. The local multiplier, i.e., the effect of own-state transfers on own-state income holding fixed other state's income, at a four-quarter horizon is approximately 3.4. The cross-state spillover multiplier is about -0.7, but not statistically different from zero. The aggregate multiplier, i.e., the sum of its local and spillover components, equals 2.7. More generally, our paper provides a template for conducting inference that decomposes an aggregate effect into its local and spillover components.
We develop a new framework to measure market-wide (systemic) tail risk in the cross-section of high-frequency stock returns. We estimate the time-varying jump intensities of asset prices and introduce a testing approach that identifies multi-asset tail risk based on the release times of scheduled news announcements. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we find that most of the FOMC announcements create systemic left tail risk, but there is no evidence that macro announcements do so. The magnitude of the tail risk induced by Fed news varies over the business cycle, peaks during the global financial crisis and remains high over different phases of unconventional monetary policy. We use our approach to construct a Fed-induced systemic tail risk (STR) indicator. STR helps explain the pre-FOMC announcement drift and significantly increases variance risk premia, particularly for the meetings without press conferences.
We explore the ability of Large Language Models (LLMs) to produce conditional inflation forecasts during the 2019-2023 period. We use a leading LLM (Google AI's PaLM) to produce distributions of conditional forecasts at different horizons and compare these forecasts to those of a leading source, the Survey of Professional Forecasters (SPF). We find that LLM forecasts generate lower mean-squared errors overall in most years, and at almost all horizons. LLM forecasts exhibit slower reversion to the 2% inflation anchor. We argue that this method of generating forecasts is inexpensive and can be applied to other time series.
The paper presents a two-country model in which a destination country chooses its immigration quota and proactive counterterrorism actions in response to immigration from a terror-plagued source country. After the destination country fixes its two policies, immigrants decide between supplying labor or conducting terrorist attacks, which helps determine equilibrium labor supply and wages. The analysis accounts for the marginal disutility of lost rights/freedoms stemming from stricter counterterror measures as well the inherent radicalization of migrants. Comparative statics involve changes to those two parameters. For example, an enhanced importance attached to lost rights is shown to limit immigration quotas and counterterrorism actions. In contrast, increased source-country radicalization reduces immigration quotas but has an ambiguous effect on optimal proactive measures. Extensions involving defensive policies and destination-country citizens radicalization are considered.
Researchers have carefully studied post-meeting central bank communication and have found that it often moves markets, but they have paid less attention to the more frequent central bankers’ speeches. We create a novel dataset of US Federal Reserve speeches and use supervised multimodal natural language processing methods to identify how monetary policy news affect financial volatility and tail risk through implied changes in forecasts of GDP, inflation, and unemployment. We find that news in central bankers’ speeches can help explain volatility and tail risk in both equity and bond markets. We also find that markets attend to these signals more closely during abnormal GDP and inflation regimes. Our results challenge the conventional view that central bank communication primarily resolves uncertainty.
We incorporate time-averaging into the canonical model of Heckman, Lochner, and Taber (1998) (HLT) to study retirement decisions, government policies, and their interaction with the aggregate labor supply elasticity. The HLT model forced all agents to retire at age 65, while our model allows them to choose career lengths. A benchmark social security system puts all of our workers at corner solutions of their career-length choice problems and lets our model reproduce HLT model outcomes. But alternative tax and social security arrangements dislodge some agents from those corners, bringing associated changes in equilibrium prices and human capital accumulation decisions. A reform that links social security benefits to age but not to employment status eliminates the implicit tax on working beyond 65. High taxes with revenues returned lump-sum keep agents off corner solutions, raising the aggregate labor supply elasticity and threatening to bring about a “dual labor market” in which many people decide not to supply labor.
This paper studies the role of credit constraints in accounting for the dynamics of firm exit during the Great Recession. We present novel firm-level evidence on the role of credit constraints on exit behavior during the Great Recession. Firms in financial distress, with tighter access to credit, are more likely to default than firms with more access to credit. This difference widened substantially in the Great Recession while, in contrast, default rates did not vary much by size, age, or productivity. We identify conditions under which standard models of firms subject to financial frictions can be consistent with these facts.
The U.S. labor force participation rate (LFPR) experienced a record drop during the early pandemic. While it has since recovered to 62.2% as of December 2022, it was still 1.41 pp below its pre-pandemic peak. This gap is explained mostly by a permanent decline in the LFPR for workers older than 55. This paper argues that wealth effects driven by the historically high returns in major asset classes such as stocks and housing may have influenced these trends. Combining an estimated model of wealth effects on labor supply with micro data on balance sheet composition, we show that changes in net worth caused by realized returns explain half of the drop in LFPR in the 2020-21 period and over 80% of "excess retirements'' during the same period.
In the design of an optimal tax-transfer system, there are two complementary conventional wisdoms: the labor-efficiency argument and the debt-efficiency argument. The former emphasizes the trade-off between redistribution and distortions in the labor market, while the latter emphasizes the trade-off between gains from monopoly rents and distortions in the asset market. We use an analytically tractable infinite-horizon model with both ex-ante and ex-post heterogeneity to show that neither argument is complete in the design of the tax-transfer system. Instead, in Aiyagari-type models the optimal system should be determined at the point where the intertemporal wedge between the market interest rate and the time discount rate is completely eliminated, provided that the government fiscal space permits an interior Ramsey steady state. Otherwise the optimal labor tax rate approaches 100% regardless of the Pareto weight distribution in the social welfare function.
This paper examines how the election of 1912 changed the makeup of Congress and led to the Federal Reserve Act. The decision of Theodore Roosevelt and other Progressives to run as third-party candidates split the Republican Party and enabled Democrats to capture the White House and Congress. We show that the election produced a less polarized Congress and that new members were more likely to support the Act. Absent the Republican split, Republicans would likely have held the White House and Congress, and enactment of legislation to establish a central bank would have been unlikely or certainly quite different.
The literature on war deals with finances, causes, or consequences. But, how do war-related expenditures affect economically-relevant outcomes at a war’s conclusion (e.g., prevailing side, duration, and casualties)? I present a model of attrition and characterize the effects of GDP at a military conclusion (one side cannot fight anymore) and a political conclusion (one side quits). The estimated model fits the data for the battle of Iwo Jima well. Analyzing data for the current Russo-Ukrainian war through the lenses of the model suggests that additional support to Ukraine could yield a shorter, cheaper war with less destruction on both sides.
A slowdown in population growth causes a decline in business dynamism by increasing the share of old businesses. But how does it affect productivity growth? We answer this question by extending a standard firm dynamics model to include endogenous productivity growth. Theoretically, the growth rate of the size of surviving old businesses is a “sufficient statistic" for determining the direction and magnitude of the impact of population growth on TFP growth. Quantitatively, this effect is significant across balanced growth paths for the United States and Japan. TFP growth in the United States falls by 0.10-0.23 percentage points because of the slowing in population growth between 1900 and 2060. The same driving force produces a noticeably bigger response in Japan. Despite the significant long-run effect, we discover that changes in TFP growth are slow in reaction to population growth changes due to two short-run counterbalancing factors.
I develop a dynamic model of migration and labor market choice with incomplete markets and uninsurable income risk to quantify the effects of international trade on workers’ employment reallocation, earnings, and wealth. Macroeconomic conditions in different labor markets and idiosyncratic shocks shape agents’ labor market choices, consumption, earnings, and asset accumulation over time. Despite the rich heterogeneity, the model is highly tractable as the optimal consumption, labor supply, capital accumulation, and migration and reallocation decisions of individual workers across different markets have closed-form expressions and can be aggregated. I study the asymmetric impact of international trade on the evolution of employment, earnings, and wealth, and decompose the frictions workers face to reallocate across U.S. sectors and regions into those with a transitory effect and those with long-lasting consequences.
We use 1993–2015 Norwegian administrative panel data on wealth and income to study lifecycle wealth dynamics. At age 50, the excess wealth of the top 0.1%, relative to mid-wealth households, is accounted for by higher saving rates (34%), initial wealth (32%), and higher returns (27%), while higher labor income (5%) and inheritances (1%) account for the residual. One-fourth of the wealthiest—the “New Money”—start with negative wealth but experience rapid wealth growth early in life. Relative to the “Old Money”, the New Money are characterized by even higher saving rates and returns, and also by higher labor income.
While earnings risk is essentially subjective, it is typically inferred from administrative data. We introduce a survey to measure subjective earnings risk, paying particular attention to the expected impacts of job transitions on earnings. Linking with administrative data provides multiple credibility checks. Subjective expectations about earnings growth and job transitions are consistent with actual realizations when appropriately aggregated. We also find subjective earnings risk is lower than risk inferred from administrative data because expected earnings growth is heterogeneous, even within narrow population groups. A life-cycle search model calibrated to the administrative data can recover the basic patterns of subjective risk.
This paper studies the drivers of global shipping dynamics and their aggregate implications. We document novel evidence on the dynamics of global shipping supply, demand, and prices. Motivated by this evidence, we set up a multi-country dynamic model of international trade with a global shipping market where shipping companies and importers endogenously determine shipping supply and prices. We find the model can successfully account for the dynamics of global shipping observed in the aftermath of COVID-19 and that accounting for these has important implications for the dynamics of aggregate economic activity.
We investigate what principles should govern the evolution and maturity structure of the national debt when nominal government securities constitute an important form of exchange media. Even in the absence of government funding risk, we find a rationale for issuing nominal debt in different maturities, purposely mispricing long-term debt, and growing the nominal debt to support a strictly positive inflation target. The policy of discounting long-term debt and supporting a strictly positive inflation target provides superior risk-sharing arrangements for clienteles characterized by different degrees of patience. Pareto improvements are possible only if these policies are offered jointly.
This paper unpacks the role of offshoring in the enforcement of trade agreements. In a two-country model of task offshoring, we show that by depressing demand and thus demand
for embodied labor, own-tariff effects on factor content weighted terms of trade are: (i) negative in upstream countries, backfiring on upstream workers, and (ii) positive in downstream countries
which render imported labor tasks even cheaper. This progression in own-tariff effects on terms of trade along the supply chain presents a novel challenge to the effectiveness of dispute settlement rules designed to nullify unwarranted terms of trade gains. The pros and cons of deep trade integration as a remedy, involving well-enforced labor standards both upstream and downstream as an integral part of trade agreements, are highlighted.