We provide evidence on the real-time predictive content of the National Financial Conditions Index (NFCI), for conditional quantiles of U.S. real GDP growth. Our work is distinct from the literature in two specific ways. First, we construct (unofficial) real-time vintages of the NFCI. This allows us to conduct out-of-sample analysis without introducing the kind of look-ahead biases that are naturally introduced when using a single current vintage. We then develop methods for conducting asymptotic inference on tests of equal tick loss between nested quantile regression models when the data are subject to revision. We conclude by evaluating the real-time predictive content of NFCI vintages for quantiles of real GDP growth. While our results largely reinforce the literature, we find gains to using real-time vintages leading up to recessions — precisely when policymakers need such a monitoring device.
We study the determinants of lifetime earnings (LE) inequality in the U.S. by
focusing on job ladder dynamics and on-the-job learning as sources of wage growth.
Using administrative data, we document that i) lower LE workers change jobs
more often, which is mainly driven by nonemployment; ii) average annual earnings
growth for job stayers is similar, around 2% in the bottom two-thirds of the LE
distribution, whereas for job switchers it rises with LE; iii) top LE workers enjoy
around 10% average earnings growth regardless of job switching. We estimate
a job ladder model with on-the-job learning featuring a rich set of worker types
and firm heterogeneity. We find that the vast differences across worker types in
job ladder risk—job loss, job finding, and contact rates—account for 80% of wage
growth differences among workers below median LE. Above the median, almost all
lifetime wage growth differences are a result of Pareto-distributed learning ability.
We conclude that different economic forces are driving the inequality in different
parts of the LE distribution.
Previous studies show the Fed has a forecast advantage over the private sector, either because it devotes more resources to forecasting or because it has an informational advantage in knowing the path of future monetary policy. We evaluate the Fed's forecast advantage to determine how much of it results from the Fed's knowledge of the conditioning path. We develop two tests---an instrumental variable encompassing test and a path-dependent encompassing test---to equalize the Fed's information set with the private sector's. We find that, generally, the Fed does not encompass the private sector when the latter has knowledge of the future of monetary policy. Further, we find that between 20 and 30 percent of the difference between the Fed's average mean squared forecast error and the private sector's can be explained by monetary policy.
Using administrative data from Norway, we first present stylized facts on labor earnings dynamics between 1993 and 2017 and its heterogeneity across narrow population groups. We then investigate the parents' role in children's income dynamics—the intergenerational transmission of income dynamics. We find that children of high-income, high-wealth fathers enjoy steeper income growth over the life cycle and face more volatile but more positively skewed income changes, suggesting that they are more likely to pursue high-return, high-risk careers. Children of poorer fathers also face more volatile incomes, but theirs grow more gradually and are more left skewed. Furthermore, the income dynamics of fathers and children are strongly correlated. In particular, children of fathers with steeper life-cycle income growth, more volatile incomes, or higher downside risk also have income streams of similar properties. We also confirm that fathers' significant role in workers' income dynamics is not simply spurious because of omitted variables, such as workers' own permanent income. These findings shed new light on the determinants of intergenerational mobility.
Over the last few decades, international trade has increased at a rapid pace, altering domestic production and labor demand in different sectors of the economy. A growing literature has studied the heterogeneous effects of trade shocks on workers’ industry and occupation employment and on welfare when reallocation decisions are costly. The estimated effects critically depend on data on workers’ reallocation patterns, which is typically plagued with coding errors. In this paper, I study the consequences of misclassification errors for estimates of the labor market effects of international trade and show that structural parameter values and the estimated effects are biased when the analysis uses uncorrected data. I develop an econometric framework to jointly estimate
misclassification probabilities, corrected mobility matrices, and structural parameters in a unified way. Under different model specifications, I compare how the estimated effects of a trade shock differ on whether the analysis uses correct mobility measures and parameters. The results show that estimated employment and welfare effects of a trade shock are substantially different, raising an important warning for quantitative exercises using mobility data with coding errors.
Are users of a bibliographic database interested in learning about replications? Can we motivate them to learn? To answer these questions, we performed an experiment on a RePEc (Research Papers in Economics) website: Using randomized stratification, we allocated 324 replications and their corresponding original studies to clusters; we then drew from those clusters to select treatment and control groups. We added brightly colored tabs to the relevant webpages to alert visitors to the existence of a replication study or to the original study of a replication. We monitored traffic over three phases lasting several months: a) no treatment, b) treatment on one group, c) treatment on both groups. We find a statistically significant increase in visits to replication pages, but the effect is small: Click-throughs to the replications occurred only 1% to 1.6% of the time.
We develop a simple model of relationship lending where lenders have an incentive to evergreen loans by offering better terms to less productive and more indebted firms. We detect such lending distortions using loan-level supervisory data for the United States. Low-capitalized banks systematically distort their risk assessments of firms to window-dress their balance sheets and extend relatively more credit to underreported borrowers. Consistent with our theoretical predictions, these effects are driven by larger outstanding loans and low-productivity firms. We incorporate the theoretical mechanism into a dynamic heterogeneous-firm model to show that evergreening can affect aggregate outcomes, resulting in lower interest rates, higher levels of debt, and lower aggregate productivity.
This article documents the long-term relationship among juvenile conviction, occupation choices, employment, wages, and recidivism. Using data from NLSY97, we document that youths who are convicted at or before age 17 have lower full-time employment rate and lower wage growth rate even after 10 years into the labor market. Merging the NSLY97 with occupational characteristics data from O*NET, we show that youths with a juvenile conviction are less likely to be employed in occupations that have a higher on-the-job (OTJ) training requirement and these high OTJ occupations have higher wage and wage growth. The accumulated occupation-specific work experience, general experience, and education are important to explain the gaps in wage and recidivism between youths with and without a juvenile conviction. Our results highlight the important role of occupation choices as a human capital investment vehicle through which juvenile crimes have a long-term impact on wages and recidivism.
I study the short- and long-term effects of trade agreements with strict intellectual property (IP) provisions on innovation, growth and welfare. I develop a quantitative multi-country trade model with endogenous productivity through innovation and adoption that features imperfect IP rights enforcement. A counterfactual analysis shows that improving IP protection in exchange for market access increases welfare, innovation and growth in the world. However, welfare gains along the transition accrue differently across countries. While developed countries benefit both in the short- and in the long- run from these agreements, developing countries experience short-run losses; these losses are amplified if IP improvement is not accompanied by trade liberalization. In contrast to findings from standard trade models, liberalizing trade without improving IP rights decreases welfare and innovation in the long-run, making the distortion of imperfect IP protection worse.
This paper reviews recent studies on the impact of financial frictions on international trade. We first present evidence on the relation between measures of access to external finance and export decisions. We then present an analytical framework to analyze the impact of financial frictions on firms' export decisions. Finally, we review recent applications of this framework to investigate the impact of financial frictions on international trade dynamics across firms, industries, and in the aggregate. We discuss related empirical, theoretical, and quantitative studies throughout.
A two-stage game investigates how counterterrorism measures affect within-country competition between two rival terrorist groups. Although such competition is commonplace (e.g., al-Nusra Front and Free Syria Army; Revolutionary Armed Forces of Colombia and the National Liberation Army; and al-Fatah and Hamas), there is no theoretical treatment of how proactive and defensive measures influence this interaction. Previous studies on rival terrorist groups are solely empirical concerning group survival, outbidding, and terrorism level, while ignoring the role that government countermeasures exert on the rival groups’ terrorism. In a theoretical framework, alternative counterterrorism actions have diverse impacts on the level of terrorism depending on relative group sizes and government-targeting decisions. In the two-stage game, optimal counterterrorism policy rules are displayed in terms of how governments target symmetric and asymmetric terrorist groups. Comparative statics show how parameter changes affect Nash or subgame perfect equilibrium outcomes.
We develop a quantitative framework to assess the cross-state implications of a U.S. trade policy change: a unilateral increase in the import tariff from 2 to 25 across all goods-producing sectors. Although the U.S. gains overall from the tariff increase, we find the impact differs starkly across locations. Changes in real consumption (welfare) range from as high as 3.8% in Wyoming to $-0.3% in Florida, depending mainly on how exposed states are to differentially-impacted sectors. As a result, the "preferred'' tariff rate varies greatly across states. Foreign retaliation in trade policy substantially reduces the welfare gains across states, while perpetuating the cross-state variation in those gains. The presence of internal trade frictions amplifies the welfare impacts of changes in trade policy.
This paper presents a method to decompose the causal effect of government defense spending into: (i) a local (or direct) effect, and (ii) a spillover (or indirect) effect. Each effect is measured as a multiplier: the unit change in output of a one unit change in government spending. We apply this method to study the effect of U.S. defense spending on output using regional panel data. We estimate a positive local multiplier and a negative spillover multiplier. By construction, the sum of the local and spillover multipliers provides an estimate of the aggregate multiplier. The aggregate multiplier is close to zero and precisely estimated. We show that enlisting disaggregate data improves the precision of aggregate effect estimates, relative to using aggregate time series alone. Our paper provides a template for researchers to conduct inference about local, spillover and aggregate causal effects in a unified framework.
This paper empirically investigates the causal linkages between COVID-19 spread, government health containment and economic support policies, and economic activity in the U.S. up to the introduction of vaccines in early 2021. We model their joint dynamics as generated by a structural vector autoregression and estimate it using U.S. state-level data. We identify structural shocks to the variables by making assumptions on their short-run relation consistent with salient epidemiological and economic features of COVID-19. We isolate the direct impact of COVID-19 spread and policy responses on economic activity by controlling for demand fluctuations using disaggregate exports data. We find that health containment and economic support policies are highly effective at curbing the spread of COVID-19 without leading to a long-term contraction of economic activity.
We quantify the barriers that impede the integration of immigrants into foreign labor markets and investigate their aggregate implications. We develop a model of occupational choice with natives and immigrants of multiple types whose decisions are subject to wedges which distort their allocation across occupations. We estimate the model to match salient features of U.S. and cross-country individual-level data. We find that there are sizable GDP gains from removing the wedges faced by immigrants in U.S. labor markets, accounting for approximately one-fifth of the overall economic contribution of immigrants to the U.S. economy. These effects arise from both increased flows from non-participation to predominantly manual jobs as well as from reallocation within the market sector that raises productivity in non-routine cognitive jobs. We contrast our findings for the U.S. with estimates for 11 high-income countries and document substantial differences in the magnitude of immigrant wedges across countries. Importantly, we find differences in the distribution of immigrant wedges across occupations lead to substantial variation in the gains from removing immigrant misallocation, even among countries with similar average degrees of distortions.
Based on patterns of employment transitions, we identify three different types of workers in the US labor market: α’s β’s and γ’s. Workers of type α make up over half of all workers, are most likely to remain on the same job for more than 2 years and, when they become unemployed, typically find a new job within 1 quarter. Workers of type γ comprise less than one-fifth of workers, have a low probability of staying on the same job for more than 2 years and, when they become unemployed, face a high probability of remaining jobless for more than 1 year. Workers of type β are in between αs and γ’s. The earnings losses caused by displacement are relatively small and transitory for α-workers, while they are large and persistent for γ-workers. During the Great Recession, excess unemployment for α-workers rose by little and was reabsorbed quickly; unemployment for γ-workers rose by 20 percentage points and was not reabsorbed 4 years after its peak. We use a search-theoretic model of the labor market to rationalize the different patterns of employment transitions across types. The model naturally explains both the variation in the consequences of job displacement across types, and the variation in the dynamics of unemployment during the Great Recession. Our view is that several puzzling micro and macro phenomena about the labor market are driven by the behavior of the small group of γ-workers.
The role of unconditional lump-sum transfers in improving social welfare in heterogenous agent models has not been thoroughly understood in the literature. We adopt an analytically tractable Aiyagari-type model to study the distinctive role of unconditional lump-sum transfers in reducing consumption inequality due to ex-post uninsurable income risk under borrowing constraints. Our results show that in the presence of ex-post heterogeneity and in the absence of wealth inequality, unconditional lump-sum transfers are not a desirable tool for reducing consumption inequality---the Ramsey planner opts to rely solely on public debt and a linear labor tax (in the absence of a lump-sum tax) to mitigate income risk without the need for lump-sum transfers, in contrast to the result obtained by Werning (2007), Azzimonti and Yared (2017), and Bhandari, Evans, Golosov, and Sargent (2017) in models with ex-ante heterogeneity.
Quantitative macroeconomics is often portrayed as a science—because of its intensive use of high-powered mathematics—with the possible limitation of being unable to conduct controlled experiments. To qualify as a science, however, theories in that discipline must meet a minimum number of criteria: (i) It has explanatory power to explain phenomena; (ii) it has predictive power to yield quantifiable and falsifiable statements about new phenomenon; and (iii) it has operational power to change the world.
A scientific theory consists of axioms and working hypotheses that facilitate the derivation of contestable statements from the axioms.2 Hence, simply laying out a list of contradictions between a theory’s implications and the data is often insufficient to disqualify a theory as science; it may have just challenged its working hypotheses, not its axioms. But, challenging a theory’s working hypotheses is a crucial step to improve or falsify a theory. This is why Isaac Newton spent so much effort in his Principia Mathematica to deal with the law of motion under air friction.
This article discusses one of the working hypotheses of the Arrow-Debreu paradigm and its dynamic stochastic general equilibrium reincarnation in quantitative macroeconomics—the supply curve and its embodiment in the neoclassical production function. The supply curve is a much stronger pillar than the demand curve in holding up the Arrow-Debreu paradigm, but we argue in this article that the neoclassical production function embodying the supply curve is full of cracks.
More specifically, we show that the neoclassical production function is not quantifiable as a working hypothesis to support the Arrow-Debreu DSGE model, unlike the chemical reaction equations based on Lavoisier’s oxygen theory of combustion. The neoclassical production function relies on the unobservable and unmeasurable Solow residual to explain the quantity of output produced at the firm, industry, or national level, and the hypothetical factors of production (capital and labor) are much like “fire, air, water, and earth” in the ancient Greek theory of the universe. Because the working hypotheses of quantitative macroeconomics are not themselves quantifiable, the neoclassical theory is not yet a science. And this explains the lack of power for DSGE models to predict the 2008 Financial Crisis and the inability of economic theory to change the world by engineering or recreating economic prosperity in developing countries.
While aggregate shocks account for most business cycle fluctuations, sectoral shocks have become relatively more important since the 1980s. Previous studies show that sectoral shocks propagate through industry supply chains. Typically, sectors are defined by similarities in function and/or market. While some industries have supply chains within their own sector (vertical), others have supply chains across a number of sectors (horizontal). Similarity in these supply chain characteristics appear to be a determining factor in how industries comove. Using industrial production data of 82 four-digit NAICS industries over the period 1972 to 2019, this comovement is analyzed in a panel Markov-switching model incorporating a number of features relevant for sub-national analysis: (i)industry-specific trends that differentiate cyclical downturns from secular declines; (ii) a national-level business cycle; and (iii) factors that represent industrial comovement. While national-level shocks are typically still the most important driver of cyclical fluctuations, endogenously clustering by industry comovement highlights the role of sectoral shocks.
Cohen, Diether, and Malloy (Journal of Finance, 2007), find that shifts in the demand curve predict negative stock returns. We use their approach to examine changes in supply and demand at the time of FOMC announcements. We show that shifts in the demand for borrowing Treasuries and agencies predict quantitative easing. A reduction in the quantity demanded at all points along the demand curve predicts expansionary quantitative easing announcements.
We investigate a test of conditional predictive ability described in Giacomini and White (2006; Econometrica). Our main goal is simply to demonstrate existence of the null hypothesis and, in doing so, clarify just how unlikely it is for this hypothesis to hold. We do so using a simple example of point forecasting under quadratic loss. We then provide simulation evidence on the size and power of the test. While the test can be accurately sized we find that power is typically low.
Free college proposals have become increasingly popular in many countries of the world. To evaluate their potential effects, we develop and estimate a dynamic model of college enrollment, performance, and graduation. A central piece of the model, student effort, has a direct effect on class completion, and an indirect effect in mitigating the risk of not completing a class or not remaining in college. We estimate the model using rich, student-level administrative data from Colombia, and use the estimates to simulate free college programs that differ in eligibility requirements. Among these, universal free college expands enrollment the most, but it does not affect graduation rates and has the highest per-graduate cost. Performance-based free college, in contrast, delivers a slightly lower enrollment expansion yet a greater graduation rate at a lower per-graduate cost. Relative to universal free college, performance-based free college places greater risk on students, but precisely for this reason leads them to better outcomes. Nonetheless, even performance-based free college fails to deliver a large increase in graduation rate, suggesting that additional, complementary policies might be required to elicit the large effort increase needed to raise graduation rates.
This paper studies the impact of a new class of investors on the dynamics of U.S. housing affordability after the Financial Crisis. Using a novel instrumental variable and processing 85 million housing transactions, we find that investors' purchases increase the price-to-income ratio, especially in the bottom price-tier, the entry point for first-time buyers. Investors cause a short-run reduction in the vacancy rate of owner-occupied units and a medium-run positive response of construction. These equilibrium responses mitigate the effect on affordability. The effects on price-to-income and price-to-rent ratios depend on the housing supply elasticity. In highly elastic areas investors affect rents more than prices, whereas in areas that are highly inelastic investors have the opposite effect.
We study a dynamic macro model to capture the trade-off between policies that simultaneously decrease output and the rate of transmission of an epidemic. We find that optimal policies initially restrict employment but partial loosening occurs before the peak of the epidemic. The arrival of a vaccine (even if only a small fraction can be vaccinated in the short run) implies a relaxation of stay-at-home policies and, in some cases, results in an increase in the speed of infection. The monetary value of producing a vaccine decreases rapidly as time passes. The value that society assigns to averting deaths is a major determinant of the optimal policy.
This paper uses a dynamic competitive spatial equilibrium framework to evaluate the contribution of rural-urban migration induced by structural transformation to the behavior of Chinese housing markets. In the model, technological progress drives workers facing heterogeneous mobility costs to migrate from the rural agricultural sector to the higher paying urban manufacturing sector. Upon arrival to the city, workers purchase housing using long-term mortgages. Quantitatively, the model fits cross-sectional house price behavior across a representative sample of Chinese cities between 2003 and 2015. The model is then used to evaluate how changes to city migration policies and land supply regulations affect the speed of urbanization and house price appreciation. The analysis indicates that making migration policy more egalitarian or land policy more uniform would promote urbanization but also would contribute to larger house price dispersion
We estimate the effects that the different financial deregulations in the U.S. have had on the country's income distribution. We find that the different reforms have moved inequality in drastically different directions. On the one hand, during the late 1970s and early 1980s, the removal of intra- and inter-state branching restrictions and the elimination of state-varying rates ceilings decreased inequality, as they mostly enhanced the incomes of workers in the lower tail of the income distribution. On the other hand, the repeal of the Glass-Steagall Act in 1999 substantially increased inequality, as it mostly –and by large amounts-- increased the incomes of workers in the upper tail of the distribution.
To explore the mechanisms underlying the different effects, we also examine the responses within and across individuals in different age groups and compare finance vs non-finance workers. Our findings indicated that models based solely on capital skill complementarities (CSC) are insufficient because they would imply similar responses to all reforms. We construct a model that emphasizes the endogenous changes in the heterogeneous access (and choices) of households' financial products. The model naturally explains how the different deregulations impacted the opposite tails of the income distribution by capturing the changes in the financial markets available to households of different incomes and characteristics.
This article extends the work of Fawley and Neely (2013) to describe how major central banks have evolved unconventional monetary policies to encourage real activity and maintain stable inflation rates from 2013 through 2019. By 2013, central banks were moving from lump-sum asset purchase programs to continuing asset purchase programs, which are conditioned on economic conditions, careful communication strategies, bank lending programs with incentives and negative interest rates. This article reviews how central banks tailored their unconventional monetary methods to their various challenges and the structures of their respective economies.
This paper quantifies the positive and normative effects of capital controls on international economic activity under The Bretton Woods international financial system. We develop a three-region world economic model consisting of the U.S., Western Europe, and the Rest of the World. The model allows us to quantify the impact of these controls through an open economy general equilibrium capital flows accounting framework. We find these controls had large effects. Counterfactuals show that world output would have been 6% larger had the controls not been implemented. We show that the controls led to much higher welfare for the rest of the world, moderately higher welfare for Europe, but much lower welfare for the U.S. We interpret the large U.S. welfare loss as an estimate of the implicit value to the U.S. of preventing capital flight from other countries and thus promoting economic and political stability in ally and developing countries.
When setting initial compensation, some firms set a fixed, non-negotiable wage while others bargain. In this paper we propose a parsimonious search and matching model with two sided heterogeneity, where the choice of wage-setting protocol, wages, search intensity, and degree of randomness in matching are endogenous. We find that posting and bargaining coexist as wage-setting protocols if there is sufficient heterogeneity in match quality, search costs, or market tightness and that labor market tightness and relative costs of search play a key role in the optimal choice of the wage-setting mechanism. Finally, we show that bargaining prevalence is positively correlated with wages, residual wage dispersion, and labor market tightness, both in the model and in the data.
Who prevails when fiscal and monetary authorities disagree about the value of public expenditure and how much to discount the future? When the fiscal authority sets debt as its main policy instrument it achieves fiscal dominance, rendering the preferences of the central bank, and thus its independence, irrelevant. When the central bank sets the nominal interest rate it renders fiscal impatience (its debt bias) irrelevant, but still faces its expenditure bias. I find that the expenditure bias has a major impact on welfare through higher public spending, while the effect on other policies is relatively minor. In contrast, the debt bias affects debt, deficits and inflation, but has a minor impact on expenditure and welfare. I also find that the central bank can do little to overcome the negative impact of the fiscal authority's expenditure bias, though there are still gains from properly designing the central bank.