Knowledge that Transforms

Abstract This article examines the labor market implications of the EU posting policy, a large temporary migration program facilitated by the liberalization of the free provision of services in Europe. Posting allows EU firms to send (post) their employees abroad to export customer-facing services. Combining administrative data and quasi-experimental policy variation, I find that the policy permanently increased total factor mobility in Europe without crowding out traditional migration. This result suggests that unrealized gains from trade in factor services remained despite the absence of regulatory barriers to trade and migration in the EU. Furthermore, posted workers are mostly sent from low-wage countries to perform manual tasks in sectors formerly insulated from trade, and they represent a substantial share of EU migrant workers. In receiving countries, posting had persistent negative effects on employment for domestic workers in the more exposed sectors and local labor markets, but it had no effects on domestic wages. In low-wage sending countries, firms in formerly “nontradable” sectors experienced increased sales, profits, and tax payments when exporting services through posting. Posted workers earn more once sent abroad but remain paid at lower wages than comparable domestic workers in the receiving country. Wage gains for posted workers are mostly explained by minimum wages enforced by the EU policy, highlighting the role of labor market regulations in shaping the way gains from globalization are shared between labor and capital owners in origin countries.

More than two million U.S. households have an eviction case filed against them each year. Policy makers at the federal, state, and local levels are increasingly pursuing policies to reduce the number of evictions, citing harm to tenants and high public expenditures related to homelessness. We study the consequences of eviction for tenants using newly linked administrative data from two major urban areas: Cook County (which includes Chicago) and New York City. We document that before housing court, tenants experience declines in earnings and employment and increases in financial distress and hospital visits. These pre trends pose a challenge for disentangling correlation and causation. To address this problem, we use an instrumental variables approach based on cases randomly assigned to judges of varying leniency. We find that an eviction order increases homelessness and hospital visits and reduces earnings, durable goods consumption, and access to credit in the first two years. Effects on housing and labor market outcomes are driven by effects for female and Black tenants. In the longer run, eviction increases indebtedness and reduces credit scores.

Abstract We study how Americans respond to idiosyncratic and exogenous changes in household wealth and unearned income. Our analyses combine administrative data on U.S. lottery winners with an event study design. We first examine individual and household earnings responses to these windfall gains, finding significant and sizable wealth and income effects. On average, an extra $1 of unearned income in a given period reduces household labor earnings by about 50 cents, decreases total labor taxes by 10 cents, and increases consumption expenditure by 60 cents. These effects are heterogeneous across the income distribution, with households in higher quartiles of the income distribution reducing their earnings by a larger amount. Next we examine margins of adjustment other than earnings and, in the course of doing so, address a number of important economic questions about how additional wealth or unearned income affect retirement decisions and labor market dynamics, family formation and dissolution, entrepreneurship and self-employment, and geographic mobility and neighborhood choice. Last, we carefully compare our findings to those reported in existing lottery studies. This comparison reveals that existing U.S. studies substantially underestimate wealth and income effects because they use measures that understate the earnings responses and overstate the after-tax wealth changes associated with lottery wins.

Abstract How should we measure changes in consumer welfare given observed data on prices and expenditures? This article proposes a nonparametric approach that holds under arbitrary preferences that may depend on observable consumer characteristics, for example, when expenditure shares vary with income. Using total expenditures under a constant set of prices as our money metric for real consumption (welfare), we derive a principled measure of real consumption growth featuring a correction term relative to conventional measures. We show that the correction can be nonparametrically estimated with an algorithm leveraging the observed, cross-sectional relationship between household-level price indices and household characteristics such as income. We demonstrate the accuracy of our algorithm in simulations. Applying our approach to data from the United States, we find that the magnitude of the correction can be large because of the combination of fast growth and lower inflation for income-elastic products. Setting reference prices in 2019, we find that (i) the uncorrected measure underestimates average real consumption per household in 1955 by 11.5%, and (ii) the correction reduces the annual growth rate from 1955 to 2019 by 18 basis points, which is larger than the well-known “expenditure-switching bias” over the same time horizon.

Abstract I investigate the consequences of firms’ joint import and export decisions in the context of large devaluations. I provide empirical evidence that large devaluations are characterized by an increase in the aggregate share of imported inputs in total input spending and by reallocation of resources toward import-intensive firms, contrary to what standard quantitative trade models predict. These facts are explained by the expansion of exporters, which are intense importers. I develop a model where firms globally decide their import and export strategies and discipline it to match salient features of the Mexican micro data. After a devaluation, the model reproduces the pattern of low aggregate substitution and firm reallocation observed in the data. Compared with a benchmark without global firms, the model predicts higher growth of total exports and imports and a smaller reduction in the trade deficit.

Abstract We estimate the equilibrium effects of a public school grant program administered through school councils in Pakistani villages with multiple public and private schools and clearly defined catchment boundaries. The program was randomized at the village level, allowing us to estimate its causal impact on the market. Four years after the start of the program, test scores were 0.2 standard deviations higher in public schools. We find evidence of an education multiplier: test scores in private schools were also 0.2 standard deviations higher in treated markets. Consistent with standard models of product differentiation, the education multiplier is greater for those private schools that faced a greater threat to their market power. Accounting for private sector responses increases the program’s cost-effectiveness by 85% and affects how a policy maker would target spending. Given that markets with several public and private schools are now pervasive in low- and middle-income countries, prudent policy requires us to account for private sector responses to public policy, both in policies’ design and evaluation.

Abstract This article studies the long-run effects of slavery and restrictive Jim Crow institutions on Black Americans’ economic outcomes. We track individual-level census records of each Black family from 1850 to 1940 and extend our analysis to neighborhood-level outcomes in 2000 and surname-based outcomes in 2023. We show that Black families whose ancestors were enslaved until the Civil War have considerably lower education, income, and wealth than Black families whose ancestors were free before the Civil War. The disparities between the two groups have persisted substantially because most families enslaved until the Civil War lived in states with strict Jim Crow regimes after slavery ended. In a regression discontinuity design based on ancestors’ enslavement locations, we show that Jim Crow institutions sharply reduced Black families’ economic progress in the long run.

Abstract While hypothesis testing is a highly formalized activity, hypothesis generation remains largely informal. We propose a systematic procedure to generate novel hypotheses about human behavior, which uses the capacity of machine learning algorithms to notice patterns people might not. We illustrate the procedure with a concrete application: judge decisions about whom to jail. We begin with a striking fact: the defendant’s face alone matters greatly for the judge’s jailing decision. In fact, an algorithm given only the pixels in the defendant’s mug shot accounts for up to half of the predictable variation. We develop a procedure that allows human subjects to interact with this black-box algorithm to produce hypotheses about what in the face influences judge decisions. The procedure generates hypotheses that are both interpretable and novel: they are not explained by demographics (e.g., race) or existing psychology research, nor are they already known (even if tacitly) to people or experts. Though these results are specific, our procedure is general. It provides a way to produce novel, interpretable hypotheses from any high-dimensional data set (e.g., cell phones, satellites, online behavior, news headlines, corporate filings, and high-frequency time series). A central tenet of our article is that hypothesis generation is a valuable activity, and we hope this encourages future work in this largely “prescientific” stage of science.