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Crime and Mismeasured Punishment: Marginal Treatment Effect with Misclassification

The Review of Economics and Statistics 2026 108(1), 44-56 open access
I partially identify the marginal treatment effect (MTE) when the treatment is misclassified. I explore two restrictions, allowing for dependence between the instrument and the misclassification decision. If the signs of the propensity scores’ derivatives are equal, I identify the MTE sign. If those derivatives are similar, I bound the MTE. To illustrate, I analyze the impact of alternative sentences (fines and community service versus no punishment) on recidivism in Brazil, where court appeals processes generate misclassification. The estimated misclassification bias may be as large as 10% of the largest possible MTE, and the bounds contain the correctly estimated MTE.

Disentangling Reputation from Selection Effects in Markets with Informational Asymmetries: A Field Experiment

The Review of Economics and Statistics 2026 open access
In markets with asymmetric information between sellers and buyers, feedback mechanisms are important to increase market efficiency and reduce the informational disadvantage of buyers. Feedback mechanisms might work because of self-selection of more trustworthy sellers into markets with such mechanisms or because of reputational concerns of sellers. We show in a field experiment how to disentangle self-selection from reputation effects. Based on 476 taxi rides with four different types of taxis, we find strong evidence for reputation effects but little support for self-selection effects. We discuss policy implications of our findings.

Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data

The Review of Economics and Statistics 2026 108(3), 792-806
We propose a Cramér–von Mises–type test for testing whether the mean potential outcome given a specific treatment level has a weakly monotonic relationship with the continuous treatment under unconfoundedness. To flexibly control for a possibly high-dimensional set of covariates, our test is based on a double debiased machine learning method. We show that our test controls asymptotic size and is consistent against any fixed alternative. We apply our test to evaluate the Job Corps program and reject a weakly negative relationship between the treatment (hours in academic and vocational training) and labor market performance among relatively low treatment values.

Information Transmission in Groups: Peer Influence in High-Stakes, Irreversible Financial Decisions

The Review of Economics and Statistics 2026
We study the influence of workplace peers on a high-stakes, irreversible retirement plan choice. Midcareer U.S. military personnel choose between higher future pension payouts or an immediate bonus plus lower future payouts. With peers defined as those who have locked in their choices and personnel assignment rules ensuring that peer groups are exogenously formed, we capture the causal impact of peers. Greater peer take-up of the bonus, which is difficult to compare to the alternative plan but often extremely costly over one’s lifetime, discourages choosers from selecting the bonus. Peers have special impact within professional, race, and gender groups.

Intergenerational Mobility in the Land of Inequality

The Review of Economics and Statistics 2026 open access
We provide the first estimates of intergenerational income mobility using tax data for a large developing country, namely Brazil. We measure formal income from tax and payroll data, and we train machine learning models on census and survey data to predict informal income. We quantify the estimation bias resulting from income imputation and other sources of measurement error, and show that such bias remains negligible in our context. A 10 percentile increase in parental income rank is associated on average with a 5.5 percentile increase in child income rank, with considerable variation across sociodemographic groups and geographical areas.

Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding

The Review of Economics and Statistics 2026 open access
Predictive algorithms inform consequential decisions in settings with selective labels: outcomes are observed only for units selected by past decision makers. This creates an identification problem under unobserved confounding — when selected and unselected units differ in unobserved ways that affect outcomes. We propose a framework for robust design and evaluation of predictive algorithms that bounds how much outcomes may differ between selected and unselected units with the same observed characteristics. These bounds formalize common empirical strategies including proxy outcomes and instrumental variables. Our estimators work across bounding strategies and performance measures such as conditional likelihoods, mean squared error, and true/false positive rates. Using administrative data from a large Australian financial institution, we show that varying confounding assumptions substantially affects credit risk predictions and fairness evaluations across income groups.

How Big Is the Media Multiplier? Evidence from Dyadic News Data

The Review of Economics and Statistics 2026 108(3), 696-711 open access
This paper estimates the size of the media multiplier, an easily generalizable model-based measure of how far media coverage magnifies the economic response to shocks. We combine monthly aggregated and anonymized credit card activity data from 114 card-issuing countries in 5 destination countries with a large corpus of news coverage in issuing countries reporting on violent events in the destinations. To define and quantify the media multiplier, we estimate a model in which latent beliefs, shaped by either events or news coverage, drive card activity. According to the model, media coverage can more than triple the economic impact of an event. We document, through our model, that this effect is highly heterogeneous and depends on the broader media representation of countries in each other’s news. We speculate about the role of the media in driving international travel patterns.

Family-Leave Mandates and Female Labor at U.S. Firms: Evidence from a Trade Shock

The Review of Economics and Statistics 2026
We examine how the 1993 Family and Medical Leave Act (FMLA) impacts the gender composition at U.S. firms experiencing a negative demand shock. Combining changes in Chinese imports across industries between 2000 and 2003 and a sharp regression discontinuity to identify FMLA status, we find that an increase in import competition decreases the share of female employment, earnings, and promotions at FMLA relative to non-FMLA firms. This effect is driven by women in prime child-bearing ages and without college degrees and is pronounced at firms with all male managers. These results suggest that job-protected leave mandates may exacerbate gender inequalities in response to adverse shocks.

Revisiting the Interest Rate Effects of Federal Debt

The Review of Economics and Statistics 2026
This paper revisits the relationship between federal debt and interest rates in the U.S. A common approach is to regress long-term forward interest rates on long-term projections of federal debt. We show that issues regarding nonstationarity have become more pronounced over the last 20 years, significantly biasing recent estimates. Estimating the model in first differences rather than in levels addresses these concerns. We find that a 1 percentage point increase in the debt-to-GDP ratio raises the 5-year-ahead, 5-year Treasury rate by about 3 basis points. Roughly half of the interest rate response is driven by a higher nominal term premium.

Gender Norms and Female Labor Supply: Evidence from Export Shocks in Vietnam

The Review of Economics and Statistics 2026
We study how economic development affects female labor force participation, focusing on the role of gender norms. Analyzing quasi-random variation in provincial exports in reunified Vietnam from 2002 to 2018, we find that positive economic shocks reduced women’s labor market engagement, particularly among married women from wealthier households and those with husbands in more skilled occupations. This trend is more pronounced in the South (formerly capitalist) than in the North (always socialist), and among native Southerners compared to Northerners relocated to the South after the war. Our findings highlight how gender role attitudes shape women’s responses to rising incomes.