Abstract In France, place-based policies channel public subsidies to low-income urban zones labeled ‘‘priority” neighborhoods. Yet, such policies may backfire by stigmatizing the targeted areas. This paper exploits a quasi-experimental discontinuity created by a reform that redrew the subsidy map using a local poverty cutoff to evaluate impacts on school outcomes, population sorting, and urban segregation across labeled and unlabeled neighborhoods. Using a difference-in-differences design, we show that public middle schools in newly designated neighborhoods experienced a persistent decline in enrollment relative to schools in unlabeled areas just above the cutoff. This territorial stigma, driven by school avoidance across all socioeconomic groups, redirected pupils to public schools in unlabeled areas and, among wealthier families, to private schools. Policy designation also depressed housing prices and triggered reverse gentrification, while educational support proved insufficient to offset rising urban segregation. Crucially, the stigma persisted even after neighborhoods lost their subsidized status, leading to sustained declines in academic achievement due to both reputational damage and subsidy withdrawal.
Abstract This study examines whether racial outrage in the media can result from the incentives of elites who seek to divide society for political gain, focusing on the late 19th century Southern United States. At this time, the Democratic Party had strong political incentives to incite racial outrage, and local Democratic elites exercised considerable influence over newspapers, the only mass media at the time. Using high-frequency historical newspaper data and difference-in-differences and triple-difference estimation strategies, we find evidence consistent with Democratic elites orchestrating a racist propaganda campaign to sway white voters. Supporting analyses are consistent with Democrats benefiting from anti-Black propaganda in the subsequent elections.
Abstract Women are significantly underrepresented in the technology sector. We design an experimental study using field data to identify the role of statistical discrimination in job applicant assessments. First, we measure the programming skills of job applicants for a programming job. Then, we recruit a large sample of employers consisting of human resource and tech professionals and incentivize them to predict the performance of these applicants based on their standardized resumes. We find no significant gender differences in programming skills. However, consistent with statistical discrimination we find employers perceive female applicants to be significantly less skilled. We also provide experimental evidence that the perceived gender skill gap can be readily eliminated. Employers who were randomized to have access to additional information such as aptitude or personality do not believe that there are gender differences in programming skills. Together, these findings suggest that tech employers believe women are less skilled programmers. Nonetheless, in the context of hiring, the scope for statistical discrimination may be limited in practice as employers often have access to more information when assessing applicants.
Abstract I study the introduction of statutory caps on executive pay ratios (pay caps) in a span-of-control economy with heterogeneous managerial talent. Managers hire fewer workers than they would in the absence of pay caps, and the marginal product of labour is not equalized among firms. The ability of the marginal manager declines. Inequality between managers and workers, and among managers, declines, but inequality among workers increases. Quantitatively, overall inequality decreases substantially, especially via a reduction in top income shares, but the GDP losses are also significant. In addition, the redistribution favours the “middle” deciles between 50 and 90, rather than the bottom 50% of the income distribution. Future work will build on this “first pass” to analyse the effect of pay caps in economies distorted by monopsony power, non-pecuniary benefits of control, and managerial rent extraction.
Abstract As interest in the distributional effects of climate policies gains prominence, designing electricity tariffs that are both efficient and equitable becomes critical. Efficiency often favors the shift from time-invariant to time-of-use (ToU) or real-time prices (RTP), but this transition may have distributional implications. We develop a framework to assess the implications and the channels through which distributional impacts manifest. Central to our approach is a novel method that infers individual household income by combining zip-code-level income data with household-level electricity consumption. We demonstrate the value of this method in the Spanish context. First, we show that using more granular estimates of income has an impact on the distributional assessment of electricity tariffs. Second, we find that the potential distributional impact of RTP is very modest compared to the impact of ToU. The most salient effect of RTP is to increase bill volatility, particularly so for the low-income group.
