Persistent air-pollution problems have led authorities in many cities around the world to impose limits on car use by means of vintage-specific restrictions or low-emission zones. Any vintage restriction must establish not only the cars that face a restriction but also its geographic area of application. As a result of the restriction, a fraction of restricted cars are exported outside the restricted area. Because restricted cars become cheaper, emissions in the restricted area could increase if exported cars remain too close to it. The extent to which such emissions leakage can occur crucially depends on transaction costs in the car market. We study this possibility with a model of the car market that allows for transaction costs and data from Santiago’s 2017 vintage restriction. We fail to find emissions leakage, at least severe enough to undo the 2017 policy effects. Interestingly, transaction costs are shown to have a non-monotonic impact on emissions, and hence, on welfare.
We study a regulation in Chile that mandates warning labels on products whose sugar or caloric concentration exceeds certain thresholds. We show that consumers substitute from labeled to unlabeled products—a pattern mostly driven by products that consumers mistakenly believe to be healthy. On the supply side, we find substantial reformulation of products and bunching at the thresholds. We develop and estimate an equilibrium model of demand for food and firms' pricing and nutritional choices. We find that food labels increase consumer welfare by 1.8% of total expenditure, and that these effects are enhanced by firms' responses. We then use the model to study alternative policy designs. Under optimal policy thresholds, food labels and sugar taxes generate similar gains in consumer welfare, but food labels benefit the poor relatively more.
Local air pollution has led authorities in many cities around the world to impose limits on car use by means of driving restrictions or license-plate bans. By placing uniform restrictions on all cars, many of these programs have created incentives for drivers to buy additional, more polluting cars. We study vintage-specific restrictions, which place heavy limits on older, polluting vehicles and no limits on newer, cleaner ones. We use a novel model of the car market and results from Santiago's 1992 program, the earliest program to use vintage-specific restrictions, to show that such restrictions should be designed to work exclusively through the extensive margin (type of car driven), never through the intensive margin (number of miles driven). If so, vintage restrictions can yield important welfare gains by moving the fleet composition toward cleaner cars, comparing well to alternative instruments such as scrappage subsidies and pollution-based registration fees.
We study the aggregate and heterogeneous effects of a front-of-package labeling policy implemented in Chile. We find that consumers reduced their sugar and caloric intake by 9% and 6%, reductions explained by consumers purchasing healthier products and firms reformulating their offerings. On the demand side, labels prompt consumers to substitute within categories rather than between categories. Within-category responses are more pronounced when labels provide new information. On the supply side, we observe bunching at regulatory thresholds with substantial heterogeneity across categories, consistent with heterogeneous costs of product reformulation. We conclude that considering policy-response heterogeneity is key for effective policy design.
We study the causal interpretation of instrumental variables (IV) estimands of nonlinear, multivariate structural models with respect to rich forms of model misspecification. We focus on guaranteeing that the researcher's estimator is sharp zero consistent, meaning that the researcher concludes that the endogenous variable has no causal effect on the outcome whenever this is actually the case. Sharp zero consistency generally requires the researcher's estimator to satisfy a condition that we call strong exclusion. When a researcher has access to excluded, exogenous variables, strong exclusion can often be achieved by appropriate choice of estimator and instruments. Failure of strong exclusion can lead to large bias in estimates of causal effects in realistic situations. Our results cover many settings of interest including models of differentiated goods demand with endogenous prices and models of production with endogenous inputs.
This paper studies how schools respond to financial incentives. Governments can penalize institutions with high dropout or loan default rates, and these institutions can respond by increasing quality or changing the selection of students. We build an equilibrium model to illustrate the trade-off faced by policymakers. We study the predictions of the model using a 2017 reform in Brazil, which made schools pay a fee for students receiving federal student loans that dropped out or defaulted. Consistent with the predictions of the model, we find that schools more reliant on government aid reduced dropout rates, primarily by increasing quality.
We study the consequences of affirmative action in centralized college admissions systems. We develop an empirical framework to examine the effects of a large-scale program in Brazil that required all federal institutions to reserve half their seats for socioeconomically and racially marginalized groups. By exploiting admissions cutoffs, we find that marginally benefited students are more likely to attend college and are enrolled at higher-quality degrees four years later. Meanwhile, there are no observed impacts for marginally displaced non-targeted students. To study the effects of larger changes in affirmative action, we estimate a joint model of school choices and potential outcomes. We find that the policy has impacts on college attendance and persistence that imply a virtually one-to-one income transfer from the non-targeted to the targeted group. These findings indicate that introducing affirmative action can increase equity without affecting efficiency.
We investigate the equilibrium effects of subsidized student loans on tuition costs, enrollment, and student welfare. Two opposing forces make the impact on tuition theoretically ambiguous. First, students with loans become less price-sensitive because they do not bear the total tuition cost, causing tuition to rise (direct effect). Second, loan programs tend to increase the market share of more price-sensitive students, reducing tuition (composition effect). We develop a model of the supply and demand for higher education and estimate it leveraging a large change in the availability of student loans in Brazil. We find that Brazil’s current loan program raises prices by 1.6% and enrollment by 11% relative to a counterfactual without loans. We decompose the price effect into its direct (2.7% increase) and composition (1.1% decrease) components. Finally, we show that an alternative policy that gives loans only to low-income students raises enrollment by 16% relative to a counterfactual without loans. Most of the difference in enrollment between the two policies are due to price reductions coming from a stronger composition effect in the alternative policy.