Nano Barahona

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 a regulation in Chile that mandates front-of-package warning labels on products whose sugar or caloric concentration exceeds certain thresholds. We find that after the introduction of the regulation, consumers reduced their overall sugar and caloric intake by 9% and 6%, respectively. This change is explained by consumers buying healthier products and firms reformulating their products. On the demand side, labels induce consumers to substitute within categories rather than between categories. On the supply side, we document bunching at regulatory thresholds, with substantial heterogeneity across categories. We provide insights to inform the design of effective food labeling policies.

We consider the choice of instrumental variables when a researcher's structural model may be misspecified. We contrast included instruments, which have a direct causal effect on the outcome holding constant the endogenous variable of interest, with excluded instruments, which do not. We show conditions under which the researcher's estimand maintains an interpretation in terms of causal effects of the endogenous variable under excluded instruments but not under included instruments. We apply our framework to estimation of a linear instrumental variables model, and of differentiated goods demand models under price endogeneity. We show that the distinction between included and excluded instruments is quantitatively important in simulations based on an application. We extend our results to a dynamic setting by studying estimation of production function parameters under input endogeneity

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 1.2% and enrollment by 11% relative to a counterfactual without loans. In contrast, we show that an alternative policy that gives loans only to low-income students raises prices by just 0.3% and enrollment by 16%. Most of the difference in enrollment between the two policies are due to price changes coming from a stronger composition effect in the alternative policy.

This paper empirically studies the distributional consequences of affirmative action in the context of a centralized college admission system. We examine the effects of a large-scale program in Brazil that mandated all federal public institutions to reserve half their seats for public high-school students, prioritizing those from socioeconomically and racially marginalized groups. After the policy was put in place, the representation of public-high school students of color in the most selective federal degrees increased by 73%. We exploit degree admission cutoffs to estimate the effects of increasing affirmative action by one reserved seat on the quality of the degree attended four years later. Our estimates indicate that the gains for benefited students are 1.6 times the costs experienced by displaced students. To study the effects of larger changes in affirmative action, we estimate a joint model of school choice and potential outcomes. We identify the model using exogenous variation in test scores—arising from random assignment to graders of varying strictness—that changes the availability of degrees for otherwise identical individuals. We find that the policy creates impacts on college attendance and persistence that imply overall income gains of around 1% for the average targeted student, and losses of around 1% for the average non-targeted student.

This paper studies how schools respond to financial incentives. Governments can penal- ize 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.