There is a long-standing debate about the extent to which economic theory should inform econometric modeling and estimation. This debate is particularly evident in the program/policy evaluation literature, where reduced-form (experimental or quasi-experimental) and structural modeling approaches are often viewed as rival methodologies. Reduced-form proponents criticize the assumptions invoked in structural applications. Structural modeling advocates point to the limitations of reduced-form approaches in not being able to inform about program impacts prior to implementation or about the costs and benefits of program designs that deviate from the one that was implemented. In this paper, we argue that there is a new emerging view of a natural synergy between these two approaches, that they can be melded to exploit the advantages and ameliorate the disadvantages of each. We provide examples of how data from randomized controlled trials (RCTs), the exemplar of reduced form practitioners, can be used to enhance the credibility of structural estimation. We also illustrate how the structural approach complements experimental analyses by enabling evaluation of counterfactual policies/programs. Lastly, we survey many recent studies that combine these methodologies in various ways across different subfields within economics.

This paper estimates a model of the effort decisions of students and teachers in a classroom setting to understand the performance of Mexican high school students on curriculum-based examinations. The model allows for student heterogeneity in initial mathematics preparation and knowledge preference and for teacher heterogeneity in instructional ability and preferences for student knowledge. Survey data include multiple measurements of student and teacher effort, student and teacher preferences, student initial knowledge, and teacher ability. The most important factor accounting for poor performance, the lack of sufficient prior preparation, suggests a mismatch between the curriculum content and entering grade-level mathematics knowledge.

This paper uses data from a randomized social experiment in Mexico to estimate and validate a dynamic behavioral model of parental decisions about fertility and child schooling, to evaluate the effects of the PROGRESA school subsidy program, and to perform a variety of counterfactual experiments of policy alternatives. Our method of validation estimates the model without using post-program data and then compares the model’s predictions about program impacts to the experimental impact estimates. The results show that the model’s predicted program impacts track the experimental results. Our analysis of counterfactual policies reveals an alternative subsidy schedule that would induce a greater impact on average school attainment at similar cost to the existing program.

This paper develops a spatial general equilibrium job search model to study the effects of local and universal minimum wage policies on employment, wages, job postings, vacancies, migration, and welfare. Workers search for jobs locally and in neighboring areas, deciding whether to migrate or commute after receiving remote offers. The model, estimated using ACS and QWI data, reliably forecasts commuting responses to city minimum wage hikes. Simulations show that low-skill (noncollege) workers benefit from local wage increases up to $12.50. The greatest per capita welfare gain for all workers is achieved by a $15.25 universal minimum wage.

This paper uses experimental data from the Head Start Impact Study (HSIS) combined with nonexperimental data from the Early Childhood Longitudinal Study–Birth Cohort (ECLS-B) to study the performance of nonexperimental estimators for evaluating Head Start program impacts. The estimators studied include parametric cross-section and difference-in-differences regression estimators and nonparametric cross-section and difference-in-differences matching estimators. The estimators are used to generate program impacts on cognitive achievement test scores, child health measures, parenting behaviors, and parent labor market outcomes. Some of the estimators closely reproduce the experimental results, but a priori it would be difficult to know whether the estimator works well for any particular outcome. Pre-program exogeneity tests eliminate some outcomes and estimators with the worst biases, but estimators/outcomes with substantial biases pass the tests. The difference-in-differences matching estimator exhibits the best performance in terms of low bias values and capturing the pattern of statistically significant treatment effects. However, the variation in bias is greater across outcomes examined than across methods.

Conditional cash transfer (CCT) programs innovate by conditioning transfers to poor families on investments in the human capital of children and other family members. The Mexican CCT program Progresa/Oportunidades began in 1997 and has served as a model for many of the now over sixty countries with CCTs around the world, in large part due to its initial evaluation with an experimental design and numerous follow-up studies. This article reviews the literature on the development, evaluation, and findings of Progresa/Oportunidades, summarizing what is known about program effects, taking into account corrections for multiple-hypothesis testing.

We present a theoretical model of airport searches. The model extends previous work in the area in that detection conditional on search is imperfect. The hit rates tests for racial bias developed in Knowles, Persico, and Todd (2001) is shown to apply even in the presence of imperfections in monitoring. We then study two channels for improving airport security: better targeting and better detection. We show that better targeting does not necessarily decrease the overall crime rate, although it will decrease crime in the group that is targeted. Improved detection rates unambiguously decrease crime. Group-specific improvements in detection do not necessarily increase the number of searches for those groups. The analysis is extended to allow for the possibility that criminal passengers disguise themselves as members of low-crime groups.