To make high-quality research more accessible and easier to explore.

Fields:
13 results

The Best of Both Worlds: Combining Randomized Controlled Trials with Structural Modeling

Journal of Economic Literature 2023 61(1), 41-85
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.

Assessing the Impact of a School Subsidy Program in Mexico: Using a Social Experiment to Validate a Dynamic Behavioral Model of Child Schooling and Fertility

American Economic Review 2006 96(5), 1384-1417
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.

Distributional Effects of Local Minimum Wages: A Spatial Job Search Approach

Journal of Labor Economics 2025 43(S1), S221-S267
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.

Assessing the Performance of Nonexperimental Estimators for Evaluating Head Start

Journal of Labor Economics 2017 35(S1), S7-S63
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 Transfers: The Case ofProgresa/Oportunidades

Journal of Economic Literature 2017 55(3), 866-915
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.

Passenger Profiling, Imperfect Screening, and Airport Security

American Economic Review 2005 95(2), 127-131 open access
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.

Teacher Quality in Public and Private Schools under a Voucher System: The Case of Chile

Journal of Labor Economics 2016 34(2), 319-362 open access
Chile is unusual in having long-term experience with nationwide school vouchers. A key criticism of school voucher systems is that they make it easier for private schools to attract better teachers to the detriment of public schools. This paper uses longitudinal data from Chile to estimate a discrete choice dynamic programming (DCDP) model of teacher and nonteacher labor supply decisions and to explore how wage policies affect the composition of the teacher labor force in public and private schools. In the model, individuals first decide whether to get a teaching degree and then choose annually from among five work/home sector alternatives. Empirical results show that private voucher schools attract better teachers than public schools. However, the existence of the private voucher sector also draws higher-productivity individuals into the teaching profession.

Understanding Black–White Wage Differentials: 1960–1990

American Economic Review 2000 90(2), 344-349
Understanding Black-White Wage Differentials, 1960-1990 Author(s): James J. Heckman, Thomas M. Lyons, Petra E. Todd Source: The American Economic Review, Vol. 90, No. 2, Papers and Proceedings of the One Hundred Twelfth Annual Meeting of the American Economic Association, (May, 2000), pp. 344 -349 Published by: American Economic Association Stable URL: http://www.jstor.org/stable/117248 Accessed: 16/08/2008 00:56

Evaluating Preschool Programs When Length of Exposure to the Program Varies: A Nonparametric Approach

The Review of Economics and Statistics 2004 86(1), 108-132
Nonexperimental data are used to evaluate impacts of a Bolivian preschool program on cognitive, psychosocial, and anthropometric outcomes. Impacts are shown to be highly dependent on age and exposure duration. To minimize the effect of distributional assumptions, program impacts are estimated as nonparametric functions of age and duration. A generalized matching estimator is developed and used to control for nonrandom selectivity into the program and into exposure durations. Comparisons with three groups—children in the feeder area not in the program, children in the program for ≤ 1 month, and children living in similar areas without the program—indicate that estimates are robust for significant positive effects of the program on cognitive and psychosocial outcomes with ≥ 7 months' exposure, although the age patterns of effects differ slightly by comparison group.