I am an assistant professor of economics at IÉSEG school of Management and a research affiliate at IZA. Starting 2025, I will be a CNRS researcher at LEM (CNRS UMR 9221). I hold a Ph.D. in economics from the University of Illinois at Urbana-Champaign. My research focuses on development and labor economics, with a special interest on topics regarding education and policy evaluation in developing economies. 

I am the organizer of the IFLAME Seminar Series. Please contact me in case you want to present. 

Contact:

Email: j.munoz@ieseg.fr

Address:  1 parvis de la Défense, 92044 Paris-La Défense cedex – France. 


Link to my CV: Here 

Link to my Ideas Profile:  Ideas - Repec

Publications and Forthcoming

Teacher quality is a key factor in improving student academic achievement. As such, educational policymakers strive to design systems to hire the most effective teachers. This paper examines the effects of a national policy reform in Colombia that established a merit-based teacher-hiring  system intended to enhance teacher quality and improve student learning. Implemented in 2005 for all public schools, the policy ties teacher-hiring decisions to candidates' performance on an exam evaluating subject-specific knowledge and teaching aptitude. The implementation of the policy led to many experienced contract teachers being replaced by high exam-performing novice teachers. We find that though the policy sharply increased pre-college test scores of teachers, it also decreased the overall stock of teacher experience and led to sharp decreases in students' exam performance and educational attainment. Using a difference-in-differences strategy to compare the outcomes of students from public and private schools over two decades, we show that the hiring reform  decreased students' performance on high school exit exams by 8 percent of a standard deviation, and reduced the likelihood that students enroll in and graduate from college by more than 10 percent. The results underscore that relying exclusively on specific ex ante measures of teacher quality to screen candidates, particularly at the expense of teacher experience, may unintentionally reduce students' learning gains.

Using longitudinal data of college graduates in Colombia, we estimate labor market returns to postsecondary degrees and to various skills - including literacy, numeracy, foreign language, and field-specific skills. Graduates of academic programs and schools of higher reputation obtain higher earnings relative to vocational public programs. A one standard deviation increase in each skill predicts average earnings increases of one to three percent. Returns vary along the earnings distribution, with tenure, with the degree of job specialization, and by gender. Our results imply that degrees and skills capture different human capital components that are rewarded differently in the labor market.  

Some Children Left Behind: Variation in the Effects of an Educational Intervention.

Joint with Julie Buhl-Wiggers, Jason Kerwin, Jeff Smith, and Rebecca Thornton.  

Journal of Econometrics, July 2024, volume 243, issues 1-2.

DOI | NBER Working Paper | IZA Working Paper | Replication Files

Press Coverage: VoxDev

We document substantial variation in the effects of a highly-effective literacy program in northern Uganda. The program increases test scores by 1.40 SDs on average, but standard statistical bounds show that the impact standard deviation exceeds 1.0 SD. This implies that the variation in effects across our students is wider than the spread of mean effects across all randomized evaluations of developing country education interventions in the literature. This very effective program does indeed leave some students behind. At the same time, we do not learn much from our analyses that attempt to determine which students benefit more or less from the program. We reject rank preservation, and the weaker assumption of stochastic increasingness leaves wide bounds on quantile-specific average treatment effects. Neither conventional nor machine-learning approaches to estimating systematic heterogeneity capture more than a small fraction of the variation in impacts given our available candidate moderators

Do school shootings erode property values? 

Joint with Ruchi Singh

Regional Science and Urban Economics, 98, January 2023.

 DOI | IFLAME Working Paper

Press Coverage: UI News; OZY; Realtor.com

We examine how residential property values are impacted by school shootings, which are crimes that have a very low probability of being repeated in the same location. We exploit the exogenous timing of eleven mass shootings that took place between 1998 and 2014,  and use a difference-in-differences framework to estimate the causal effect of these school shootings on property values in the affected school attendance area. We find that house prices decline by an average of around 2.4 percent in a four-year period after a mass school shooting. We also find that enrollment falls in the affected school district, suggesting that families subsequently avoid schools in areas that have experienced such events.

The Economics Behind the Math Gender Gap: Colombian Evidence on the Role of Sample Selection

Journal of Development Economics, 2018, 135, pp. 368-391.  

DOI

Featured in: Marginal Revolution

The literature that has previously shown that boys outperform girls in math tests has failed to explain the underlying causes of the phenomenon. This math gender gap has been documented to vary across countries, and shown to grow as students advance through school. In this paper I suggest that these patterns may be explained by sample selection caused by gender differences in schooling's opportunity costs, which lead lower-achieving males to drop out. I present and test the implications of a labor supply model that examines the opportunity cost of school attendance and, thereby, the observed math gender gap. Using an exogenous policy change, the launch of a conditional cash transfer program in Colombia, I estimate that sample selection explains between 50 percent and 60 percent of the gap. Estimates of non-parametric bounds show that selection in the lower quantiles of the male distribution explains a significant portion of the gap.

We use 292 household surveys from eighteen Latin American countries to document patterns in secondary school graduation rates over the period 1990–2010. We find that enrollment and graduation rates increased during that period, while dropout rates decreased. We provide two types of explanations for these patterns. Countries implemented changes on the supply side to improve access, by increasing the resources allocated to education and designing policies to help students stay in school. Despite this progress, graduation rates are still generally low, and there are remarkable gaps in educational outcomes in terms of gender, income quintiles, and regions within countries. The quality of education is also generally low. 

Working Papers

Flooding the Brains: Natural Disasters, Student Outcomes, and the Urban-Rural Gap in Human Capital.

Conditionally accepted at Economic Development and Cultural Change.

I provide evidence that natural disasters negatively impact student outcomes, potentially explaining the lower academic achievement of students in rural areas compared to those in urban areas. Using data from the census of Colombian schools and employing a difference-in-differences strategy that leverages variation from an unusual rainfall shock affecting more than two million people in urban and rural Colombia, I find that these disruptions increase school dropout rates and decrease learning for the remaining students for at least a decade. The effects are concentrated on students enrolled in rural schools, while those in urban schools remain unaffected. I explore several mechanisms and rule out the possibility that the effects are driven by selective migration or a loss of educational resources. Instead, I find evidence that the rainfall shock increased poverty and led poorer, rural children into unemployment and additional work hours.

We use census-like data and a regression discontinuity design to study the labor market impacts of a signal provided by a government-sponsored award to top-performing students on a nationwide college exit exam in Colombia. Students who can signal their high level of specific skills earn seven to ten percent more than identical students lacking such a signal. The signal allows workers to find jobs in more productive firms and sectors that better use their skills. The positive returns persist for up to five years. The signal favors workers from less advantaged groups who enter the market with weaker signals. 

This paper examines the impact of trade liberalization on wage inequality in developing economies. We study a new mechanism that may amplify or lessen the inequality effect of trade. In particular, we include different degrees of substitutability between labor and intermediate inputs across sectors into a dynamic quantitative trade model. We use administrative data from Colombia and exploit exogenous tariff variation to estimate the key elasticities of the model through an indirect inference approach. We find complementarities between labor and intermediate inputs in the non-tradable sector and substitutability in the manufacturing and agricultural sectors. Armed with the estimates, we compute the gains from the trade reform, finding that different substitutabilities in the production function amplify the wage inequality effects.

I employ candidate-level data from oral admission exams to assess how jury gender composition impacts student performance in non-blind testing. Students are assigned to evaluating committees quasi-randomly, ensuring an exogenous gender mix of jury members. A 10 percent increase in male committee members leads to a decrease of 0.02 standard deviations in scores, even after accounting for fixed effects. This decline is mainly driven by lower scores among male students evaluated by all-male committees. Evidence indicating that male jury members grade male candidates more harshly is provided. These results reveal noteworthy gender-based influences on student performance in non-blind testing.

 Life-cycle income growth rates differ significantly across countries. In this paper, we study the relative importance of human capital accumulation, labor market frictions and labor market opportunities in shaping life-cycle age-income profiles in Brazil, Colombia and the United States. We begin by documenting strong correlations between these three channels and the steepness of the life-cycle wage profiles across all three countries. Then, through the lens of a random search model with learning on the job, we find that labor market opportunities and labor market frictions can be as important as human capital accumulation in some countries when explaining the differences in the life-cycle wage profile.  

The allocation of resources within the household has been extensively theorized, but empirical evidence on this topic has been very scarce. Endogeneity concerns hinder this type of analysis due to the lack of identifying variation within the household. In this paper, we overcome these difficulties by exploiting a unique setting that introduced random variation in resource allocation within households. We evaluate the effects of a program that provided alternative delivery methods of conditional cash transfers in Bogotá, Colombia, and allocated resources at the student level. The individual randomization implied that some households had treated and untreated siblings, allowing us to extend the analysis to estimate spillover effects of the program on beneficiaries and their siblings. Students were randomly allocated to a standard design and a design that prioritized enrollment in tertiary education. We find that standard delivery methods increase educational outcomes for treated children but decrease the same outcomes for untreated siblings of treated students. We rationalize the results by estimating a structural model that uses the standard delivery method for estimation and the alternative delivery method for validation

Selected Work in Progress

Signaling and Migrant Labor Market Integration: Experimental evidence from Colombia.

Joint with Matías Busso, Carolina Gonzalez-Velosa, Cynthia Van der Werf.

AEA Registry

Labor market signaling plays a crucial role in the job-matching process by reducing information frictions faced by employers. In this paper, we analyze whether the returns to signaling vary based on the accuracy of ex-ante signals. We estimate the heterogeneous returns to signaling by comparing locals and migrants, who differ in the accuracy of their available education signals. Our analysis employs data from a skill certification program in Colombia that provides both locals and migrants with a common credible signal within the labor market. Selection into the program was randomized, with 30 percent of spots allocated to migrants. Our estimation strategy leverages this random assignment to estimate the heterogeneous returns to signaling for both locals and migrants. Our findings offer valuable insights for policy improvements aimed at enhancing the labor market integration of migrants by assessing the heterogeneous returns of labor market signaling.

Using Artificial Intelligence to Improve Student Learning in the Developing World.

Joint with Felipe Barrera-Osorio.

How Many Children Left Behind? A Meta-Analysis of Treatment Effect Heterogeneity in Developing-Country Education Programs

Joint with Hanna Han, Jason Kerwin, Jeff Smith, and Rebecca Thornton.

Seasonality, School Calendar, and School Enrollment: Quasi-experimental evidence from Rural Colombia.

Joint with Abu Shonchoy, and Anderson Tami.

We assess whether crop seasonality impacts school dropout rates in rural areas. Schooling calendars often coincide with harvesting calendars in numerous regions, posing a significant challenge for rural students in developing countries due to the substantial increase in the opportunity cost of remaining enrolled in school. To investigate this phenomenon, we leverage variation resulting from an unexpected change in school calendars among public schools in two states in Colombia, leading to an increased overlap in the number of weeks between school attendance and harvesting seasons. The findings reveal that this overlap resulted in a higher incidence of school dropouts, suggesting that a potential policy solution for addressing high dropout rates in rural schools is to adjust the school and harvesting calendars.