Job Market Paper

Identification and Estimation of Intergenerational Income Mobility Measures

Abstract
Measuring the intergenerational transmission of lifetime economic status is complicated by researchers often only observing snapshots of income at specific ages. Consequently, standard practice estimates intergenerational mobility using income averages, introducing life-cycle bias that compromises reliability and comparability across studies, time, and place. I develop a missing data framework that exploits available income data and observable characteristics to eliminate life-cycle bias. This method combines nonparametric identification with Neyman-orthogonal moments to construct debiased machine learning estimators for intergenerational income mobility measures under plausible missing-at-random and testable independence assumptions. I apply this framework to estimate the intergenerational elasticity for the U.S. using the Panel Study of Income Dynamics across birth cohorts from 1954 to 1977 with rolling 10-year windows. While existing approaches estimate values between 0.41 and 0.54, the proposed method yields substantially higher estimates ranging from 0.6 to 0.7, averaging 0.64. These results align closely with recent evidence using long time averages over mid-career periods, reinforcing high U.S. intergenerational persistence.

Working Papers

Here Comes the Rain: Weather Shocks and Economic Outcomes in Ecuador
R&R at World Development

Abstract
This paper examines the heterogeneous effect of precipitation shocks on poverty status in Ecuador. Using gridded monthly precipitation data from 2007 to 2021, we define measures for the excess and deficit in precipitation levels at the parish geographical level. Weather data are merged with household socioeconomic information derived from the National Survey of Employment, Unemployment, and Underemployment (ENEMDU). Our empirical findings reveal that both excess and deficit in precipitation significantly affect poverty status, with considerable heterogeneity across economic sectors. Variations in the Standardized Precipitation Index, whether positive or negative, lead to an increased probability of poverty among workers in the primary sector. In contrast, we find poverty-reducing effects in the secondary and tertiary sectors, with their magnitude being shaped by formality status, urban/rural location, and self-employment status. The analysis identifies per-capita household income and labor earnings as key transmission channels, with precipitation shocks having redistributive effects on labor income in the tertiary sector, while amplifying inequality in the primary sector.

Family Background and Economic Mobility: Evidence from the US

Abstract
This paper examines how family background relates to economic mobility for disadvantaged children. We use data from the Panel Study of Income Dynamics for below-median income, multiple-child families. Using a novel approach combining family fixed effects, Empirical Bayes shrinkage, and SHapley Additive exPlanations, we identify which family characteristics most strongly predict children’s economic outcomes relative to their parents, holding parental income constant. Our findings reveal that race and family structure are the primary predictors, accounting for 35% and 22.4% of the explained variation, respectively. While supporting the well-documented racial disparities in intergenerational mobility, our results suggest that the role of family structure in intergenerational mobility extends beyond the single- versus two-parent household distinction.

An Inferential Framework to Reduce Climate Risk
with Gustavo Canavire-Bacarreza, Carlos Rodriguez-Castelán, and Carolina Vélez-Ospina

Abstract
With the increase of climatic shocks, quantifying their impact on vulnerability to poverty has gained significant attention. This paper extends the simulation approach to climate vulnerability of Hill and Porter (2017) for the design of targeted, place-based public policies to prevent and mitigate climate risk. We propose using SHAP values to characterize the most vulnerable to climate shocks and estimate the heterogeneous impact of specific climate shocks on poverty vulnerability. We illustrate our approach empirically by considering Ecuador, a biodiverse country with high exposure to climate risk and vulnerability. Our analysis reveals that the vulnerable are mostly informal individuals, working in the primary sector, and living in rural areas, located in the Amazonian Region, which motivates implementing a targeted place-based formalization policy. Our analysis highlights the importance of implementing preventive measures in Imbabura and Pastaza. While the former ranks among the three provinces most affected by droughts and floods, the latter is one of the most affected by maximum temperatures and droughts.

Publications

On the Effects of Wildfires on Poverty in Bolivia
with Gustavo Canavire-Bacarreza and Andrey Ramos
Journal of Development Economics (2025)
A spatial one-sided error model to identify where unarrested criminals live
with Andrés Ramírez-Hassan
Economic Modelling (2025)
Efficiency in Poverty Reduction in Bolivia
with Gustavo Canavire-Bacarreza and Javier Beverinotti
Journal of Policy Modeling (2025)
Promoting academic honesty: a Bayesian causal analysis of an integrity pilot campaign
with Andrés Ramírez-Hassan
Education Economics (2022)
Working paper version available here
Revisiting Tax Effort in Emerging Markets
with Gustavo Canavire-Bacarreza, Maria Cecilia Deza, and Osmel Manzano
Public Finance Review (2022)
Working paper version available here

Chapters in Books

Evaluating Educational Policies in Practice
with Vedant Bhardwaj and María Valkov
Economics of Education, Springer Nature (2025)

Contributions to Policy Reports

Poverty and Equity Assessment in Ecuador (in Spanish)
World Bank (2025)
Series: How to accelerate economic growth and strengthen the middle class (in Spanish), Inter-American Development Bank (2020), covering: Perú, Colombia, Ecuador, and Bolivia.