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"Kramer vs. Kramer: On the Importance of Children and Divorce Filings for Understanding Divorce Rates in the U.S."
PDF version [pdf]
I document that approximately 70% of divorce filings in the 1970's were done by wives in the United States. Since then, this figure has experienced a large decline, reaching 56% in 2015. At the same time, divorce rates sharply increased from 1960 until the mid 1980s and have declined since then. I construct a life cycle model of endogenous marriage and unilateral divorce with endogenous labor supply and savings that jointly explains these facts. I use my model to measure the contribution of changes in the gender-wage gap, property division laws and child custody arrangements in explaining the divorce patterns over time. First, the reduction in the gender-wage gap generates two opposing effects. On the one hand, the reduction of the gender-wage gap increases the value of divorce for married women and, on the other hand, unmarried women become more selective in the marriage market thus raising the quality of newly formed matches. Second, children increase the value of divorce for the custodial parent; so a higher probability of getting child custody raises the chances of filing for divorce. Third, a higher share of assets assigned to wives upon divorce can either increase or decrease divorce rates by altering the savings decision of the household. My model accounts for approximately 50 per cent of the decline in divorce filings and 70 per cent of the variation in divorce rates between 1970 and 2015. I find that the decrease in the gender-wage gap and the increase in the probability of getting child custody for men are major drivers behind the changes in divorce rates and in divorce filings, respectively. Importantly, I find that failure to match who files for divorce can lead to opposite counterfactual results.
"A Quantitative Theory of the HIV Epidemic:Education, Risky Sex and Asymmetric Learning" with Daniela Iorio and Raül Santàeulalia-Llopis
PDF version [pdf]
Online Appendix [pdf].
We explore learning about HIV infection odds from risky sex as a new mechanism explaining the Sub-Saharan Africa HIV epidemic. Our novel empirical evidence reveals U-shaped relationship between education and being HIV positive across epidemic stages, which prompts the idea of asymmetric learning: more educated individuals potentially learn faster and update their (latent) beliefs about infection odds more accurately than less educated individuals, inducing earlier sexual behavioral change among the more educated. Our nonstationary model incorporates three HIV epidemic stages, chronologically: a myopic stage where agents are unaware of how risky sex causes infections, a learning stage where agents update beliefs on infection odds, and an ARV stage reflecting treatment introduction. Anchored in the micro evidence—explaining the HIV-education gradient—we find that our learning mechanism is powerful: a 5-year earlier learning reduces new AIDS deaths by almost 45%, and a 10-year earlier learning results in a 60% drop.
"Stage-Based Identification of Policy Effects" with Christopher Busch, Alexander Ludwig and Raül Santaeulàlia-Llopis
PDF version [pdf].
Online Appendix [pdf].
We develop a method that identifies the effects of nationwide policy, i.e., policy implemented across all regions at the same time. The core idea is to track outcome paths in terms of stages rather than time, where a stage of a regional outcome at time t is its location on the support of a reference path. The method proceeds in two steps. First, a normalization maps the time paths of regional outcomes onto the reference path—using only pre-policy data. This uncovers cross-regional heterogeneity of the stage at which policy is implemented. Second, this stage variation identifies policy effects inside a window of stages where a stage-leading region provides the no-policy counterfactual path for non-leading regions that are subject to policy inside that window. We assess our method’s performance with Monte-Carlo experiments, illustrate it with empirical applications, and show that it captures heterogeneous policy effects across stages.
"Evaluating the Effectiveness of Policies Against a Pandemic" with Christopher Busch, Alexander Ludwig and Raül Santaeulàlia-Llopis
PDF version [pdf].
A post on this article appeared in the Barcelona SE Focus blog.
We apply a novel method to evaluate policies against a pandemic. In the context of the application, the essence of our approach is the insight that epidemic dynamics are best tracked over stages, rather than over time. The application focuses on the nationwide stay-home policy enacted in Spain against the Covid-19 pandemic. We find that the policy saved 16.8% of lives relative to the number of deaths that would have occurred had it not been for the policy intervention. Its effectiveness evolves with the epidemic and is larger when implemented at earlier stages.
"HIV Diffusion: Evidence from One Million Blood Tests" with Daniela Iorio and Raül Santaeulàlia-Llopis
We mine 1 million HIV tests to empirically show how the HIV epidemic diffuses across demographic and economic groups. We show how the patterns of HIV infection change across stages of the epidemic.
"Agricultural productivity in Bolivia before and after the 2006 reform" with Sergio Bobka
We compute a measure of agricultural TPF for Bolivian Agricultural Production Units (APU) before and after the 2006 agricultural reform. Using very detailed farm level census data on input and output quantities in production we are able back out individual farm productivity for the years 1984 and 2013. We then conduct a missallocation exercise where we observe a reduction of the degree of factor missallocation between the years 1984 and 2013, probably associated to the 2006 land reform.