"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 Stage-Based Identification of Policy Effects" with Christopher Busch, Alexander Ludwig and Raül Santaeulàlia-Llopis
Working paper version (Epidemic application only) [pdf].
A post on this article appeared in the Barcelona SE Focus blog.
We develop a novel empirical approach to identify the effectiveness of policies, which we apply 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 overstages, rather than over time. We use a normalization procedure that makes the pre-policy paths of the epidemic identical across regions. The procedure uncovers regional variation in the stage of the epidemic at the time of policy implementation. This variation delivers clean identi-fication of the policy effect based on the epidemic path of a leading region that serves asa counterfactual for other regions. The application focuses on the nationwide stay-homepolicy 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.
"A Quantitative Theory of the HIV Epidemic:Education, Risky Sex and Asymmetric Learning" with Daniela Iorio and Raül Santàeulalia-Llopis
Using micro survey data, we show that the relationship between education and the probability of HIV infection is U-shaped (positive-zero-positive) over the course of the epidemic. In contrast, the relationship between education and knowledge about the process of HIV infection follows an inverted U-shaped pattern. We develop a non-stationary quantitative macroeconomic theory with heterogeneous agents that is consistent with these facts. Our theory endogenizes the entire course of the HIV epidemic across its different stages: a pre-HIV epidemic stage; a myopic HIV stage in which agents are not aware of the process of HIV infection; a learning stage in which agents heterogeneously---across education groups---learn about the process of infection; and an anti-retroviral (ARV) stage that modifies the effects of HIV infection on individuals. We show that asymmetric learning is key to reproduce both the micro patterns that we document and the aggregate evolution of the HIV epidemic. In further counterfactual experiments, we assess the effects of an early understanding of the virus and its mode of infection, improvements in the composition of education, the earlier (and universal) adoption of ARVs and the use of PrEP to prevent further spread.
"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.
"Evaluating the Effectiveness of Policies Against a Pandemic" with Christopher Busch, Alexander Ludwig and Raül Santaeulàlia-Llopis
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.
"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.