We construct a matching model on the marriage market along more than one characteristic, where individuals have preferences over physical attractiveness (proxied by anthropometric characteristics) and market and household productivity of potential mates (proxied by socioeconomic...

We analyze the interaction of race with physical and socioeconomic characteristics in the U.S. marriage market, using the Panel Study of Income Dynamics from 1999 to 2009 for black, white, and inter-racial couples. We consider the anthropometric characteristics of both spouses, together with...

We develop a matching model on the marriage market, where individuals have preferences over the smoking status of potential mates, and over their socioeconomic quality. Spousal smoking is bad for non-smokers, but it is neutral for smokers, while individuals always prefer high socioeconomic...

We study the determinants of season of birth of the first child, for white married women aged 25-45 in the US, using birth certificate and Census data. We also analyze stated preferences for season of birth using our own Amazon Mechanical Turk survey. The prevalence of quarters 2 and 3 is...

We analyze how attractiveness rated at the start of the interview is related to weight (controlling for height), and BMI, separately by gender and also accounting for interviewer fixed effects, in a nationally representative sample. We are the first to show that height, weight, and BMI all...

We investigate gender differences across socioeconomic and wellbeing dimensions after three months of lockdown in the UK, using an online sample of approximately 1,500 respondents in Prolific, representative of the UK population with regards to age, sex and ethnicity. We find that women's mental...

We investigate assortative mating on education using a sample of couples from the Health and Retirement Study. We estimate a reduced-form linear matching function, which links wife's education to husband's education and both wife's and husband's unobservable characteristics. Using OLS we find...

This study employs six Machine Learning methods - Logit, Lasso-Logit, Ridge-Logit, Random Forest, Extreme Gradient Boosting, and an Ensemble - alongside registry data on abortions in Spain from 2011-2019 to predict multiple abortions and assess monetary savings through targeted interventions. We...

Argentina hit headlines around the world in 2002 on account of the largest debt default in history and a sudden economic collapse that generated statistics reminiscent of those from the Great Depression. In this article we focus on other consequences of the crisis that are not so obvious but...

We design an infrastructure experiment in Mexico to evaluate the impact of street pavement on housing values and household outcomes. We find that the provision of street pavement raises housing values by 16% and land values by 54%, according to professional appraisals. Using homeowner...