We extend classical ideal point estimation to allow voters to have different preferences when voting in different domains – for example when voting on agricultural policy than when voting on defense policy. Our scaling procedure results in estimated ideal points on a common scale. As a result,...

We develop a Bayesian nonparametric model to assess the effect of systematic risks on multiple financial markets, and apply it to understand the behavior of the S&P500 sector indexes between January 1, 2000 and December 31, 2011. More than prediction, our main goal is to understand the evolution...

In this paper, we examine the relationship between the COVID-19 lockdowns and mental health-related Google searches throughout Latin America. Using Google Trends data and an event-study design, we explore the association between country-specific stay-at-home orders and internet searches...

We define a dynamic and self-adjusting mixture of Gaussian Graphical Models to cluster financial returns, and provide a new method for extraction of nonparametric estimates of dynamic alphas (excess return) and betas (to a choice set of explanatory factors) in a multivariate setting. This...

Researchers have speculated that the economic and social consequences of COVID-19 will harm women's health. This paper tests this claim in the immediate aftermath of Mexico City's COVID-19 stay-at-home order using call-center data. We use an event-study design to track calls for fertility...