This paper addresses the steep learning curve in Machine Learning faced by noncomputer scientists, particularly social scientists, stemming from the absence of a primer on its fundamental principles. I adopt a pedagogical strategy inspired by the adage "once you understand OLS, you can work your...

In this paper, we describe a novel iterative procedure called SISTA to learn the underlying cost in optimal transport problems. SISTA is a hybrid between two classical methods, coordinate descent ("S"-inkhorn) and proximal gradient descent ("ISTA"). It alternates between a phase of exact...

Most definitions of algorithmic bias and fairness encode decisionmaker interests, such as profits, rather than the interests of disadvantaged groups (e.g., racial minorities): Bias is defined as a deviation from profit maximization. Future research should instead focus on the causal effect of...

We use matched employer-employee data and firm balance sheet data to investigate the importance of firm productivity and firm labor market power in explaining firm heterogeneity in wage formation. We use a linear regression model with one interacted high dimensional fixed effect to estimate...

We propose a novel structural method to empirically identify economies of scale in household consumption. We assume collective households with consumption technologies that define the public and private nature of expenditures through Barten scales. Our method recovers the technology by solely...

The Global Crisis demonstrated to the world that Ratings Agencies had misled the public about the stability of financial institutions. The Finance literature had decided that it was impossible to have bubbles in financial markets and any surge in the stock market would be self-correcting. Recent...

We show that the main nonparametric identification finding of Abbring and Van den Berg (2003b, Econometrica) for the effect of a timing-chosen treatment on an event duration of interest does not hold. The main problem is that the identification is based on the competing-risks identification...