We investigate how workers adjust to firms' investments into new digital technologies, including artificial intelligence, augmented reality, or 3D printing. For this, we collected novel data that links survey information on firms' technology adoption to administrative social security data. We...

Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job...

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...

This paper consolidates recent methodological developments based on Double Machine Learning (DML) with a focus on program evaluation under unconfoundedness. DML based methods leverage flexible prediction methods to control for confounding in the estimation of (i) standard average effects, (ii)...

Binary treatments are often ex-post aggregates of multiple treatments or can be disaggregated into multiple treatment versions. Thus, effects can be heterogeneous due to either effect or treatment heterogeneity. We propose a decomposition method that uncovers masked heterogeneity, avoids...

Many models of investor behavior predict that investors prefer assets that they believe to have positively skewed return distributions. We provide a direct test of this prediction in a representative sample of the Dutch population. Using individual-level data on return expectations for a broad...

In this paper we develop a job portfolio model of dual job holding based on a Stone-Geary utility function. We derive the associated Slutsky equation components. Because the job portfolio model applies only to unconstrained dual jobholders, we separate individuals who moonlight because of an...

Recent advances in behavioral genetics have enabled the discovery of genetic scores linked to a variety of economic outcomes, including education. We build on this progress to demonstrate that the same genetic variants that predict educational attainment independently predict household wealth in...

Analysing the US Panel Study of Income Dynamics, we present a new empirical method to investigate the extent to which households reduce their financial risk exposure when confronted with background risk. Our novel modelling approach - termed a deflated fractional ordered probit model -...