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...

While stock market expectations are among the most important primitives of portfolio choice models, their measurement has proved challenging for some respondents. We argue that the magnitude of measurement error in subjective expectations can be used as an indicator of the degree to which...

We document that an internal locus of control can be hindering in financial market situations, where short-term outcomes are determined by chance. The reason is that internally controlled individuals may tend to (over-)react to random outcomes. Our evidence is based on an experiment in which...

We investigate the relationship between subjective probabilities of future stock market returns and decisions about stockholding. Specifically, we examine whether acting upon subjective probabilities is confined to individuals with high cognitive skills. We explore this question using data from...

We examine how emerging market (EM) investors allocate their stock portfolios internationally. Using both country-level and institution-level data, we find that the coming wave of EM investors systematically over- and under-weight their holdings in some target countries. These abnormal foreign...

We examine the impact of Articial Intelligence (AI) on productivity in the context of taxi drivers. The AI we study assists drivers with finding customers by suggesting routes along which the demand is predicted to be high. We find that AI improves drivers' productivity by shortening the...