Large language models (LLMs) have quickly become popular as labor-augmenting tools for
programming, writing, and many other processes that benefit from quick text generation. In …

We present an empirical framework for creating dynamic coupon targeting strategies for high-
dimensional and high-frequency settings, and we test its performance using a large-scale …

We apply a machine learning technique to characterize habit formation in two large panel
data sets with objective measures of 1) gym attendance (over 12 million observations) and …

This paper investigates consumer inertia in health insurance markets, where adverse
selection is a potential concern. We leverage a major change to insurance provision that …

Demand elasticities and other features of demand are critical determinants of the answers to
most positive and normative questions about market power or the functioning of markets in …

We study a regulation in Chile that mandates warning labels on products whose sugar or
caloric concentration exceeds certain thresholds. We show that consumers substitute from …

Marketing is a field that is rich in data. Our data is of high quality, often at a highly
disaggregate level, and there is considerable variation in the key variables for which …

Consideration set models generalize discrete-choice models by relaxing the assumption
that consumers consider all available options. Determining which options were considered …

In light of the widely discussed political divide and increasing societal polarization, we
investigate in this paper whether the polarization of political ideology extends to consumers' …

This book provides an accessible approach to Bayesian computing and data analysis, with
an emphasis on the interpretation of real data sets. Following in the tradition of the …