We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance--in terms of SDF Sharpe ratio and test asset pricing errors--is improving in model parameterization (or "complexity"). Our empirical findings verify the...

The United Nations Human Development Index (HDI) is arguably the most widely used alternative to gross domestic product for measuring national development. This is in large part due to its multidimensional nature, as it incorporates not only income, but also education and health. However, the...

Skewness is a prevalent feature of macroeconomic time series and may arise exogenously because shocks are asymmetrically distributed, or endogenously, as shocks propagate through production networks. Previous theoretical work often studies these two possibilities in isolation. We nest all...

Many of the challenges in the estimation of dynamic heterogeneous treatment effects can be resolved with local projection (LP) estimators of the sort used in applied macroeconometrics. This approach provides a convenient alternative to the more complicated solutions proposed in the recent...

We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

Geoeconomic pressure--the use of existing economic relationships by governments to achieve geopolitical or economic goals--is a prominent feature of global power dynamics. This paper introduces a methodology using large language models (LLMs) to systematically identify the application of and...

Income is simultaneously one of the most important variables used by economists and the variable most likely to be missing due to item non-response. While observations that are missing income responses are often dropped from analyses, such treatment is usually inappropriate. More appropriate...

Are speculators driving up oil prices? Should we raise energy prices to slow global warming? The present study takes a small number of such questions and compares the views of economic experts with those of the public. This comparison uses a panel of more than 2000 respondents from YouGov with...

We study the distribution of political speech across U.S. firms. We develop a measure of political engagement based on firms' communications (earnings calls, regulatory filings, and social media), by training a large language model to identify statements that contain political opinions. Using...