Abstract: In this paper, we demonstrate how to enhance the validity of causal inference with unstructured high-dimensional treatments like texts, by leveraging the power of generative Artificial Intelligence. Specifically, we propose to use a deep...
The study of culture in social science research increasingly relies on large-scale data, yet existing resources remain constrained by limited source diversity and a lack of detailed information on human societies. In this project, we are...
Abstract: Quizzes are central to contemporary education around the world and of great interest to researchers across the social sciences (in psychology, sociology, political science, health, business, and other fields) who want to assess knowledge levels...
Abstract: Should researchers control for the observable history of variables, such as lagged dependent variables, or unobservable confounders, such as fixed effects, when attempting to establish causality in panel data? In this paper, we review two...
Abstract: Understanding the causal effects of time-varying treatments is critical in many domains, such as evaluating the impact of heart transplants on patient outcomes. Physicians face a challenge in determining whether transplants significantly improve...
Abstract:Countries have employed a wide range of policy instruments to mitigate climate change. These policies share a common pattern: governments initially rely on subsidies, together with command-and-control regulations, and eventually adopt carbon...
Abstract: Estimation of heterogeneous treatment effects plays an essential role in various scientific fields, industries, and policy-making settings. Although many existing methods estimate conditional average treatment effects (CATEs) based on the data...
Abstract: Social scientists often use ranking questions to study people's opinions and preferences. However, little is understood about the general nature of measurement errors in such questions, let alone their statistical consequences and what...
Abstract: To understand the patterns and trends of various forms of inequality, quantitative social science research has typically relied on statistical models linking the conditional mean of an outcome variable to a set of explanatory factors. A prime...
Abstract: In the past few years, there has been a flurry of computer science research on sortition, the task of randomly sampling a representative subset of people. This work has so far been primarily applied to choose members of citizens' assemblies, but...
