Economics

I develop a revealed preference framework to test whether an aggregate allocation of indivisible objects satisfies Pareto efficiency and individual rationality (PI) without observing individual preferences. Exploiting the type-based…

This paper investigates the decentralized provision of public goods in directed networks. We establish a correspondence between kernels in graph theory and specialized equilibria in which players either contribute a fixed threshold amount…

This paper examines how regulation can push an oligopoly from one pricing regime to another. It uses rich data from Chilean pharmacy chains to study a ban on comparative price advertising. Before the ban, ads created demand spillovers…

Despite a substantial body of theoretical and empirical research in the fields of conjoint and discrete choice analysis as well as product line optimization, relatively few papers focused on the simulation of subsequent competitive dynamics…

We study the evolution of intergenerational educational mobility and related distributional statistics in Spain. Over recent decades, mobility has risen by one-third, coinciding with pronounced declines in inequality and assortative mating…

This study proposes an end-to-end algorithm for policy learning in causal inference. We observe data consisting of covariates, treatment assignments, and outcomes, where only the outcome corresponding to the assigned treatment is observed.…

Using detailed data on workplace benefits linked with administrative registers in Korea, we analyze patterns of separations and job transitions to study how parents sort into family-friendly firms after childbirth. We examine two…

We study instrumental variable regression in data rich environments. The goal is to estimate a linear model from many noisy covariates and many noisy instruments. Our key assumption is that true covariates and true instruments are…

We describe a novel framework for discrete choice modeling and price optimization for settings where scheduled service options (often hierarchical) are offered to customers, which is applicable across many businesses including some within…

We show how state-of-the-art large language models (LLMs), seemingly inapplicable to the small samples typical of macroeconomics, can be trained effectively for macroeconomic forecasting. We estimate a dynamic stochastic general equilibrium…

This paper develops new identification results for multidimensional continuous measurement-error models where all observed measurements are contaminated by potentially correlated errors and none provides an injective mapping of the latent…

When are dynamics valuable? In Bayesian environments with public signals and no intertemporal commitment, we study a seller who allocates an economically single-shot resource over time. We provide necessary and sufficient conditions under…

Experiments deliver credible treatment-effect estimates but, because they are costly, are often restricted to specific sites, small populations, or particular mechanisms. A common practice across several fields is therefore to combine…

This study examines the relationship between trade openness, logistics performance, and economic growth within G20 economies. Using a Bootstrap Autoregressive Distributed Lag (ARDL) model augmented by a dynamic error correction mechanism…

The response of illicit drug consumers to policy changes like legalization is mediated by demand behavior. Since individual drug use is driven by many unobservable factors, accounting for unobserved heterogeneity becomes crucial for…

A Markov-switching observation-driven model is a stochastic process $((S_t,Y_t))_{t \in \mathbb{Z}}$ where $(S_t)_{t \in \mathbb{Z}}$ is an unobserved Markov chain on a finite set and $(Y_t)_{t \in \mathbb{Z}}$ is an observed stochastic…

A class of simultaneous equation models arise in the many domains where observed binary outcomes are themselves a consequence of the existing choices of of one of the agents in the model. These models are gaining increasing interest in the…

This paper examines how data inputs shape competition among artificial intelligences (AIs) in pricing games. The dataset assigns labels to consumers and divides them into different markets, thereby inducing multimarket contact among AIs. We…

Evidence on the effectiveness of retraining U.S. unemployed workers primarily comes from evaluations of training programs, which represent one narrow avenue for skill acquisition. We use high-quality records from Ohio and a matching method…

We develop a spectral approach for identifying and estimating average counterfactual outcomes under a low-rank factor model with short panel data and general outcome missingness patterns. Applications include event studies and studies of…