Economics

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This paper studies market design for generative AI intermediation. AI answer systems can improve user experience while diverting visits that finance publisher content and generate source-level quality signals. I show that an AI platform that underinternalizes future content reproduction retains too little referral traffic and can make costly open-web information subcritical, even with truthful content, accurate answers, and rational users. The mechanism can be self-reinforcing: less source-level measurement weakens conventional search, inducing further AI reliance. Sustainable repair requires replacing displaced revenue and deleted measurement through visitor-replacement royalties, audited p..

Large language models (LLMs) are lowering the entry barriers to working with exciting data sources that used to require strong data science skills, such as handwritten ledgers, text, images, or sound recordings. This guide provides an introduction for researchers who are new to LLMs. It sets out a step-by-step workflow for turning a research idea into working code and data, and describes the four main ways of interacting with an LLM: the chat window, editor-integrated assistants, agentic coding tools, and the API. It then works through the decisions a practitioner meets in sequence, beginning with whether an LLM is the right tool and whether the data are allowed to be sent to one, then how t..

Parents may invest differently across children by compensating the disadvantaged child or by reinforcing the child with higher expected returns. We study this question using a conditional cash transfer experiment that uniquely randomized transfers at the student level, generating exogenous variation in transfer exposure across siblings within the same household. The transfers increased short-run attendance among treated students but generated negative spillovers on untreated siblings: untreated siblings of treated students were 3.7 percentage points less likely to graduate from college, a decline of about 30 percent relative to the control mean. We interpret these effects using a dynamic mod..

What information do policymakers need to design Pigouvian taxes or subsidies? Standard logic suggests that it is sufficient to know the size of the externality and unnecessary to know about quantities. Yet this logic is incorrect if interventions have fixed costs, taxes create deadweight losses, or there are distributional concerns. We present a model in which these considerations can make it more valuable for policymakers to learn about equilibrium quantities. We apply the model to congestion pricing, which has high fixed costs, and to a proposed housing subsidy in Boston that features deadweight losses and distributional concerns.

We ask how far the choice of which moments to match can push estimates in misspecified structural models. The answer is: very far. Under regularity conditions, an adversarial researcher informed about the data distribution can choose moments that render any parameter value the unique solution to the population moment-matching problem. Moreover, in many cases they can do so with little increase in model-implied standard errors relative to maximum likelihood. We illustrate both results in a menu-cost model.