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Articles 31 - 60 of 3476
Full-Text Articles in Economics
Boundaries Of Inequality: The Political Economy Of Redlining And Modern Mortgage Credit, Kyle Guo
Boundaries Of Inequality: The Political Economy Of Redlining And Modern Mortgage Credit, Kyle Guo
Harvey M. Applebaum ’59 Award
This paper investigates the legacy of historical redlining on contemporary access to mortgage credit across three distinct urban policy environments: Baltimore, Philadelphia, and Manhattan. I find that while historical redlining is associated with a statistically significant negative effect on mortgage approval rates, the magnitude of this direct effect is relatively small. In comparison, applicant race, particularly for Black applicants, is a stronger predictor of mortgage approval rates across cities and models. This study utilizes 1930s Home Owners’ Loan Corporation (HOLC) residential security maps and Home Mortgage Disclosure Act (HMDA) data from 2007 to 2017, and uses ordinary least squares (OLS) …
The Macroeconomics Of Intergenerational Mental Health Dynamics, Boaz Abramson, Job Boerma, Diego Daruich, Aleh Tsyvinski
The Macroeconomics Of Intergenerational Mental Health Dynamics, Boaz Abramson, Job Boerma, Diego Daruich, Aleh Tsyvinski
Cowles Foundation Discussion Papers
We develop a quantitative macroeconomic theory of child mental health. The theory is grounded in child psychiatry, formalized in a life-cycle heterogeneous agent model of child development, and disciplined using micro data on mental health of children and parents. Intergenerational transmission of mental illness arises due to both biological factors and parental behavior. Parents experiencing mental illness have negative expectations and lose time due to rumination. As a result, they invest less in their child’s mental health. We use the model to evaluate policies designed to improve child mental health. We show that subsidizing mental health treatment for children generates …
Position: The Pre/Post-Training Boundary Should Govern Ip In Industry–Academia Ml Collaborations, Dirk Bergemann, Soheil Ghili, Nitzan Mekel-Bobrov
Position: The Pre/Post-Training Boundary Should Govern Ip In Industry–Academia Ml Collaborations, Dirk Bergemann, Soheil Ghili, Nitzan Mekel-Bobrov
Cowles Foundation Discussion Papers
Industry–academia ML collaborations routinely fail to launch—not for scientific reasons, but because academics must publish while companies must protect models trained on proprietary data, and no standard contract framework resolves this tension. Because contracts are negotiated by legal departments alone, many apparent legal disputes are incentive misalignment problems that only scientists at the table can correctly diagnose. We propose PBOS (Protect-the-Business / Open-Source-the-Science), a community-adoptable contract template anchored to a single technically-grounded boundary: pre-training artifacts (architectures, training code, benchmarks, untrained weights) are open science; post-training artifacts (weights trained on proprietary data) are business IP. This boundary is technically meaningful, legally …
Class Peers As Competitors And Educators: The Consequences Of Rank-Based Academic Rewards, Mark R. Rosenzweig, Bing Xu
Class Peers As Competitors And Educators: The Consequences Of Rank-Based Academic Rewards, Mark R. Rosenzweig, Bing Xu
Cowles Foundation Discussion Papers
This paper examines the theoretical and empirical consequences of rank-based reward systems in schools in which students’ performance and effort are evaluated relative to their peers. In such environments, classmates act simultaneously as competitors—due to rank-determined rewards—and as educators through peer learning and assistance. Using nationally representative panel survey data from U.S. high schools, combined with administrative information on the location assignments of new refugee student cohorts, we exploit variation in school competition policies and class ability compositions to identify empirically their dual effects on student effort and peer learning. We develop a theoretical tournament model with heterogeneous students who …
Regional Economic Impacts And Emission Responses Under Solar Radiation Modification, Jenny Bjordal, Evelien Van Dijk, Henri Cornec, Anthony A. Smith Jr, Trude Storelvmo
Regional Economic Impacts And Emission Responses Under Solar Radiation Modification, Jenny Bjordal, Evelien Van Dijk, Henri Cornec, Anthony A. Smith Jr, Trude Storelvmo
Cowles Foundation Discussion Papers
Solar Radiation Modification (SRM) has been proposed as a potential tool to limit increases in global or regional temperatures caused by anthropogenic greenhouse gas emissions. While previous research has extensively examined the climate system’s response to various SRM strategies, as well as their aggregate economic consequences, the regional distribution of economic impacts has received less attention. In this study, we use NorESM2–DIAM—an Earth System Model coupled to a high-resolution integrated assessment model—to assess the economic impacts, measured in GDP per capita, in an idealised SRM scenario where incoming solar radiation is reduced by 1%. Our results suggest that, relative to …
Beyond Exposure: Predicting Ai Adoption Based On Comparative Advantage, Ilse Lindenlaub, Ryungha Oh, Maria Alejandra Rodriguez, Laura Veldkamp
Beyond Exposure: Predicting Ai Adoption Based On Comparative Advantage, Ilse Lindenlaub, Ryungha Oh, Maria Alejandra Rodriguez, Laura Veldkamp
Cowles Foundation Discussion Papers
We document and explain the gap between measures of AI exposure and measures of AI adoption in the workplace. This leads us to propose a new AI adoption index based on comparative advantage. Using the representative German DiWaBe employee survey linked to worker and establishment information, we compare worker-reported AI use to prominent exposure measures and find that the relationship is weak. Motivated by this gap, we develop a framework in which adoption depends not only on technical feasibility—AI’s absolute advantage measured by exposure—but on profitability—AI’s comparative (dis)advantage relative to a specific worker—balancing AI productivity against AI user costs and …
Towards A Methodology For Measuring Rental Property Ownership In The United States, Stephanie Kestelman, Rebecca Diamond, John Eric Humphries, Kate Pennington, Winnie Van Dijk, John Voorheis
Towards A Methodology For Measuring Rental Property Ownership In The United States, Stephanie Kestelman, Rebecca Diamond, John Eric Humphries, Kate Pennington, Winnie Van Dijk, John Voorheis
Cowles Foundation Discussion Papers
Roughly one-third of U.S. households rent their homes, yet measuring who owns rental property is difficult: ownership is frequently obscured by LLCs, partnerships, and other intermediary entities that separate legal from economic control. We develop a method that traces ownership through administrative records—combining deeds and property assessments with the Census Bureau’s Business Register, IRS Schedule K-1 filings, and SEC filings on REITs—to identify ultimate owners and construct property portfolios across the full landlord size distribution. Applying the method to 11 large CBSAs, we find that individual landlords own a large majority of rental units, though their share varies meaningfully across …
From People’S War To People’S Rule: Rebel Governance And The Foundations Of Inclusive Democracy, Bhishma Bhusal, Michael Callen, Rohini Pande, Soledad Prillaman, Deepak Singhania, Apurva Subedi
From People’S War To People’S Rule: Rebel Governance And The Foundations Of Inclusive Democracy, Bhishma Bhusal, Michael Callen, Rohini Pande, Soledad Prillaman, Deepak Singhania, Apurva Subedi
Cowles Foundation Discussion Papers
How does wartime rebel governance shape post-conflict institutions? We study this in Nepal, where the Maoist People's War (1996–2006) dismantled a 240-year caste-based monarchy and ended with Maoists entering democratic politics. During the conflict, Maoists established sub-national “People’s Governments” that administered justice, collected taxes, and delivered local services. Using a spatial regression-discontinuity design, we show that exposure to People's Governments increased political knowledge and participation especially among historically marginalized indigenous groups (Janajatis). Exposure also reshaped party institutions and inter-party competition: candidate-selection committees in more exposed areas have 26 percent more Janajati members who, drawing on novel implicit-attitude data, exhibit less …
Learning Through Imitation: An Experiment, Marina Agranov, Gabriel Lopez-Moctezuma, Philipp Strack, Omer Tamuz
Learning Through Imitation: An Experiment, Marina Agranov, Gabriel Lopez-Moctezuma, Philipp Strack, Omer Tamuz
Cowles Foundation Discussion Papers
We compare how well agents aggregate information in two repeated social learning environments. In the first setting agents have access to a public data set. In the second they have access to the same data, and also to the past actions of others. Despite the fact that actions contain no additional payoff-relevant information, and despite potential herd behavior, free riding and information overload issues, observing and imitating the actions of others leads agents to take the optimal action more often in the second setting. We also investigate the effect of group size, as well as a setting in which agents …
Search Costs, Intermediation, And Trade: Experimental Evidence From Ugandan Agricultural Markets, Lauren Falcao Bergquist, Craig Mcintosh, Meredith Startz
Search Costs, Intermediation, And Trade: Experimental Evidence From Ugandan Agricultural Markets, Lauren Falcao Bergquist, Craig Mcintosh, Meredith Startz
Discussion Papers
We study the large-scale experimental rollout of a platform that reduced search and matching frictions in Ugandan agricultural markets by connecting buyers and sellers. Market integration improved substantially: trade increased and price gaps fell. Interpreting the experiment through a trade model, we estimate treatment effects accounting for equilibrium changes that impact control markets. The intervention reduced fixed trade costs by 20% and increased trade flows between treated markets by 7% and across all markets by 1%. Scale economies shaped engagement:few farmers used the platform, but equilibrium price convergence from improved arbitrage by larger traders passed through to farm revenue.
Wage Gap Disclosure In The Tropics, Pablo Castro, Mayara Felix, Ieda Matavelli, Bobak Pakzad-Hurson
Wage Gap Disclosure In The Tropics, Pablo Castro, Mayara Felix, Ieda Matavelli, Bobak Pakzad-Hurson
Cowles Foundation Discussion Papers
We evaluate the effects of mandatory disclosures of firm-specific gender wage gaps in Brazil—the first developing country to enact a large-scale pay transparency law. The mandate took effect in 2023, automatically releasing to the public government-curated reports showing firm-specific gender wage gaps, separately by major occupational groups, for formal sector firms with 100 employees or more. Regression discontinuity estimates on outcomes one year after the release show that the mandated disclosures had no effects on the gender wage ratio, average wages for men or women, or the number of occupations within firms. We document that gender wage gaps persist in …
How Wasteful Is Signaling?, Alex Frankel, Navin Kartik
How Wasteful Is Signaling?, Alex Frankel, Navin Kartik
Cowles Foundation Discussion Papers
Signaling is wasteful. But how wasteful? We study the fraction of surplus dissipated in a separating equilibrium. For isoelastic environments, this waste ratio has a simple formula: β/(β + σ), where β is the benefit elasticity (reward to higher perception) and σ is the elasticity of higher types’ relative cost advantage. The ratio is constant across types and is independent of other parameters, including convexity of cost in the signal. We show that the directional effects of β and σ on waste extend to non-isoelastic environments.
From Conversations To Mechanisms: Aligning Advertiser Incentives In Ai-Powered Product Recommendations, Dirk Bergemann, Marek Bojko, Paul Dütting, Renato Paes Leme, Haifeng Xu, Song Zuo
From Conversations To Mechanisms: Aligning Advertiser Incentives In Ai-Powered Product Recommendations, Dirk Bergemann, Marek Bojko, Paul Dütting, Renato Paes Leme, Haifeng Xu, Song Zuo
Cowles Foundation Discussion Papers
We study the design of efficient dynamic recommendation systems, such as AI shopping assistants, in which a platform interacts with a user over multiple rounds to identify the most suitable product among those offered by advertisers. Advertisers have multi-dimensional private information: their private value from a purchase and private information about the user’s preferences. In each round, the platform displays recommendations; the user learns product characteristics of the shown items and then chooses whether to purchase, exit without purchasing, or submit a new query. These actions generate a stream of feedback—purchase, exit, and follow-up queries—that is informative about the user’s …
Cross-Border Product Adoption: Individual Imports, Migrant Networks, And Domestic Retailers, David Argente, Esteban Méndez, Diana Van Patten
Cross-Border Product Adoption: Individual Imports, Migrant Networks, And Domestic Retailers, David Argente, Esteban Méndez, Diana Van Patten
Cowles Foundation Discussion Papers
This paper studies how new varieties enter markets and become locally available. We provide causal evidence of demand externalities that operate in two steps. First, information about new varieties diffuses directly through real-world social ties among consumers. Second, early purchases generate an indirect spillover to firms: local retailers learn from 'pioneer' consumers which new varieties are most likely to succeed and adjust their product offerings accordingly. We study this process in the context of direct-to-consumer imports. Using customs records on individuals' purchases matched to population-wide social networks, international migrant links, and retailer catchment areas, we document economically meaningful demand externalities. …
Pay-Per-Crawl Pricing For Ai: The Lm-Tree Agent, Richard Archer, Soheil Ghili, Nima Haghpanah
Pay-Per-Crawl Pricing For Ai: The Lm-Tree Agent, Richard Archer, Soheil Ghili, Nima Haghpanah
Cowles Foundation Discussion Papers
No abstract provided.
Growth With New And Old Technologies, Bernardo Ribeiro
Growth With New And Old Technologies, Bernardo Ribeiro
Cowles Foundation Discussion Papers
This paper proposes a semi-endogenous growth theory that incorporates technology vintages and the endogenous evolution of multiple technological paradigms through innovation. It provides a characterization of both balanced growth equilibrium and transitional dynamics in an environment where new technologies continuously emerge. From a positive perspective, the model rationalizes two distinct empirical patterns. Using two centuries of US patent data, I first document that the age profile of patents has a pronounced hump shape: most contemporary patents build upon technologies that are between 50 and 100 years old. Second, this age profile has remained stable throughout the past century. From a …
Soft-Floor Auctions: Harnessing Regret To Improve Efficiency And Revenue, Dirk Bergemann, Kevin Breuer, Peter Crampton, Jack Hirsch, Yero S. Ndiaye, Axel Ockenfels
Soft-Floor Auctions: Harnessing Regret To Improve Efficiency And Revenue, Dirk Bergemann, Kevin Breuer, Peter Crampton, Jack Hirsch, Yero S. Ndiaye, Axel Ockenfels
Cowles Foundation Discussion Papers
A soft-floor auction asks bidders to accept an opening price to participate in a second-price auction. If no bidder accepts, lower bids are considered using first-price rules. Soft floors are common despite being irrelevant with standard assumptions. When bidders regret losing, soft-floor auctions are more efficient and profitable than standard optimal auctions. Revenue increases as bidders are inclined to accept the opening price to compete in a regret-free second-price auction. Efficiency improves because a soft floor allows for a lower hard reserve, reducing the frequency of no sale. Theory and experiment confirm these motivations from practice.
Early Childcare Attendance And Cognitive Skills In Adolescence, Ingvild Almas, Nina Drange, Costas Meghir, Henrik Daae Zachrisson
Early Childcare Attendance And Cognitive Skills In Adolescence, Ingvild Almas, Nina Drange, Costas Meghir, Henrik Daae Zachrisson
Cowles Foundation Discussion Papers
This paper examines the impact of early childcare on academic achievement for children in grade 5 and grade 9, based on a 2003 policy expansion that created quasi-random variation in slot availability for children aged 1–2. Starting childcare one year earlier increases math scores by 9.7% of a standard deviation (SD) in grade 9. Children whose mothers do not hold a high school diploma benefit by a significant 0.28% of a SD at grade 9, reducing the math achievement gap from children of higher-educated mothers by about one third. We also present evidence of strong improvements for children of immigrants.
Capital Flows And The Global Collateral Cycle, Ana Fostel, John Geanakoplos, Gregory Phelan
Capital Flows And The Global Collateral Cycle, Ana Fostel, John Geanakoplos, Gregory Phelan
Cowles Foundation Discussion Papers
Cross-country disparities in collateral technologies alone can account for large capital flows among mature economies, and allow the most advanced country to run a permanent trade deficit. When the collateral technology advantage is in creating negative beta (super safe) financial assets backed by positive beta assets, a Global Collateral Cycle emerges, with pro-cyclical gross and net flows and increased global asset price volatility. The supply of super safe assets is necessarily curtailed in downturns, providing a complementary (supply) channel to the flight to safety (demand) channel for explaining why US safe asset prices rise during crises.
Organizational Targets In General Equilibrium, Joel P. Flynn, George Nikolakoudis, Karthik Sastry
Organizational Targets In General Equilibrium, Joel P. Flynn, George Nikolakoudis, Karthik Sastry
Cowles Foundation Discussion Papers
We build a general equilibrium model in which firms endogenously choose whether to target prices or quantities. We characterize how these choices of organizational targets depend on firms' uncertainty about microeconomic and macroeconomic factors. In equilibrium, the transmission of both nominal and real shocks hinges on firms' organizational targets. For example, under otherwise identical microfoundations, money is neutral under quantity targets and non-neutral under price targets. We further characterize how targets shape firms' strategic interactions and prove that the macroeconomic uncertainty that arises from each choice of targets reinforces incentives to choose that target. That is, choices of organizational targets …
Training Language Models For Bilateral Trade With Private Information, Dirk Bergemann, Soheil Ghili, Xinyang Hu, Chuanhao Li, Zhuoran Yang
Training Language Models For Bilateral Trade With Private Information, Dirk Bergemann, Soheil Ghili, Xinyang Hu, Chuanhao Li, Zhuoran Yang
Cowles Foundation Discussion Papers
Bilateral bargaining under incomplete information provides a controlled testbed for evaluating large language model (LLM) agent capabilities. Bilateral trade demands individual rationality, strategic surplus maximization, and cooperation to realize gains from trade. We develop a structured bargaining environment in which LLMs negotiate via tool calls within an event-driven simulator, separating binding offers from natural-language messages to enable automated evaluation. The environment serves two purposes: as a benchmark for frontier models and as a training environment for open-weight models via reinforcement learning. In benchmark experiments, a round-robin tournament among five frontier models (15,000 negotiations) reveals that effective strategies implement price discrimination …
Black Swans And Financial Stability: A Framework For Building Resilience, Daniel J. Barth, Stacey L. Schreft
Black Swans And Financial Stability: A Framework For Building Resilience, Daniel J. Barth, Stacey L. Schreft
Journal of Financial Crises
This article refines the concept of black swans, typically described as highly unlikely and catastrophic events, to be internally consistent. It explores features of the financial system that prevent the eradication of black swans. The main implication is the need to enhance the financial system’s resilience to withstand unforeseen events rather than focus on past crises. The article introduces a “resilience principle” for designing official-sector policies that can achieve such goals. The principle calls for policies that are adaptable, universal, and systemic. The article provides examples of policies with these features, assuming that the official sector is not better positioned …
Delegation And Verification Under Ai, Lingxiao Huang, Wenyang Xiao, Nisheeth K. Vishnoi
Delegation And Verification Under Ai, Lingxiao Huang, Wenyang Xiao, Nisheeth K. Vishnoi
Cowles Foundation Discussion Papers
As AI systems enter institutional workflows, workers must decide whether to delegate task execution to AI and how much effort to invest in verifying AI outputs, while institutions evaluate workers using outcome-based standards that may misalign with workers’ private costs. We model delegation and verification as the solution to a rational worker’s optimization problem, and define worker quality by evaluating an institution-centered utility (distinct from the worker’s objective) at the resulting optimal action. We formally characterize optimal worker workflows and show that AI induces phase transitions, where arbitrarily small differences in verification ability lead to sharply different behaviors. As a …
On Local Overidentification And Efficiency Gains In Modern Causal Inference And Data Combination, Xiaohong Chen, Haitian Xie
On Local Overidentification And Efficiency Gains In Modern Causal Inference And Data Combination, Xiaohong Chen, Haitian Xie
Cowles Foundation Discussion Papers
This paper studies nonparametric local (over-)identification and the semiparametric efficiency in modern causal frameworks. We develop a unified approach that begins by translating structural models with latent variables into their induced statistical models of observables and then analyzes local overidentification through conditional moment restrictions. We apply this approach to three popular classes of causal models: (1) the general treatment model under unconfoundedness; (2) the negative control model, and (3) the long-term causal inference model under unobserved confounding. The first model yields a locally just-identified statistical model, implying that all regular asymptotically linear estimators of the treatment effect have the same …
Triple/Double-Debiased Lasso, Denis Chetverikov, Joseph R.V. Sørensen, Aleh Tsyvinski
Triple/Double-Debiased Lasso, Denis Chetverikov, Joseph R.V. Sørensen, Aleh Tsyvinski
Cowles Foundation Discussion Papers
In this paper, we propose a triple (or double-debiased) Lasso estimator for inference on a low-dimensional parameter in high-dimensional linear regression models. The estimator is based on a moment function that satisfies not only first- but also second-order Neyman orthogonality conditions, thereby eliminating both the leading bias and the second-order bias induced by regularization. We derive an asymptotic linear representation for the proposed estimator and show that its remainder terms are never larger and are often smaller in order than those in the corresponding asymptotic linear representation for the standard double Lasso estimator. Because of this improvement, the triple Lasso …
First Proof Solutions And Comments, Mohammed Abouzaid, Andrew J. Blumberg, Martin Hairer, Joe Kileel, Tamara G. Kolda, Paul D. Nelson, Daniel Spielman, Nikhil Srivastava, Rachel Ward, Shmuel Weinberger, Lauren Williams
First Proof Solutions And Comments, Mohammed Abouzaid, Andrew J. Blumberg, Martin Hairer, Joe Kileel, Tamara G. Kolda, Paul D. Nelson, Daniel Spielman, Nikhil Srivastava, Rachel Ward, Shmuel Weinberger, Lauren Williams
Cowles Foundation Discussion Papers
Here we provide our solutions to the First Proof questions. We also discuss the best responses from publicly available AI systems that we were able to obtain in our experiments prior to the release of the problems on February 5, 2025. We hope this discussion will help readers with the relevant domain expertise to assess such responses.
Stochastic Optimization And Coupling, Frank Yang, Kai Hao Yang
Stochastic Optimization And Coupling, Frank Yang, Kai Hao Yang
Cowles Foundation Discussion Papers
We study optimization problems in which a linear functional is maximized over probability measures that are dominated by a given measure according to an integral stochastic order in an arbitrary dimension. We show that the following four properties are equivalent for any such order: (i) the test function cone is closed under pointwise minimum, (ii) the value function is affine, (iii) the solution correspondence has a convex graph with decomposable extreme points, and (iv) every ordered pair of measures admits an order-preserving coupling. As corollaries, we derive the extreme and exposed point properties involving integral stochastic orders such as multidimensional …
The Changing Landscape Of International Development: An Introduction, Pascaline Dupas, Pinelopi K. Goldberg, Rohini Pande
The Changing Landscape Of International Development: An Introduction, Pascaline Dupas, Pinelopi K. Goldberg, Rohini Pande
Discussion Papers
Since the late 1980s, extreme poverty has declined sharply, life expectancy and schooling have increased, and electoral democracy has expanded. However poverty reduction has slowed in recent years, particularly following the COVID-19 pandemic, amid intensifying conflict, fragility, climate risks, democratic backsliding, and the erosion of global trends—including trade integration and geopolitical stability—that once supported growth. These dynamics raise three interrelated questions: what barriers impede further progress; where will future growth in lower-income countries come from; and how can growth be broadly shared. Taking stock of 15 chapters forthcoming in Volume 6 of the Handbook of Development Economics, we discuss how …
The Changing Landscape Of International Development: An Introduction, Pascaline Dupas, Pinelopi Goldberg, Rohini Pande
The Changing Landscape Of International Development: An Introduction, Pascaline Dupas, Pinelopi Goldberg, Rohini Pande
Cowles Foundation Discussion Papers
Since the late 1980s, extreme poverty has declined sharply, life expectancy and schooling have increased, and electoral democracy has expanded. However poverty reduction has slowed in recent years, particularly following the COVID-19 pandemic, amid intensifying conflict, fragility, climate risks, democratic backsliding, and the erosion of global trends—including trade integration and geopolitical stability—that once supported growth. These dynamics raise three interrelated questions: what barriers impede further progress; where will future growth in lower-income countries come from; and how can growth be broadly shared. Taking stock of 15 chapters forthcoming in Volume 6 of the Handbook of Development Economics, we discuss how …
The Geometry Of Learning Under Ai Delegation, Lingxiao Huang, Nisheeth K. Vishnoi
The Geometry Of Learning Under Ai Delegation, Lingxiao Huang, Nisheeth K. Vishnoi
Cowles Foundation Discussion Papers
As AI systems shift from tools to collaborators, a central question is how the skills of humans relying on them change over time. We study this question mathematically by modeling the joint evolution of human skill and AI delegation as a coupled dynamical system. In our model, delegation adapts to relative performance, while skill improves through use and decays under non-use; crucially, both updates arise from optimizing a single performance metric measuring expected task error. Despite this local alignment, adaptive AI use fundamentally alters the global stability structure of human skill acquisition. Beyond the high-skill equilibrium of human-only learning, the …