UCLA Professor Martin Hackmann wins the Warren C. Scoville Distinguished Teaching Award for Winter 2024

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UCLA Professor Martin Hackmann has won the Warren C. Scoville Distinguished Teaching Award for Winter 2024 for his course Econ131: Economics of Health and Healthcare. The course focuses on the economic analysis of the U.S. medical care sector, a major industry with $4.5 trillion in spending, accounting for 17% of GDP. It delves into the economics of health care, focusing on the production and financing of medical services. Key topics include health insurance, asymmetric information, hospital competition, physician roles in patient choices, and government interventions. Emphasizing both theory and evidence, the course covers seminal theoretical models and empirical landmark studies that test key predictions and present crucial facts for public debate. The course covers health care demand, socioeconomic health disparities, the physician labor market, the hospital industry, insurance demand, adverse selection, moral hazard, pharmaceuticals, innovation, technology’s impact on health care costs, and significant health programs like Medicaid, Medicare, and employer-sponsored insurance. Professor Hackman’s profile can be found here.

Former UCLA Graduate Student Fernanda Rojas-Ampuero Wins the 2024 Dorothy Thomas Award

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Former UCLA Graduate Student Fernanda Rojas-Ampuero, now a Professor in the Department of Economics at the University of Wisconsin, won the Population Association of America’s highly competitive 2024 Dorothy Thomas Award for best graduate student paper. Her paper, entitled “Sent Away: The Long-Term Effects of Slum Clearance on Children and Families,” documents how Chile’s mandated slum-clearance programs between 1979-1985 had large, negative long-run effects on children and parents. Displaced children earned 14% less as adults, achieved 0.64 fewer years of education, and were more likely to work in informal jobs. Displaced parents had higher mortality rates and died at younger ages.  While at UCLA, Fernanda was a recipient of CCPR’s Treiman award, and received her Ph.D. in economics in 2022. Her dissertation was advised by Professors Dora Costa (chair), Adriana Lleras-Muney, and Michela Giorcelli.

UCLA Professors Board and Meyer-ter-Vehn receive AEJ Best Paper Award

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UCLA Professors Simon Board and Moritz Meyer-ter-Vehn received the American Economic Journal (AEJ) Best Paper Award for their paper ‘A Reputational Theory of Firm Dynamics’ published in the American Economic Journal: Microeconomics in 2022. The annual AEJ Best Paper Award is given to the best paper published in each of the American Economic Journals: Applied Economics, Economic Policy, Macroeconomics, and Microeconomics over the last three years.

The announcement can be found here.

The paper here.

Paper by UCLA Professor Pierre-Olivier Weill was featured in NBER Digest

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A paper by UCLA Professor Pierre-Olivier Weill studying bond trading was featured in the February issue of NBER Digest. The paper finds that, in addition to the characteristics of a bond trade request, the characteristics of the bond trader are important in determining the time to consummating a trade and the failure rate.

The February issue of NBER Digest can be found here.

The paper can be found here.

Should we regulate artificial intelligence?

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By Joao Guerreiro

Joao Guerreiro

Joao Guerreiro

The short stories in Isaac Asimov’s “I, Robot” discussed some of the dilemmas associated with artificial intelligence (AI). New developments in AI technology have brought these concerns from the pages of science-fiction stories to the forefront of policy discussions. In May 2023, a global AI consortium declared AI risks a priority, similar to pandemics and nuclear war. The G7 started the Hiroshima AI Process for global AI regulation. Both the European Union and the U.S. are discussing regulatory frameworks. Ideas include mandatory testing, holding developers accountable, and classifying AI into risk tiers. The critical issue is the uncertainty surrounding AI’s societal costs and benefits.

How should AI be regulated in the presence of uncertainty regarding the AI’s potential adverse external effects? Professor Joao Guerreiro, with Sergio Rebelo (Kellogg School of Management) and Pedro Teles (Banco de Portugal and Catolica-Lisbon School of Business and Economics), tackles this question in a recent paper: “Regulating Artificial Intelligence.” The paper evaluates regulatory approaches using a normative analysis. The authors explore two settings. In the first scenario, uncertainty is only resolved after the release of the AI. In the second scenario, it is possible to beta-test the algorithm to assess external effects.

In the absence of beta testing, there’s a mismatch between the optimal AI novelty level for society and what naturally arises in an unregulated market. The paper argues that the social optimum, or the ideal balance of AI novelty and safety, is generally more conservative than what the market would select without regulation. With beta testing, developers can learn the external effects of the AI by testing before release. This approach helps resolve uncertainties regarding potential negative externalities. Still, the social optimum requires a higher degree of conservativism both in testing and the algorithm’s release.

The authors evaluate three regulatory frameworks. First, they show that subjecting algorithms to regulatory approval is insufficient to implement the social optimum– since developers still have the incentive to go for too-risky algorithms. Second, simply holding developers liable for the external effects of the algorithms is also insufficient to implement the social optimum in the presence of limited liability. Finally, they show that mandating beta testing to assess the externalities and holding developers liable for the adverse effects of the algorithm can achieve the social optimum, even in the presence of limited liability.

Overall, the paper’s findings highlight the complexity of AI regulation and the need for nuanced approaches that balance innovation and safety. By considering various scenarios and regulatory frameworks, it provides valuable insights for policymakers and stakeholders in the AI field.

David Henning was awarded this year’s Summit Fellowship in Applied Economics

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David Henning is the recipient of this year’s Summit Fellowship in Applied Economics for his work on tax compliance using tax data on firms in Uganda.
The award was established by Albert J. Lee to support UCLA students advancing economics through creative use of data. Albert Lee is the Founding Partner and Expert Economist of Summit. He received his Ph.D. in economics from UCLA, and serves on the Board of Visitors at the Economics Department at UCLA.