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DTSTART;TZID=America/New_York:20190403T143000
DTEND;TZID=America/New_York:20190403T153000
DTSTAMP:20240514T181644Z
CREATED:20240212T112705Z
LAST-MODIFIED:20240514T181644Z
UID:10002077-1554301800-1554305400@cmsa.fas.harvard.edu
SUMMARY:Deregulation through Direct Democracy: Lessons from Liquor
DESCRIPTION:Speaker:  Sarah Moshary (University of Chicago) \nTitle:  Deregulation through Direct Democracy: Lessons from Liquor \nAbstract:  This paper examines the merits of state control versus private provision of spirits retail\, using the 2012 deregulation of liquor sales in Washington state as an event study. We document effects along a number of dimensions: prices\, product variety\, convenience\, substitution to other goods\, state revenue\, and consumption externalities. We estimate a demand system to evaluate the net effect of privatization on consumer welfare. Our findings suggest that deregulation harmed the median Washingtonian\, even though residents voted in favor of deregulation by a 16% margin. Further\, we find that vote shares for the deregulation initiative do not reflect welfare gains at the ZIP code level. We discuss implications of our findings for the efficacy of direct democracy as a policy tool.
URL:https://cmsa.fas.harvard.edu/event/4-3-2019-colloquium/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-040319.png
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DTSTART;TZID=America/New_York:20190410T143000
DTEND;TZID=America/New_York:20190410T153000
DTSTAMP:20240514T181503Z
CREATED:20240212T112326Z
LAST-MODIFIED:20240514T181503Z
UID:10002069-1554906600-1554910200@cmsa.fas.harvard.edu
SUMMARY:Inequality Aversion\, Populism\, and the Backlash Against Globalization
DESCRIPTION:Speaker: Pietro Veronesi (University of Chicago) \nTitle: Inequality Aversion\, Populism\, and the Backlash Against Globalization \nAbstract: Motivated by the recent rise of populism in western democracies\, we develop a model in which a populist backlash emerges endogenously in a growing economy. In the model\, voters dislike inequality\, especially the high consumption of “elites.” Economic growth exacerbates inequality due to heterogeneity in risk aversion. In response to rising inequality\, rich-country voters optimally elect a populist promising to end globalization. Countries with more inequality\, higher financial development\, and current account deficits are more vulnerable to populism\, both in the model and in the data. Evidence on who voted for Brexit and Trump in 2016 also supports the model.
URL:https://cmsa.fas.harvard.edu/event/4-10-2019-colloquium/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-041019-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20190417T163000
DTEND;TZID=America/New_York:20190417T173000
DTSTAMP:20240514T180443Z
CREATED:20240212T095021Z
LAST-MODIFIED:20240514T180443Z
UID:10001936-1555518600-1555522200@cmsa.fas.harvard.edu
SUMMARY:Machine Learning Physics: From Quantum Mechanics to Holographic Geometry
DESCRIPTION:Speaker: Yi–Zhuang You (UCSD)\n\n\n\nTitle: Machine Learning Physics: From Quantum Mechanics to Holographic Geometry\n\n\n\nAbstract: Inspired by the “third wave” of artificial intelligence (AI)\, machine learning has found rapid applications in various topics of physics research. Perhaps one of the most ambitious goals of machine learning physics is to develop novel approaches that ultimately allows AI to discover new concepts and governing equations of physics from experimental observations. In this talk\, I will present our progress in applying machine learning technique to reveal the quantum wave function of Bose-Einstein condensate (BEC) and the holographic geometry of conformal field theories. In the first part\, we apply machine translation to learn the mapping between potential and density profiles of BEC and show how the concept of quantum wave function can emerge in the latent space of the translator and how the Schrodinger equation is formulated as a recurrent neural network. In the second part\, we design a generative model to learn the field theory configuration of the XY model and show how the machine can identify the holographic bulk degrees of freedom and use them to probe the emergent holographic geometry.\n\n\n[1] C. Wang\, H. Zhai\, Y.-Z. You. Uncover the Black Box of Machine Learning Applied to Quantum Problem by an Introspective Learning Architecture https://arxiv.org/abs/1901.11103\n[2] H.-Y. Hu\, S.-H. Li\, L. Wang\, Y.-Z. You. Machine Learning Holographic Mapping by Neural Network Renormalization Group https://arxiv.org/abs/1903.00804\n[3] Y.-Z. You\, Z. Yang\, X.-L. Qi. Machine Learning Spatial Geometry from Entanglement Features https://arxiv.org/abs/1709.01223
URL:https://cmsa.fas.harvard.edu/event/4-17-2019-colloquium/
LOCATION:MA
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-041719-5.png
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20190424T163000
DTEND;TZID=America/New_York:20190424T173000
DTSTAMP:20240514T180043Z
CREATED:20240212T103852Z
LAST-MODIFIED:20240514T180043Z
UID:10001998-1556123400-1556127000@cmsa.fas.harvard.edu
SUMMARY:Credible Mechanisms
DESCRIPTION:Speaker: Shengwu Li (Harvard)\n\n\nTitle: Credible Mechanisms\n\nAbstract: Consider an extensive-form mechanism\, run by an auctioneer who communicates sequentially and privately with agents. Suppose the auctioneer can deviate from the rules provided that no single agent detects the deviation. A mechanism is credible if it is incentive-compatible for the auctioneer to follow the rules. We study the optimal auctions in which only winners pay\, under symmetric independent private values. The first-price auction is the unique credible static mechanism. The ascending auction is the unique credible strategy-proof mechanism.
URL:https://cmsa.fas.harvard.edu/event/4-24-2019-colloquium/
LOCATION:MA
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-042419.png
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