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Summary

The Costs of Employment Segregation: Evidence from the Federal Government under Woodrow Wilson
Author(s):
Abhay Aneja, University of California at Berkeley
Guo Xu, University of California, Berkeley and NBER
Discussant(s):
Warren Whatley, University of Michigan
Abstract:

Aneja and Xu link newly-digitized personnel records of the U.S. government for 1907-1921 to census data to study the segregation of the civil service by race under President Woodrow Wilson. Using a difference-in-differences design around Wilson's inauguration, the researchers find that the introduction of employment segregation increased the black-white earnings gap by eight percentage points. This increasing gap is driven by a reallocation of existing black civil servants to lower paid positions, lowering their returns to education. Importantly, the negative effects extend beyond Wilson's presidency. Using census data for 1900-1940, Aneja and Xu show that segregation caused a relative decline in the home ownership rate of black civil servants. Moreover, by comparing children of black and white civil servants in adulthood, the researchers provide evidence that descendants of black civil servants who were exposed to Wilson's presidency exhibit lower levels of education, earnings, and social mobility. Their combined results thus document significant short and long-run costs borne by minorities during a unique episode of state-sanctioned discrimination.

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In addition to the conference paper, the research was distributed as NBER Working Paper w27798, which may be a more recent version.

The Effect of Social Media on Elections: Evidence from the United States
Author(s):
Thomas Fujiwara, Princeton University and NBER
Karsten Müller, Princeton University
Carlo Schwarz, Bocconi University
Discussant(s):
Roee Levy, Massachusetts Institute of Technology
Abstract:

Fujiwara, Müller, and Schwarz study how social media affects election outcomes using variation in the number of Twitter users across U.S. counties induced by participants of the 2007 South by Southwest (SXSW) festival, a key event in Twitter's rise to popularity. They show that this variation, which remains predictive of Twitter use a decade later, is unrelated to electoral outcomes before the platform's mass adoption. Our results suggest that exposure to Twitter lowered the Republican vote share in the 2016 and 2020 presidential elections, but had limited effects on turnout and vote shares in House and Senate races, as well as previous presidential elections. Evidence from two sources of survey data indicates that the effects are driven by independent and moderate voters. Our results are consistent with the idea that Twitter's relatively liberal content can persuade voters to alter their views.

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The Political Economic Causes of the Soviet Great Famine, 1932–33
Author(s):
Andrei Markevich, New Economics School
Natalya Naumenko, George Mason University
Nancy Qian, Northwestern University and NBER
Discussant(s):
Yuri Zhukov, University of Michigan
Abstract:

This paper documents several new facts about the Soviet Great Famine, 1932-33. There was no aggregate food shortage. Regional mortality rates were unrelated to per capita food production, but positively associated with ethnic Ukrainian population share. Political loyalty to and peasant resistance against the regime were positively associated with famine mortality and state food procurement in regions populated by ethnic Ukrainians. The findings show that, all else equal, ethnic Ukrainians suffered disproportionally high famine mortality and imply ethnic bias in famine-era policies. A back-of-the-envelope calculation indicates that ethnic bias against Ukrainians explains 77% of famine deaths in Russia, Ukraine and Belarus, and 92% in Ukraine.

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Social Media and Protests in China
Author(s):
Bei Qin, Hong Kong Baptist University
David Stromberg, Stockholm University
Yanhui Wu, University of Hong Kong
Discussant(s):
Jaya Wen, Harvard Business School
Abstract:

This paper studies whether and how social media affect the dynamics of protests in China in the 2009-2017 period. Based on a dataset of 13.2 billion microblog posts, Qin, Stromberg, and Wu use retweets to construct a network of social media information flows across cities and exploit its rapid expansion to identify causal effects. The researchers find that despite strict government control, Chinese social media have a sizeable effect on the geographic spread of protests and strikes. While the effect is rapid and short-lived and predominantly occurs between similar events, social media considerably increase the scope of protests. Further evidence shows that the effect is likely to be driven by tacit coordination and emotional reactions rather than explicit coordination and sharing tactics. Their study sheds light on the debate regarding whether social media strengthen authoritarian regimes.

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Persistent Polarizing Effects of Persuasion: Experimental Evidence from Turkey
Author(s):
Ceren Baysan, University of Essex
Discussant(s):
David H. Yanagizawa-Drott, University of Zurich
Abstract:

Exposing voters to non-state-provisioned information is presumed to counter incumbents' efforts to keep voters uninformed in order to remain in power. In this study, Baysan estimates the effect of randomized information campaigns on voter behavior and ideology in Turkey. The design allows her to estimate heterogeneous effects of information campaigns. Baysan finds that voter response to the same campaigns increased political polarization and the effect persisted at least two years. She concludes that reducing censorship can be polarizing and, because average measures mask both positive and negative treatment effects, the impact of information campaigns on civil society is underestimated.

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The Economics of Partisan Gerrymandering
Author(s):
Alexander Wolitzky, Massachusetts Institute of Technology
Anton Kolotilin, University of New South Wales
Discussant(s):
Wioletta Dziuda, University of Chicago
Abstract:

In the United States, the boundaries of legislative districts are often drawn by political partisans. In the resulting partisan gerrymandering problem, a designer partitions voters into equal-sized districts with the goal of winning as many districts as possible. When the designer can perfectly predict how each individual will vote, the solution is to pack unfavorable voters into homogeneous districts and crack favorable voters across districts that each contain a bare majority of favorable voters. Wolitzky and Kolotilin study the more realistic case where the designer faces both aggregate and individual-level uncertainty, provide conditions under which appropriate generalizations of the pack and crack solution remain optimal, and analyze comparative statics. Optimal districting plans are equivalent to special cases of segregate-pair districting, a generalization of pack and crack where all sufficiently unfavorable voter types are segregated in homogeneous districts, and the remaining types are matched in a negatively assortative pattern. Methodologically, the reseachers exploit a mathematical connection between gerrymandering---partitioning voters into districts---and information design---partitioning states of the world into signals.

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Individual and Collective Information Acquisition: An Experimental Study
Author(s):
Pellumb Reshidi, Princeton University
Alessandro Lizzeri, Princeton University and NBER
Leeat Yariv, Princeton University and NBER
Jimmy H. Chan, Chinese University of Hong Kong
Wing Suen, The University of Hong Kong
Discussant(s):
Marina Agranov, California Institute of Technology and NBER
Abstract:

Many committees--juries, political task forces, etc.--spend time gathering costly information before reaching a decision. Reshidi, Lizzeri, Yariv, Chan, and Suen report results from lab experiments focused on such information collection processes. The researchers consider decisions governed by individuals and groups and compare how voting rules affect outcomes. Reshidi, Lizzeri, Yariv, Chan, and Suen also contrast static information collection, as in classical hypothesis testing, with dynamic collection, as in sequential hypothesis testing. Generally, outcomes approximate the theoretical benchmark and sequential information collection is welfare enhancing relative to static collection. Nonetheless, several important departures emerge. Static information collection is excessive, and sequential information collection is non-stationary, producing declining decision accuracies over time. Furthermore, groups using majority rule yield especially hasty and inaccurate decisions.

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Minority Turnout and Representation under Cumulative Voting. An experiment.
Author(s):
Alessandra Casella, Columbia University and NBER
Jeffrey Guo, Columbia University
Michelle Jiang, Columbia University
Discussant(s):
Pedro Dal Bó, Brown University and NBER
Abstract:

Under majoritarian election systems, securing participation and representation of minorities remains an open problem, made salient in the US by its history of voter suppression. One remedy recommended by the courts is Cumulative Voting (CV): each voter has as many votes as open positions and can cumulate votes on as few candidates as desired. Theory predicts that CV encourages the minority to overcome obstacles to voting: although each voter is treated equally, CV increases minority's turnout relative to the majority, and the minority's share of seats won. A lab experiment based on a costly voting design strongly supports both predictions.

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In addition to the conference paper, the research was distributed as NBER Working Paper w28674, which may be a more recent version.

Participants

Avidit Acharya, Stanford University
Maja Adena, Wissenschaftszentrum Berlin für Sozialforschung
Pat Akey, University of Toronto
Alex P. Albright, Harvard University
Francis Annan, Georgia State University
Lydia Assouad, Paris School of Economics
Carlos Avenancio, Indiana University
Susanna B. Berkouwer, University of Pennsylvania
Apurav Y. Bhatiya, University of Warwick
Chris A. Bidner, Simon Fraser University
Bruno Caprettini, University of Zurich
Ramona Dagostino, University of Rochester
Matz Dahlberg, Uppsala University
Gianmarco Daniele, Bocconi University
Sabyasachi Das, Ashoka University
Antoni-Italo De Moragas, CUNEF
Antoine Deeb, University of Califronia Santa-Barbara
Francesco Drago, University of Catania
Wioletta Dziuda, University of Chicago
Ulrich Eberle, Princeton University
Jon Eguia, Michigan State University
Gabriel A. Facchini, European University Institute
Matteo F. Ferroni, Boston University
Andrea Gallice, University of Turin
Matteo Gamalerio, University of Barcelona
Tommaso Giommoni, ETH Zurich
Arda Gitmez, Bilkent University
Gabriele Gratton, University of New South Wales
Jan Gromadzki, Warsaw School Economics
Olle Hammar, Uppsala University
Esther Hauk, IAE-CSCI
Yujung G. Hwang, Johns Hopkins University
Mathias Iwanowsky, University of Munich
Federica Izzo, University of California at San Digeo
William Janeway, University of Cambridge
Karam Kang, Carnegie Mellon University
Philipp M. Kastrau, Universitat Pompeu Fabra
Anne Sofie B. Knudsen, Lund University
Vasily Korovkin, CERGE-EI
Roee Levy, Massachusetts Institute of Technology
Sunghun Lim, Texas Tech University
Matt Lowe, University of British Columbia
Meera Mahadevan, University of California at Irvine
Andrei Markevich, New Economics School
Paolo Masella, University of Mannheim
Nicola Mastrorocco, Trinity College Dublin
Mike Meurer, Boston University
Juan S. Morales, University of Toronto
Karsten Müller, Princeton University
Natalya Naumenko, George Mason University
Margherita Negri, University of St Andrews
Anna Nicińska, University of Warsaw
Petra Laura Oreskovic, Harvard University
Bei Qin, Hong Kong Baptist University
Diego Ramos-Toro, Dartmouth College
Itzchak T. Raz, Hebrew University
Devesh Rustagi, University of Nottingham
Alessandro Saia, University of Lausanne
Margaret Samahita, University College Dublin
Wayne A. Sandholtz, Nova School of Business and Economics
Emilie Sartre, Center for Research in Economics and Statistics (CREST)
Willem Sas, University of Stirling
Ursina M. Schaede, University of Zurich
Mark Schelker, University of St. Gallen
Carlo Schwarz, Bocconi University
Simin Seury, York University
Ashish Shenoy, University of California, Davis
Kenneth Shepsle, Harvard University
Clara Sievert, Harvard University
Arthur Silve, Université Laval
Christiane Szerman, Princeton University
Gabriel Z. Tourek, Massachusetts Institute of Technology
Ana Tur-Prats, University of California at Merced
Felipe Valencia Caicedo, University of British Columbia
Pierre-Louis Vezina, King's College London
Felipe Vial, University of California, Berkeley
Warren Whatley, University of Michigan
Yanhui Wu, University of Hong Kong
Alexander Yarkin, Brown University
Yuri Zhukov, University of Michigan

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