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GDPR and the Lost Generation of Innovative Apps
Rebecca Janßen, ZEW Mannheim
Reinhold Kesler, University of Zurich
Michael Kummer, University of East Anglia
Joel Waldfogel, University of Minnesota and NBER
Timothy F. Bresnahan, Stanford University and NBER

The General Data Protection Regulation (GDPR), enacted with the goal of protecting user privacy, imposed compliance costs on app developers and may have inhibited revenue generation. Using data on 4.1 million apps at the Google Play Store from 2016 to 2019, Janssen, Kesler, Kummer, and Waldfogel document that GDPR induced the exit of about a third of available apps. Moreover, in the quarters following implementation, entry of new apps fell by over half. While the exiting apps had very little usage, the reduction in entry was more consequential for consumers. Because app success is unpredictable at launch, the missing apps would have been nearly as useful, on average, as those that still entered: Post-GDPR entry cohorts, less than half as large as their pre-GDPR counterparts, account for just over half as much usage as average pre-GDPR cohorts at the same ages. After documenting these descriptive facts, Janssen, Kesler, Kummer, and Waldfogel estimate a structural model of demand and entry in the app market. Comparing equilibria with and without GDPR, they find that GDPR reduces consumer surplus by 32 percent and aggregate app usage by 26 percent. The researchers conclude that, whatever the privacy benefits of GDPR, they come at substantial costs to consumers and producers.

Advertising Effects in Equilibrium
Sarah Moshary, University of Chicago

Platforms face a tradeoff in determining the optimal amount of advertising: while selling advertising space generates revenue, it may also reduce the attractiveness of the platform to consumers, who may in turn exit. As an example, a newspaper must decide how to allocate column inches between advertisements and news stories. Similarly, a search engine must decide how and in what order to present sponsored and organic search results. In order to optimize advertising, these platforms must understand the cost of advertising - that is, how advertising changes consumer behavior. The chief challenge in estimating the effect of advertising is endogeneity. That is, a regression of churn on advertising volumes is confounded by advertisers' targeting policies. This paper exploits an experiment on a large e-commerce platform to estimate the causal effect of advertising on consumer behavior. In the experiment, a random sample of users is shielded from all advertising. The paper documents how advertising affects consumers, sellers, and equilibrium prices on the platform; the results suggest that advertising acts to enhance the salience of sponsored items rather than to signal unobserved quality.

Shocks and Technology Adoption: Evidence from Electronic Payment Systems
Filippo Mezzanotti, Northwestern University
Apoorv Gupta, Dartmouth College
Nicolas Crouzet, Northwestern University
Daniel Björkegren, Brown University

Theories of coordination failures in technology adoption have been influential in economics, but empirical evidence on their importance is limited. This paper studies the role of this friction in the adoption of digital payments systems, using data from the largest provider of electronic wallets in India during the 2016 Demonetization. The researchers'r empirical strategy exploits variation in the intensity with which Indian districts were exposed to the cash contraction induced by the Demonetization. Consistent with a dynamic technology adoption model with complementarities, Mezzanotti, Gupta, and Crouzet show that the rate of adoption of the technology increased persistently in response to the large but temporary cash contraction. Estimates of the model indicate that the 6-month adoption response would have been 60% lower absent adoption complementarities. This suggests that large but temporary policy interventions can resolve coordination failures in technology adoption, though Mezzanotti, Gupta, and Crouzet highlight an important limitation of this logic: temporary interventions can also exacerbate initial differences in adoption across regions or markets.

Personal Social Networks, Technology Skills, and Workers’ Digital Resilience
David Gordo. Burtch, Boston University
Miguel Godinho de Matos, Catolica Lisbon School of Business & Economics
Francisco Lima, Universidade de Lisboa
Prasanna Tambe, University of Pennsylvania

With the recent, sweeping transition to remote work arrangements, due to the COVID-19 pandemic, workplace peer-support mechanisms have grown strained, fostering concerns about professional isolation, the long-run implications for worker performance. In this study, Burtch, Godinho de Matos, and Lima consider that potential remote workers may substitute workplace peer support with support from personal social networks, outside of the organization. Drawing on a novel, large and granular dataset that incorporates worker earnings, employment relationships, demographics, family-connections, educational backgrounds and employers' remote work practices, for 400,000 Portuguese workers, the researchers estimate that partner technology expertise has significant spillover benefits for a worker's wages following a shift to remote-work. Specifically, Burtch, Godinho de Matos, and Lima estimate that the wage return from spousal technology skills was approximately 75% of the wage return from own technology skills. Burtch, Godinho de Matos, and Lima demonstrate the robustness of their findings to alternative explanations and measures, and the researchers discuss the implications of their findings for firms, remote workers and society.

Misconduct and Reputation under Imperfect Information
Francis Annan, Georgia State University
Tavneet Suri, Massachusetts Institute of Technology and NBER

Misconduct - market actions that are unethical and indicative of fraud or wrongdoing - is a significant yet poorly understood issue that underlies many economic and financial transactions. Does misconduct in markets matter? When and how does reputation acts as a discipline against seller misconduct? Annan designs a field experiment to study the impact of two-sided anti-misconduct information programs on markets, which the researcher deploys on the local markets for mobile money (Human ATMs) in Ghana. Annan shows that, at baseline, these markets are characterized by substantial imperfect information, consumer mistrust, and vendor misconduct. The information programs led to a large reduction in misconduct (-21 pp = -72%) and as a result, an increase in overall market activity, firm sales and consumer welfare. Annan develops a simple sanctioning framework between vendors and consumers that shows the treatment effect is due to a combination of more accurate consumers' beliefs about misconduct and increased reputation concerns. Together, the results indicate a potentially significant source of local financial market frictions, where market activities are underprovided due to misconduct and difficulty in building reputation. Social sanctions through reputational impacts can promote formal local markets when formal sanctions are weak.

The Pricing Strategies of Online Grocery Retailers
Diego Aparicio, IESE Business School
Zachary Metzman, Massachusetts Institute of Technology
Roberto Rigobon, Massachusetts Institute of Technology and NBER
Matthew Gentzkow, Stanford University and NBER

Matched product data is collected from the leading online grocers in the U.S. The same products are identified in scanner data. The paper documents pricing strategies within and across online (and offline) retailers. First, online retailers exhibit less uniform pricing than offline retailers. Second, online price dispersion across competing chains in narrow geographies is higher than offline retailers. Third, variation in offline elasticities, shipping distance, pricing frequency, and local demographics are utilized to explain price differentiation. Surprisingly, pricing flexibility (across time) magnifies price differentiation (across locations). This evidence motivates a high-frequency study to recover the patterns of algorithmic pricing. Online grocery retailers change prices very frequently and in small magnitudes, have lower menu costs, are less synchronized, constantly explore the price grid, and often match competitors’ prices.


This paper was distributed as Working Paper 28639, where an updated version may be available.


Alessandro Acquisti, Carnegie Mellon University
Nuruddin Ahmed, Massachusetts Institute of Technology
Anna Airoldi, New York University
Francis Annan, Georgia State University
Itai Ater, Tel Aviv University
Or Avishay-Rizi, Tel-Aviv University
Yeon Ju Baik, University of Wisconsin–Madison
Yannis Bakos, New York University
Maxime Bonelli, HEC Paris
David Gordo. Burtch, Boston University
Dennis J. Campbell, University of Virginia
Aviv M. Caspi, Cornell University
AJ Yuan Chen, University of Southern California
Cristobal Cheyre, Cornell University
Alexander Copestake, University of Oxford
Erich M. Denk, Boston University
Timothy J. DeStefano, Harvard University
Shaoyin Du, University of Rochester
Luise Eisfeld, Toulouse School of Economics
Atiye Cansu Erol, University of Pennsylvania
Agata Farina, New York University
Samuel Goldberg, Northwestern University
Andreea D. Gorbatai, University of California, Berkeley
George Gui, Stanford University
Il-Horn Hann, University of Maryland
Ward Hanson, Stanford University
Philip Hanspach, European University Institute
Sherry He, University of California at Los Angeles
Lisa Y. Ho, Massachusetts Institute of Technology
Brett Hollenbeck, University of California at Los Angeles
Hao Hu, Georgia Institute of Technology
Can Huang, University of California, Berkeley
Shinjae Jang, Rice University
Rebecca Janßen, ZEW Mannheim
Jikhan Jeong, Florida Polytechnic University
Rafael Jimenez, University of Chicago
Garrett Johnson, Boston University
Brian Kahin, OECD Directorate for Science, Technology and Innovation
Aarushi Kalra, Brown University
Kirthi Kalyanam, Santa Clara University
Hyunwook Kang, Texas A&M
Sukhun Kang, London Business School
rupali kaul, Stanford University
Aaron Kaye, University of Michigan
Reinhold Kesler, University of Zurich
Gyu Hyun Kim, Iowa State University
Richard Kneller, University of Nottingham
Nikita Kotsenko, Hebrew University of Jerusalem
Michael Kummer, University of East Anglia
Anja Lambrecht, London Business School
Jungyoun Lee, Northwestern University
Xiaoxia Lei, Shanghai Jiao Tong University
Tin Cheuk Leung, Wake Forest University
Faqiang Li, Pennsylvania State University
Hui Li, Carnegie Mellon University
Pearl Z. Li, Stanford University
Yuxiao Li, University of Chicago
Jinan Lin, University of California Irvine
Tesary Lin, Boston University
Yanli Lin, Ohio State University
Samuel Lite, Harvard University
Siqi Liu, Brandeis University
Yi Liu, University of Pennsylvania
Yongdong Liu, University College London
Zhenqi Liu, Johns Hopkins University
Wei Lu, University of Toronto
Ilya Lukibanov, University of Southern California
Théo Marquis, University Paris-Saclay
Preston McAfee, Google
Milan Miric, University of Southern California
Alex Moehring, Massachusetts Institute of Technology
Giovanni Montanari, New York University
Zanele T. Munyikwa, Massachusetts Institute of Technology
Leon Musolff, Princeton University
Sridhar Narayanan, Stanford University
Han Loong. Ng, Pennsylvania State University
Robin Ng, Universite Catholique de Louvain
The Linh Bao Nguyen, University of Maryland
Thi Mai Anh Nguyen, Massachusetts Institute of Technology
Gbadebo Odularu, Bay Atlantic University
Prasanna Parasurama, New York University
Mohammad S. Rahman, Purdue University
Bhoomija Ranjan, Monash University
Oren Rigbi, Ben-Gurion University
Gregory Rosston, Stanford University
Angela S. Ryu, Columbia University
Stephan Sagl, Pennsylvania State University
Suproteem K. Sarkar, Harvard University
Gregor Schubert, UCLA Anderson School of Management
Regina Seibel, University of Zurich
Vatsala Shreeti, Toulouse School of Economics
Fangfei Shu, University of Southern California
Michael Sullivan, Yale University
Chenshuo Sun, New York University
Monic Sun, Boston University
Zhengyun Sun, Harvard University
Xuan Teng, University of Michigan, Ann Arbor
Jonathan D. Timmis, World Bank
Matteo Tranchero, University of California at Berkeley
Kalinda Ukanwa, University of Southern California
Freyja van den Boom, Bournemouth University
Clémentine Van Effenterre, University of Toronto
Daniel A. Vignon, University of Michigan
Xiaoning Wang, University of Pennsylvania
Thomas J. Weinandy, Western Michigan University
Kathrin Wernsdorf, Munich Graduate School of Economics
Alexander White, Tsinghua University
Nataliya L. Wright, Harvard University
Shunyao Yan, Goethe University Frankfurt
Bo Yang, University of Southern California
Jeremy Z. Yang, Massachusetts Institute of Technology
Matthew R. Yeaton, Columbia University
Helen (Shuxuan) Zeng, Carnegie Mellon University
Georgios Zervas, Boston University
Lingling Zhang, University of Maryland
Walter W. Zhang, University of Chicago
Wei Zhou, University of Arizona
Zhou Zhou, Boston University

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