NBER

Ying Fan

Department of Economics
University of Michigan
611 Tappan Street
Ann Arbor, MI 48109
Tel: 734/763-3096

E-Mail: EmailAddress: hidden: you can email any NBER-related person as first underscore last at nber dot org
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NBER Program Affiliations: IO
NBER Affiliation: Faculty Research Fellow
Institutional Affiliation: University of Michigan

NBER Working Papers and Publications

May 2020Heterogeneous Actions, Beliefs, Constraints and Risk Tolerance During the COVID-19 Pandemic
with A. Yeşim Orhun, Dana Turjeman: w27211
During a pandemic, an individual's choices can determine outcomes not only for the individual but also for the entire community. Beliefs, constraints and preferences may shape behavior. This paper documents demographic differences in behaviors, beliefs, constraints and risk preferences across gender, income and political affiliation lines during the new coronavirus disease (COVID-19) pandemic. Our main analyses are based on data from an original nationally representative survey covering 5,500 adult respondents in the U.S. We find substantial gaps in behaviors and beliefs across gender, income and partisanship lines; in constraints across income levels; and in risk tolerance among men and women. Based on location data from a large sample of smartphones, we also document significant differen...
July 2019Firms and Collective Reputation: a Study of the Volkswagen Emissions Scandal
with Ruediger Bachmann, Gabriel Ehrlich, Dimitrije Ruzic: w26117
This paper uses the 2015 Volkswagen emissions scandal as a natural experiment to provide evidence that collective reputation externalities matter for firms. We find that the Volkswagen scandal reduced the U.S. sales of the other German auto manufacturers—BMW, Mercedes-Benz, and Smart—by about 105,000 vehicles worth $5.2 billion. The decline was principally driven by an adverse reputation spillover, which was reinforced by consumer substitution away from diesel vehicles and was partially offset by substitution away from Volkswagen. These estimates come from a model of vehicle demand, the conclusions of which are also consistent with difference-in-differences estimates. We provide direct evidence on internet search behavior and consumer sentiment displayed on social media to support our inte...

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