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Work in Progress


Working Papers (see also at SSRN):

  • “Social Media and Democracy: Experimental Results” (with Freek van Gils and Wieland Müller).
    • Paper_image Social media have become a main source of information for many voters. Political interest groups on social media platforms have the ability to (i) microtarget news based on individual-level voter data and (ii) obfuscate their identities, which can be exploited to spread disinformation. Two proposed interventions to prevent election manipulation by disinformation are a microtargeting ban and disclosure requirements. An empirical foundation for these interventions is missing. We experimentally study the effects of the implementation of a microtargeting ban and disclosure of interests in a social media environment on voting behavior. Our results show that mandatory disclosure of interests, in combination with or without a microtargeting ban, increases the efficiency of aggregate voter decision-making. However, only the combination of disclosure of interests and a microtargeting ban counteracts election manipulation. The implementation of a microtargeting ban without disclosure requirements has adverse effects.
  • How important are user-generated data for search result quality? Experimental evidence” (with Tobias J. Klein, Madina Kurmangaliyeva, and Patricia Prüfer); previous versions dissemniated as CCP Working Paper No. 22-07, TILEC Discussion Paper No. 2022-016.
    • Paper_image Do some search engines produce better search results because their algorithm is better, or becausethey have access to more data from past searches? We document that the algorithm of a small search engine can produce non-personalized results that are of similar quality to the dominant firm’s (Google), if it has enough data, and that overall differences in the quality of search results are explained by searches for rare queries. This is confirmed by results from an experiment, in which we keep the algorithm of the search engine fixed and only vary the amount of data it uses as an input. Because 74% of the traffic in our data come from rare queries, these are the pivotal dimension of competition, where a search engine must perform well to offer users high quality and gain market share. Our results suggest that a small search engine would be able to produce search results that are of similar quality as Google’s, if it had access to the data users generated by using Google in the past. We discuss why data sharing may increase innovation here.
  • The Nonprofit’s Dilemma” (with Yilong Xu); TILEC Discussion Paper No. 2021-012, CentER Discussion Paper No. 2021-021.
    • Paper_image Nonprofit firms producing services that are of broad public concern — mission-driven organizations — pay lower wages and often use low-powered incentive schemes, which has been explained by binding financial constraints and the threat to attract wrong worker types if wages are increased. Yet, they face higher labor turnover than for-profit firms, which is very costly. We construct a simple model that reproduces these stylized facts, explains the high labor turnover of mission-driven organizations, and suggests a way out of this nonprofit’s dilemma, based on insights from the economic psychology literature. We construct testable empirical hypotheses and offer managerial and policy implications.
  • Big Data and Democracy” (with Freek van Gils and Wieland Müller); TILEC Discussion Paper No. 2020-003, CentER Discussion Paper No. 2020-011.
    • Paper_image Recent technological developments have raised concerns about threats to democracy because of their potential to distort election outcomes: (a) data-driven voter research enabling political microtargeting, and (b) growing news consumption via social media and news aggregators that obfuscate the origin of news items, leading to voters’ unawareness about a news sender’s identity. We provide a theoretical framework in which we can analyze the effects that microtargeting by political interest groups and unawareness have on election outcomes in comparison to “conventional” news reporting. We show which voter groups suffer from which technological development, (a) or (b). While both microtargeting and unawareness have negative effects on voter welfare, we show that only unawareness can flip an election. Our model framework allows the theory-based discussion of policy proposals, such as to ban microtargeting or to require news platforms to signal the political orientation of a news item’s originator.

Work in Progress:

  • “Clash of Classification Institutions” (with Gillian Hadfield and Vatsalya Srivastava)
    • Classification institutions assign a normative label, acceptable or wrongful, to human behavior: laws, social norms, religious rules, cultural traditions, etc. Thereby they shape the expectations about other people’s behavior, reduce uncertainty, and create trust in other’s actions. We construct a dynamic model where two classification institutions with different enforcement mechanisms, social norms and legal order, clash. We show how laws crowd out norms, and when and how norms decay gradually, where more and more players first stop enforcing and then stop complying with the norm as time proceeds. We also show that the existence of legal order can undermine norms, even if legal order cannot enforce its own laws very effectively. In such a case, players may rationally ignore the classification of both norms and laws and engage in novel behavior, implying the breakdown of both governance mechanisms. Finally, we apply the model to issues of immigration, developing countries and colonization, former Soviet republics, failed states, and how to organize a multicultural society.
  • “Classification Through Thick and Thin: Permissive Norms and Strict Laws” (with Gillian Hadfield and Vatsalya Srivastava)
  • “The Proper Scope of Government in Hospitals” (with Lapo Filistrucchi and Phuc Phung)
  • “A Test for Data-Drivenness of Markets” (with Tobias Klein, Madina Kurmangaliyeva, and Patricia Prüfer)
  • “Economic Governance and Institutional Design”
  • “Collusion and Communication” (with Cedric Argenton and Wieland Müller)

Retired/Dormant Papers:

  • Innovation Contests

    An earlier version was formerly distributed under the title “Semi-Public Competitions”; CentER Discussion Paper, No. 2009-33; TILEC Discussion Paper, No. 2008-023.

    • Paper_image The process of innovation is driven by two main factors: new inventions and institutions supporting the transformation of inventions into marketable innovations. This paper studies such an institution, called an innovation contest, and shows that it can mitigate a dilemma on the market for ideas. The sponsor of an innovation contest publicizes the ranking of winners, which motivates entrepreneurs to participate in the contest. But information about losers remains private with the sponsor. This allows him to place better informed bids on valuable losers’ projects. Efficiency increases because both entrepreneurs and investors have better incentives to enter the market.
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