Publications
- Complementarities between algorithmic and human decision-making: The case of antibiotic prescribing (Open Access), with Michael A. Ribers, Quantitative Marketing and Economics, forthcoming.
Supersedes “Machine learning and physician prescribing: a path to reduced antibiotic use” and “Battling antibiotic resistance: can machine learning improve prescribing?”Columns: DIW Weekly Report 19/2019 (in English), DIW Wochenbericht 19/2019 and Oekonomenstimme (in German).
AI-generated podcast (by Google’s NotebookLM)
- Provider effects in antibiotic prescribing: Evidence from physician exits (Open Access), with Shan Huang, Journal of Human Resources, forthcoming.
Column (in German): DIW Wochenbericht 38/2024. In the press: Dagens Medicin (in Danish)
- Assessing the value of data for prediction policies: The case of antibiotic prescribing (Open Access), with Shan Huang and Michael A. Ribers, Economics Letters, Vol. 213, 110360, 2022.
Column (in German): DIW Wochenbericht 13-14/2021.
- Career prospects and effort incentives: evidence from professional soccer, with Jeanine Miklós-Thal, Management Science, Vol. 62(6), pp. 1645-1667, 2016. Last working paper version. Online Appendix: Download. Reprinted in Learning in Labour Markets, edited by Michael Waldman, Edward Elgar Publishing, Cheltenham, 2017.
Column (in German): ZEW News 9/2009.
- Belief precision and effort incentives in promotion contests, with Jeanine Miklós-Thal, Economic Journal, Vol. 125(589), pp. 1952-1963, 2015. Last working paper version.
- Regulation of pharmaceutical prices: evidence from a reference price reform in Denmark, with Ulrich Kaiser, Susan Mendez, and Thomas Rønde, Journal of Health Economics, Vol. 36, pp. 174-187, 2014. Last working paper version.
Column (in German): DIW Wochenbericht 14/2014.
Working Papers
- Machine predictions and human decisions with variation in payoffs and skill: the case of antibiotic prescribing, with Michael A. Ribers, Berlin School of Economics Discussion Paper Nr. 27 (download pdf). Revise and resubmit at Journal of the European Economic Association.
We analyze how machine learning predictions may improve antibiotic prescribing in the context of the global health policy challenge of increasing antibiotic resistance. Estimating a binary antibiotic treatment choice model, we find variation in the skill to diagnose bacterial urinary tract infections and in how general practitioners trade off the expected cost of resistance against antibiotic curative benefits. In counterfactual analyses we find that providing machine learning predictions of bacterial infections to physicians increases prescribing efficiency. However, to achieve the policy objective of reducing antibiotic prescribing, physicians must also be incentivized. Our results highlight the potential misalignment of social and heterogeneous individual objectives in utilizing machine learning for prediction policy problems.
- Returns to data: evidence from web tracking, with Luis Aguiar, Tomaso Duso, Jonas Hannane, and Christian Peukert, DIW Discussion Paper Nr. 2091 (download pdf).
Column (in German): DIW Wochenbericht 27/2023. Media coverage in taz, Table.Media, finanzen.net, and ntv (in German).
AI-generated podcast (by Google’s NotebookLM)
Tracking online user behavior is essential for targeted advertising and is at the heart of the business model of major online platforms. We analyze tracker-specific web browsing data to show how the prediction quality of consumer profiles varies with data size and scope. We find decreasing returns to the number of observed users and tracked websites. However, prediction quality increases considerably when web browsing data can be combined with demographic data. We show that Google, Facebook, and Amazon, which can combine such data at scale via their digital ecosystems, may thus attenuate the impact of regulatory interventions such as the GDPR. In this light, even with decreasing returns to data small firms can be prevented from catching up with these large incumbents. We document that proposed data-sharing provisions may level the playing field concerning the prediction quality of consumer profiles.
- Facebook shadow profiles, with Luis Aguiar, Christian Peukert, and Maximilian Schaefer, DIW Discussion Paper Nr. 1998 (download pdf).
Column (in German): DIW Wochenbericht 29-30/2022. Media coverage in Tagesspiegel, Der Standard, Kronenzeitung, Heise, PC-Welt, BR, and Computerwoche podcast (in German).
We quantify Facebook’s ability to build shadow profiles by tracking individuals across the web, irrespective of whether they are users of the social network. For a representative sample of US Internet users, we find that Facebook is able to track about 40% of the browsing time of both users and non-users of Facebook, including on privacy-sensitive domains and across user demographics. We show that the collected browsing data can produce accurate predictions of personal information that is valuable for advertisers, such as age or gender. Because Facebook users reveal their demographic information to the platform, and because the browsing behavior of users and non-users of Facebook overlaps, users impose a data externality on non-users by allowing Facebook to infer their personal information.
We analyze the effects of a hypothetical payment card fee regulation on bank profits, consumer welfare, and merchant welfare. We model consumers’ and merchants’ bank choices for debit card services, cardholders’ demand for card usage (conditional on bank choice), and how banks account for these in setting card fees to their customers. To estimate the model, we use bank-level data and survey data from the Norwegian debit card scheme, BankAxept. We conduct counterfactual exercises to analyze the effects of interchange fee regulations in the debit card scheme.
- A note on regressions with interval data on a regressor, with Daniel Cerquera and Francois Laisney. Online Appendix: Download
Former title: Considerations on partially identified regression models, Centre for European Economic Research Discussion Paper 2012-024, BETA (Bureau d’Economie Théorique et Appliquée) Working Paper No. 2012-07, Online Appendix: Download
- Consumer welfare and unobserved heterogeneity in discrete choice models: the value of Alpine road tunnels, with Daniel Cerquera, Centre for European Economic Research Discussion Paper 2010-095
Work in progress
- Career concerns and managerial risk taking: evidence from the NFL, with Paul Bose and Florian Schütt
- The causal effect of antibiotic prescribing on population antibiotic resistance, with Shan Huang, Michael Allan Ribers, Barbara Juliane Holzknecht, Jonas Bredtoft Boel, Jette Brommann Kornum, and Michael Pedersen
- Competitive pressure and antibiotic prescribing in primary care, with Temulun Borjigen
My research repositories and social media profiles