Consumers' Privacy Choices in the Era of Big Data (with J. Prüfer)
While consumers often feel overwhelmed by the complexity involved in choices regarding personal data, sellers with superior information processing algorithms are enabled to make more tailored offers in times of increasing datafication. We construct a model where consumers are confronted with a seller whose big data algorithms extract surplus via customized pricing. They face a trade-off between a direct, transaction cost-free sales channel and a privacy-protecting, but costly, channel when buying a product. We show that the privacy-protecting channel is used even in the absence of an explicit taste for privacy if consumers are not too strategically sophisticated, thereby providing a micro-foundation for consumers' privacy choices.
Keywords: Privacy, Big Data, Perfect Price Discrimination, Sophistication-k equilibrium
JEL Codes: L11, D11, D83, D01, L86
A summary of my job market paper is featured in the series of guest posts from job market candidates on the website of SIOE: Why you might want to pay for privacy even if you think you have "nothing to hide".
Climate Policy Commitment Devices (with R. Gerlagh, S. Trautmann, G. v.d. Kuilen)
We develop a dynamic resource extraction game that mimics the global multi-generation planning problem for climate change and fossil fuel extraction. We implement the game under different conditions in the laboratory. Compared to a "liberal" baseline condition, we find that policy interventions that provide a costly commitment device or reduce climate threshold uncertainty reduce resource extraction. We also study two ethics conditions to assess the underlying social preferences and the viability of ecological dictatorship. Our results suggest climate-change policies to focus on investments that lock the economy into carbon-free energy sources.
Keywords: Climate Change, Coordination, Laboratory Experiment
JEL Codes: C91, C92 Q54
Work in Progress
Predictive Algorithms and Consumer Behavior
This project investigates how consumers fare when predictive algorithms are not working for, but against them: when they predict not only which product a consumer is interested in, but also how much he or she is willing to pay for it. Developing a laboratory experiment, where subjects can hide their assigned valuation of a good from a computerized seller at a cost, I ask: Do subjects anticipate that hiding their valuation can be exploited in such markets and can their behavior be explained by a limited sophistication model of level-k thinking? Preliminary tests show subjects’ behavior to be inconsistent with unlimited strategic sophistication as the strategic nature of the game seems hard to grasp.
Keywords: Perfect Price Discrimination, Laboratory Experiment, Level-k Thinking
JEL Codes: C91, D84, D03