Climate Policy Commitment Devices (with R. Gerlagh, S. Trautmann, G. v.d. Kuilen)
Journal of Environmental Economics & Management, 92 (Nov 2018), p. 331-343
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 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 conditions to assess the underlying social preferences and the viability of ecological dictatorship. Our results suggest that climate change policies that focus on investments that lock the economy into carbon-free energy sources provide an important commitment device in the intertemporal cooperation problem.
Keywords: Climate Policy Instruments, Intertemporal Cooperation, Climate Game, Experiments
JEL Codes: C91, D62, D99, Q38, Q54
Recent progress in information technologies provides sellers with detailed knowledge about consumers’ preferences, approaching perfect price discrimination in the limit. We construct a model where consumers with less strategic sophistication than the seller's pricing algorithm face a trade-off when buying. They choose between a direct, transaction cost-free sales channel and a privacy-protecting, but costly, anonymous channel. We show that the anonymous channel is used even in the absence of an explicit taste for privacy if consumers are not too strategically sophisticated. This provides a micro-foundation for consumers’ privacy choices. Some consumers benefit but others suffer from their anonymization.
Keywords: Privacy, Big Data, Perfect Price Discrimination, Level-k thinking
JEL Codes: L11, D11, D83, D01, L86
A brief summary of this 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".
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