Publications

Working papers

• Do I Really Want to Buy This? Preference Discovery and Consumer Search. Joint with Tobias Klein and Christoph Walsh. [PDF]
  • One of the most invoked assumptions in economics is that consumers know their preferences when making choices. Although theories and experiments in psychology and behavioral economics suggest that this may be unrealistic, there is relatively little evidence from the field on this question. In this paper, we use detailed clickstream data from a large Central Asian online platform to study the extent to which consumers learn about their preferences while searching for a smartphone. To quantify the speed at which this takes place and account for other factors, most notably that consumers obtain additional product information when they inspect product pages, we estimate a rich search model in which consumers learn about their willingness to pay each time they visit the checkout page. Consumers initially underestimate their price sensitivity and update it along the way. Taking this into account shows that consumers are more price sensitive than a standard search model would predict, and an intervention that prompts consumers to end their search early can lead to potential welfare loss.
  • Selected presentations: SEG Tilburg, Workshop on Digital Markets 2024
• Flexible Use of Sequential Search Data: A Partial Ranking Structure. (Draft on Request) Slides
  • Sequential search data has become increasingly important in economics and market research. However, the existing structure based on Weitzman’s (1979) Optimal Search Rules provides limited support for empirical study, making researchers struggle between using search data with a high computation burden or discarding them completely. This paper reformulates the solution of optimal sequential search with a partial ranking structure, establishing a fully static relationship among product values. This simplifies the model’s empirical application while preserving complete search information. With the new structure, I discuss the identification arguments and estimation implementation. I show its flexibility in handling scenarios with partial search information, additional ranking information, and structural changes within the search process (e.g., search and product discovery) with low computational cost.
  • Selected presentations: SEG Tilburg

Work in Progress

• Endogenous Search.
  • Consumers typically search to resolve product uncertainty under imperfect information before purchase. Beyond product attributes and search costs, consumers’ search decisions are generally assumed to be driven by unobserved pre-search taste, often considered independent of other product characteristics. However, the assumption of independence in pre-search taste remains unverified. Consumers may perceive a correlation between price and unknown quality information, introducing endogeneity between search decisions and product prices beyond their inherent preferences. This relationship can bias the estimation of consumers’ search behavior. Building on the decomposition of joint probabilities in the search process from my previous paper, I developed an estimation method with the potential to address this issue.