• Evaluating Search Cost Models: Estimation and Prediction
- Author(s)
- Simon Martin, Adrian Düll, Heiko Karle, Heiner Schumacher
- Abstract
The classic search models assume that consumers adhere to a particular method of search
(sequential or non-sequential) and that they know the true price distribution. In this paper,
we evaluate how well the search cost estimates from classic models predict search out-
comes – the amount of search and purchase prices – when these assumptions are violated.
To this end, we conduct an online experiment in which we vary searchers’ information
about the price distribution of a homogeneous good. For each treatment, we (i) estimate
search costs, (ii) fit each model to the estimated search cost distribution to obtain in-
and out-of-sample predictions about outcomes, and (iii) compare predicted and realized
outcomes. We find that the prediction performance of each model is largely robust to
violations of the informational assumption. Further, the prediction performance of the
sequential and non-sequential search model are similar, despite the fact that the search
environment strongly favors sequential search.- Organisation(s)
- Department of Economics
- External organisation(s)
- Leopold-Franzens-Universität Innsbruck, Frankfurt School of Finance & Management, Katholieke Universiteit Leuven
- No. of pages
- 77
- Publication date
- 2025
- Austrian Fields of Science 2012
- 502013 Industrial economics
- Keywords
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/cfd3a97a-217e-4e80-b150-00075cbb91b0