• Graduate program
    • Why Tinbergen Institute?
    • Program Structure
    • Courses
    • Course Registration
    • Recent PhD Placements
    • Facilities
    • Admissions
  • Research
  • News
  • Events
    • Summer School
      • Crash Course in Experimental Economics
      • Introduction in Genome-Wide Data Analysis
      • Research on Productivity, Trade, and Growth
      • Econometric Methods for Forecasting and Data Science
  • Times

Moraga-González, J. and Wildenbeest, M. (2008). Maximum likelihood estimation of search costs. European Economic Review, 52(5):820-848.


  • Journal
    European Economic Review

In a recent paper Hong and Shum [2006. Using price distributions to estimate search costs. Rand Journal of Economics 37, 257-275] present a structural method to estimate search cost distributions. We extend their approach to the case of oligopoly and present a new maximum likelihood method to estimate search costs. We apply our method to a data set of online prices for different computer memory chips. The estimates suggest that the consumer population can be roughly split into two groups which either have quite high or quite low search costs. Search frictions confer a significant amount of market power to the firms: Despite more than 20 firms operating in each of the markets, we estimate price-cost margins to be around 25{%}. The paper also illustrates how the structural method can be employed to simulate the effects of the introduction of a sales tax.