Maximum Likelihood Estimation of Search Costs

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.<P>This discussion paper has resulted in a publication in the <A HREF="http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V64-4P59XD2-1&_user=499884&_coverDate=07%2F31%2F2008&_rdoc=4&_fmt=high&_orig=browse&_srch=doc-info(%23toc%235804%232008%23999479994%23691064%23FLA%23display%23Volume)&_cdi=5804&_sort=d&_docanchor=&_ct=8&_acct=C000024499&_version=1&_urlVersion=0&_userid=499884&md5=72c5b07d36fc7bd6459fb38121d60294"><I>European Economic Review</I></A>, 2008, 52(5), 820-48.