Abstract
Many studies have examined how various factors affect prices in online auctions. These studies assume that the relationship between price and the seller's reputation take a variety of functional forms, most frequently linear or linear-log. Others divide the sellers into categories by their reputations, and control for dummy variables indicating the seller's category. Identifying the correct functional form is a critical issue for research on any topic involving online auctions. Studies that assume the wrong functional form run the risk of generating biased and inconsistent estimates of the effect of their variables of interest. In this study, the price-reputation relationship is estimated under each of these functional forms using data from auctions of three different products. The estimated effect of reputation on price is substantially larger when using a categorical specification. The models are then subjected to specification tests which suggest that the categorical model is the most appropriate choice.
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