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This study provides an alternative approach that takes account of the unobserved effects of each seller under a sample selection framework while using online auction data. We use data collected from Yahoo! Kimo Auction (Taiwan) to demonstrate that earlier empirical results of online auction studies may be biased due to violating the assumption of independence of the error terms between sample observations. Empirical findings show that seller reputation is no longer as the most important factor for buyers to bid on items, while the sample data confirm the unobserved heterogeneity of sellers and sample selection problem. [ABSTRACT FROM PUBLISHER]

This paper explores how seller reputation affects auction prices using detailed Taiwanese data. Our empirical results show that returns to reputation are nonlinear and differ considerably across different reputation scores. Marginal returns to scores drop sharply after the first reputation quartile, indicating that building up sellers’ reputation is extremely important, especially in the early stage. Our study reveals that the mechanism of seller reputations is effective in mitigating asymmetric information in online auctions. [ABSTRACT FROM AUTHOR]