Publisher:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft, Kiel und Hamburg
Abstract:
We examine empirically whether individuals evaluating used cars efficiently aggregate all relevant information on its constituent characteristics. Based on detailed field data on more than 80,000 used car offers in a large online marketplace, we provide evidence for biased information processing. While the precise date of first registration, i.e., its "age", is publicly and prominently stated for each car, we identify an amplified value adjustment for otherwise identical cars at year-count changes. These discontinuities indicate that individuals over-react to the figure displayed in the latter, while underrating the finer information on a car's age as conveyed through the month of first registration. Moreover, we are able to replicate the findings from Lacetera et al (2009) and find discontinuous drops in prices at 10,000km odometer thresholds. While the latter finding, as suggested by Lacetera et al (2009), is consistent with a left-digit bias in the processing of numerical information, the first finding cannot be explained by this. Our findings underline that information-processing heuristics matter also in markets with large stakes and easily observed information