PENNIES FROM EBAY: THE DETERMINANTS OF PRICE IN ONLINE AUCTIONS^*

Abstract

This paper presents an exploratory analysis of the determinants of prices in online auctions for collectible United States one-cent coins at the eBay Web site. Starting with an initial data set of 20,000 auctions, we perform regression analysis on a restricted sample of 461 coins for which we obtained estimates of book value. We have three major findings. First, a seller's feedback ratings, reported by other eBay users, have a measurable effect on her auction prices. Negative feedback ratings have a much greater effect than positive feedback ratings do. Second, minimum bids and reserve prices have positive effects on the final auction price. In particular, minimum bids appear only to have a significant effect when they are binding on a single bidder, as predicted by theory. Third, when a seller chooses to have her auction last for a longer period of days, this significantly increases the auction price on average.

On the pricing rule in electronic auctions

“…Before moving on, it will also be useful to define some additional notation. Let the 8 The analysis done in this section extends straightforwardly to the more general case of affiliated private values (APV), where the joint density is log-supermodular and values are correlated. Although this is likely a more realistic model, the notation and derivations under APV are considerably more cumbersome, whereas the special case of IPV allows for a relatively simpler exposition of the main ideas I wish to explore.…”

Econometrics of auctions by least squares

“…To provide a specific example, several studies investigated the importance attributed by consumers to the reputation of sellers in eBay using specifications of this sort (Houser and Wooders, 2000;Lucking-Reiley et al, 2000;McDonald and Slawson, 2002;Melnik and Alm, 2002). The problem with analyses that rely on such specification is not in the right-hand side of regression -covariates may indeed impact consumer preferences in a linear fashion -but rather in the left-hand side.…”

Optimal bidding in online auctions

“…w t = 0 u t > q t h t v t = 1) x t+1 = q t h t+1 = u t (4) w t = 0 u t > h t q t v t = 1) x t+1 = h t h t+1 = u t (5) w t = 0 h t u t q t v t = 1) x t+1 = m a x ( u t x t ) h t+1 = 0 (6) w t = 0 q t h t v t = 0) x t+1 = h t h t+1 = 0 (7) w t = 0 h t q t v t = 0) x t+1 = m a x ( q t x t ) h t+1 = 0 (8) w t = 1 q t u t h t v t = 1) x t+1 = u t h t+1 = 0 (9) w t = 1 u t > q t h t v t = 1) x t+1 = q t h t+1 = u t (10) w t = 1 u t h t > q t v t = 1) x t+1 = m a x ( q t x t ) h t+1 = u t (11) w t = 1 u t > h t q t v t = 1) x t+1 = m a x ( q t x t ) h t+1 = u t (12) w t = 1 q t h t v t = 0) x t+1 = h t h t+1 = 0 (13) w t = 1 h t > q t v t = 0) x t+1 = m a x ( q t x t ) h t+1 = h t (14) Eqs. (1)- (8) are for the case when w t = 0.…”