Modeling Online Auction Prices And Their Dynamics Using Functional Data Analysis

Abstract

Online auctions have become increasingly popular in recent years, and as a consequence, there is a growing body of emphirical research on this topic. Most of that research treats data from online auctions as cross-sectional and consequently, ignores the changing dynamics that occurs during an auction. In this work, we take a different look at online auctions and propose to study an auction's price evolution and associated price dynamics. Specifically, we develop a model to study factors that affect formation of price in an auction. Modeling price and its dynamics in online auctions is challenging because traditional methods cannot adequately account for two features of online auction data: (1) the unequal spacing of bids and (2) the changing dynamics of price and bidding throughout the auction. Our model accounts for these special features by using modern functional data analysis techniques. Our analysis suggests that the opening bid positively affects online auction price level of PDA at the beginning of the auction and its effect declines toward the end of the auction. Key words and phrases: Functional regression analysis, spline smoothing, eBay,

online auction, auction dynamics, price evolution.