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Internet auctions have recently gained widespread popularity and are one of the most suc-cessful forms of electronic commerce. We examine a dataset of eBay coin auctions to explore features of online bidding and selling behavior. We find that profit margins for bidders appear to be slim on average, that previous bidding experience does not play a significant role in ob-served bidding behavior and that bidding activity is concentrated at the end of the auction. We then develop new econometric techniques to estimate a structural model of bidding to address three main issues. First, we measure the extent of the winner's curse. We find that for a representative auction in our sample, a bidder's expected profits fall by 3.2 percent when the expected number of bidders increases by one. Second, we document that costly entry is a key component in understanding observed bidding behavior. For a representative auction in our sample, a bidder requires $3.20 of expected profit to enter the auction. Third, we study the seller's choice of reserve prices. We find that items with higher book value tend to be sold using a secret reserve price with a low minimum bid. We find that this is, to a first approximation, consistent with maximizing behavior.