This dissertation pursues to find an answer empirically to the question of the
revenue ranking between the multiple price auction and the single price auction. I also
attempt to get empirical clues in terms of the efficiency ranking between the two.
Under the assumptions of symmetric bidders and private independent value (PIV), I
derive the optimal bidding conditions for both auction formats. Following the
structural model estimation approach, I estimate the underlying distribution of market
clearing price using the nonparametric resampling strategy and recover the biddersÂ
unknown true valuations corresponding to each observed bid point. With these
estimated valuations of the bidders, I calculate what the upper bound of the revenue
would have been under the Vickery auction to perform the counterfactual revenue
comparison with the actual revenue. I find that, ex-post, the multiple price auction
yields more revenue to the Korean Treasury than the alternative. I also investigate the
efficiency ranking by comparing the number of bids switched and the amount of
surplus change which would occur when the bidders are assumed to report their true
valuations as their bids. I find that the multiple price auction is also superior to the
alternative in efficiency which supports the current theoretical prediction. Finally, I
investigate the robustness of my model and empirical results by relaxing the previous
assumptions. I, first, extend the model and estimation to the case of asymmetric
bidders where the bidders are divided into two groups based on their size. It shows that
the model and estimation framework are still valid and that the empirical findings are
very similar to the symmetric case. I also test for the presence of common value (CV)
component in the bidders valuation function. I propose the simple regression model
adopting the idea of the policy experimental approach. I obtain quite an inconclusive
result in general but find some evidence supporting PIV for relatively higher bid prices
while supporting CV for lower bid prices.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/3051 |
| Date | 12 April 2006 |
| Creators | Kang, Boo-Sung |
| Contributors | Puller, Steven |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | 930775 bytes, electronic, application/pdf, born digital |
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