Lecture on "Nonparametric Identification of k-Double Auctions Using Price Data"
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Lecture on "Nonparametric Identification of k-Double Auctions Using Price Data"
DateandTime: 2017-03-23 21:15:00

Speaker: Li Huihui, Assistant Professor, the Wang Yanan Institute for Studies in Economics, Xiamen University

Date: March 23, 2017

Time: 2:30 pm- 4:00 pm

Location: B423 Juxian Hall, Zhixin Building, Central Campus

Sponsor: the School of Economics


Abstract:

This paper studies the model identification problem of k-double auctions between one buyer and one seller when the transaction price, rather than the traders' bids, can be observed. Given that only the price data is available, I explore an identification strategy that utilizes the double auctions with extreme pricing weight (k = 1 or 0) and exclusive covariates that shift only one trader's value distribution to identify both the buyer's and the seller's value distributions nonparametrically. First, as each exclusive covariate can take at least two values, the buyer's and the seller's value distributions are partially identified from the price distribution for k = 1 or k = 0. The identified set is sharp and can be easily computed. I provide a set of sufficient conditions under which the traders' value distributions are point identified. Second, when the exclusive covariates are continuous, it is shown that the buyer's and the seller's value distributions will be uniquely determined by a partial differential equation that only depends on the price distribution, provided that the value distributions are known for at least one value of the exclusive covariates.


Bio:

Dr. Li Huihui completed his Ph.D. from Pennsylvania State University in 2016. He is currently assistant professor of Wang Yanan Institute for Studies in Economics (WISE) and School of Economics, Xiamen University. His main research interests include Econometrics, Industrial Organization and Applied Microeconomics. He has published in top journals such as China Economic Journal, Economic and Social Development.


For more information, please visit:

http://www.view.sdu.edu.cn/new/2017/0321/89029.html


Edited by: Liu Huan




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