Curriculum Vitae (pdf) - Southern Illinois University

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REFERENCES Alison Watts, Professor, Department of Economics, SIUC Mail Code 4515, 1000 Faner Drive, Carbondale, IL 62901 Phone: 1-618-453-5072 E-mail: wattsa@siu.edu Chifeng Dai, Associate Professor, Department of Economics, SIUC Mail Code 4515, 1000 Faner Drive, Carbondale, IL 62901 Phone: 1-618-453-5347 E-mail: daic@siu.edu Sajal Lahiri, Professor and Vandeveer Chair, Department of Economics, SIUC Mail Code 4515, 1000 Faner Drive, Carbondale, IL 62901 Phone: 1-618-453-9472 E-mail: lahiri@siu.edu Jason D. Tanner, Ph.D., Professor of Business, Department of Business Education John A. Logan College 700 Logan College Road, Carterville, IL 62918 Phone: 1-618-985-2828 Ext. 8170 E-mail: jasontanner@jalc.edu DISSERTATION OUTLINE “Trade Networks under Asymmetric Information”, Job Market Paper Buyer and seller interactions are analyzed with intermediaries called traders using a network structure. Goods are traded in the market through those networks. Each seller and buyer is linked to a trader through a network but not directly linked to each other. Our main contribution to the literature is that we introduce asymmetric information on the valuation of goods by sellers and buyers. Our model basically consists of a two-stage game with incomplete information. First, the trader offers bid prices to the sellers and ask prices to the buyers. Second, trade takes place when the sellers and/or buyers accept the trader`s offers. The trader tries to maximize his profit. First, we analyze even network structures: one seller-one trader-one buyer and two buyers-one trader-two sellers. Our main finding for the one seller-one buyer network is that the trader never sets the same bid and ask prices to the seller and the buyer, respectively. Another result in the second setting is that the trader sometimes offers different prices to sellers or to buyers when the penalty is almost zero. For the asymmetric network case when one trader is linked to one seller and two buyers, we find that offering the same ask price to both buyers usually yields the maximum expected payoff to the trader. However, when the trader is linked to two sellers and one buyer, we see that that the trader sometimes offers the same price to all three parties to receive the maximum profit. “Multiple Traders’ Networks under Asymmetric Information” In this paper, we allow there to be multiple traders and analyze how buyer and seller prices are influenced by competition among traders in a model of uncertainty. We start by considering a network with one seller, two traders and one buyer. The seller and buyer have strong positions 4
and they both will try to benefit from the competition between the two traders. The traders compete in the sense of a Bertrand duopoly to choose the price where each trader aims to maximize his profit. We also examine different network structures involving two sellers and one buyer with two traders and the network formation with three sellers-two traders-one buyer. We note that the sellers who are not subject to the competition between two traders suffer from the consequences of the monopoly competition. We compute the equilibrium bid and ask prices offered by the traders for all three networks. There will not be one fixed price that the traders offer the seller and buyer both of whom benefit from the competition in the last two network structures. Finally, we look for the maximum expected payoff for each trader by investigating the best responses to the given bid and ask price schedules. We find that one trader’s best responses depend on the conditions on the valuations for the traded good. “Middlemen in the Housing Market: An Application to Trade Networks” Middlemen, either as individuals or realtors, seem to have influential effects on the pricing strategy in the housing market. In this paper, we analyze the contribution of the middlemen in the housing market as an application to trade networks. We work on a specific dataset related to the housing prices for two main neighborhoods in Atlanta, Georgia. The characteristics of those neighborhoods differ in terms of being close to downtown or far from downtown but including mainly high-valued residential houses. We start by examining the returns that individuals who are defined to be intermediaries in the market get during each housing transaction. Finally, we compare and contrast the returns for those two neighborhoods with distinct properties in order to investigate if any of these neighborhoods yield higher returns for the middlemen. 5
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Curriculum Vitae (pdf) - Southern Illinois University

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