Conference Agenda

Tips to navigate the program:

  • Overview of all papers on a specific day: click on the day (e.g. Date: Thursday, 24/Aug/2017). To download papers, you will need to access the session by clicking on its title first.
  • Program index: click on the Authors tab below.
  • Location name: to display all sessions taking place in that room
  • Search box: to search for authors, papers and sessions.

Please notes that changes in the program might occur.

If your name is not displayed in the program, please register in our conference system.

If your paper information is not up to date, please send us an email at

Session Overview
APT-3: Market Structure, Information, and Learning
Friday, 25/Aug/2017:
8:30am - 10:00am

Session Chair: Ioanid Rosu, HEC Paris
Location: O135

Show help for 'Increase or decrease the abstract text size'

Information and Competition with Symmetry

Pete Kyle1, Mina Lee2

1University of Maryland; 2Washington University in St. Louis

Discussant(s): Gyuri Venter (Copenhagen Business School)

This paper investigates the strategic foundations for rational expectations equilibrium. In the model, risk-averse traders with two signal - private information and endowment shocks - submit demand schedules to trade a risky asset. Traders are divided into groups. Within groups, traders share common signals; signals are different across different groups. Either traders become price takers or the price becomes fully revealing, but not both, as the number of competitors per group goes to infinity. As the number of groups goes to infinity, neither price taking nor fully revealing prices are obtained. Measuring competition by the quantity traded as a fraction of that traded by a price-taker, we show that optimal exercise of market power has opposite implications for competition and price informativeness.

EFA2017-1847-APT-3-Kyle-Information and Competition with Symmetry.pdf

How Auctions Amplify House-Price Fluctuations

Alina Arefeva

Johns Hopkins University

Discussant(s): Christophe Spaenjers (HEC Paris)

I develop a tractable dynamic model of the housing market where the prices are determined in auctions rather than by Nash bargaining as in the housing search model from the literature. The model with auctions mimics the actual housing markets by generating fluctuations between the booms and busts. During the boom multiple buyers compete for each house, while in the bust buyers are choosing between several available houses. The model produces highly volatile house prices, improving on the benchmark housing search model and helping to solve the puzzle of excess volatility of house prices. This high volatility arises in the auction model because of the competition between buyers with heterogenous values. With heterogenous values, the method of choosing the buyer among all the interested buyers becomes important for the quantitative properties of the model. In the benchmark model with Nash bargaining, the buyer is chosen randomly among all interested buyers. Then the average of buyers' house values determines the house price. In the auction model the buyer is chosen by the maximum bid among all interested buyers, so the highest value determines the house prices. During the housing booms, the highest values increase more than the average values, making the sales price more volatile. This high volatility is efficient, since the equilibrium in the model decentralizes the solution of the social planner problem, constrained by the search frictions.

EFA2017-1407-APT-3-Arefeva-How Auctions Amplify House-Price Fluctuations.pdf

Learning Through Crowdfunding

Katrin Tinn, Gilles Chemla

Imperial College Business School

Discussant(s): Daniel Schmidt (HEC Paris)

This paper examines the role of reward-based crowdfunding in learning about demand and improving investment decisions. The information gathered while raising funds from consumers provides firms with a real option to invest if demand is sufficiently high. Despite moral hazard problems stemming from the firms' ability to divert the funds raised, all-or-nothing schemes are nearly as efficient as frictionless surveys and full money-back guarantees. Dominant platforms adopt features such as limited campaign length and transparency between backers, which are essential to overcome moral hazard. Our results are consistent with stylized facts and provide new testable implications.

EFA2017-1547-APT-3-Tinn-Learning Through Crowdfunding.pdf

Contact and Legal Notice · Contact Address:
Conference: EFA 2017
Conference Software - ConfTool Pro 2.6.109+TC
© 2001 - 2017 by H. Weinreich, Hamburg, Germany