Jihye Jeon Headshot

I am a PhD candidate in Economics at New York University Stern School of BusinessMy primary research fields are Industrial Organization and Applied Microeconomics with a focus on information and firm dynamics. 

I am on the job market and will be available for interviews at the 2017 AEA annual meeting in Chicago.

Email: jjeon@stern.nyu.edu
New York University
Stern School of Business
44 West 4th Street
New York, NY 10012

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Working Papers

Learning and Investment under Demand Uncertainty in Container Shipping (Job Market Paper)

Abstract: This paper develops a dynamic oligopoly model of investment to investigate how firms invest under demand fluctuations and what drives boom-and-bust cycles of investment. I depart from the standard assumption that firms know the true model of demand and its parameters. Instead, I allow firms to form and revise expectations about demand based on information available at each decision-making moment. I estimate the model using firm-level data from the container shipping industry. Results show that a model with learning successfully predicts the boom-bust investment patterns observed in the data, while a full-information model fails to do so. Counterfactual experiments reveal that (i) strategic incentives play an important role in creating oversupply, as well as increasing the volatility of investment; (ii) scrapping subsidies can reduce excess capacity but cause a loss in consumer surplus; and (iii) under learning higher demand volatility  leads to more drastic revisions of beliefs, which amplifies investment boom-bust cycles. I show that the regulator's modeling choice for firms' expectations has important policy implications, namely in merger evaluation. 


The Competitive Effects of Information Sharing (with John Asker, Chaim Fershtman, and Ariel Pakes)

Abstract: We investigate the impact of information sharing between rivals in a dynamic auction with asymmetric information. Firms bid in sequential auctions to obtain  inputs.  Their inventory of inputs, determined by the results of past auctions, are privately known state variables that determine bidding incentives.  The model is analyzed numerically under different information sharing rules. The analysis uses the restricted experience based equilibrium concept of Fershtman and Pakes (2012) which we refine to mitigate multiplicity issues. We find that increased information about competitors' states increases participation and inventories, as the firms are more able to avoid the intense competition in low inventory states. While average bids are lower, social welfare is unchanged and output is increased. Implications for the posture of antitrust regulation toward information sharing agreements are discussed.