Projects

Participants: Yeon oh Ji and Semin Kim

Participants: Yeon oh Ji and Semin Kim

Presented at 2023 KAEA Annual Meeting.


Participants: Jiwon Kim, Seongrae Kim, and Chang-Koo Chi

Description: In many economic settings, agents compete by making irreversible investments before the outcome of competition is known. For example, lobbying activities, R&D races, and competition for promotions, all have this property. The all-pay auction has been used to model this type of competition, and the auction differs from standard auctions in one principal respect: all bidders (including losers) forfeit their entire bids. 

In this project, we consider an alternative payment rule that awards the loser (partial) compensation or reward if his costly bid exceeds a pre-specified threshold. This compensation scheme is intended to encourage the participants to bid more aggressively, by providing a partial refund to the loser. We investigate the impact of the payment rule on the contestants' equilibrium strategy and the total amount of bids.
* We initiated the project in the middle of September 2022, and we are currently planning to present our preliminary results in the reading group.    


Participants: Seong Kyun Kim (Ph.d student), Chang-Koo Chi, Jay Pil Choi, Jong-Hee Hahn

Description: When making a purchase decision in today's society, consumers often rely on an intermediary's advice and search results. The intermediary's job is to provide its users relevant information. However, the intermediary does have a clear incentive to bias its advice and steer more consumers towards a particular product (often referred to as self-preferencing). For example, Apple and Google have been accused of privileging their own app developers. There has been vigorous discussion on the issue of whether this kind of practice is anti-competitive and how it should be dealt with, and economists have sharply divided views on self-preferencing. Some economists argue that self-preferencing is detrimental to competition, whereas others argue that it actually strengthens the sellers' incentives to innovate their products. 

To better understand the practice in digital platforms, we build up a simple Hotelling model that allows for one digital platform recommending one of two products to consumers. To be specific, a unit-mass consumers are distributed along the Hotelling line, but when purchasing a product, consumers do not know their exact position; in other words, they have limited information about which product is more suited for themselves and search for the desired product on the platform. On the other hand, the platform is better informed about the consumer's taste (i.e., the value of matching products) and presents each consumer a recommended product. We characterize the search algorithm maximizing the platform's revenue when one seller is vertically integrated with the platform, and examine its impact on consumer surplus.      
* We initiated the project in the middle of August 2022, and early work has been presented at Hokkaido University and 한국계량경제학회.     


Participants: Cho, Hyunjun; Kim, Jin Yeub; and Park, Jaeok


Participants: Ko, Sanghwi; and Park, Jaeok