Research Fields
The economics of networks, Experimental and behavioral economics, Labor economics, Finance
Papers
Job market paper and working papers
The effect of networks on cooperation in the finitely repeated prisoner’s dilemma (Job Market Paper)
I discuss the effect of networks on cooperation in the finitely repeated prisoner’s dilemma using three approaches: the game-theoretical model approach, the belief-based learning model approach, and the experimental approach. (1) The game-theoretical model consists of two games: the simple repeated PD (prisoner’s dilemma) game for finite rounds and the repeated PD game on a network after the simple repeated PD game. In the repeated PD game on a network, players choose their game partners who can be neighbors on a network based on mutual consent. I find the subgame perfect pairwise-Nash equilibria in which all players defect and are completely connected or isolated. (2) The belief-based learning model allows updating players’ strategies by learning opponents’ strategies so that it explains the cooperative actions not explained by the game-theoretical model but observed in the experiments. My learning model shows that the strategies based on excluding defectors in network formation drive cooperation. (3) I examine the effect of networks on cooperative actions in human groups in the finitely repeated PD using three game experiments: the simple repeated game, the cheap talk repeated game, and the networked repeated game. First, the average cooperation rate in the networked repeated game is the highest among the three games. Second, the network formation in the networked repeated game is associated with increased cooperation. Finally, cooperators (defectors) are connected with other cooperators (defectors) in the network, and cooperation can be achieved by connections among cooperators who exclude defectors from the network.
Analysis of international migration using a network approach: How is it different from international tourism?
In this paper, I discuss the characteristics of international migration and tourism using a network approach. I identify the characteristics of international migration by comparing them with international tourism. International migration networks have shown quite stable structural properties as time passes. The migration networks are regressed on several explanatory factors to identify the relationship between the formation of international migration networks and many factors driving migration. The explanatory variables in my models are classified into two categories: non-network structural and network structural variables. Social, economic, distance, language, safety, and climate change factors are non-network structural variables. I consider the community structure, in-degree, betweenness, and closeness centralities. Migration to wealthy, economically equal, and safe countries for investment is significantly observed. Migration to escape climate change is not significant for now, but the result shows the future negative impact of climate change on international migration. The international tourism networks show quite different characteristics from the migration networks. International tourism networks have been denser as time passes, contrary to international migration networks. Tourism for consumption, not investment, is significantly observed. The betweenness centrality of a destination country and the community structure are strongly tied to forming international migration and tourism networks. Migration and tourism to linguistically similar and shorter in distance countries have been observed.
Measuring systemic risk in the US stock market using a network approach
In this paper, I suggest a novel systemic risk measure using a network approach. I construct stock networks using the Minimum Spanning Tree (MST) based on the Pearson and Spearman rank correlation matrices of stock returns listed in S & P 500. I use two network centralities which I suggest as another factor to explain the risk-adjusted volatilities of stocks, which is unexplained by the Fama-French five factors and the momentum factor, to quantify connectedness among stocks: the degree based on direct connections among stocks and the community’s influence strength based on indirect connections in communities, detected by modularity maximization. The statistical and dynamic properties of network centralities for the Pearson and Spearman rank correlation matrices are almost identical, and stocks in similar industry sectors are in the same community for both correlation matrices. Systemic risk is defined by multiplying the risks due to direct and indirect connections among stocks without a particular assumption of the return distribution. An increase in systemic risk is observed in the US financial recessions: the recession after the dot-com bubble and the subprime mortgage crisis.
The effect of networks on cooperation in the finitely repeated prisoner’s dilemma (Job Market Paper) [Appendix]
Appendix for the effect of networks on cooperation in the finitely repeated prisoner’s dilemma
Publications
1. K. Yim, G. Oh, S. Kim, Understanding Financial Market States Using an Artificial Double Auction Market. PLoS ONE 11(3): e0152608. doi:10.1371/journal.pone.0152608 (2016)
2. H. Kim, K. Yim, S. Kim, G. Oh, Nonlinear properties of the Korea fund market. Journal of the Korean Physical Society 67(12), 2039-2044 (2015)
3. K. Yim, G. Oh, S. Kim, An analysis of the financial crisis in the KOSPI market using Hurst exponent. Physica A 410, 327-334 (2014)
4. JG. Ha, K. Yim, S. Kim, & WS. Jung, Entropy analysis in foreign exchange markets and economic crisis. Journal of the Korean Physical Society, 61(4), 638-646 (2012)