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Myong-Hun Chang

Professor of Economics

Deparment of Economics
Cleveland State University
2121 Euclid Avenue, RT1719
Cleveland, OH 44115-2214

B.S., Cornell University, 1984
M.A., Johns Hopkins University, 1987
Ph.D., Johns Hopkins University, 1988


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Myong-Hun Chang is Professor and Chair of the Economics Department at Cleveland State University. He studied Operations Research & Industrial Engineering as an undergraduate at Cornell University.  Upon graduating with a B.S. in 1984, he entered the graduate program in Economics at The Johns Hopkins University, earning a Ph.D. in 1988.  His primary research interests are in industrial Organization, organization theory, and game-theoretic and computational modeling of complex social and economic systems. In addition to Cleveland State University, he has taught at The Johns Hopkins University and the Owen Graduate School of Management at Vanderbilt University as a visiting faculty.

His current research projects include the following:

  1. Industry Dynamics: The objective of this project is to build a computational model of industry evolution which has the capacity to generate a large number of empirical regularities, and is rich enough to allow extensive comparative dynamics analyses involving various industry-specific factors. The model has evolved through several generations of earlier primitive versions. The very first version focused solely on the shakeout dynamics in an infant industry with no external technological shocks. The results from this preliminary version were published in Journal of Economic Interaction and Coordination (2009). The second version allowed for external technological shocks but with no adaptive R&D by the firms. The results from this model were reported in a chapter in Oxford Handbook of Computational Economics and Finance (forthcoming). The third version of the model with exogenously specified R&D by firms was presented in Eastern Economic Journal (2011: a symposium issue on Agent-based Computational Economics). The most general version of this line of models is presented in a forthcoming book, A Computational Model of Industry Dynamics (Routledge). This model allows firms to adapt to external technological shocks by autonomously performing R&D in search of improved technologies.
  2. Corporate Leniency Program and Cartels: In this project, Joseph E. Harrington, Jr. (Wharton - University of Pennsylvania) and I look at the impact the corporate leniency program has on the formation and sustainability of cartels in a population of industries. The ultimate objective is to evaluate the effectiveness of the program using a computational model in which the births and deaths of the cartels are fully endogenized. The base model involving a population of heterogeneous industries was presented in an analytical paper published in a recent issue of Journal of European Economic Association (2009).
  3. Endogenous Social Networks: This project investigates the dynamic structure and performance of social networks that emerge endogenously in a population of adaptive agents, when they are engaged in the process of discovery through innovation and imitation.  Various results from this line of research have been reported in American Journal of Sociology (2005), Organization Science (2007), Advances in Complex Systems (2011), and Administrative Sciences (2013).
  4. Organizational Structure: This research examines how the design of coordination and communication structures influences the dynamics of individual and social learning in complex organizational systems. Recent work in this line explored the impact of centralization and decentralization on the performance of co-evolving multi-unit business firms in a competitive environment.  The outcomes of this project have been published in a number of refereed journals, including Computational and Mathematical Organization Theory (1997), Management Science (2000, 2003), and Journal of Economic Dynamics and Control (2005). This project has evolved into an on-going project which explores the role of communication and information processing in endogenous hierarchies.

All of these research efforts employ game-theoretic and/or agent-based computational modeling techniques.  His research on organizations and the related literature are surveyed in a co-authored chapter in Handbook of Computational Economics II: Agent-Based Computational Economics (edited by Leigh Tesfatsion and Ken Judd).