An Agent-Based Simulation of the Stolper–Samuelson Effect
- 265 Downloads
We demonstrate that agent-based simulations can exhibit results in line with classic macroeconomic theory. In particular, we present an agent-based simulation of an Arrow–Debreu economy that accurately exhibits the Stolper–Samuelson effect as an emergent property. Absent of a Walrasian auctioneer or any other central coordination, we let firm and consumer agents of different types interact in an open, money-driven market. Exogenous preference shocks result in price and wage shifts that are in accordance with the general equilibrium solution, not only qualitatively but also quantitatively with high accuracy. Key to this achievement are three independent measures. First, we overcome the poor input synchronization of conventional price finding heuristics of firms in agent-based models by introducing sensor prices, a novel approach to price finding that decouples information exploitation from information exploration. Second, we improve accuracy and convergence by employing exponential search as exploration algorithm. Third, we normalize prices indirectly by fixing dividends, thereby stabilizing the system’s dynamics.
KeywordsComputational economics Agent-based economics Price finding Price normalization Sensor prices System dynamics
We would like to thank Johannes Brumm and Gregor Reich for their valuable inputs, Abraham Bernstein for pointing us to system dynamics, Krzysztof Kuchcinski and Radoslaw Szymanek for the JaCoP solver, and participants of CEF 2015 – most notably Ulrich Wolffgang – for their helpful comments.
- Bruno, R. (2015). Version control systems to facilitate research collaboration in economics. Computational Economics. doi: 10.1007/10614-015-9513-8.
- Catalano, M., & Di Guilmi, C. (2015). Dynamic stochastic generalised aggregation in a multisectoral macroeconomic model. In Proceedings of the 21st International Conference on Computing in Economics and Finance (CEF 2015). Google Scholar
- Eidson, E. D., & Ehlen, M. A. (2005). NISAC agent-based laboratory for economics (N-ABLETM): Overview of agent and simulation architectures. Technical Report SAND2005-0263, Sandia National Laboratories.Google Scholar
- Kim, D. H. (1992). Guidelines for drawing causal loop diagrams. The Systems Thinker, 3(1), 5–6.Google Scholar
- Milgrom, P., & Roberts, J. (1994). Economics, organization and management. Englewood Cliffs: Prentice-Hall.Google Scholar
- Negishi, T. (1972). General equilibrium theory and international trade. North-Holland Publishing Company: Amsterdam.Google Scholar
- Seppecher, P. (2012). Jamel: A java agent-based macroeconomic laboratory. doi: 10.2139/ssrn.2669488.
- Wolffgang, U. (2015). A multi-agent non-stochastic economic simulator. In Proceedings of the 21st International Conference on Computing in Economics and Finance (CEF 2015). Google Scholar