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Estimating Micromotives from Macrobehavior

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Abstract

In large economic systems the observed data are usually macro-data; an agent-based model is a set of individual decision makers that in uence the macro behavior of the system both trough their direct actions and trough the in uence they have on the other decision makers. The complexity of the model impedes an explicit analytical relation between the micro-parameters and the macro-behavior, and in turn the use of "traditional" econometric tools. This paper develops an estimation procedure that allows the estimation of the agents' micromotives in an agent-based model using the emerging behavior of the system. Starting from a simple stock market model, in which agents learn by interacting, the properties of simulation-based estimations are investigated. As a rst step in the direction of extending and adapting the econometric literature to agent-based models, the paper is focused on the consistency and on the bias of the estimates.

Suggested Citation

  • Grazzini Jakob, 2011. "Estimating Micromotives from Macrobehavior," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201111, University of Turin.
    • Handle: RePEc:uto:dipeco:201111
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    1. Jacob Grazzini & Matteo Richiardi & Lisa Sella, 2012. "Indirect estimation of agent-based models.An application to a simple diffusion model," LABORatorio R. Revelli Working Papers Series 118, LABORatorio R. Revelli, Centre for Employment Studies.
    2. Jakob Grazzini, 2012. "Analysis of the Emergent Properties: Stationarity and Ergodicity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-7.

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