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Why Complex, Data Demanding and Difficult to Estimate Agent Based Models? Lessons from a Decades Long Research Program

Gunnar Eliasson ()
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Gunnar Eliasson: Royal Institute of Technology (KTH), Stockholm, Sweden

International Journal of Microsimulation, 2018, vol. 11, issue 1, 4-60

Abstract: Questions are often raised about the economy-wide long-term consequences of micro (policy) interventions in an economy. To answer such questions, complex high dimensional, agent-based and difficult to estimate models are needed. This soon takes the economist outside the range of mathematics s/he is comfortable with. Such was, however, the ambition of the Swedish micro firm to macroeconomic systems modelling project presented in this essay, initiated almost 45 years ago. This model is presented as a Reference model for theoretical and empirical studies, with the ambition to understand the roles of the “birth, life and death†of business agents in the volution of a self-coordinated market economy, without the help of a Walrasian central planner. Mathematical simulation is argued to be the effective tool for such theoretical and empirical analyses. Four problems have been chosen that demand a model of the Reference type to address, and that the Reference model has been used to address. They are (1) exploring the interior structures of the model for surprise analytical outcomes not previously observed, or thought of; (2) quantifying the long-term costs and benefits of large structure changing micro-interventions in the economy; (3) studying long-term historical economic systems evolutions, and asking what could have happened alternatively, if the historic evolution would have originated differently, and (4) generalizing from case observations.

Keywords: : CALIBRATION VS ESTIMATION; HISTORICAL AGENT MODELLING; MATHEMATICAL SIMULATION; MODULAR DESIGN (search for similar items in EconPapers)
JEL-codes: C5 C81 D21 D58 L16 L21 M13 O1 (search for similar items in EconPapers)
Date: 2018
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