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

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  • Gunnar Eliasson

    (Royal Institute of Technology (KTH), Stockholm, Sweden)

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.

Suggested Citation

  • Gunnar Eliasson, 2018. "Why Complex, Data Demanding and Difficult to Estimate Agent Based Models? Lessons from a Decades Long Research Program," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 4-60.
  • Handle: RePEc:ijm:journl:v10:y:2018:i:1:p:4-60
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    References listed on IDEAS

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    Cited by:

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    2. Bo Carlsson & Gunnar Eliasson & Karolin Sjöö, 2018. "The Swedish industrial support program of the 1970s revisited," Journal of Evolutionary Economics, Springer, vol. 28(4), pages 805-835, September.
    3. Richiardi, Matteo & Bronka, Patryk & van de Ven, Justin, 2023. "Back to the future: Agent-based modelling and dynamic microsimulation," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA8/23, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.

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    More about this item

    Keywords

    : CALIBRATION VS ESTIMATION; HISTORICAL AGENT MODELLING; MATHEMATICAL SIMULATION; MODULAR DESIGN;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure
    • L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm
    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

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