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Stock-Flow Dynamic Projection

Author

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  • LI, XI HAO
  • Gallegati, Mauro

Abstract

Borrowing from our experience in agent-based computational economic research from `bottom-up', this paper considers economic system as multi-level dynamical system that micro-level agents' interaction leads to structural transition in meso-level, which results in macro-level market dynamics with endogenous fluctuation or even market crashes. By the concept of transition matrix, we develop technique to quantify meso-level structural change induced by micro-level interaction. Then we apply this quantification to propose the method of dynamic projection that delivers out-of-sample forecast of macro-level economic variable from micro-level big data. We testify this method with a data set of financial statements for 4599 firms listed in Tokyo Stock Exchange for the year of 1980 to 2012. The Diebold-Mariano test indicates that the dynamic projection has significantly higher accuracy for one-period-ahead out-of-sample forecast than the benchmark of ARIMA models.

Suggested Citation

  • LI, XI HAO & Gallegati, Mauro, 2015. "Stock-Flow Dynamic Projection," MPRA Paper 62047, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:62047
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    References listed on IDEAS

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    Cited by:

    1. Venables, Anthony J., 2017. "Breaking into tradables: Urban form and urban function in a developing city," Journal of Urban Economics, Elsevier, vol. 98(C), pages 88-97.

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    More about this item

    Keywords

    economic forecasting; dynamic projection; multi-level dynamical system; transition matrix;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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