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Calibration and validation of macroeconomic simulation models by statistical causal search

Author

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  • Martinoli, Mario
  • Moneta, Alessio
  • Pallante, Gianluca

Abstract

We introduce a general procedure for macroeconomic models’ calibration and validation. Configurations of parameters are selected on the basis of a loss function involving a distance between model-derived structural coefficients and their empirical counterparts. These, in both cases, are locally identified by exploiting non-Gaussianity in a structural vector autoregressive framework under a data-driven approach. We use model confidence set to account for the uncertainty in the selection procedure. We provide a measure of validation by comparing (model’s and empirical) shocks-variables structure. We apply our procedure to a complex macroeconomic simulation model that studies the link between climate change and economic growth.

Suggested Citation

  • Martinoli, Mario & Moneta, Alessio & Pallante, Gianluca, 2024. "Calibration and validation of macroeconomic simulation models by statistical causal search," Journal of Economic Behavior & Organization, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:jeborg:v:228:y:2024:i:c:s0167268124004001
    DOI: 10.1016/j.jebo.2024.106786
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    More about this item

    Keywords

    Model evaluation; Identification; Independent component analysis; Causal inference; Model confidence set; Minimum distance index;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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