Calibration and validation of macroeconomic simulation models by statistical causal search

Mario Martinoli, Alessio Moneta () and Gianluca Pallante

Journal of Economic Behavior & Organization, 2024, vol. 228, issue C

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.

Keywords: Model evaluation; Identification; Independent component analysis; Causal inference; Model confidence set; Minimum distance index (search for similar items in EconPapers)
JEL-codes: C32 C52 E37 (search for similar items in EconPapers)
Date: 2024
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Working Paper: Calibration and Validation of Macroeconomic Simulation Models by Statistical Causal Search (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:228:y:2024:i:c:s0167268124004001

DOI: 10.1016/j.jebo.2024.106786

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