A non-parametric model-based approach to uncertainty and risk analysis of macroeconomic forecast

Claudia Miani () and Stefano Siviero
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Claudia Miani: Bank of Italy

No 758, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: It has increasingly become standard practice to supplement point macroeconomic forecasts with an appraisal of the degree of uncertainty and the prevailing direction of risks. Several alternative approaches have been proposed in the literature to compute the probability distribution of macroeconomic forecasts; all of them rely on combining the predictive density of model-based forecasts with subjective judgment about the direction and intensity of prevailing risks. We propose a non-parametric, model-based simulation approach, which does not require specific assumptions to be made regarding the probability distribution of the sources of risk. The probability distribution of macroeconomic forecasts is computed as the result of model-based stochastic simulations which rely on re-sampling from the historical distribution of risk factors and are designed to deliver the desired degree of skewness. By contrast, other approaches typically make a specific, parametric assumption about the distribution of risk factors. The approach is illustrated using the Bank of Italy�s Quarterly Macroeconometric Model. The results suggest that the distribution of macroeconomic forecasts quickly tends to become symmetric, even if all risk factors are assumed to be asymmetrically distributed.

Keywords: macroeconomic forecasts; stochastic simulations; balance of risks; uncertainty; fan-charts (search for similar items in EconPapers)
JEL-codes: C14 C53 E37 (search for similar items in EconPapers)
Date: 2010-04
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-rmg and nep-upt
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Citations: View citations in EconPapers (7)

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