This paper provides new indices of global macroeconomic uncertainty and investigates the cross-country transmission of uncertainty using a global vector autoregressive (GVAR) model. The indices measure the dispersion of forecasts that results from parameter uncertainty in the GVAR. Relying on the error correction representation of the model, we distinguish between measures of short-run and long-run uncertainty. Over the period 2000Q1-2016Q4, global short-run macroeconomic uncertainty strongly co-moves with financial market volatility, while long-run uncertainty is more highly correlated with economic policy uncertainty. We quantify global spillover effects by decomposing uncertainty into the contributions from individual countries. On average, over 40% of country-specific uncertainty is of foreign origin.
Graziano Moramarco (2020). Measuring Global Macroeconomic Uncertainty. Bologna : Dipartimento di Scienze Economiche, Università di Bologna [10.6092/unibo/amsacta/6404].
Measuring Global Macroeconomic Uncertainty
Graziano Moramarco
2020
Abstract
This paper provides new indices of global macroeconomic uncertainty and investigates the cross-country transmission of uncertainty using a global vector autoregressive (GVAR) model. The indices measure the dispersion of forecasts that results from parameter uncertainty in the GVAR. Relying on the error correction representation of the model, we distinguish between measures of short-run and long-run uncertainty. Over the period 2000Q1-2016Q4, global short-run macroeconomic uncertainty strongly co-moves with financial market volatility, while long-run uncertainty is more highly correlated with economic policy uncertainty. We quantify global spillover effects by decomposing uncertainty into the contributions from individual countries. On average, over 40% of country-specific uncertainty is of foreign origin.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.