Assessing International Commonality in Macroeconomic Uncertainty and Its Effects
Andrea Carriero (),
Todd Clark and
No 1803, Working Papers (Old Series) from Federal Reserve Bank of Cleveland
This paper uses a large vector autoregression (VAR) to measure international macroeconomic uncertainty and its effects on major economies, using two datasets, one with GDP growth rates for 19 industrialized countries and the other with a larger set of macroeconomic indicators for the U.S., euro area, and U.K. Using basic factor model diagnostics, we first provide evidence of significant commonality in international macroeconomic volatility, with one common factor accounting for strong comovement across economies and variables. We then turn to measuring uncertainty and its effects with a large VAR in which the error volatilities evolve over time according to a factor structure. The volatility of each variable in the system reflects time-varying common (global) components and idiosyncratic components. In this model, global uncertainty is allowed to contemporaneously affect the macroeconomies of the included nations—both the levels and volatilities of the included variables. In this setup, uncertainty and its effects are estimated in a single step within the same model. Our estimates yield new measures of international macroeconomic uncertainty, and indicate that uncertainty shocks (surprise increases) lower GDP and many of its components, adversely affect labor market conditions, lower stock prices, and in some economies lead to an easing of monetary policy.
Keywords: Business cycle uncertainty; stochastic volatility; large datasets (search for similar items in EconPapers)
JEL-codes: C11 C55 E32 F44 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ifn and nep-mac
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