On tail fatness of macroeconomic dynamics

Xiaochun Liu ()

Journal of Macroeconomics, 2019, vol. 62, issue C

Abstract: I first propose a quantile-based robust measure of tailedness. The empirical estimates of the new measure indicate that the assumed thick-tailed distributions in the recent literature have to some extent overestimated the degree of macroeconomic tail fatness due to the ambiguity of kurtosis. Further comparing the assumed thick-tailed distributions in forecasting macroeconomic dynamics multiple-period-ahead, I find clear evidence of the following best-performing specifications: the symmetric exponential power distribution for forecasting quarterly macroeconomic dynamics and the symmetric Student’s t distribution with time-varying volatility for forecasting monthly macroeconomic variables. Finally, the forecasting performance decomposition suggests that modeling tail fatness in macroeconomic disturbances provides significantly better predictive content than the benchmark models.

Keywords: Quantile-based tailedness; Tail decomposition; Model confidence set; Encompassing test; Fluctuation test; Forecasting performance decomposition (search for similar items in EconPapers)
JEL-codes: C22 E32 E37 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmacro:v:62:y:2019:i:c:s0164070418303367

DOI: 10.1016/j.jmacro.2019.103154

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