• Media type: E-Book
  • Title: Measuring Interdependence of Inflation Uncertainty
  • Contributor: Lee, Seohyun [VerfasserIn]
  • imprint: [S.l.]: SSRN, 2022
  • Published in: KDI School of Pub Policy & Management Paper ; No. 04, 2022
  • Extent: 1 Online-Ressource (43 p)
  • Language: English
  • DOI: 10.2139/ssrn.4187397
  • Identifier:
  • Keywords: inflation uncertainty ; interdependence ; GARCH ; copulas ; at-risk ; conditional forecasting ; identification through heteroskedasticity ; Arbeitspapier ; Graue Literatur
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments August 11, 2022 erstellt
  • Description: The unprecedented fiscal and monetary policy responses during the COVID-19 crisis have increased uncertainty about inflation. During crises periods, the strength of the transmission of inflation uncertainty shocks from one country to another tends to intensify. This paper examines empirical methodologies to measure the strength of the interdependence of inflation uncertainty between the UK and the euro area. We first estimate inflation uncertainty by expost forecast errors from a bivariate VAR GARCH model. The interdependence of uncertainty is estimated using a probability model. The results imply that the spillover of uncertainty is stronger for uncertainty about distant future than near future. The evidence from quantile regressions shows that such empirical method could suffer from bias if endogeneity is not properly addressed. To identify structural parameters in an endogeneity representation of interdependence, we exploit heteroskedasticity in the data across different regimes determined by the ratio of variances. The results no longer exhibit stronger interdependence at longer horizons. Estimated by different sample periods, the strength of the propagation of inflation uncertainty intensifies during the Global Financial Crisis while the interdependence significantly weakens during the post-crisis period
  • Access State: Open Access