Evidence on time-varying inflation synchronization
Karol Szafranek ()
Economic Modelling, 2021, vol. 94, issue C, 1-13
Most studies on global inflation are conducted on homogeneous, advanced-economy, low-frequency samples and present evidence favouring the global inflation paradigm. I challenge this consensus view by quantifying price co-movements across a large, heterogeneous sample of countries, while accounting for volatility clustering in monthly inflation data. Estimation results broadly validate the global dimension of inflation but reveal that the strength of the link between global and domestic inflation is time-varying. Price co-movements have continued to be strongest for advanced economies and have increased considerably in emerging economies in recent years. However, they have remained feeble for low-income countries in the last two decades. Inflation synchronization tends to increase due to oil price shocks affecting most economies in a similar way, global economic expansions or recessions spilling over across economies and owing to more coordinated monetary policy of major central banks. Thus, marked price co-movements indicate the prevalence of common factors affecting inflation across countries.
Keywords: Inflation synchronization; Global inflation; DCC GARCH; Time-varying correlations (search for similar items in EconPapers)
JEL-codes: C32 E31 F62 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:94:y:2021:i:c:p:1-13
Access Statistics for this article
Economic Modelling is currently edited by S. Hall and P. Pauly
More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().