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Title:The Home Bias and Capital Income Flows between Countries and Regions PDF Logo
Authors:Artis, Michael J.
Hoffmann, Mathias
Issue Date:2006
Series/Report no.:Technical Report / Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2006,13
Abstract:This paper documents a marked increase in international consumption risk sharing throughout the recent globalization period. Unlike earlier studies that have found it difficult to document a consistent effect of financial globalization on international consumption comovements, we make use of the information implicit in the relative levels of consumption and output to measure long-run risk sharing among OECD countries and US federal states. We derive our empirical setup from a deliberately simplistic model in which countries can trade perpetual claims to each other?s output (Shiller securities). This model allows us to identify the channels through which improvements in international risk sharing have come about. The model predicts crosscountry and cross-regional income flows with considerable precision. Both international income flows as well as consumption risk sharing have increased since 1990, in line with the gradual removal of country portfolio home bias documented elsewhere. Still, the increase in international income flows falls short of explaining all of the consumption risk sharing we see in international data. We show that heterogeneity in countries? gross foreign asset positions is important in explaining this result. While countries with less portfolio home bias enjoy better consumption risk sharing, our findings also suggest that heterogeneity in country portfolios opens an separate channel for consumption risk sharing, possibly through asymmetric valuation effects that have been emphasized in the recent literature.
Subjects:Consumption Risk Sharing
International and regional business cycles
Capital flows
Home Bias
Non-stationary panel data
JEL:F36
E21
C23
Document Type:Working Paper
Appears in Collections:Technical Reports, SFB 475: Komplexitätsreduktion in multivariaten Datenstrukturen, TU Dortmund

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