Financial stress spillover across Asian Countries

Abstract

This paper uses fractional integration techniques to explore the stochastic properties of the Financial Stress Indices (FSIs) of 10 Asian countries, further investigating the bilateral linkages between them to ascertain how financial stress spreads among countries in the region. For the FSIs of each country, the results show that all the estimated orders of integration are in the interval (0, 1) implying fractional integration and a long memory pattern. Thus, shocks will have transitory though long‐lasting effects. For the cross‐country spillovers of the FSIs, we find that convergence is satisfied in all cases with values of the differencing parameter around 0 and thus showing short memory behavior. It is worth noting that for the larger economies in the region, Japan and China, financial stress transmission between Japan and the smaller economies was faster than with respect to China. Overall, the results provide valuable information on the financial market activity of the countries in the region. To check for the robustness of the baseline results we also use systemic risk measures for these countries, CoVaR with the results showing evidence of fractional integration for the individual series, with all values of the differencing parameter in the range (0, 1). For convergence, there is a substantial reduction in the degree of integration, though the results are not as clear as with the FSIs.

Time-varying predictability of financial stress on inequality in United Kingdom

“…Given that financial stress across economies can spillover (Gil-Alana et al. , 2020), as part of future research, it would be interesting to compare the role of international financial stress on UK's inequality, relative to domestic financial distress.…”

“…Given that financial stress across economies can spillover (Gil-Alana et al, 2020), as part of future research, it would be interesting to compare the role of international financial stress on UK's inequality, relative to domestic financial distress. Further, it would be interesting to use mixed data sampling (MIDAS) methods to predict the future path of low-frequency (annual) inequality growth based on data of high-frequency data of financial stress available for many economies around the world.…”