Long and short term dynamic causal transmission amongst international stock markets

Abstract This paper investigates the dynamic causal linkages amongst nine major international stock price indexes. In order to gauge the causal transmission patterns we employ very recent methods of: (i) vector error-correction modeling and (ii) level VAR modeling with possibly integrated and cointegrated processes, advocated by: (i) Toda and Phillips (Econometrica, 61 (1993) 1367) and (ii) Toda and Yamamoto (J. Econometrics, 66 (1995) 225), respectively. The paper illustrates how such methods may be appropriately augmented in a compatible fashion to unearth previously unfounded linkage properties inherent amongst a system of stock price indexes. In particular, we demonstrate that previous research, by using ordinary difference VARs, ignored an important component of linkages displayed purely over the long run. This untapped evidence essentially provides robust and very useful information to international financial analysts and investors. At a substantive level, results of this study tend to support the contention offered by several studies in the literature of significant interdependencies between the established OECD and the Asian markets, and also the leadership of the US and UK markets over the short and long run. The levels VAR, however, illustrate the Japanese market's influence as an additional long run leader. Findings seem to be plausible given that these three markets (US, UK and Japan) have consistently contributed over 75% of global stock market capitalization over the major part of the sample under consideration. At a methodological level, this analysis also provides a primer for the wealth of applied financial econometric research focusing on dynamic causal inference which involve systems containing possibly integrated and cointegrated processes.