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We assess the presence of herding by considering the lead-lag relationship of sovereign ratings assigned by the three main rating agencies at the individual country level. Given that different rating agencies may have different levels of expertise (reputation) for different countries it is not obvious that the lead-lag relationship is homogeneous across countries. We therefore conduct poolability tests within this context to assess this assumption and find evidence of heterogeneity. This leads us to conduct country-by-country time-series tests to assess the lead-lag relationship among agencies. To our knowledge we are the first to do this and thereby extend the literature on herding among rating agencies' sovereign assignments. We also consider changes in the lead-lag relationship through time by splitting the sample into pre-crisis and crisis periods to assess the extent to which any herding is intentional and our results indicate some degree of heterogeneity through time. To the extent that there is herding we find that it is generally towards Standard and Poor's ratings confirming our expectations given that this agency is regarded as possessing the greatest reputational capital. However, our results do not support the expectation that Fitch is a follower for more (a leader for less) countries than Moody's.

Based on the non-structural model – disequilibrium approach (Goddard and Wilson, 2009), this paper presents an empirical assessment of the degree of competition within the Vietnamese banking system from 1999 to 2009. We examine a greater number of environmental covariates and different dependent variables compared to previous applications of this model. Moreover, we use lagged input prices (to avoid endogeneity) and exclude assets (to avoid specification bias) in our models. The results indicate that the Vietnamese banking system operates in a monopolistic environment.

We assess herding by considering the lead-lag relationship of sovereign ratings assigned by the 3 main rating agencies at the individual country level. The only previous study of such a lead-lag relationship (Alsakka and ap Gwilym, 2010) used pooled data methods that assume this lead-lag relationship is homogeneous across countries. Given that different rating agencies may have different levels of expertise (reputation) for different countries it is not obvious that such homogeneity holds. We therefore conduct poolability tests within this context to assess this assumption and find evidence of heterogeneity. This leads us to conduct country-by-country time-series tests to assess the lead-lag relationship among agencies. To our knowledge we are the first to do this and thereby extend the literature on herding among rating agencies' sovereign assignments. We also consider changes in the lead-lag relationship through time by splitting the sample into pre-crisis and crisis periods to assess the extent to which any herding is intentional and our results indicate some degree of heterogeneity through time. To the extent that there is herding we find that it is generally towards Standard and Poor’s ratings confirming our expectations given that this agency is regarded as possessing the greatest reputational capital. However, our results do not support the expectation that Fitch is a follower for more (a leader for less) countries than Moody’s.

This study analyses bank efficiency in Vietnam from 1999 to 2009. We use a unique data sample that allows us to capture the development of the Vietnamese banking sector over the last decade. We apply an advanced methodological approach introduced by Simar and Wilson (2007) to examine bank efficiency in Vietnam. An integral part of the analysis is to explore the determinants of bank efficiency. The results indicate that large and very large banks are more efficient than small and medium sized banks with small banks having the lowest efficiency scores in the system. We also argue that banks with large branch networks and those that have been in existence for a long time are less efficient than other banks.

This paper examines whether the level of financial development helps lower countries’ inefficiency using time-dependent robust conditional directional distance functions in a sample of 91 countries over 1970–2011. The overall results reveal that the effect of financial development on countries’ productive inefficiency is highly nonlinear, and depends on countries’ income levels, suggesting that higher levels of financial development are enhancing more countries’ catching-up ability rather than their technological change.