mechanism and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. Using changes in volatility …) analysis. Such restrictions are typically just-identifying but can be checked by utilizing changes in volatility. This paper … reviews and contrasts the volatility models that have been used for this purpose. Three main approaches have been used …

panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error … heteroskedasticity of unknown form in the idiosyncratic error component. Finally, we derive a robust Hausman-test of the spatial random …

unknown heteroskedasticity in the innovations. We first generalize the generalized moments (GM) estimator suggested in …

) heteroskedasticity and nonlinearity in the relation between the error-ridden covariate and another, error-free, covariate in the equation …

This paper is concerned with carbon price volatility and the underlying causes of large price movements in the European … emissions trading market. Based on the application of a combined jump-GARCH model the behavior of EUA prices is characterized …. The jump-GARCH model explains the unsteady carbon price movement well and, moreover, shows that between 40 and 60 percent …

This paper is concerned with carbon price volatility and the underlying causes of large price movements in the European … emissions trading market. Based on the application of a combined jump-GARCH model the behavior of EUA prices is characterized …. The jump-GARCH model explains the unsteady carbon price movement well and, moreover, shows that between 40 and 60 percent …

, and Slovakia) using GARCH and TARCH models between 1999 and 2006. Despite these countries adopted inflation targeting … implied higher volatility of exchange rates when it substantially deviated from the implicit target rates for all countries …. Finally, we find significant asymmetric effects of the volatility of exchange rates in all analyzed countries. …