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The development of multivariate generalized autoregressive conditionally heteroscedastic (MGARCH) models from the original univariate specifications represented a major step forward in the modelling of time series. MGARCH models permit time-varying conditional covariances as well as variances,...
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This article proposes a new model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to evolve separately. The model uses only the standard Student`s t-density and...
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This article employs a database of over 2000 observations of Foreign Direct Investment (FDI) projects in UK regions. We analyse this data by means of various multinomial and conditional logit models in order to identify the major determinants of the location choices of these inward investments....
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