In this paper we present an exact maximum likelihood treatment for the estimation of a Stochastic Volatility in Mean … (SVM) model based on Monte Carlo simulation methods. The SVM model incorporates the unobserved volatility as an explanatory … variable in the mean equation. The same extension is developed elsewhere for Autoregressive Conditional Heteroskedastic (ARCH …

. At the same time, there is discussion regarding the robustness of the results of empirical growth studies. In a seminal … paper, Knack and Keefer (1997) assess the effect of trust on growth. This paper analyses the robustness of their results … along several dimensions, acknowledging the complexity of therobustness concept. Our findings show that the robustness of …

The empirical economic growth literature is criticized for its lack of robustness. For different definitions of … robustness, conclusions vary from 'almost every correlation is fragile' to 'a substantial number of explanatory variables are … robustness using quasi-experiments. The analysis pertains to sign, size and significance of the effects, and we relax the quasi …

distribution. The robustness of the concomitant test statistic is assessed, and four different methods are discussed for applying …

This paper proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH … empirical application to S&P index log-returns. Several non-nested GARCH-type models are estimated and combined to predict the …

parsimonious and effective GARCH(1,1) model with Student-<I>t</I> innovations. The estimation procedure is fully automatic and thus …

for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … the intraday volatility measure. For forecasting horizons ranging from one day to one week the most accurate out …