We construct twelve marginal--copula combinations using three marginal distributions (normal, <italic>t</italic> and <italic>S_U </italic>-normal) and four types of copulas (normal, skewed normal, <italic>t</italic> and skewed <italic>t</italic>). Bivariate empirical evidence shows that the choice of marginal distribution plays a more important role in the Value...

This study provides a nonparametric test for the parametric conditional distribution in the sample selection model. The nonparametric test statistic proposed by Fan et al. (2006) is applied to the Korean housing demand model. Test results indicate that the conditional normality in the housing...

This study compares parametric and nonparametric quantile regression methods using Monte Carlo simulations. Simulation results indicate that the nonparametric quantile regression approach is more appropriate, particularly when the underlying model is nonlinear or the error term follows a...

This study examines the long-run information role of open interest in futures markets. It is found that open interest of the futures markets for storable commodities shares the same long-run information as the futures prices, but not for the nonstorable futures markets. Furthermore, the futures...

This paper examines risk minimization hedging effectiveness for major storable and nonstorable agricultural commodity futures markets. Based on the error correction model - bivariate GARCH frameworks, some evidence is found that the hedging effectiveness is stronger for storable commodities than...

This study examines the effect of the recent radical agricultural liberalization policy, i.e. the 1996 FAIR Act, on agricultural commodity price volatility using Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. Results of the study indicate that the agricultural...