In the context of the partially linear semiparametric model examined by Robinson (1988), we show that root-n-consisten estimation results established using kernel and series methods can also be obtained by using k-nearest-neighbor (k-nn) method.

In this paper we employ an additive semiparametric partially linear model to uncover the way that initial output and schooling levels affect growth rates. Our results based on marginal integration allow for graphical representation of the non-linearities that characterize the effects that these...

This study proposes a semiparametric estimate and a test for base-independence equivalence scale. Our semiparametric approach is based on nondensity weighted loss function in contrast to Pendakur's (1999) density weighted loss function. Simulation results indicate that our specification tends to...

This study examines long-run relationships and short-run dynamic causal linkages among the US, Japanese, and ten Asian emerging stock markets, with the particular attention to the 1997-1998 Asian financial crisis. Extending related empirical studies, comparative analyses of pre-crisis, crisis,...

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...

We have developed a measure for systemic risk under the bivariate SU-normal distribution, and estimated systemic risk conditional upon the VaR of financial institutions. Simulation results show that both the normal and the quantile regression estimates are downward biased relative to the...