In order to forecast one-step ahead volatility, we calculated jump intensity by using estimated parameters of a duration model of price change. In this procedure, we do not assume any distribution on log-return. Although we do not make any distributional assumption, we may practically choose a...

In this paper, we propose the use of bootstrapping methods to obtain correct critical values for dating breaks. Following the procedure proposed in Banerjee, Lazarova and Urga (1998), we consider the case of estimating a system with two or more marginal processes and a conditional process....

This paper studies weak exogeneity of conditioning variables for the inference of a subset of parameters of the conditional student's t and elliptical linear regression models considered by Spanos (1994). Weak exogeneity of the conditioning variables is shown to hold for the inference of...

Researchers typically assume experimental subjects have rational expectations. If the object of the experiment is to learn the distibution of decision makers' types, then this amounts to assuming subjects' know the very thing the researcher wishes to learn. We propose a method of conducting...

We consider a semiparametric log periodogram regression estimation of memory parameter $d$ for non-stationary fractional time series using wavelet transformation. We propose wavelet-based log periodogram regression estimator, and obtain the asymptotic mean squared error, consistency and...

We consider semiparametric log periodogram regression estimation of memory parameter for the latent process in long memory stochastic volatility models. It is known that though widely used among researchers, the Geweke and Porter-Hudak (1983; GPH) LP estimator violates the Gaussian or Martingale...

This paper provides conditions for identification and estimation of the conditional or unconditional average effect of a binary treatment or policy on a scalar outcome in models where treatment may be misclassified. Misclassification probabilities and the true probability of treatment are also...

Finite-sample inference methods are developed for quantile regression models. The methods are conservative in that (i) they apply to arbitrary sample sizes without the liberal assumption that sample sizes approach infinity, (ii) they apply when the quantiles are partially or set identified,...

A quadratic function is frequently used in regression to infer the existence of an extremum in a relationship. Examples abound in fields such as economics, epidemiology and environmental science. However, most applications provide no formal test of the extremum. Here we compare the Delta method...

Copulas offer a convenient way of modelling multivariate observations and capturing the intrinsic dependence between the components of a multivariate random variable. A semiparametric method for estimating the dependence parameters of copulas was proposed by Genest, Ghoudi and Rivest (1995), in...