This paper introduces a new class of long memory model for volatility of stock returns, and applies the model on squared returns for BRICS (Brazil, Russia, India, China, and South Africa) countries. The conditional first- and second-order moments are provided. The CLS, FGLS and QML estimators...

This paper considers statistical inference for the heteroscedastic varying coefficient model. We propose an efficient estimator for coefficient functions that is more efficient than the conventional local-linear estimator. We establish asymptotic normality for the proposed estimator and conduct...

This paper compares generalized method of moments (GMM) and simulated maximum likeli- hood (SML) approaches to the estimation of the panel probit model. Both techniques circumvent multiple integration of joint density functions without the need to restrict the error term variance-covariance...

Estimating binary choice models with endogeneity is of considerable importance in microeconometrics. The leading control function approach does not apply when the endogenous variable is binary. We propose a multi-stage estimation procedure for a heteroscedastic binary choice model with an...

The objective of this paper is to introduce the break preserving local linear (BPLL) estimator for the estimation of unstable volatility functions. Breaks in the structure of the conditional mean and/or the volatility functions are common in Finance. Markov switching models (Hamilton, 1989) and...

Using the power kernels of Phillips, Sun and Jin (2006, 2007), we examine the large sample asymptotic properties of the t-test for different choices of power parameter (rho). We show that the nonstandard fixed-rho limit distributions of the t-statistic provide more accurate approximations to the...