This paper studies the empirical applications of the autocorrelation tests, the unit root tests, and the efficient estimation procedures introduced in Guo and Phillips (1999a) to daily return series for the Samp;P 500 Index and a set of eight individual stocks. As a further example of estimating...

This paper proposes a novel positive nonparametric estimator of the conditional variance function without reliance on logarithmic or other transformations. The estimator is based on an empirical likelihood modification of conventional local level nonparametric regression applied to squared mean...

This paper develops a linearity test that can be applied to cointegrating relations. We consider the widely used RESET specification test and show that when this test is applied to nonstationary time series its asymptotic distribution involves a mixture of noncentral chi-squared distributions,...

We develop a nonparametric estimator for the volatility structure of the zero coupon yield curve in the Heath, Jarrow-Morton framework. The estimator incorporates cross-sectional restrictions along the maturity dimension, and also allows for measurement errors, which arise from the estimation of...

This paper studies statistical inference and efficient instrumental variable (IV) estimation in the ARCH model when there are autoregressive (AR) components in the conditional mean. The main focus of the paper is the construction of efficient IV estimators for the second moment parameters. The...

The presence of conditional heteroskedasticity invalidates standard autocorrelation tests such as the Durbin-Watson statistic and its many variants, and reduces the power of standard unit root tests like the Dickey-Fuller test. This paper addresses the problem of testing for AR(1) and AR(p)...

A new family of kernels is suggested for use in heteroskedasticity and autocorrelation consistent (HAC) and long run variance (LRV) estimation and robust regression testing. The kernels are constructed by taking powers of the Bartlett kernel and are intended to be used with no truncation (or...

This paper considers stationary regression models with near-collinear regressors. Limit theory is developed for regression estimates and test statistics in cases where the signal matrix is nearly singular in finite samples and is asymptotically degenerate. Examples include models that involve...