Often researchers find parametric models restrictive and sensitive to deviations from the
parametric specifications; semi-nonparametric models are more flexible and robust, but lead …

The premise of this article is that learning procedures used to train artificial neural networks
are inherently statistical techniques. It follows that statistical theory can provide considerable …

The most authoritative and up-to-date core econometrics textbook available Econometrics is
the quantitative language of economic theory, analysis, and empirical work, and it has …

This book provides the most comprehensive treatment to date of microeconometrics, the
analysis of individual-level data on the economic behavior of individuals or firms using …

The second edition of a comprehensive state-of-the-art graduate level text on
microeconometric methods, substantially revised and updated. The second edition of this …

When I worked on my Introduction to Multiple Time Series Analysis (Lutk ̈ ̈-pohl (1991)), a
suitable textbook for this? eld was not available. Given the great importance these methods …

This paper considers tests for parameter instability and structural change with unknown
change point. The results apply to a wide class of parametric models that are suitable for …

This paper is concerned with the estimation of covariance matrices in the presence of
heteroskedasticity and autocorrelation of unknown forms. Currently available estimators that …

This paper tests two of the simplest and most popular trading rules—moving average and
trading range break—by utilizing the Dow Jones Index from 1897 to 1986. Standard …

In this paper we present inference methods which are based on an 'incorrect'criterion, in the
sense that the optimization of this criterion does not directly provide a consistent estimator of …