This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasimaximum likelihood estimation, generalised method of moments, nonparametrics and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships.

In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem proof presentation, this book is very concerned with implementation issues in order to provide a fast track between theory and applied work. Consequently many of the econometric methods discussed in the book are illustrated by means of a suite of programs written in GAUSS, MATLABR® and R. The computer code emphasises the computational side of econometrics and follows the notation in the book as closely as possible, thereby reinforcing the principles presented in the text. More generally, the computer code also helps to bridge the gap between theory and practice by enabling the reproduction of both theoretical and empirical results published in recent journal articles. The reader, as a result, may build on the code and tailor it to more involved applications.