May Contain Mark-Ups

By A.C Harvey

“The Econometric Analysis of Time Series”by A.C. Harvey is a comprehensive guide to understanding and applying econometric theory to time series data. The book is structured into several key sections, each addressing different aspects of econometric analysis. It Begins with an introduction to the importance of econometrics in estimating relationships suggested by economic theory, testing hypotheses, and making predictions. The book covers linear regression models, least squares estimation, properties of the ordinary least squares (OLS) estimator, generalized least squares (GLS), and prediction. It also delves into the method of maximum likelihood (ML) estimation, its properties, and its application to regression models, discussing sufficiency, the Cramer-Rao lower bound, and robustness of ML estimators. Further, the book explores numerical optimization techniques, including the Newton-Raphson method and two-step estimators, and discusses test procedures and model selection strategies. It addresses regression models with serially correlated disturbances, dynamic models, and simultaneous equation models, emphasizing the integration of recent advances in time series analysis into econometric theory.

The book also highlights the importance of understanding the dynamic aspects of econometric models and the challenges associated with specifying suitable models for time series data. Practical considerations such as the use of instrumental variables, handling heteroscedasticity, and constructing robust estimators are also covered, providing a thorough foundation for both theoretical and applied econometric analysis.

John Wiley & Sons, 1990, 384 pages