James D. Hamilton Livres

The last decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.-- "Journal of Economics"

This collection features cutting-edge papers on business cycles and financial analysis, focusing on advancements in Markov-switching models applied to these areas. The introduction reviews existing methods and recent findings from the past decade. Individual chapters examine U.S. and European business cycles, emphasizing monetary policy, oil shocks, and the interrelationships among key variables. The text also discusses the short-run and long-run impacts of economic recessions. Another significant topic is the detailed exploration of currency crises and the potential for bubbles or fads in stock prices. A concluding chapter presents valuable new insights into testing regime-switching behavior. Overall, the book offers a comprehensive overview of innovative methods and results in estimation and inference through Markov-switching time-series analysis. A notable aspect is its illustration of diverse applications using a unified methodology. This theme is particularly relevant for macroeconomics readers, econometrics professionals, scholars, and graduate students. Gratitude is expressed to the authors for their impactful contributions and to the reviewers for their meticulous attention in evaluating the work.