Time Series Analysis
Review Time Series Analysis
by JAMES D. HAMILTON
Description
James Hamilton gives a comprehensive look at the economic and time series and presents it through an explainer in Time Series Analysis. In this book, Hamilton highlights the important advances and innovations, including vector autoregressions, generalized method of moments, statistical consequences of unit roots, and nonlinear time series models.
Time Series Analysis gives both students and researches a survey of time series analysis and serves as powerful reference material. This book’s existence has added a significant contribution to the time series analysis field and related studies. Combining theory and technique, this book is surely a vital cog for econometrics textbooks collection.
About the Author
James Hamilton is an econometrician. He is teaching at the University of California in San Diego. His writings were proven to be a good contribution in time series as well as energy economics. He earned his Ph.D. from the University of California. His writings include High Frequency Ultrasound Imaging Using Optics and Time Series Analysis.
Table of Contents
The book presents the following topics:
1 Difference Equations
2 Lag Operators
3 Stationary ARMA Processes
4 Forecasting
5 Maximum Likelihood Estimation
6 Spectral Analysis
7 Asymptotic Distribution Theory
8 Linear Regression Models
9 Linear Systems of Simultaneous Equations
10 Covariance-Stationary Vector Processes
11 Vector Autoregressions
12 Bayesian Analysis
13 The Kalman Filter
14 Generalized Method of Moments
15 Models of Nonstationary Time Series
16 Processes with Deterministic Time Trends
17 Univariate Processes with Unit Roots
18 Unit Roots in Multivariate Time Series
19 Cointegration
20 Full-Information Maximum Likelihood Analysis of Cointegrated Systems
21 Time Series Models of Heteroskedasticity
22 Modeling Time Series with Changes
A Mathematical Reviews
B Statistical Tables
C Answer to Selected Exercises
D Greek Letters and Mathematical Symbols Used in the Text
