Applied Econometric Times Series
Enders continues to provide business professionals with an accessible introduction to time-series analysis. He clearly shows them how to develop models capable of forecasting, interpreting, and testing hypotheses concerning economic data using the latest techniques. The third edition includes new discussions on parameter instability and structural breaks as well as out-of-sample forecasting methods. New developments in unit root test and cointegration tests are covered. Multivariate GARCH...
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Accessible & Modern Techniques for Time-Series Analysis Assuming only a basic understanding of multiple regression analysis, this classic introduction to time-series analysis shows how to develop models capable of forecasting, interpreting, and testing hypotheses concerning economic data using modern techniques. Numerous real-world examples from fields ranging from agricultural economics to transnational terrorism further illustrate the various techniques. This new edition reflects both sound structure and recent advances in time-series econometrics, such as out-of-sample forecasting techniques, nonlinear time-series models, Monte Carlo analysis, and bootstrapping. Features:New discussion of parameter instability and structural breaks including tests for endogenous breaks.New coverage of developments in cointegration tests and in unit root tests.Improved discussions on out-of-sample forecasting methods and multivariate GARCH models.Numerous illustrations of key concepts and detailed example using real-world data.Step-by-step approach to time-series estimation.Additional questions and empirical exercises that enable students to practice the techniques covered in the test. Data sets are available on the text’s companion Web site.Emphasizes difference equations as the foundation of all time-series models. Booknews A review of recent advances in time series analysis, providing a balance between macro and microeconomic application and using examples drawn from agricultural economics, international finance, and transnational terrorism. Emphasizes the importance of difference equations, and assumes some background in multiple regression analysis. Software packages such as RATS, SAS, or SHAZAM are necessary to work through the exercises. A data disk with computer programs accompanies the Instructor's Manual. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Ch. 1Difference Equations11Time-Series Models22Difference Equations and Their Solutions73Solution by Iteration104An Alternative Solution Methodology165The Cobweb Model206Solving Homogeneous Difference Equations257Finding Particular Solutions for Determimstic Processes358The Method of Undetermined Coefficients389Lag Operators4510Forward-Versus Backward-Looking Solutions48Ch. 2Stationary Time-Series Models631Stochastic Difference Equation Models632ARMA Models673Stationarity684Stationarity Restrictions for an ARMA(p, q) Model725The Autocorrelation Function786The Partial Autocorrelation Function827Sample Autocorrelations of Stationary Series868Box-Jenkins Model Selection959The Forecast Function9910A Model of the WPI10611Seasonality111Ch. 3Modeling Economic Time Series: Trends and Volatility1351Economic Time Series: The Stylized Facts1352ARCH Processes1393ARCH and GARCH Estimates of Inflation1494Estimating a GARCH Model of the WPI: An Example1525A GARCH Model of Risk1566The ARCH-M Model1587Maximum Likelihood Estimation of GARCH and ARCH-M Models1628Deterministic and Stochastic Trends1669Removing the Trend17610Are There Business Cycles?18111Stochastic Trends and Univariate Decompositions185Ch. 4Testing for Trends and Unit Roots2111Unit Root Processes2122Dickey-Fuller Tests2213Extensions of the Dickey-Fuller Tests2254Examples of the Augmented Dickey-Fuller Test2335Phillips-Perron Tests2396Structural Change2437Problems in Testing for Unit Roots251Ch. 5Multiequation Time-Series Models2691Intervention Analysis2702Transfer Function Models2773Estimating a Transfer Function2864Limits to Structural Multivariate Estimation2915Introduction to VAR Analysis2946Estimation and Identification3007The Impulse Response Function3058Hypothesis Testing3129Example of a Simple VAR: Terrorism and Tourism in Spain31610Structural VARs32011Examples of Structural Decompositions32412The Blanchard and Quah Decomposition33113Decomposing Real and Nominal Exchange Rate Movements: An Example338Ch. 6Cointegration and Error-Correction Models3551Linear Combinations of Integrated Variables3562Cointegration and Common Trends3633Cointegration and Error Correction3654Testing for Cointegration: The Engle-Granger Methodology3735Illustrating the Engle-Granger Methodology3776Cointegration and Purchasing-Power Parity3817Characteristic Roots, Rank, and Cointegration3858Hypothesis Testing in a Cointegration Framework3939Illustrating the Johansen Methodology39610Generalized Purchasing-Power Parity400Statistical tables A. Empirical Distributions of the [tau] Statistics419Statistical tables B. Empirical Distributions of the [phi] Statistics420Statistical tables C. Empirical Distributions of the [lambda[subscript max]] and [lambda[subscript trace]] Statistics421References423Author Index427Subject Index429
\ BooknewsA review of recent advances in time series analysis, providing a balance between macro and microeconomic application and using examples drawn from agricultural economics, international finance, and transnational terrorism. Emphasizes the importance of difference equations, and assumes some background in multiple regression analysis. Software packages such as RATS, SAS, or SHAZAM are necessary to work through the exercises. A data disk with computer programs accompanies the Instructor's Manual. Annotation c. Book News, Inc., Portland, OR (booknews.com)\ \
