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Applied Econometric Time Series 4th edition [Mīkstie vāki]

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(University of Alabama)
  • Formāts: Paperback / softback, 496 pages, height x width x depth: 221x150x31 mm, weight: 522 g
  • Sērija : Wiley Series in Probability and Statistics
  • Izdošanas datums: 24-Oct-2014
  • Izdevniecība: John Wiley & Sons Inc
  • ISBN-10: 1118808568
  • ISBN-13: 9781118808566
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Applied Econometric Time Series 4th editionPalielināt
  • Formāts: Paperback / softback, 496 pages, height x width x depth: 221x150x31 mm, weight: 522 g
  • Sērija : Wiley Series in Probability and Statistics
  • Izdošanas datums: 24-Oct-2014
  • Izdevniecība: John Wiley & Sons Inc
  • ISBN-10: 1118808568
  • ISBN-13: 9781118808566
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781118808566.html
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Applied Econometric Time Series, 4th Edition demonstrates modern techniques for developing models capable of forecasting, interpreting, and testing hypotheses concerning economic data. In this text, Dr. Walter Enders commits to using a “learn-by-doing” approach to help readers master time-series analysis efficiently and effectively.

Preface vii
About The Author x
Chapter 1 Difference Equations 1(46)
Introduction
1(1)
1 Time-Series Models
1(6)
2 Difference Equations and Their Solutions
7(3)
3 Solution by Iteration
10(4)
4 An Alternative Solution Methodology
14(4)
5 The Cobweb Model
18(4)
6 Solving Homogeneous Difference Equations
22(9)
7 Particular Solutions for Deterministic Processes
31(3)
8 The Method of Undetermined Coefficients
34(6)
9 Lag Operators
40(3)
10 Summary
43(1)
Questions and Exercises
44(3)
Chapter 2 Stationary Time-Series Models 47(71)
1 Stochastic Difference Equation Models
47(3)
2 ARMA Models
50(1)
3 Stationarity
51(4)
4 Stationarity Restrictions for an ARMA (p, g) Model
55(5)
5 The Autocorrelation Function
60(4)
6 The Partial Autocorrelation Function
64(3)
7 Sample Autocorrelations of Stationary Series
67(9)
8 Box—Jenkins Model Selection
76(3)
9 Properties of Forecasts
79(9)
10 A Model of the Interest Rate Spread
88(8)
11 Seasonality
96(6)
12 Parameter Instability and Structural Change
102(7)
13 Combining Forecasts
109(3)
14 Summary and Conclusions
112(1)
Questions and Exercises
113(5)
Chapter 3 Modeling Volatility 118(63)
1 Economic Time Series: The Stylized Facts
118(5)
2 ARCH and GARCH Processes
123(7)
3 ARCH and GARCH Estimates of Inflation
130(4)
4 Three Examples of GARCH Models
134(7)
5 A GARCH Model of Risk
141(2)
6 The ARCH-M Model
143(3)
7 Additional Properties of GARCH Processes
146(6)
8 Maximum Likelihood Estimation of GARCH Models
152(2)
9 Other Models of Conditional Variance
154(4)
10 Estimating the NYSE U.S. 100 Index
158(7)
11 Multivariate GARCH
165(7)
12 Volatility Impulse Responses
172(2)
13 Summary and Conclusions
174(2)
Questions and Exercises
176(5)
Chapter 4 Models With Trend 181(78)
1 Deterministic and Stochastic Trends
181(8)
2 Removing the Trend
189(6)
3 Unit Roots and Regression Residuals
195(5)
4 The Monte Carlo Method
200(6)
5 Dickey—Fuller Tests
206(4)
6 Examples of the Dickey—Fuller Test
210(5)
7 Extensions of the Dickey—Fuller Test
215(12)
8 Structural Change
227(8)
9 Power and the Deterministic Regressors
235(3)
10 Tests with More Power
238(5)
11 Panel Unit Root Tests
243(4)
12 Trends and Univariate Decompositions
247(7)
13 Summary and Conclusions
254(1)
Questions and Exercises
255(4)
Chapter 5 Multiequation Time-Series Models 259(84)
1 Intervention Analysis
281
2 ADLs and Transfer Functions
267(10)
3 An ADL of Terrorism in Italy
277(4)
4 Limits to Structural Multivariate Estimation
281(4)
5 Introduction to VAR Analysis
285(5)
6 Estimation and Identification
290(4)
7 The Impulse Response Function
294(9)
8 Testing Hypotheses
303(6)
9 Example of a Simple VAR: Domestic and Transnational Terrorism
309(4)
10 Structural VARs
313(4)
11 Examples of Structural Decompositions
317(4)
12 Overidentified Systems
321(4)
13 The Blanchard—Quah Decomposition
325(6)
14 Decomposing Real and Nominal Exchange Rates: An Example
331(4)
15 Summary and Conclusions
335(2)
Questions and Exercises
337(6)
Chapter 6 Cointegration And Error-Correction Models 343(64)
1 Linear Combinations of Integrated Variables
344(7)
2 Cointegration and Common Trends
351(2)
3 Cointegration and Error Correction
353(7)
4 Testing for Cointegration: The Engle—Granger Methodology
360(4)
5 Illustrating the Engle—Granger Methodology
364(6)
6 Cointegration and Purchasing Power Parity
370(3)
7 Characteristic Roots, Rank, and Cointegration
373(7)
8 Hypothesis Testing
380(9)
9 Illustrating the Johansen Methodology
389(4)
10 Error-Correction and ADL Tests
393(4)
11 Comparing the Three Methods
397(3)
12 Summary and Conclusions
400(1)
Questions and Exercises
401(6)
Chapter 7 Nonlinear Models And Breaks 407(72)
1 Linear Versus Nonlinear Adjustment
408(2)
2 Simple Extensions of the ARMA Model
410(3)
3 Testing for Nonlinearity
413(7)
4 Threshold Autoregressive Models
420(7)
5 Extensions of the TAR Model
427(6)
6 Three Threshold Models
433(6)
7 Smooth Transition Models
439(6)
8 Other Regime Switching Models
445(4)
9 Estimates of STAR Models
449(4)
10 Generalized Impulse Responses and Forecasting
453(8)
11 Unit Roots and Nonlinearity
461(5)
12 More on Endogenous Structural Breaks
466(8)
13 Summary and Conclusions
474(1)
Questions and Exercises
475(4)
Index 479
Walter Enders, is the Lee Bidgood Chair of Economics at the University of Alabama. He received his doctorate in economics from Columbia University in New York. His research focuses on time-series econometrics with a special emphasis on the dynamic aspects of terrorism. He has published over fifty articles including those in the American Economic Review, the American Political Science Review, and the Journal of Business and Economics Statistics.