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Applied Econometric Times Series, 3rd Edition

Book Description

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 models are also presented. In addition, several statistical examples have been updated with real-world data to help business professionals understand the relevance of the material.

Table of Contents

  1. Cover Page
  2. Title Page
  3. Copyright
  4. Dedication
  5. PREFACE
  6. ABOUT THE AUTHOR
  7. Brief Contents
  8. Contents
  9. CHAPTER 1: DIFFERENCE EQUATIONS
    1. INTRODUCTION
    2. 1. TIME-SERIES MODELS
    3. 2. DIFFERENCE EQUATIONS AND THEIR SOLUTIONS
    4. 3. SOLUTION BY ITERATION
    5. 4. AN ALTERNATIVE SOLUTION METHODOLOGY
    6. 5. THE COBWEB MODEL
    7. 6. SOLVING HOMOGENEOUS DIFFERENCE EQUATIONS
    8. 7. PARTICULAR SOLUTIONS FOR DETERMINISTIC PROCESSES
    9. 8. THE METHOD OF UNDETERMINED COEFFICIENTS
    10. 9. LAG OPERATORS
    11. 10. SUMMARY
    12. QUESTIONS AND EXERCISES
    13. ENDNOTES
    14. APPENDIX 1.1: IMAGINARY ROOTS AND DE MOIVRE'S THEOREM
    15. APPENDIX 1.2: CHARACTERISTIC ROOTS IN HIGHER-ORDER EQUATIONS
  10. CHAPTER 2: STATIONARY TIME-SERIES MODELS
    1. 1. STOCHASTIC DIFFERENCE EQUATION MODELS
    2. 2. ARMA MODELS
    3. 3. STATIONARITY
    4. 4. STATIONARITY RESTRICTIONS FOR AN ARMA( p, q ) MODEL
    5. 5. THE AUTOCORRELATION FUNCTION
    6. 6. THE PARTIAL AUTOCORRELATION FUNCTION
    7. 7. SAMPLE AUTOCORRELATIONS OF STATIONARY SERIES
    8. 8. BOX–JENKINS MODEL SELECTION
    9. 9. PROPERTIES OF FORECASTS
    10. 10. A MODEL OF THE INTEREST RATE SPREAD
    11. 11. SEASONALITY
    12. 12. PARAMETER INSTABILITY AND STRUCTURAL CHANGE
    13. 13. SUMMARY AND CONCLUSIONS
    14. QUESTIONS AND EXERCISES
    15. ENDNOTES
    16. APPENDIX 2.1: ESTIMATION OF AN MA(1) PROCESS
    17. APPENDIX 2.2: MODEL SELECTION CRITERIA
  11. CHAPTER 3: MODELING VOLATILITY
    1. 1. ECONOMIC TIME SERIES: THE STYLIZED FACTS
    2. 2. ARCH PROCESSES
    3. 3. ARCH AND GARCH ESTIMATES OF INFLATION
    4. 4. TWO EXAMPLES OF GARCH MODELS
    5. 5. A GARCH MODEL OF RISK
    6. 6. THE ARCH-M MODEL
    7. 7. ADDITIONAL PROPERTIES OF GARCH PROCESSES
    8. 8. MAXIMUM-LIKELIHOOD ESTIMATION OF GARCH MODELS
    9. 9. OTHER MODELS OF CONDITIONAL VARIANCE
    10. 10. ESTIMATING THE NYSE INTERNATIONAL 100 INDEX
    11. 11. MULTIVARIATE GARCH
    12. 12. SUMMARY AND CONCLUSIONS
    13. QUESTIONS AND EXERCISES
    14. ENDNOTES
    15. APPENDIX 3.1: MULTIVARIATE GARCH MODELS
  12. CHAPTER 4: MODELS WITH TREND
    1. 1. DETERMINISTIC AND STOCHASTIC TRENDS
    2. 2. REMOVING THE TREND
    3. 3. UNIT ROOTS AND REGRESSION RESIDUALS
    4. 4. THE MONTE CARLO METHOD
    5. 5. DICKEY–FULLER TESTS
    6. 6. EXAMPLES OF THE DICKEY–FULLER TEST
    7. 7. EXTENSIONS OF THE DICKEY–FULLER TEST
    8. 8. STRUCTURAL CHANGE
    9. 9. POWER AND THE DETERMINISTIC REGRESSORS
    10. 10. TESTS WITH MORE POWER
    11. 11. PANEL UNIT ROOT TESTS
    12. 12. TRENDS AND UNIVARIATE DECOMPOSITIONS
    13. 13. SUMMARY AND CONCLUSIONS
    14. QUESTIONS AND EXERCISES
    15. ENDNOTES
    16. APPENDIX 4.1: THE BOOTSTRAP
    17. APPENDIX 4.2: DETERMINATION OF THE DETERMINISTIC REGRESSORS
    18. ENDNOTES
  13. CHAPTER 5: MULTIEQUATION TIME-SERIES MODELS
    1. 1. INTERVENTION ANALYSIS
    2. 2. TRANSFER FUNCTION MODELS
    3. 3. ESTIMATING A TRANSFER FUNCTION
    4. 4. LIMITS TO STRUCTURAL MULTIVARIATE ESTIMATION
    5. 5. INTRODUCTION TO VAR ANALYSIS
    6. 6. ESTIMATION AND IDENTIFICATION
    7. 7. THE IMPULSE RESPONSE FUNCTION
    8. 8. TESTING HYPOTHESES
    9. 9. EXAMPLE OF A SIMPLE VAR: TERRORISM AND TOURISM IN SPAIN
    10. 10. STRUCTURAL VARs
    11. 11. EXAMPLES OF STRUCTURAL DECOMPOSITIONS
    12. 12. THE BLANCHARD–QUAH DECOMPOSITION
    13. 13. DECOMPOSING REAL AND NOMINAL EXCHANGE RATES: AN EXAMPLE
    14. 14. SUMMARY AND CONCLUSIONS
    15. QUESTIONS AND EXERCISES
    16. ENDNOTES
  14. CHAPTER 6: COINTEGRATION AND ERROR-CORRECTION MODELS
    1. 1. LINEAR COMBINATIONS OF INTEGRATED VARIABLES
    2. 2. COINTEGRATION AND COMMON TRENDS
    3. 3. COINTEGRATION AND ERROR CORRECTION
    4. 4. TESTING FOR COINTEGRATION: THE ENGLE–GRANGER METHODOLOGY
    5. 5. ILLUSTRATING THE ENGLE–GRANGER METHODOLOGY
    6. 6. COINTEGRATION AND PURCHASING POWER PARITY
    7. 7. CHARACTERISTIC ROOTS, RANK, AND COINTEGRATION
    8. 8. HYPOTHESIS TESTING
    9. 9. ILLUSTRATING THE JOHANSEN METHODOLOGY
    10. 10. ERROR-CORRECTION AND ADL TESTS
    11. 11. COMPARING THE THREE METHODS
    12. 12. SUMMARY AND CONCLUSIONS
    13. QUESTIONS AND EXERCISES
    14. ENDNOTES
    15. APPENDIX 6.1: CHARACTERISTIC ROOTS, STABILITY, AND RANK
    16. APPENDIX 6.2: INFERENCE ON A COINTEGRATING VECTOR
  15. CHAPTER 7: NONLINEAR TIME-SERIES MODELS
    1. 1. LINEAR VERSUS NONLINEAR ADJUSTMENT
    2. 2. SIMPLE EXTENSIONS OF THE ARMA MODEL
    3. 3. PRETESTING FOR NONLINEARITY
    4. 4. THRESHOLD AUTOREGRESSIVE MODELS
    5. 5. EXTENSIONS OF THE TAR MODEL
    6. 6. THREE THRESHOLD MODELS
    7. 7. SMOOTH-TRANSITION MODELS
    8. 8. OTHER REGIME-SWITCHING MODELS
    9. 9. ESTIMATES OF STAR MODELS
    10. 10. GENERALIZED IMPULSE RESPONSES AND FORECASTING
    11. 11. UNIT ROOTS AND NONLINEARITY
    12. 12. SUMMARY AND CONCLUSIONS
    13. QUESTIONS AND EXERCISES
    14. ENDNOTES
  16. STATISTICAL TABLES
  17. REFERENCES
  18. INDEX