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EViews 3.1 Users Guide3rd Edition
Copyright 19941999 Quantitative Micro Software, LLC
All Rights Reserved
Printed in the United States of America
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Disclaimer
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Trademarks
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Quantitative Micro Software, LLC
4521 Campus Drive, PMB 336, Irvine CA, 92612-2699
Telephone: (949) 856-3368
Fax: (949) 856-2044
e-mail: [email protected]
web:
http://www.eviews.com
Table of Contents
PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
PART I. EVIEWS FUNDAMENTALS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
CHAPTER 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5
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CHAPTER 2. A DEMONSTRATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
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CHAPTER 3. EVIEWS BASICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
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CHAPTER 6. EVIEWS DATABASES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
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CHAPTER 9. STATISTICAL GRAPHS USING SERIES AND GROUPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
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CHAPTER 10. GRAPHS, TABLES, AND TEXT OBJECTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
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CHAPTER 14. FORECASTING FROM AN EQUATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305
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CHAPTER 15. SPECIFICATION AND DIAGNOSTIC TESTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329
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PART IV. ADVANCED SINGLE EQUATION ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .357
CHAPTER 16. ARCH AND GARCH ESTIMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359
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CHAPTER 17. DISCRETE AND LIMITED DEPENDENT VARIABLE MODELS . . . . . . . . . . . . . . . . . . . . . . 381
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CHAPTER 18. THE LOG LIKELIHOOD (LOGL) OBJECT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431
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PART V. MULTIPLE EQUATION ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453
CHAPTER 19. SYSTEM ESTIMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455
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CHAPTER 20. VECTOR AUTOREGRESSION AND ERROR CORRECTION MODELS . . . . . . . . . . . . . . . . . 477
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CHAPTER 21. STATE SPACE MODELS AND THE KALMAN FILTER . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505
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CHAPTER 22. POOLED TIME SERIES, CROSS-SECTION DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 525
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Table of Contentsvii
CHAPTER 23. MODELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551
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APPENDIX A. MATHEMATICAL OPERATORS AND FUNCTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 565
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APPENDIX B. GLOBAL OPTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 579
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APPENDIX C. DATE FORMATS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 583
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APPENDIX D. WILDCARDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 587
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APPENDIX E. ESTIMATION ALGORITHMS AND OPTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591
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APPENDIX F. INFORMATION CRITERIA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599
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REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .601
INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .607
Preface
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Chapter 2. A Demonstration
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Dependent Variable: LOG(M1)Method: Least SquaresDate: 10/19/97 Time: 22:43Sample(adjusted): 1952:2 1992:4Included observations: 163 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C 1.312383 0.032199 40.75850 0.0000LOG(GDP) 0.772035 0.006537 118.1092 0.0000
RS -0.020686 0.002516 -8.221196 0.0000DLOG(PR) -2.572204 0.942556 -2.728967 0.0071
R-squared 0.993274 Mean dependent var 5.692279Adjusted R-squared 0.993147 S.D. dependent var 0.670253S.E. of regression 0.055485 Akaike info criterion -2.921176Sum squared resid 0.489494 Schwarz criterion -2.845256Log likelihood 242.0759 F-statistic 7826.904Durbin-Watson stat 0.140967 Prob(F-statistic) 0.000000
R2
24Chapter 2. A Demonstration
Specification and Hypothesis Tests
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F-statistic 23.53081 Probability 0.000003Chi-square 23.53081 Probability 0.000001
Breusch-Godfrey Serial Correlation LM Test:
F-statistic 813.0060 Probability 0.000000Obs*R-squared 136.4770 Probability 0.000000
Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 10/19/97 Time: 22:45
Variable Coefficient Std. Error t-Statistic Prob.
C -0.006355 0.013031 -0.487683 0.6265LOG(GDP) 0.000997 0.002645 0.376929 0.7067
RS -0.000567 0.001018 -0.556748 0.5785DLOG(PR) 0.404143 0.381676 1.058864 0.2913RESID(-1) 0.920306 0.032276 28.51326 0.0000
R-squared 0.837282 Mean dependent var 1.21E-15Adjusted R-squared 0.833163 S.D. dependent var 0.054969S.E. of regression 0.022452 Akaike info criterion -4.724644Sum squared resid 0.079649 Schwarz criterion -4.629744Log likelihood 390.0585 F-statistic 203.2515Durbin-Watson stat 1.770965 Prob(F-statistic) 0.000000
26Chapter 2. A Demonstration
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Dependent Variable: LOG(M1)Method: Least SquaresDate: 10/19/97 Time: 22:48Sample(adjusted): 1952:3 1992:4Included observations: 162 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C 0.071297 0.028248 2.523949 0.0126LOG(GDP) 0.320338 0.118186 2.710453 0.0075
RS -0.005222 0.001469 -3.554801 0.0005DLOG(PR) 0.038615 0.341619 0.113036 0.9101
LOG(M1(-1)) 0.926640 0.020319 45.60375 0.0000LOG(GDP(-1)) -0.257364 0.123264 -2.087910 0.0385
RS(-1) 0.002604 0.001574 1.654429 0.1001DLOG(PR(-1)) -0.071650 0.347403 -0.206246 0.8369
R-squared 0.999604 Mean dependent var 5.697490Adjusted R-squared 0.999586 S.D. dependent var 0.669011S.E. of regression 0.013611 Akaike info criterion -5.707729Sum squared resid 0.028531 Schwarz criterion -5.555255Log likelihood 470.3261 F-statistic 55543.30Durbin-Watson stat 2.393764 Prob(F-statistic) 0.000000
Forecasting from an Estimated Equation27
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Dependent Variable: LOG(M1)Method: Least SquaresDate: 10/19/97 Time: 22:52Sample(adjusted): 1952:3 1992:4Included observations: 162 after adjusting endpointsConvergence achieved after 14 iterations
Variable Coefficient Std. Error t-Statistic Prob.
C 1.050340 0.328390 3.198453 0.0017LOG(GDP) 0.794929 0.049342 16.11057 0.0000
RS -0.007395 0.001457 -5.075131 0.0000DLOG(PR) -0.008019 0.348689 -0.022998 0.9817
AR(1) 0.968100 0.018190 53.22283 0.0000
R-squared 0.999526 Mean dependent var 5.697490Adjusted R-squared 0.999514 S.D. dependent var 0.669011S.E. of regression 0.014751 Akaike info criterion -5.564584Sum squared resid 0.034164 Schwarz criterion -5.469288Log likelihood 455.7313 F-statistic 82748.93Durbin-Watson stat 2.164265 Prob(F-statistic) 0.000000
Inverted AR Roots .97
28Chapter 2. A Demonstration
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98Chapter 5. Working with Data
Illustration
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100Chapter 5. Working with Data
Chapter 6. EViews Databases
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118Chapter 6. EViews Databases
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126Chapter 6. EViews Databases
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140Chapter 6. EViews Databases
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Descriptive Statistics for LWAGECategorized by values of MARRIED and UNIONDate: 10/15/97 Time: 01:11Sample: 1 1000Included observations: 1000
MeanMedianStd. Dev. UNIONObs. 0 1 All
0 1.993829 2.387019 2.0529721.906575 2.409131 2.0149030.574636 0.395838 0.568689
305 54 359
MARRIED 1 2.368924 2.492371 2.4001232.327278 2.525729 2.3978950.557405 0.380441 0.520910
479 162 641
All 2.223001 2.466033 2.2754962.197225 2.500525 2.3025850.592757 0.386134 0.563464
784 216 1000
Descriptive Statistics for LWAGECategorized by values of MARRIED and UNIONDate: 10/15/97 Time: 01:08Sample: 1 1000Included observations: 1000
UNION MARRIED Mean Median Std. Dev. Obs.0 0 1.993829 1.906575 0.574636 305
1 2.368924 2.327278 0.557405 479All 2.223001 2.197225 0.592757 784
1 0 2.387019 2.409131 0.395838 541 2.492371 2.525729 0.380441 162All 2.466033 2.500525 0.386134 216
All 0 2.052972 2.014903 0.568689 3591 2.400123 2.397895 0.520910 641All 2.275496 2.302585 0.563464 1000
148Chapter 7. Series
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Simple Hypothesis Tests
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Variable CategoriesLWAGE 5UNION 2MARRIED 2Product of Categories 20
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204Chapter 9. Statistical Graphs Using Series and Groups
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Variable Coefficient Std. Error t-Statistic Prob.
C -1.699912 0.164954 -10.30539 0.0000LOG(IP) 1.765866 0.043546 40.55199 0.0000
TB3 -0.011895 0.004628 -2.570016 0.0106
R-squared 0.886416 Mean dependent var 5.663717Adjusted R-squared 0.885800 S.D. dependent var 0.553903S.E. of regression 0.187183 Akaike info criterion -0.505429Sum squared resid 12.92882 Schwarz criterion -0.473825Log likelihood 97.00980 F-statistic 1439.848Durbin-Watson stat 0.008687 Prob(F-statistic) 0.000000
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Variable Coefficient Std. Error t-Statistic Prob.
C 0.004233 0.012745 0.332092 0.7406LOG(X(-1)) 0.099840 0.112539 0.887163 0.3774LOG(W(-1)) 0.194219 0.421005 0.461322 0.6457
Weighted Statistics
R-squared 0.016252 Mean dependent var 0.009762Adjusted R-squared -0.005609 S.D. dependent var 0.106487S.E. of regression 0.106785 Akaike info criterion -1.604274Sum squared resid 1.026272 Schwarz criterion -1.522577Log likelihood 77.59873 F-statistic 0.743433Durbin-Watson stat 1.948087 Prob(F-statistic) 0.478376
Unweighted Statistics
R-squared -0.002922 Mean dependent var 0.011093Adjusted R-squared -0.025209 S.D. dependent var 0.121357S.E. of regression 0.122877 Sum squared resid 1.358893Durbin-Watson stat 2.086669
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Variable Coefficient Std. Error t-Statistic Prob.
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Variable Coefficient Std. Error t-Statistic Prob.
C -1.209268 0.039151 -30.88699 0.0000LOG(GDP) 1.094339 0.004924 222.2597 0.0000
R-squared 0.996168 Mean dependent var 7.480286Adjusted R-squared 0.996148 S.D. dependent var 0.462990S.E. of regression 0.028735 Sum squared resid 0.156888F-statistic 49399.36 Durbin-Watson stat 0.102639Prob(F-statistic) 0.000000
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256Chapter 12. Additional Regression Methods
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Variable Coefficient Std. Error t-Statistic Prob.
C -1.420705 0.203266 -6.989390 0.0000LOG(GDP) 1.119858 0.025116 44.58782 0.0000
AR(1) 0.930900 0.022267 41.80595 0.0000
R-squared 0.999611 Mean dependent var 7.480286Adjusted R-squared 0.999607 S.D. dependent var 0.462990S.E. of regression 0.009175 Sum squared resid 0.015909F-statistic 243139.7 Durbin-Watson stat 1.931027Prob(F-statistic) 0.000000
Inverted AR Roots .93
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258Chapter 12. Additional Regression Methods
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Two-Stage Least Squares259
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yt f xt ,( ) t+=
f xt
S ( ) yt f xt ,( )( )2
t y f X ,( )( ) y f X ,( )( )= =
f
yt 1 2 Ltlog 3 Ktlog t+ + +=
yt 1Lt2Kt
3 t+=
G ( )( ) y f X ,( )( ) 0=
G ( ) f X ,( )
NLLS s2G bNLLS( )G bNLLS( )( )
1=
bNLLS
Nonlinear Least Squares261
3:
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Specifying Nonlinear Least Squares
4:
' G
@@#A@7A@29A@*%AA>
4
y = c(1) + c(2)*(k^c(3)+l^c(4))
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G
4 4>
y = cf(11) + cf(12)*(k^cf(13)+l^cf(14))
4
G=
y = c(11) + c(12)*(k^cf(1)+l^cf(2))
4
.'4
y = (c(1)*x + c(2)*z + 4)^2
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@#77)A
.:
4
(c(1)*x + c(2)*z + 4)^2
yt c 1( )xt c 2( )zt 4+ +( )2
t+=
S c 1( ) c 2( ),( ) yt c 1( )xt c 2( )zt 4+ +( )2( )
2
t=
262Chapter 12. Additional Regression Methods
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@#77&A
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