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Main Author:	Baltagi, Badi H. 1954- (Author)
Format:	Book
Language:	English
Published:	Berlin [u.a.] Springer 2008
Edition:	4. ed.
Subjects:	Econometría Économétrie Econometrics Ökonometrie Lehrbuch
Online Access:	Inhaltsverzeichnis Inhaltsverzeichnis Klappentext
Physical Description:	XV, 392 S. graph. Darst. 242 mm x 193 mm
ISBN:	3540765158 9783540765158

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adam_text	Table of Contents Preface VII Table of Contents XI Part I 1 1 What Is Econometrics? 3 1.1 Introduction ...................................... 3 1.2 A Brief History .................................... Г, 1.3 Critiques of Econometrics ............................... 7 1.4 Looking Ahead ..................................... 8 Notes ............................................. 9 References ........................................... 10 2 Basic Statistical Concepts 13 2.1 Introduction ...................................... 13 2.2 Methods of Estimation ................................ 13 2.3 Properties of Estimators ............................... l(i 2.4 Hypothesis Testing .................................. 21 2.5 Confidence Intervals .................................. 30 2.6 Descriptive Statistics ................................. 31 Xotes ............................................. 36 Problems ........................................... 36 References ........................................... 42 Appendix ........................................... 42 3 Simple Linear Regression 49 3.1 Introduction ...................................... 49 3.2 Least Squares Estimation and the Classical Assumptions ............. 50 3.3 Statistical Properties of Least Squares ........................ ΰό 3.4 Estimation of it .................................... 56 3.5 Maximum Likelihood Estimation ........................... 57 3.6 A Measure of Fit ................................... 5* 3.7 Prediction ....................................... 60 3.i< Residual Analysis ................................... 60 3.9 Numerical Example .................................. (¡3 3.10 Empirical Example .................................. (j 1 Problems ........................................... 67 References ........................................... 71 Appendix .......................................... I _ Multiple Regression Analysis 73 4.1 Introduction ...................................... 73 XII Table of Contents 4.2 Least Squares Estimation ............................... 73 4.3 Residual Interpretation of Multiple Regression Estimates ............. 75 4.4 Overspecification and Underspecification of the Regression Equation ....... 76 4.5 R-Squared versus R-Bar-Squared .......................... 78 4.6 Testing Linear Restrictions .............................. 78 4.7 Dummy Variables ................................... 81 Note .............................................. 85 Problems ........................................... 85 References ........................................... 91 Appendix ........................................... 92 5 Violations of the Classical Assumptions 95 5.1 Introduction ...................................... 95 5.2 The Zero Mean Assumption ............................. 95 5.3 Stochastic Explanatory Variables .......................... 96 5.4 Normality of the Disturbances ............................ 98 5.5 Heteroskedasticity ................................... 98 5.6 Autocorrelation .................................... 109 Notes ............................................. 119 Problems ........................................... 120 References ........................................... 126 6 Distributed Lags and Dynamic Models 129 6.1 Introduction ...................................... 129 6.2 Infinite Distributed Lag ................................ 135 6.2.1 Adaptive Expectations Model (AEM) .................... 136 6.2.2 Partial Adjustment Model (РАМ) ...................... 137 6.3 Estimation and Testing of Dynamic Models with Serial Correlation ....... 137 6.3.1 A Lagged Dependent Variable Model with AR(1) Disturbances ..... 138 6.3.2 A Lagged Dependent Variable Model with MA(1) Disturbances ..... 140 6.4 Autoregressive Distributed Lag ............................ 141 Note .............................................. 142 Problems ...........................................142 References ...........................................144 Part II 147 7 The General Linear Model: The Basics 149 7.1 Introduction ..................... 149 7.2 Least Squares Estimation ............... 149 7.3 Partitioned Regression and the Frisch-Waugh-Lovell Theorem ..........152 7.4 Maximum Likelihood Estimation ...........................154 7.5 Prediction ................... 157 7.6 Confidence Intervals and Test of Hypotheses ....................158 7.7 Joint Confidence Intervals and Test of Hypotheses .................158 Table of Contents XIII 7.8 Restricted MLE and Restricted Least Squares ...................159 7.9 Likelihood Ratio, Wald and Lagrange Multiplier Tests ...............160 Notes .............................................165 Problems ...........................................165 References ...........................................170 Appendix ...........................................171 8 Regression Diagnostics and Specification Tests 177 8.1 Influential Observations ................................177 8.2 Recursive Residuals ..................................185 8.3 Specification Tests ...................................194 8.4 Nonlinear Least Squares and the Gauss-Newton Regression ............204 8.5 Testing Linear versus Log-Linear Functional Form .................212 Notes .............................................214 Problems ...........................................214 References ...........................................218 9 Generalized Least Squares 221 9.1 Introduction ......................................221 9.2 Generalized Least Squares ..............................221 9.3 Special Forms of Ω ..................................223 9.4 Maximum Likelihood Estimation ...........................224 9.5 Test of Hypotheses ..................................224 9.6 Prediction .......................................225 9.7 Unknown Ω ......................................225 9.8 The W, LR and LM Statistics Revisited ......................226 9.9 Spatial Error Correlation ...............................228 Note ..............................................229 Problems ...........................................230 References ...........................................234 10 Seemingly Unrelated Regressions 237 10.1 Introduction ......................................237 10.2 Feasible GLS Estimation ...............................239 10.3 Testing Diagonality of the Variance-Covariance Matrix ..............242 10.4 Seemingly Unrelated Regressions with Unequal Observations ...........242 10.5 Empirical Example ..................................244 Problems ...........................................245 References ...........................................249 11 Simultaneous Equations Model 253 11.1 Introduction ......................................253 11.1.1 Simultaneous Bias ...............................253 11.1.2 The Identification Problem ..........................256 11.2 Single Equation Estimation: Two-Stage Least Squares ...............259 11.2.1 Spatial Lag Dependence ...........................266 XIV Table of Contents 11.3 System Estimation: Three-Stage Least Squares ...................267 11.4 Test for Over-Identification Restrictions .......................269 11.5 Hausman s Specification Test .............................271 11.6 Empirical Example: Crime in North Carolina ....................273 Notes ............................................. 277 Problems ...........................................277 References ...........................................287 Appendix ...........................................289 12 Pooling Time-Series of Cross-Section Data 295 12.1 Introduction ......................................295 12.2 The Error Components Model ............................295 12.2.1 The Fixed Effects Model ...........................296 12.2.2 The Random Effects Model .........................298 12.2.3 Maximum Likelihood Estimation ......................302 12.3 Prediction .......................................303 12.4 Empirical Example ..................................303 12.5 Testing in a Pooled Model ..............................307 12.6 Dynamic Panel Data Models .............................311 12.6.1 Empirical Illustration .............................314 12.7 Program Evaluation and Difference-in-Differences Estimator ...........316 12.7.1 The Difference-in-Differences Estimator ...................317 Problems ...........................................317 References ...........................................320 13 Limited Dependent Variables 323 13.1 Introduction ......................................323 13.2 The Linear Probability Model ............................323 13.3 Functional Form: Logit and Probit ..........................324 13.4 Grouped Data .....................................326 13.5 Individual Data: Probit and Logit ..........................331 13.6 The Binary Response Model Regression .......................332 13.7 Asymptotic Variances for Predictions and Marginal Effects ............334 13.8 Goodness of Fit Measures ...............................334 13.9 Empirical Examples ..................................335 13.10 Multinomial Choice Models ..............................339 13.10.1 Ordered Response Models ..........................339 13.10.2 Unordered Response Models .........................340 13.11 The Censored Regression Model ...........................341 13.12 The Truncated Regression Model ..........................344 13.13 Sample Selectivity ...................................345 Notes .............................................347 Problems ..........................................347 References ............................ 351 Appendix ...........................................353 Table of Contents XV 14 Time-Series Analysis 355 14.1 Introduction ......................................355 14.2 Stationarity ......................................355 14.3 The Box and Jenkins Method ............................356 14.4 Vector Autoregression.................................360 14.5 Unit Roots .......................................361 14.6 Trend Stationary versus Difference Stationary ...................365 14.7 Cointegration .....................................366 14.8 Autoregressive Conditional Heteroskedasticity ...................368 Note ..............................................371 Problems ...........................................371 References ...........................................375 Appendix 379 List of Figures 385 List of Tables 387 Index 389 ВАШ Н. BAIT. is distinguished Professor of Economics, and Senior Research Associate at the Center for Policy Research, Syracuse Uni¬ versity. He received his Ph.D. in Economics at the University of Pennsylvania in 1979. Before joining Syracuse University, he served on the faculty at the University of Houston and Texas A&M University. He is a fellow of the Journal of Econometrics and a recipient of the Multa and Plura Scripsit Awards from Econo¬ metric Theory. baltag 1 ■ Econometrics Ш 4th Edition This textbook teaches some of the basic econometric methods and the underlying assumptions behind them. It also includes a simple and concise treatment of more advanced topics in spatial correlation, panel data, limited dependent variables, regression diagnostics, specifica¬ tion testing and time series analysis. Some of the strengths of this book lie in presenting difficult material in a simple, yet rigorous manner. Each chapter has a set of theoretical exercises as well as an empirical illus¬ tration using a real economic application. These empirical exercises usually replicate a published article using Stata or Eviews.
adam_txt	Table of Contents Preface VII Table of Contents XI Part I 1 1 What Is Econometrics? 3 1.1 Introduction . 3 1.2 A Brief History . Г, 1.3 Critiques of Econometrics . 7 1.4 Looking Ahead . 8 Notes . 9 References . 10 2 Basic Statistical Concepts 13 2.1 Introduction . 13 2.2 Methods of Estimation . 13 2.3 Properties of Estimators . l(i 2.4 Hypothesis Testing . 21 2.5 Confidence Intervals . 30 2.6 Descriptive Statistics . 31 Xotes . 36 Problems . 36 References . 42 Appendix . 42 3 Simple Linear Regression 49 3.1 Introduction . 49 3.2 Least Squares Estimation and the Classical Assumptions . 50 3.3 Statistical Properties of Least Squares . ΰό 3.4 Estimation of it" . 56 3.5 Maximum Likelihood Estimation . 57 3.6 A Measure of Fit . 5* 3.7 Prediction . 60 3.i< Residual Analysis . 60 3.9 Numerical Example . (¡3 3.10 Empirical Example . (j 1 Problems . 67 References . 71 Appendix . I _ Multiple Regression Analysis 73 4.1 Introduction . 73 XII Table of Contents 4.2 Least Squares Estimation . 73 4.3 Residual Interpretation of Multiple Regression Estimates . 75 4.4 Overspecification and Underspecification of the Regression Equation . 76 4.5 R-Squared versus R-Bar-Squared . 78 4.6 Testing Linear Restrictions . 78 4.7 Dummy Variables . 81 Note . 85 Problems . 85 References . 91 Appendix . 92 5 Violations of the Classical Assumptions 95 5.1 Introduction . 95 5.2 The Zero Mean Assumption . 95 5.3 Stochastic Explanatory Variables . 96 5.4 Normality of the Disturbances . 98 5.5 Heteroskedasticity . 98 5.6 Autocorrelation . 109 Notes . 119 Problems . 120 References . 126 6 Distributed Lags and Dynamic Models 129 6.1 Introduction . 129 6.2 Infinite Distributed Lag . 135 6.2.1 Adaptive Expectations Model (AEM) . 136 6.2.2 Partial Adjustment Model (РАМ) . 137 6.3 Estimation and Testing of Dynamic Models with Serial Correlation . 137 6.3.1 A Lagged Dependent Variable Model with AR(1) Disturbances . 138 6.3.2 A Lagged Dependent Variable Model with MA(1) Disturbances . 140 6.4 Autoregressive Distributed Lag . 141 Note . 142 Problems .142 References .144 Part II 147 7 The General Linear Model: The Basics 149 7.1 Introduction . 149 7.2 Least Squares Estimation . 149 7.3 Partitioned Regression and the Frisch-Waugh-Lovell Theorem .152 7.4 Maximum Likelihood Estimation .154 7.5 Prediction . 157 7.6 Confidence Intervals and Test of Hypotheses .158 7.7 Joint Confidence Intervals and Test of Hypotheses .158 Table of Contents XIII 7.8 Restricted MLE and Restricted Least Squares .159 7.9 Likelihood Ratio, Wald and Lagrange Multiplier Tests .160 Notes .165 Problems .165 References .170 Appendix .171 8 Regression Diagnostics and Specification Tests 177 8.1 Influential Observations .177 8.2 Recursive Residuals .185 8.3 Specification Tests .194 8.4 Nonlinear Least Squares and the Gauss-Newton Regression .204 8.5 Testing Linear versus Log-Linear Functional Form .212 Notes .214 Problems .214 References .218 9 Generalized Least Squares 221 9.1 Introduction .221 9.2 Generalized Least Squares .221 9.3 Special Forms of Ω .223 9.4 Maximum Likelihood Estimation .224 9.5 Test of Hypotheses .224 9.6 Prediction .225 9.7 Unknown Ω .225 9.8 The W, LR and LM Statistics Revisited .226 9.9 Spatial Error Correlation .228 Note .229 Problems .230 References .234 10 Seemingly Unrelated Regressions 237 10.1 Introduction .237 10.2 Feasible GLS Estimation .239 10.3 Testing Diagonality of the Variance-Covariance Matrix .242 10.4 Seemingly Unrelated Regressions with Unequal Observations .242 10.5 Empirical Example .244 Problems .245 References .249 11 Simultaneous Equations Model 253 11.1 Introduction .253 11.1.1 Simultaneous Bias .253 11.1.2 The Identification Problem .256 11.2 Single Equation Estimation: Two-Stage Least Squares .259 11.2.1 Spatial Lag Dependence .266 XIV Table of Contents 11.3 System Estimation: Three-Stage Least Squares .267 11.4 Test for Over-Identification Restrictions .269 11.5 Hausman's Specification Test .271 11.6 Empirical Example: Crime in North Carolina .273 Notes . 277 Problems .277 References .287 Appendix .289 12 Pooling Time-Series of Cross-Section Data 295 12.1 Introduction .295 12.2 The Error Components Model .295 12.2.1 The Fixed Effects Model .296 12.2.2 The Random Effects Model .298 12.2.3 Maximum Likelihood Estimation .302 12.3 Prediction .303 12.4 Empirical Example .303 12.5 Testing in a Pooled Model .307 12.6 Dynamic Panel Data Models .311 12.6.1 Empirical Illustration .314 12.7 Program Evaluation and Difference-in-Differences Estimator .316 12.7.1 The Difference-in-Differences Estimator .317 Problems .317 References .320 13 Limited Dependent Variables 323 13.1 Introduction .323 13.2 The Linear Probability Model .323 13.3 Functional Form: Logit and Probit .324 13.4 Grouped Data .326 13.5 Individual Data: Probit and Logit .331 13.6 The Binary Response Model Regression .332 13.7 Asymptotic Variances for Predictions and Marginal Effects .334 13.8 Goodness of Fit Measures .334 13.9 Empirical Examples .335 13.10 Multinomial Choice Models .339 13.10.1 Ordered Response Models .339 13.10.2 Unordered Response Models .340 13.11 The Censored Regression Model .341 13.12 The Truncated Regression Model .344 13.13 Sample Selectivity .345 Notes .347 Problems .347 References . 351 Appendix .353 Table of Contents XV 14 Time-Series Analysis 355 14.1 Introduction .355 14.2 Stationarity .355 14.3 The Box and Jenkins Method .356 14.4 Vector Autoregression.360 14.5 Unit Roots .361 14.6 Trend Stationary versus Difference Stationary .365 14.7 Cointegration .366 14.8 Autoregressive Conditional Heteroskedasticity .368 Note .371 Problems .371 References .375 Appendix 379 List of Figures 385 List of Tables 387 Index 389 ВАШ Н. BAIT. is distinguished Professor of Economics, and Senior Research Associate at the Center for Policy Research, Syracuse Uni¬ versity. He received his Ph.D. in Economics at the University of Pennsylvania in 1979. Before joining Syracuse University, he served on the faculty at the University of Houston and Texas A&M University. He is a fellow of the Journal of Econometrics and a recipient of the Multa and Plura Scripsit Awards from Econo¬ metric Theory. baltag 1 ■ Econometrics Ш 4th Edition This textbook teaches some of the basic econometric methods and the underlying assumptions behind them. It also includes a simple and concise treatment of more advanced topics in spatial correlation, panel data, limited dependent variables, regression diagnostics, specifica¬ tion testing and time series analysis. Some of the strengths of this book lie in presenting difficult material in a simple, yet rigorous manner. Each chapter has a set of theoretical exercises as well as an empirical illus¬ tration using a real economic application. These empirical exercises usually replicate a published article using Stata or Eviews.
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id	DE-604.BV023029199
illustrated	Illustrated
index_date	2024-07-02T19:16:18Z
indexdate	2024-07-09T21:09:21Z
institution	BVB
isbn	3540765158 9783540765158
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-016233111
oclc_num	183259583
open_access_boolean
owner	DE-92 DE-1051 DE-355 DE-BY-UBR DE-1047 DE-1102 DE-703 DE-19 DE-BY-UBM DE-706 DE-521 DE-91 DE-BY-TUM DE-573 DE-M382 DE-945 DE-2070s DE-188
owner_facet	DE-92 DE-1051 DE-355 DE-BY-UBR DE-1047 DE-1102 DE-703 DE-19 DE-BY-UBM DE-706 DE-521 DE-91 DE-BY-TUM DE-573 DE-M382 DE-945 DE-2070s DE-188
physical	XV, 392 S. graph. Darst. 242 mm x 193 mm
publishDate	2008
publishDateSearch	2008
publishDateSort	2008
publisher	Springer
record_format	marc
spelling	Baltagi, Badi H. 1954- Verfasser (DE-588)128356812 aut Econometrics Badi H. Baltagi 4. ed. Berlin [u.a.] Springer 2008 XV, 392 S. graph. Darst. 242 mm x 193 mm txt rdacontent n rdamedia nc rdacarrier Econometría lemb Économétrie Econometrics Ökonometrie (DE-588)4132280-0 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Ökonometrie (DE-588)4132280-0 s DE-604 Erscheint auch als Online-Ausgabe 978-3-540-76516-5 http://d-nb.info/985929715/04 Inhaltsverzeichnis Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016233111&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016233111&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext
spellingShingle	Baltagi, Badi H. 1954- Econometrics Econometría lemb Économétrie Econometrics Ökonometrie (DE-588)4132280-0 gnd
subject_GND	(DE-588)4132280-0 (DE-588)4123623-3
title	Econometrics
title_auth	Econometrics
title_exact_search	Econometrics
title_exact_search_txtP	Econometrics
title_full	Econometrics Badi H. Baltagi
title_fullStr	Econometrics Badi H. Baltagi
title_full_unstemmed	Econometrics Badi H. Baltagi
title_short	Econometrics
title_sort	econometrics
topic	Econometría lemb Économétrie Econometrics Ökonometrie (DE-588)4132280-0 gnd
topic_facet	Econometría Économétrie Econometrics Ökonometrie Lehrbuch
url	http://d-nb.info/985929715/04 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016233111&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016233111&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT baltagibadih econometrics

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