This text provides a unified treatment of modern econometric theory and practical econometric methods. The geometrical approach to least squares is emphasized, as is the method of moments, which is used to motivate a wide variety of estimators and tests. Simulation methods, including the bootstrap, are introduced early and used extensively. The book deals with a large number of modern topics. In addition to bootstrap and Monte Carlo tests, these include sandwich covariance matrix estimators, artificial regressions, estimating functions and the generalized method of moments, indirect inference, and kernel estimation. Every chapter incorporates numerous exercises, some theoretical, some empirical, and many involving simulation. Econometric Theory and Methods is designed for beginning graduate courses. The book is suitable for both one- and two-term courses at the Masters or Ph.D. level. It can also be used in a final-year undergraduate course for students with sufficient backgrounds in mathematics and statistics.
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"This is the best textbook of econometric theory to have emerged in a long while; and it deserves to find a place on the bookshelf of every instructor. It is bound to find favour with the students." Stephen Pollock, Queen Mary College, University of London
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Descrizione libro Cary, North Carolina, U.S.A.: Oxford Univ Pr, 2003. Soft cover. Condizione libro: New. International Edition. Absolutely Brand New Textbook. This is an International Edition Textbook. Fast shipping , 3-5 business days Delivery to US and Canada, 4-6 days delivery to EU and Asia countries via express service. Ship from Multiple Locations, including US, EU, ASIA for inventory purpose. We do not ship to PO/FPO/APO address. Printed in USA with High Quality Paper (not Indian edition due to B/W printing and poor quality paper). Book is printed in English, as the US edition. If US edition printed in color, our book printed in color too! Most international edition has different ISBN and Cover design. Occasionally. international textbooks may come with different exercises at the end of chapters. Some book may show some sales disclaimer word such as "Not for Sale or Restricted in US" on the cover page but it is absolutely legal to use in USA. Codice libro della libreria 12f019780195391053
Descrizione libro 2003. Hardcover. Condizione libro: New. 161mm x 40mm x 247mm. Hardcover. This text provides a unified treatment of modern econometric theory and practical econometric methods. The geometrical approach to least squares is emphasized, as is the method of moments,.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 768 pages. 1.220. Codice libro della libreria 9780195123722
Descrizione libro Oxford University Press. Condizione libro: New. Brand New. Codice libro della libreria 0195123727
Descrizione libro Condizione libro: New. This item is printed on demand. Codice libro della libreria 1728584-n
Descrizione libro Oxford University Press. Hardcover. Condizione libro: New. 0195123727 New Condition. Codice libro della libreria NEW4.0073796
Descrizione libro Oxford University Press, 2003. Condizione libro: New. Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: PrefaceData, Solutions, and Corrections1. Regression Models1.1. Introduction1.2. Distributions, Densities, and Moments1.3. The Specification of Regression Models1.4. Matrix Algebra1.5. Method-of-Moments Estimation1.6. Notes on Exercises1.7. Exercises2. The Geometry of Linear Regression2.1. Introduction2.2. The Geometry of Vector Spaces2.3. The Geometry of OLS Estimation2.4. The Frisch-Waugh-Lowell Theorem2.5. Applications of the FWL Theorem2.6. Influential Observations and Leverage2.7. Final Remarks2.8. Exercises3. The Statistical Properties of Ordinary Least Squares3.1. Introduction3.2. Are OLS Parameter Estimators Unbiased?3.3. Are OLS Parameter Estimators Consistent?3.4. The Covariance Matrix of the OLS Parameter Estimates3.5. Efficiency of the OLS Estimator3.6. Residuals and Error Terms3.7. Misspecification of Linear Regression Models3.8. Measures of Goodness of Fit3.9. Final Remarks3.10. Exercises4. Hypothesis Testing in Linear Regression Models4.1. Introduction4.2. Basic Ideas4.3. Some Common Distractions4.4. Exact Tests in the Classical Normal Linear Model4.5. Large-Sample Tests in Linear Regression Models4.6. Simulation-Based Tests4.7. The Power of Hypothesis Tests4.8. Final Remarks4.9. Exercises5. Confidence Intervals5.1. Introduction5.2. Exact and Asymptotic Confidence Intervals5.3. Bootstrap Confidence Intervals5.4. Confidence Regions5.5. Heteroskedasticity-Consistent Covariance Matrices5.6. The Delta Method5.7. Final Remarks5.8. Exercises6. Nonlinear Regression6.1. Introduction6.2. Method-of-Moments Estimators for Nonlinear Models6.3. Nonlinear Least Squares6.4. Computing NLS Estimates6.5. The Gauss-Newton Regression6.6. One-Step Estimation6.7. Hypothesis Testing6.8. Heteroskedasticity-Robust Tests6.9. Final Remarks6.10. Exercises7. Generalized Least Squares and Related Topics7.1. Introduction7.2. The GLS Eliminator7.3. Computing GLS Estimates7.4. Feasible Generalized Least Squares7.5. Heteroskedasticity7.6. Autoregressive and Moving-Average Processes7.7. Testing for Serial Correlation7.8. Estimating Models with Autoregressive Errors7.9. Specification Testing and Serial Correlation7.10. Models for Panel Data7.11. Final Remarks7.12. Exercises8. Instrumental Variables Estimation8.1. Introduction8.2. Correlation Between Error Terms and Regressors8.3. Instrumental Variables Estimation8.4. Finite-Sample Properties of IV Estimators8.5. Hypothesis Testing8.6. Testing Overidentifying Restrictions8.7. Durbin-Wu-Hausman Tests8.8. Bootstrap Tests8.9. IV Estimation of Nonlinear Models8.10. Final Remarks8.11. Exercises9. The Generalized Methods of Moments9.1. Introduction9.2. GMM Estimators for Linear Regression Models9.3. HAC Covariance Matrix Estimation9.4. Tests Based on the GMM Criterion Function9.5. GMM Estimators for Nonlinear Models9.6. The Method of Simulated Moments9.7. Final Remarks9.8. Exercises10. The Method of Maximum Likelihood10.1. Introduction10.2. Basic Concepts of Maximum Likelihood Estimation10.3. Asymptotic Propertied of ML Estimators10.4. The Covariance Matrix of the ML Estimator10.5. Hypothesis Testing10.6. The Asymptotic Theory of the Three Classical Tests10.7. ML Estimation of Models with Autoregressive Errors10.8. Transformations of the Dependent Variable10.9. Final Remarks10.10. Exercises11. Discrete and Limited Dependent Variables11.1. Introduction11.2. Binary Response Models: Estimation11.3. Binary Response Models: Inference11.4. Models for More than Two Discrete Responses11.5. Models for Count Data11.6. Models for Censored and Truncated Data11.7. Sample Selectivity11.8. Duration Models11.9. Final Remarks11.10. Exercises12. Multivariate Models12.1. Introduction12.2. Seemingly Unrelated Linear Regressions12.3. Systems of Nonlinear Regressions12.4. Linear Simultaneous Equations Models12.5. Maximum Likelihood Estimation12.6. Nonlinear Simultaneous Equations Models12.7. Final Remarks12.8. Appendix: Detailed Results on FIML and LIM. Codice libro della libreria ABE_book_new_0195123727
Descrizione libro Oxford University Press, 2003. Hardcover. Condizione libro: New. Codice libro della libreria P110195123727
Descrizione libro 2003. Hardcover. Condizione libro: New. 161mm x 40mm x 247mm. Hardcover. This text provides a unified treatment of modern econometric theory and practical econometric methods. The geometrical approach to least squares is emphasized, as is the metho.Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. 768 pages. 1.220. Codice libro della libreria 9780195123722
Descrizione libro Oxford University Press, USA, 2003. Hardcover. Condizione libro: New. Codice libro della libreria DADAX0195123727
Descrizione libro Oxford University Press, 2003. Hardcover. Condizione libro: New. book. Codice libro della libreria 0195123727