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Learning and practicing econometrics / William E. Griffiths, R. Carter Hill, George G. Judge

By: Contributor(s): Publication details: New York : John Wiley, c1993Description: xxv, 866 p. : ill. ; 26 cmISBN:
  • 0471513644
Subject(s): DDC classification:
  • 330.015195 GRI
Contents:
- Pt VI. Specifying and estimating economic and statistical models with feedback mechanisms. Ch. 18. An introduction to simultaneous equation econometric models. Ch. 19. Estimation and inference for the simultaneous equations model. Appendix 19A. A more efficient estimator? Appendix 19B. An application of a simultaneous equations model. - Pt. VII. Time-series and dynamic economic models. Ch. 20. Univariate time-series analysis and forecasting. Ch. 21. Bivariate and multivariate time-series models. - Pt. VIII. Econometric topics II. Ch. 22. Nonlinear least squares. Appendix 22A. Estimation of moving average models. Ch. 23. Models with discrete dependent variables. Appendix 23A. A statistical model of choice. - Pt IX. Bayesian estimation and inference. Ch. 24. The Bayesian approach to estimation and inference : some basic definitions, concepts, and applications. Appendix 24A. Bayes' rule. Ch. 25. The Bayesian approach to using sample and nonsample information in the estimation of relationships between economic variables. - Pt. X. Economic data sources and the writing task. Ch. 26. Economic data sources, guidelines for choosing a research project, and the writing of a research report. - Statistical tables. - Index.
- Pt. III. General linear statistical model. Ch. 9. A general linear statistical model : model specification and estimation. Ch. 10. Inference in the general linear statistical model. Appendix 10A. Partial derivatives revisited. Appendix 10B. The F random variable. Appendix 10C. Testing general linear hypotheses. Ch. 11 Combining sample and nonsample infromation and further applications of the general linear statistical model. Appendix 11A. The restricted leastsquares estimator for combining sample and nonsample information. - Pt. IV. Econometric topics I. Ch. 12. Dummy variables and varying coefficient models. Ch. 13. Collinear economic variables. Ch. 14. Large sample theory and models with random regressors. Appendix 14A. Consistency, random regressors and instrumental variable estimation in the general linear statistical model. - Pt. V. Linear statistical models with a general error covariance matrix. Ch. 15. Heteroskedastic errors. Ch. 16. An autocorrelated error model. Ch. 17. Estimating the parameters of a set of errror related economic relations. Appendix 17A. A general SUR formulation. Appendix 17B. Combining cross-sectional and time-series data.
Ch. 1. Why is econometrics necessary? - Pt. I. The foundations of estimation and inference. Ch. 2. Some basic ideas : statistical concepts for economists. Appendix 2A. Summation operations. Appendix 2B. The geometry of integration. Ch. 3. Statistical inference I : estimating the mean and variance of a population. Appendix 3A. The derivative : geometry and interpretation. Appendix 3B. Representing the sampling process using a new notation. Ch. 4. Statistical inference II : interval estimation and hypothesis tests for the mean of a normal population. Appendix to Pt. I. review-summary of chapters 2 to 4 . - Pt II. The simple linear statistical model. Ch. 5. Simple regression : economic and statistical model specification and estimation. Appendix 5A. Elasticities. Appendix 5B. Partial derivations and the minimum or maximum of a multivariate function. Appendix 5C. The inverse of a matrix. Ch. 6. Inference in the simple regression model : estimator sampling characteristics and properties. Ch. 7. Inference in the simple regression model : interval estimation, hypothesis testing, and prediction. Appendix 7A. Linear algebra specificaitons and derivations in prediction. Ch. 8. The simple linear statistical model : choosing the functional form, reporting results, and carrying through and econometric analysis. Appendix 8A. The derivative revisited. Appendix to Pt. II. Review-summary of chapters 5 to 8.
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 330.015195 GRI (Browse shelf(Opens below)) 1 Available TBSxx,34006,03,AD 5000011495

Includes bibliographical references and index.

- Pt VI. Specifying and estimating economic and statistical models with feedback mechanisms. Ch. 18. An introduction to simultaneous equation econometric models. Ch. 19. Estimation and inference for the simultaneous equations model. Appendix 19A. A more efficient estimator? Appendix 19B. An application of a simultaneous equations model. - Pt. VII. Time-series and dynamic economic models. Ch. 20. Univariate time-series analysis and forecasting. Ch. 21. Bivariate and multivariate time-series models. - Pt. VIII. Econometric topics II. Ch. 22. Nonlinear least squares. Appendix 22A. Estimation of moving average models. Ch. 23. Models with discrete dependent variables. Appendix 23A. A statistical model of choice. - Pt IX. Bayesian estimation and inference. Ch. 24. The Bayesian approach to estimation and inference : some basic definitions, concepts, and applications. Appendix 24A. Bayes' rule. Ch. 25. The Bayesian approach to using sample and nonsample information in the estimation of relationships between economic variables. - Pt. X. Economic data sources and the writing task. Ch. 26. Economic data sources, guidelines for choosing a research project, and the writing of a research report. - Statistical tables. - Index.

- Pt. III. General linear statistical model. Ch. 9. A general linear statistical model : model specification and estimation. Ch. 10. Inference in the general linear statistical model. Appendix 10A. Partial derivatives revisited. Appendix 10B. The F random variable. Appendix 10C. Testing general linear hypotheses. Ch. 11 Combining sample and nonsample infromation and further applications of the general linear statistical model. Appendix 11A. The restricted leastsquares estimator for combining sample and nonsample information. - Pt. IV. Econometric topics I. Ch. 12. Dummy variables and varying coefficient models. Ch. 13. Collinear economic variables. Ch. 14. Large sample theory and models with random regressors. Appendix 14A. Consistency, random regressors and instrumental variable estimation in the general linear statistical model. - Pt. V. Linear statistical models with a general error covariance matrix. Ch. 15. Heteroskedastic errors. Ch. 16. An autocorrelated error model. Ch. 17. Estimating the parameters of a set of errror related economic relations. Appendix 17A. A general SUR formulation. Appendix 17B. Combining cross-sectional and time-series data.

Ch. 1. Why is econometrics necessary? - Pt. I. The foundations of estimation and inference. Ch. 2. Some basic ideas : statistical concepts for economists. Appendix 2A. Summation operations. Appendix 2B. The geometry of integration. Ch. 3. Statistical inference I : estimating the mean and variance of a population. Appendix 3A. The derivative : geometry and interpretation. Appendix 3B. Representing the sampling process using a new notation. Ch. 4. Statistical inference II : interval estimation and hypothesis tests for the mean of a normal population. Appendix to Pt. I. review-summary of chapters 2 to 4 . - Pt II. The simple linear statistical model. Ch. 5. Simple regression : economic and statistical model specification and estimation. Appendix 5A. Elasticities. Appendix 5B. Partial derivations and the minimum or maximum of a multivariate function. Appendix 5C. The inverse of a matrix. Ch. 6. Inference in the simple regression model : estimator sampling characteristics and properties. Ch. 7. Inference in the simple regression model : interval estimation, hypothesis testing, and prediction. Appendix 7A. Linear algebra specificaitons and derivations in prediction. Ch. 8. The simple linear statistical model : choosing the functional form, reporting results, and carrying through and econometric analysis. Appendix 8A. The derivative revisited. Appendix to Pt. II. Review-summary of chapters 5 to 8.

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