- Tapa dura: 608 páginas
- Editor: McGraw-Hill Higher Education; Edición: 4 (1 de diciembre de 1996)
- Idioma: Inglés
- ISBN-10: 0079131212
- ISBN-13: 978-0079131218
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Econometric Methods (Inglés) Tapa dura – 1 dic 1996
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A classic text in the field, this new edition features a new co-author and provides a well-balanced and comprehensive study of current econometric theory and practice for undergraduate or graduate study. Traditional topics are carefully blended with newer techniques and trends. While the authors of this text assume students have taken a basic course in statistics, they provide a complete appendix on basic statistical theory for those who may need a refresher. In addition, the authors include in an appendix a review of all relevant topics in matrix algebra. Includes data disk.
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The authors cover regression, correlation and least squares in Chapter 1, starting with the simplest linear regression involving a single regressor variable. This allows for an easy introduction to the basic concepts that provide the foundation for what is to come. Chapter 2 introduces the idea of using time as regressor variable. This is a natural lead-in to the more sophisticated time series models of later chapters. It presents important econometric concepts such as elasticity. It also provides some probability theory and time series theory.
Multiple linear regression is then introduced in Chapter 3 along with the important concepts of partial correlation, the Gauss-Markov theorem and variable selection criteria. Also, parameter restrictions are considered in Chapter 3. Chapter 4 includes diagnostic checking of models and the trick of introducing dummy variables into the model to handle dichotomous and categorical variables.
The material becomes more difficult and there is an increase in the mathematical sophistication in Chapter 5. More realistic econometric models enter the discussion and the techniques of maximum likelihood, generalized least squares and Lagrange Multipliers are needed. Instrumental variables are introduced to handle such problems as the error in variables model. The technique of two stage least squares is also introduced here. Basic time series ideas and theory were introduced in Chapter 2 but first really get exploited in Chapter 6 where the concepts of heteroscadasticity and autocorrelation are introduced. Formal univariate time domain analysis of time series including the ARIMA models and trending methods are covered in Chapter 7. More complications and advanced theory are in Chapter 8.
In Chapter 9, the subject of simultaneous equations is introduced. Generalized Method of Moment methods are presented in Chapter 10 as a reasonable and simple estimation approach that is valid in large samples.
Freedman, Navidi, Peters among others have pointed out that the estimators of standard error for parameters in many of the standard econometric methods depend on asymptotic theory and often are very poor for practical problem sizes. They have shown that bootstrap methods can provide much better estimates. It is therefore nice to see that these authors recognize the importance of these resampling methods They devote a full chapter to them. Chapter 11 "A Smorgasbord of Computationally Intensive Methods" covers such resampling techniques as permutation tests, the bootstrap ("nonparametric")and the parametric bootstrap and other computer-intensive methods such as nonparametric density estimation and regression.
Other problems that are unique to econometrics are covered in Chapters 12 and 13. Also included are appendices on matrix algebra and basic statistics along with useful statistical tables. The book also includes a diskette with data examples in ASCII files.
Other reviewers have talked about its content, so I will express my opinion only.
Its audience is primarily for undergraduate students taking the first course in Econometrics. For this audience, it is difficult to find a competitor, because the book has everything you need to run a regression in a very straighforward way. That's why sometimes the book gets dry. However, it's fair to say that it is perfectly feasible to learn from it.
Yes, the matrix notation make the things difficult, but there is no other way if you want to learn well Econometrics.
The sequence of tests are presented very well.
Although overall the 4th. edition is better than the 3rd., I think the authors should have left the chapter on matrix in the body of the book and not in the appendix.
I'd say that this book is even better than Greene, and the next book to be read is Ruud.