Building better econometric models using cross section and panel data için kapak resmi
Başlık:
Building better econometric models using cross section and panel data
Yazar:
Edwards, Jeffrey A., author
ISBN:
9781606499740

9781606499757
Yazar Ek Girişi:
Basım Bilgisi:
First edition
Fiziksel Tanımlama:
xiii, 98 pages ; 23 cm
Seri:
Business expert press economics collection

Economics collection
İçerik:
1. What is a statistically adequate model and why is it important? -- 2. Basic misspecifications -- 3. Misspecifications for the more advanced reader -- 4. Original specification and drawing inference from it: two related models -- 5. Basic misspecification testing and respecification: the cross-sectional case -- 6. Variance heterogeneity: the cross-sectional case -- 7. Basic misspecification testing and respecification: the panel data case -- 8. Variance heterogeneity: the panel data case -- 9. Consistent and balanced panels -- 10. Dynamic parametric heterogeneity -- Conclusion -- References -- Index
Özet:
Many empirical researchers yearn for an econometric model that better explains their data. Yet these researchers rarely pursue this objective for fear of the statistical complexities involved in specifying that model. This book is intended to alleviate those anxieties by providing a practical methodology that anyone familiar with regression analysis can employ-a methodology that will yield a model that is both more informative and is a better representation of the data. This book outlines simple, practical procedures that can be used to specify a model that better explains the data. Such procedures employ the use of purely statistical techniques performed upon a publicly available data set, which allows readers to follow along at every stage of the procedure. Using the econometric software Stata (though most other statistical software packages can be used as well), this book demonstrates how to test for model misspecification and how to respecify these models in a practical way that not only enhances the inference drawn from the results, but adds a level of robustness that can increase the researcher's confidence in the output generated. By following this procedure, researchers will be led to a better, more finely tuned empirical model that yields better results.
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Kitap EKOBKN0001080 330.015195 EDW 2014
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