Many empirical researchers yearn for an econometricmodel that better explains their data. Yet these researchersrarely pursue this objective for fear of thestatistical complexities involved in specifying thatmodel. This book is intended to alleviate those anxietiesby providing a practical methodology that anyonefamiliar with regression analysis can employamethodology that will yield a model that is both moreinformative and is a better representation of the data.This book outlines simple, practical proceduresthat can be used to specify a model that better explainsthe data. Such procedures employ the use ofpurely statistical techniques performed upon a publiclyavailable data set, which allows readers to followalong at every stage of the procedure. Using theeconometric software Stata (though most other statisticalsoftware packages can be used as well), thisbook demonstrates how to test for model misspecificationand how to respecify these models in a practicalway that not only enhances the inference drawnfrom the results, but adds a level of robustness thatcan increase the researchers confidence in the outputgenerated. By following this procedure, researcherswill be led to a better, more finely tuned empiricalmodel that yields better results.
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Dr. Jeffrey A. Edwards is a Professor of Economics at North Carolina Agricultural and Technical State University. He is the author of dozens of publications, an editor of the Economics Collection at Business Expert Press, an assistant editor for the Journal of Economics (MVEA), and sits on the advisory board for Applied Econometrics and International Development. He has a PhD in Economics with a field major in Econometrics.
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Paperback. Zustand: New. 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. Bestandsnummer des Verkäufers LU-9781606499740
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Paperback. Zustand: New. 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. Bestandsnummer des Verkäufers LU-9781606499740
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