Free Kindle A Guide To Econometrics. 6th Edition ebooks Download
This is the perfect (and essential) supplement for all econometrics classes--from a rigorous first undergraduate course, to a first master's, to a PhD course. Explains what is going on in textbooks full of proofs and formulas Offers intuition, skepticism, insights, humor, and practical advice (dos and don’ts) Contains new chapters that cover instrumental variables and computational considerations Includes additional information on GMM, nonparametrics, and an introduction to wavelets
Paperback: 598 pages
Publisher: Wiley-Blackwell; 6 edition (February 19, 2008)
Language: English
ISBN-10: 1405182571
ISBN-13: 978-1405182577
Product Dimensions: 7.4 x 1.2 x 9.6 inches
Shipping Weight: 2.3 pounds (View shipping rates and policies)
Average Customer Review: 4.6 out of 5 stars See all reviews (57 customer reviews)
Best Sellers Rank: #225,875 in Books (See Top 100 in Books) #103 in Books > Business & Money > Economics > Econometrics #1436 in Books > Textbooks > Business & Finance > Economics
Econometrics is now a respectable topic, both in the financial industry, where it is used extensively, and in academia. Like most efforts to model phenomena in the real world, especially those that attempt to model the behavior of human agents, econometrics has had its share of critics. These critics pointed out some of the failures of the econometric models, and some of their criticism was justified. However, there have been successes as well, if one realizes that the success of a model should be determined by what a model is actually developed for.The author of this book is fully aware of what modeling is all about, and gives a very interesting overview of the major mathematical techniques used in econometrics. He characterizes econometrics as a study of how to obtain a good estimator in a situation or problem at hand that must be estimated. He recognizes that any criteria for what is "good" is somewhat subjective, but a "good" estimator it is generally believed must be computationally cost effective, unbiased, efficient, and robust. The author gives detailed discussions of these criteria in the book, and throughout most of the book more detailed mathematical derivations take place in the notes at the end of each chapter. The discussions can be a bit wordy at times in places outside of the notes for this reason. The book includes of course discussions on least squares, nonlinear regression, and Bayesian estimation of parameters. These are all topics that are fairly standard in the literature, but the author also includes discussions on topics such as neural networks and kernel estimation. An extensive list of exercises is included at the end of the book.
Throughout the 1970's, big-name sociologists with impeccable methodological and statistical credentials sought to persuade the discipline's journeymen that they should learn econometrics. The two most influential proponents of this view were the social statistics luminaries Hubert Blalock and Otis Dudley Duncan. Blalock was more optimistic than Duncan with regard to the ultimate payoff, but Duncan was more arrogantly dismissive of those who failed to heed his admonition.In response, sociology and related social science journals became much more densely quantitative. Many social scientists, as a result, felt as if they had been reduced to obslescence. After all, econometrics and the other new quantitative tools, especially path analysis, which had come to dominate the discipline were difficult topics under the best of circumstances, and most social scientists lacked the mathematical training to tackle the best known econometrics texts, such as those by Jack Johnston, Jan Kmenta, and Arthur Goldberger. Many social scientists had been introduced to the econometrics mainstay, regression analysis, but not in this highly technical form.Fortunately, the decade of the '70's also saw publication of Damodar Gujarati's introductory econometrics text, as well as the first edition of Peter Kennedy's Guide to Econometrics. Gujarati's book presented much the same material as his more insistently mathematical colleagues, but in a much more accessible form. His book could actually be used for self-instructional purposes, enabling less methodologically astute social scientists to finally figure out what was going on.
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