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Probability, Econometrics and Truth: The Methodology of Econometrics Hardcover – December 4, 2000

ISBN-13: 978-0521553599 ISBN-10: 0521553598 Edition: 1st

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Product Details

  • Hardcover: 322 pages
  • Publisher: Cambridge University Press; 1 edition (December 4, 2000)
  • Language: English
  • ISBN-10: 0521553598
  • ISBN-13: 978-0521553599
  • Product Dimensions: 9.1 x 5.9 x 1.2 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Best Sellers Rank: #3,842,432 in Books (See Top 100 in Books)

Editorial Reviews

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'A terrible gap has opened up in recent years between economists and econometricians, which has even resulted in some universities in an organisational separation of teaching and research in the two fields. Econometrics has become so technical that many economies have virtually abandoned the hope of mastering it and modern economies, on the other hand, seem to most econometricians to be a thousand miles removed from their abiding concern with the problems of inductive inference. What is needed to improve communication between the two camps is more understanding of econometrics among economists but, equally, more grasp of economics among econometricians. Hugo Keuzenkampf fulfils the latter requirement: here is an econometrician, well versed in the philosophy of economics, who views the issues of probability theory from the standpoint of an economist rather than a statistician. I have rarely read a book on econometric methodology from which I have learned so much. Econometrics cannot test, it can only estimate, says Keuzenkampf. This is a thesis I find hard to swallow but as such is the quality of his argument that he has almost convinced me of it (and I say this as one who is not dealt with too kindly in the pages that follow).' Mark Blaug, University of Exeter

'This book provides valuable discussions of central philosophical topics, e.g. induction, causation, simplicity, definitions of probability, alternative approaches to statistical inference, etc. with many references to the works of leading authorities in many fields. Then this important material, which is woefully lacking in econometrics texts, is related to past and current econometric research in a penetrating manner. Keuzenkampf is to be congratulated for providing us with a well-written, knowledgeable and illuminating discussion of fundamental issues. His book will be of great interest not only to econometricians but also to anyone interested in the foundations of statistics and its uses in economics and other sciences.' Arnold Zellner, H. G. B. Alexander Distinguished Service Professor Emeritus of Economics and Statistics, University of Chicago

'... will become a classic of the literature, his criticisms of the philosophers are first rate and original, in particular his discussion of Popper. His survey takes into account all the recent developments, recounts them accurately and mercilessly highlights their weakpoints. Technical details are kept to a necessary minimum, and skilfully deployed where needed.' Professor Colin Howson, London School of Economics

'The book is excellent reading.' Computing Reviews

Book Description

When John Maynard Keynes likened Jan Tinbergen's early work in econometrics to black magic and alchemy, he was expressing a widely held view of a new discipline. However, even after half a century of practical work and theorising by some of the most accomplished social scientist's, Keynes' comments are still repeated today. This book assesses the foundations and development of econometrics and sets out a basis for the reconstruction of the foundations of econometric inference by examining the various interpretations of probability theory which underlie econometrics.

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2 of 2 people found the following review helpful By A. J. Sutter on December 26, 2013
Format: Paperback Verified Purchase
The author of this book (HK) displays a terrific command over a wide range of literature in the philosophy of science, probability theory, statistical inference, and econometrics (EM). There's no question that his scholarship is deep, and that the book is a useful reference. Its critique of Popperian falsificationism is especially sharp. HK even has a dry sense of humor that he indulges from time to time (see, e.g., the entries for John Maynard Keynes and John Neville Keynes in the "Personalia" at the back).

The casual reader should be aware, though, that the book is also a difficult read, especially if you aren't an econometrician. The book had its origins as a Ph.D. thesis, and therefore was addressed to an expert audience; a good deal of technical jargon is taken for granted (e.g., noninformative vs. informative priors and Wald test, to choose a couple of examples at random). I came to the book already knowing a little bit about philosophy of science, probability theory and its history, and the basic idea of significance testing, and had skimmed through a fair number of applied EM studies, but there were definitely several passages about statistical tests that I had to take on faith. The prose style aims at efficiency rather than pedagogical clarity or charm.

The gist of the book's argument seems to be that what most people expect of EM -- such as that it can be used to verify or falsify economic theory -- is something that it's not capable of delivering, and that most EM practitioners are pretty oblivious to the reasons why this is the case. The author proposes that EM be used as part of a positivist program in economics, providing explanations that are good enough for making predictions, without necessarily presenting a "true" picture of what's going on in the economy.
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5 of 8 people found the following review helpful By Michael Emmett Brady on July 10, 2004
Format: Hardcover Verified Purchase
This book is already a classic.Keuzenkamp(K)blends the philosophy and history of probability and statistics with that of econometrics in such a skillful fashion that the technically trained reader(upper division courses in mathematical statistics,probability,econometrics and philosophy)will want to start reading it over again as soon as he finishs the book the first time.K correctly realizes that the goal of econometrics can only be that of estimating and not testing.K correctly shows that econometrics should be founded in the positivist(logical empiricist)tradition.Finally,an academic economist gives J M Keynes's arguments,made by Keynes in his debate with Tinbergen over the ability of econometricians to Test(with a capital T as in Truth) different theories of the business cycle,their just due.There is only one small(very small)quibble.On pages 272-273,K states:"Furthermore, an investigator may try different prior distributions in order to obtain upper and lower limits in probabilistic inference(this approach is proposed by Good and Leamer)".In fact,J M Keynes was the first advocate of this approach in Part V of A Treatise on Probability.The interested reader can find Keynes's interval approach in chapters 5,10,15,16,17,20,22,29 and 30.K has destroyed the myth,created by many philosophically illiterate economists and econometricians over the last 60-65 years,that Keynes's knowledge about mathematics and statistics was "rusty" and that he was just trying to shoot the sound ideas of other researchers "full of holes" because he didn't understand what they were doing.Keynes understood only to well.
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