
Content by Michael Emmett...
Top Reviewer Ranking: 1,026,806
Helpful Votes: 7


Guidelines: Learn more about the ins and outs of Amazon Communities.

Reviews Written by Michael Emmett Brady "mandmbrady" (Bellflower, California ,United States)





1.0 out of 5 stars
Recycled academic journal articles do not make a good book, July 18 2004
Leeson(L)essentially is republishing a few past journal articles.He includes one new essay in an attempt to tie the book together.His discussion of the KeynesTinbergen exchange of 19391940 on the methodology of ecomometrics,as well as Tinbergen's belief that he could test different theories of the business cycle and correctly model expectations, is badly marred by his belief that other economists,like M. Friedman and R. Lucas ,whose partially correct analysis appeared in print 2040 years after the pathbreaking work of Keynes,deserves equal billing with Keynes's seminal contribution that should stand alone.A vastly superior treatment of these topics was published in 2000 by H.A.Keuzenkamp,titled "Probability,Econometrics and Truth",by Cambridge University Press.Strangely,L,whose book appeared over a year later,does not cite Keuzenkamp's book.Finally,the reader on a budget would do well to xerox the essay by H.Pesaran and P.Smith,titled"Keynes on Econometrics" contained in a book of essays called"Keynes's Economics:Methodological Issues",edited by Pesarsn and Lawson in 1985.L's book is simply not worth the money .If you are going to buy a book in this area ,buy Keuzenkamp's.Period.







3.0 out of 5 stars
A highly restricted and narrow view of probability, July 18 2004
The title of this book is somewhat misleading.A more appropriate title would have been"The Probabilistic Foundations of Modern Physics:A Historical,Mathematical and Philosophical Perspective (with an appendix on Bruno de Finetti)".von Plato takes a very narrow view of what "Modern" probability is.Essentially,it is the approach of some one like R. von Mises's place selection criteria supplemented and/or replaced by de Finetti's exchangeability criteria for dealing with a series or sequence of events.J M Keynes is mentioned three times in throwaway sentences.R Carnap gets a couple of throwaway sentences.Interval estimates and/or indeterminate or imprecise probabilities are not covered in this book.In conclusion,the title is a misnomer.







4.0 out of 5 stars
What happened to Frank P. Ramsey?J M Keynes?, July 17 2004
Salsburg(S) does an excellent job discussing the historical development of the field of statistics in the 20th century.He has a way of writing that blends current statistical theory with the development of statistics over time from a historical perspective with the individuals who made it all happen,such as NeymanPearson and Sir Ronald Fisher.In this book he is close to Ian Hacking in the manner in which he weaves his story.This reviewer has a few quibbles.First,in S's discussion of the personalist(subjectivist)theory of probability,only de Finetti and Savage are covered.Since Frank Ramsey's 1922 and 1926 contributions to the subjective theory of probability,unfortunately combined with error filled critiques of John Maynard Keynes's logical theory of probability,were published BEFORE the work of de Finetti and Savage,he definitely deserved to have a prominent place in any book dealing with the history of probability and statistics.Second,there are a number of errors made in the all to brief discussion of Keynes and his logical theory of probability in his 1921 book,A Treatise on Probability(TP).Contrary to S(p.112,p.305),Keynes never received a doctorate in philosophy for writing the TP because the TP is not a doctoral dissertation.The TP was a thesis submitted for a fellowship, successfully, in 1909 at Cambridge.Keynes added a Part V to his thesis in the period from 19101914 to complete his TP.S commits another error when he chacterizes Keynesian economic policy as the manipulation of monetary policy.It is the manipulation of both fiscal and monetary policy.Finally,Keynes's probabilities are primarily intervals with a lower and an upper bound,not ordinal rankings as suggested by S.S's flawed appraisel involves a failure to translate Keynes's definition of the term "nonnumerical",which means"not by a single numeral but by two numerals".Finally,S is in too much of a hurry to take the side of Neyman,a deductivist, in his debates with Fisher,an inductivist,about significance levels(pvalues) and confidence intervals.Neyman's justification for confidence intervals is badly flawed.It essentially boils down to an arbitrary "act of will" on the part of the researcher.Fisher,who was well acquanted with Keynes's logical theory of probability,realized that Neyman's "reasoning" was actually an evasion.Unfortunately,Fisher never was clear about his reservations .Fisher simply needed to come right out and say that a 95% confidence interval means that the researcher is 95% confident that the particular parameter,say the mean,lies in that interval.Of course,this conclusion follows from the proportional syllogism,which is part of the logical theory of probability.Neyman,who was a frequentist,ends up in a quagmire of his own creation because he did not want to allow any "inductive" concepts into his theory.







5.0 out of 5 stars
Again,Hacking gets it right except for Keynes's theory, July 15 2004
Moving from Pascal and Bernoulli in the 16th and 17th centuries through Keynes, Carnap,Ramsey, de Finetti and Heisenberg in the 20th century,Hacking(H)does a commendable job blending the philosophy and history of science with the history and philosophy of probability.H's tie in of Pascal's Wager and decision theory is just one example of his ability to connect the ideas of different centuries to each other.However,there is one small criticism that must be made.It is in regards to J M Keynes's logical theory of probability put forth in A Treatise on Probability(TP) in 1921.H bases his assessment of Keynes's theory on one chapter of the TP alone.That chapter,chapter 3,was to be regarded as an introduction only.Keynes's point was that,in general,a probability could not be measured by a single number or numeral alone,i.e.,probabilities were "nonnumerical"or not by a single numeral(number).In general,Keynes argued that most probabilities required TWO numbers to specify the probability estimate,a lower bound and an upper bound.In Part II of the TP Keynes refers to his theory of "approximation".In modern terminology,Keynes's interval estimates are "indeterminate" or"imprecise" probabilities.Given the above summary of Keynes's approach to probability,the following statement by H is incorrect and very misleading:"Indeed Keynes argued masterfully in Chapter 3 of his A Treatise on Probability that many comparisons of probability are necessarily qualitative and cannot be represented by real numbers."(Hacking,p.73)While it is true that most probabilities cannot be represented by A SINGLE REAL NUMBER,most probabilities can be represented by TWO REAL NUMBERS in Keynes's approach.A strictly qualitative approach would be practically useless.Probability would not be the guide to life.







3.0 out of 5 stars
Sahlin ignores the deficiencies in Ramsey's review of Keynes, July 14 2004
Sahlin(S)does an excellent job in assessing the positive aspects of Ramsey's substantial contributions to mathematics,philosophy,economics,logic,probability ,induction,pragmatism,decision theory,and the subjectivist approach to probability.Unfortunately,S does not do a very good job of assessing the deficiency that exists in some areas of Ramsey's work.A prime example would be Ramsey's two reviews of J M Keynes's 1921 book ,titled A Treatise on Probability.Ramsey wrote reviews in 1922 and 1926.Both of these reviews are based on a reading of the first four chapters of Keynes's book plus 34 pages,apparently selected by Ramsey at random ,from Parts IIV of the rest of Keynes's book.Ramsey made a major blunder in his interpretation of Keynes's definitions of nonnumerical and nonmeasurable in chapter III of the TP(1921).Keynes defined these terms to mean not by a single numeral or number and not by a single numerical relation,respectively.Instead,Keynes argued that it generally took TWO numbers to measure a probability,an upper bound and a lower bound.The exception was the case of positive symmetrical evidence.In this case a decision maker could resort to Keynes's superior version of the principle of nonsufficient reason,the principle of indifference,to calculate exact,precise,definite point estimate using a single numeral or number.Ramsey instead argued that Keynes meant that nonnumerical meant that no numbers could in general be used to specify a probability estimate.Thus, Ramsey talks about Keynes's "mysterious"nonnumerical probabilities and "mysterious"degrees of belief,which,according to Ramsey are also "nonnumerical".Ramsey(and S)failed to take Keynes's chapter III ,page 37 warning to the reader that he should wait until after he has finished Part II of the TP BEFORE HE DRAWS ANY CONCLUSIONS FROM chapter III.Keynes's technical discussions ,in chapters 15 and 17 of the TP on using Boole's approach to establish upper and lower bounds to estimate probabilities, were not read by Ramsey(orS).The result has been that philosophers,economists ,psychologists ,etc.have,for the last 7580 years,based their assessment of Keynes's TP on reviews that Bertrand Russell correctly,and very generously,characterised as having the LEAST value of any of Ramsey's work.







2.0 out of 5 stars
All probabilities are measurable by one or two numbers, July 11 2004
There is only one essay in this collection of essays that is without severe error and hence worth reading.It is the essay titled"Keynes on Econometrics"by H.Pesaran and R.Smith(PS).They do a first rate job in discussing Keynes's correct objections to Tinbergen's methodological foundations for econometrics.The reader should note that the PS essay has been replaced as the authoritative final word by H.Keuzenkamp's (2001)book titled"Probability,Econometrics and Truth".There are several errors made by PS. They are,first,that "Keynes rejected the frequency as well as the subjective interpretations of probability in favour of a ...logical theory...This 'logical' theory of probability,together with his insistence that most probability relations are not measurable...".Keynes never rejected either theory.Keynes held that they were both special theories that were sound and valid in a limited number of cases.The logical theory of probability was a general theory that included these other theories within it.Keynes did not object at all to Ramsey's suggested use of betting quotients in order to estimate probability bounds.Likewise ,all Keynesian probabilities can be measured by either one number or TWO NUMBERS.PS have,like Ramsey,misinterpreted the meaning Keynes gave to the terms"nonnumerical"and/or"nonmeasurable"(PS,p.144).This same error is committed in essays written by T.Lawson,A.and S.Dow,G. Hodgson and A.Carabelli.Secondly,the claim that"...the lesson of The General Theory is that there are no stable economic relations."(p.147),ignores the fact that the consumption function is stable.It is the investment function that is highly unstable and volatile over time due to the fact that such irreversible spending on plant and equipment is highly susceptable to becoming obsolete,due to constant innovation and technological change,before the owner of the physical capital good has been able to recover any substantial portion of his huge initial fixed cost.In conclusion,PS also correct the many errors about the KeynesTinbergen debate which are incorporated into a number of essays in the same book in which the PS essay appears.The PS essay thus refutes the essays by J.Klant,J.Pheby and T.Lawson.







5.0 out of 5 stars
The Best Book Written On Econometrics,Philosophy,andJMKeynes, July 10 2004
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 272273,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 6065 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.







0 of 1 people found the following review helpful
1.0 out of 5 stars
Keynes's logical theory of probability is a formal theory, July 7 2004
Carabelli(C)is in way over her head.Her problems start with her absorption of the error filled reviews of Keynes's A Treatise on Probability(TP) by Frank Ramsey in 1922 and 1926 concerning the definitions of the terms"nonnumerical" and "nonmeasurable".This is combined with her own misreading of chapter 3 of the TP.Chapter 3 was meant to serve as an introduction on the problems involved in measuring probabilities.The reader was supposed to also read chapters 5,10,15,16 and 17 of the TP.Such a reader would soon realize that by "nonnumerical"Keynes meant that TWO numbers ,not one,were needed in order to estimate most probabilities.Probability estimates were in general interval(set) estimates.Carabelli comes to the nonsensical conclusion that nonnumerical meant that NO NUMBERS could be used in general to estimate probabilities unless the Principle of Indifference held.The only remaining method of dealing with probabilities was to use ordinal rankings,which could only be done some of the time.C concludes that Keynes was "antimathematical" .Her major conclusion is the following:"...the logicist interpretation of Keynes's theory appears to be based on a hasty reading of Keynes's text.In various passages Keynes did indeed speak of the "logical"character of his notion of probability.But this fact does not mean that...it was a logic of the formal type.In fact,it was an ordinary discourse logic."(Carabelli,page 145)Supposedly, Keynes had already figured out and applied the "later"philosophy of Ludwig Wittgenstein(ordinary language or discourse) in 1914 while interacting with the "early" Wittgenstein ,who accepted a logical approach to probability ,during the time Keynes was writing the TP.The only person who accepts this truly strange and incomprehensible argument is C.All other writers on Keynes's logical theory of probability recognize the basic fact that it was a formal theory.







1 of 2 people found the following review helpful
1.0 out of 5 stars
Keynes's Formal Model Appears in Chapters 3,20 and 21, July 7 2004
Coates(C)is simply mathematically illiterate.C's argument is that Keynes presents no formal mathematical representation of his theory of Effective Demand in the General Theory because he wanted to use ordinary language to express his main theoretical concepts.Supposedly,Keynes went to great pains to use a vocabulary that avoids any attempt at a theoretical analysis using the technical tools of microeconomic analysisthe theory of the firm industry,profit maximization and utility maximizing behavioral assumptions.This is because Keynes had a deep understanding and appreciation for the socalled "ordinary language"philosophy of the "later" Ludwig Wittgenstein.Contrary to C,Keynes presents a complete formal technical model of his theory in chapters 10,20 and 21 of the General Theory.He then compares and contrasts his formal theory with the formal theory presented by Pigou in chapters 810 of The Theory of Unemployment,Part II,(1933)in the appendix to chapter 19 of the General Theory.In conclusion ,this is one of the worst books ever written on the General Theory by an author who appears to have read only the first four chapters of Keynes's book.







1 of 1 people found the following review helpful
4.0 out of 5 stars
Ellsberg's Ambiguity is the Same as Keynes's Weight Index, July 6 2004
Ellsberg does an excellent job of demonstrating the very special nature of the Ramseyde FinettiSavage(RFS) subjectivist approach to both probability and decision making.The RFS approach requires the decision maker to be able to specify precise,exact,definite single number answers for all probability estimates.This is supposedly accomplished by an elicitation procedure based on the requirement that every decision is to be modeled as if it were a betting situation.Ellsberg shows that many decision makers will not accept such a betting quotients modeling approach to specifying numerical probabilities because such individuals make imprecise probability assessments.These estimates of probability are intervals.Each interval is made up of a lower probability and an upper probability.Only in the special case where the lower probability equals the upper probability will the RFS approach be sound.Ellsberg makes it very clear that he is building on the work of Good,Koopman,Smith and others in emphasizing the importance of intervals in specifying probability assessments in real world situations.Ellsberg's contribution is in terms of explaining why the vast majority of decision makers rely on intervals and not on precise probability estimates.Ellsberg's answer is that both the quantity and quality of relevant information, data or knowledge is ambiguous ,unclear,conflicting,incomplete or not available.Ambiguity represents a second dimension of decision making.This means that the RFS approach to probability estimation and the Subjective Expected Utility(SEU)theory built upon it is a special limiting case that only obtains when the information base is clear ,complete, available, and nonconflicting.Ellsberg operationalizes his concept of ambiguity by defining a variable called rho,where 0<=rho<=1.Rho is "...a number between 0 and 1 reflecting the decisionmaker's degree of confidence in or reliance upon the estimated distribution... in a particular decision problem."(Ellsberg,2001,p.194).Ellsberg then incorporates rho as a linear decision weight in a"resticted Bayes/Hurwicz criterion",i.e.,a decision rule.Unfortunately, little of Ellsberg's work is truly original.Practically everything that Ellsberg does had already been done by J.M. Keynes in his A Treatise on Probability in 1921.Unfortunately, due to the misplaced influence of two error filled reviews of Keynes's approach by Frank Ramsey,95% of the reviews being based on the first 4 chapters of Keynes's book,Keynes's imprecise interval approach,which Keynes called nonnumerical or nonmeasurable probabilities , in order to emphasis the need to use TWO numerals in the estimation of a probability,came to be looked on as some "mysterious nonnumerical probabilities" that did not obey the laws of probability.Finally,in chapter 26 of A Treatise on Probability , on page 315 and page 315,footnote 2,Keynes specifies an index w ,where w equals the weight of the evidence and measures the degree of the completeness of the relevant evidence upon which the probability estimates are based.W is defined as 0<=w<=1.Keynes then incorporates this index into a decision theoretic criterion rule which he called "a conventional coefficient of weight and risk."Letting c designate the "conventional coefficient",the goal of Keynes's decision rule is to maximize cA,where A is equal to some outcome.In this reviewer's opinion,Keynes's decision rule is greatly superior to Ellsberg's rule since Keynes correctly incorporates nonlinearity into his weighting function.It is the nonlinearity effect which is creating all of the anomalies and paradoxes in standard SEU theory.Both Ellsberg's and Keynes's work goes a very long way towards correcting these deficiencies.However,Keynes got to the mountain top first.


