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description= 15 posts published by Lars Syll during April 2016;
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uctural econometric model sem the real problem with any attempt at synthesis is that a sem is always going to be vulnerable to the key criticism in lucas and sargent 1979 without a completely consistent microfounded theoretical base there was the near certainty of inconsistency brought about by inappropriate identification restrictions so why does this matter if mainstream academic macroeconomists were seduced by anything it was a methodology a way of doing the subject which appeared closer to what at least some of their microeconomic colleagues were doing at the time and which was very different to the methodology of macroeconomics before the new classical counterrevolution the old methodology was eclectic and messy juggling the competing claims of data and theory the new methodology was rigorous unlike brad delong wren lewis seems to be impressed by the rigour brought to macroeconomics by the new classical counterrevolution and its rational expectations microfoundations and lucas critique it is difficult to see why wren lewis s portrayal of rational expectations is not as innocent as it may look rational expectations in the neoclassical economists s world implies that relevant distributions have to be time independent this amounts to assuming that an economy is like a closed system with known stochastic probability distributions for all different events in reality it is straining one s beliefs to try to represent economies as outcomes of stochastic processes an existing economy is a single realization tout court and hardly conceivable as one realization out of an ensemble of economy worlds since an economy can hardly be conceived as being completely replicated over time it is to say the least very difficult to see any similarity between these modelling assumptions and the expectations of real persons in the world of the rational expectations hypothesis we are never disappointed in any other way than as when we lose at the roulette wheels but real life is not an urn or a roulette wheel and that s also the reason why allowing for cases where agents make predictable errors in the new keynesian models doesn t take us a closer to a relevant and realist depiction of actual economic decisions and behaviours if we really want to have anything of interest to say on real economies financial crisis and the decisions and choices real people make we have to replace the rational expectations hypothesis with more relevant and realistic assumptions concerning economic agents and their expectations than childish roulette and urn analogies rigorous and precise new classical models and that goes for the new keynesian variety too cannot be considered anything else than unsubstantiated conjectures as long as they aren t supported by evidence from outside the theory or model to my knowledge no in any way decisive empirical evidence has been presented no matter how precise and rigorous the analysis and no matter how hard one tries to cast the argument in modern mathematical form they do not push economic science forwards one single millimeter if they do not stand the acid test of relevance to the target no matter how clear precise rigorous or certain the inferences delivered inside these models are they do not per se say anything about real world economies proving things rigorously in mathematical models is at most a starting point for doing an interesting and relevant economic analysis forgetting to supply export warrants to the real world makes the analysis an empty exercise in formalism without real scientific value the real tail wagging 20 apr 2016 at 19 32 posted in economics 3 comments keynes s intellectual revolution was to shift economists from thinking normally in terms of a model of reality in which a dog called savings wagged his tail labelled investment to thinking in terms of a model in which a dog called investment wagged his tail labelled savings james meade to my sons and daughters personal 19 apr 2016 at 14 55 posted in economics varia comments off on to my sons and daughters personal at the end of every principle is a promise this one is for you david tora linnea amanda and sebastian pitfalls of meta analysis 19 apr 2016 at 10 28 posted in statistics econometrics 1 comment including all relevant material good bad and indifferent in meta analysis admits the subjective judgments that meta analysis was designed to avoid several problems arise in meta analysis regressions are often non linear effects are often multivariate rather than univariate coverage can be restricted bad studies may be included the data summarised may not be homogeneous grouping different causal factors may lead to meaningless estimates of effects and the theory directed approach may obscure discrepancies meta analysis may not be the one best method for studying the diversity of fields for which it has been used glass and smith carried out a meta analysis of research on class size and achievement and concluded that a clear and strong relationship between class size and achievement has emerged 10 the study was done and analysed well it might almost be cited as an example of what meta analysis can do yet the conclusion is very misleading as is the estimate of effect size it presents between class size of 40 pupils and one pupil lie more than 30 percentile ranks of achievement such estimates imply a linear regression yet the regression is extremely curvilinear as one of the authors figures shows between class sizes of 20 and 40 there is absolutely no difference in achievement it is only with unusually small classes that there seems to be an effect for a teacher the major result is that for 90 of all classes the number of pupils makes no difference at all to their achievement the conclusions drawn by the authors from their meta analysis are normally correct but they are statistically meaningless and particularly misleading no estimate of effect size is meaningful unless regressions are linear yet such linearity is seldom investigated or if not present taken seriously h j eysenck systematic reviews in sciences are extremely important to undertake in our search for robust evidence and explanations simply averaging data from different populations places and contexts is not physics and economics 17 apr 2016 at 12 15 posted in economics 5 comments from the times of galileo and newton physicists have learned not to confuse what is happening in the model with what instead is happening in reality physical models are compared with observations to prove if they are able to provide precise explanations can one argue that the use of mathematics in neoclassical economics serves similar purposes gillies s conclusion is that while in physics mathematics was used to obtain precise explanations and successful predictions one cannot draw the same conclusion about the use of mathematics in neoclassical economics in the last half century this analysis reinforces the conclusion about the pseudo scientific nature of neoclassical economics given the systematic failure of predictions of neoclassical economics francesco sylos labini is a researcher in physics his book is to be highly recommended reading to anyone with an interest in understanding the pseudo scientific character of modern mainstream economics turning economics into a pseudo natural science is as keynes made very clear in a letter to roy harrod already back in 1938 something that has to be firmly repelled robert lucas s forecasting disaster 16 apr 2016 at 20 20 posted in economics 5 comments in milton friedman s infamous essay the methodology of positive economics 1953 it was argued that the realism or truth of a theory s assumptions isn t important the only thing that really matters is how good are the predictions made by the theory please feel free to apply that science norm to the following statement by robert lucas in wall street journal september 19 2007 i am skeptical about the argument that the subprime mortgage problem will contaminate the whole mortgage market that housing construction will come to a halt and that the economy will slip into a recession every step in this chain is questionable and none has been quantified if we have learned anything from the past 20 years it is that there is a lot of stability built into the real economy robert lucas a lousy pseudo scientist and an even worse forecaster robert lucas s pseudo science 16 apr 2016 at 09 54 posted in economics comments off on robert lucas s pseudo science the construction of theoretical models is our way to bring order to the way we think about the world but the process necessarily involves ignoring some evidence or alternative theories setting them aside that can be hard to do facts are facts and sometimes my unconscious mind carries out the abstraction for me i simply fail to see some of the data or some alternative theory robert lucas and that guy even got a nobel prize in economics economists math heavy astrologers 16 apr 2016 at 00 13 posted in economics comments off on economists math heavy astrologers ultimately the problem isn t with worshipping models of the stars but rather with uncritical worship of the language used to model them and nowhere is this more prevalent than in economics the economist paul romer at new york university has recently begun calling attention to an issue he dubs mathiness first in the paper mathiness in the theory of economic growth 2015 and then in a series of blog posts romer believes that macroeconomics plagued by mathiness is failing to progress as a true science should and compares debates among economists to those between 16th century advocates of heliocentrism and geocentrism mathematics he acknowledges can help economists to clarify their thinking and reasoning but the ubiquity of mathematical theory in economics also has serious downsides it creates a high barrier to entry for those who want to participate in the professional dialogue and makes checking someone s work excessively laborious worst of all it imbues economic theory with unearned empirical authority i ve come to the position that there should be a stronger bias against the use of math romer explained to me if somebody came and said look i have this earth changing insight about economics but the only way i can express it is by making use of the quirks of the latin language we d say go to hell unless they could convince us it was really essential the burden of proof is on them right now however there is widespread bias in favour of using mathematics the success of math heavy disciplines such as physics and chemistry has granted mathematical formulas with decisive authoritative force lord kelvin the 19th century mathematical physicist expressed this quantitative obsession when you can measure what you are speaking about and express it in numbers you know something about it but when you cannot measure it in numbers your knowledge is of a meagre and unsatisfactory kind the trouble with kelvin s statement is that measurement and mathematics do not guarantee the status of science they guarantee only the semblance of science when the presumptions or conclusions of a scientific theory are absurd or simply false the theory ought to be questioned and eventually rejected the discipline of economics however is presently so blinkered by the talismanic authority of mathematics that theories go overvalued and unchecked alan jay levinovitz you re so vain personal 15 apr 2016 at 19 18 posted in varia comments off on you re so vain personal next page recent posts arbetslöshetsiffran som styr den ekonomiska politiken 50 år efter studenten personal finding the late student stuff love s secret stein s paradox a lesson on precision and unbiasedness audioholic summer research ett välförtjänt bottenrekord arbetslösheten inte statsskulden är problemet how credible is the credibility revolution in econometrics randomness and representativeness are not the same lönebildning och arbetslöshet i 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