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description= 15 posts published by Lars Syll during October 2015;
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loads of assumptions and that most important of these are additivity and linearity let me take the opportunity to elaborate a little more on why i find these assumptions of such paramount importance and ought to be much more argued for on both epistemological and ontological grounds if at all being used limiting model assumptions in economic science always have to be closely examined since if we are going to be able to show that the mechanisms or causes that we isolate and handle in our models are stable in the sense that they do not change when we export them to our target systems we have to be able to show that they do not only hold under ceteris paribus conditions and a fortiori only are of limited value to our understanding explanations or predictions of real economic systems as the always eminently quotable keynes wrote emphasis added in treatise on probability 1921 the kind of fundamental assumption about the character of material laws on which scientists appear commonly to act seems to me to be that the system of the material universe must consist of bodies such that each of them exercises its own separate independent and invariable effect a change of the total state being compounded of a number of separate changes each of which is solely due to a separate portion of the preceding state yet there might well be quite different laws for wholes of different degrees of complexity and laws of connection between complexes which could not be stated in terms of laws connecting individual parts if different wholes were subject to different laws qua wholes and not simply on account of and in proportion to the differences of their parts knowledge of a part could not lead it would seem even to presumptive or probable knowledge as to its association with other parts these considerations do not show us a way by which we can justify induction 427 no one supposes that a good induction can be arrived at merely by counting cases the business of strengthening the argument chiefly consists in determining whether the alleged association is stable when accompanying conditions are varied 468 in my judgment the practical usefulness of those modes of inference on which the boasted knowledge of modern science depends can only exist if the universe of phenomena does in fact present those peculiar characteristics of atomism and limited variety which appears more and more clearly as the ultimate result to which material science is tending econometrics may be an informative tool for research but if its practitioners do not investigate and make an effort of providing a justification for the credibility of the assumptions on which they erect their building it will not fulfill its tasks there is a gap between its aspirations and its accomplishments and without more supportive evidence to substantiate its claims critics will continue to consider its ultimate argument as a mixture of rather unhelpful metaphors and metaphysics maintaining that economics is a science in the true knowledge business yours truly remains a skeptic of the pretences and aspirations of econometrics so far i cannot really see that it has yielded very much in terms of relevant interesting economic knowledge the marginal return on its ever higher technical sophistication in no way makes up for the lack of serious under labouring of its deeper philosophical and methodological foundations that already keynes complained about the rather one sided emphasis of usefulness and its concomitant instrumentalist justification cannot hide that neither haavelmo nor the legions of probabilistic econometricians following in his footsteps give supportive evidence for their considering it fruitful to believe in the possibility of treating unique economic data as the observable results of random drawings from an imaginary sampling of an imaginary population after having analyzed some of its ontological and epistemological foundations i cannot but conclude that econometrics on the whole has not delivered truth and i doubt if it has ever been the intention of its main protagonists our admiration for technical virtuosity should not blind us to the fact that we have to have a cautious attitude towards probabilistic inferences in economic contexts science should help us penetrate to the true process of causation lying behind current events and disclose the causal forces behind the apparent facts keynes 1971 89 vol xvii 427 we should look out for causal relations but econometrics can never be more than a starting point in that endeavour since econometric statistical explanations are not explanations in terms of mechanisms powers capacities or causes firmly stuck in an empiricist tradition econometrics is only concerned with the measurable aspects of reality but there is always the possibility that there are other variables of vital importance and although perhaps unobservable and non additive not necessarily epistemologically inaccessible that were not considered for the model those who were can hence never be guaranteed to be more than potential causes and not real causes a rigorous application of econometric methods in economics really presupposes that the phenomena of our real world economies are ruled by stable causal relations between variables a perusal of the leading econom etr ic journals shows that most econometricians still concentrate on fixed parameter models and that parameter values estimated in specific spatio temporal contexts are presupposed to be exportable to totally different contexts to warrant this assumption one however has to convincingly establish that the targeted acting causes are stable and invariant so that they maintain their parametric status after the bridging the endemic lack of predictive success of the econometric project indicates that this hope of finding fixed parameters is a hope for which there really is no other ground than hope itself real world social systems are not governed by stable causal mechanisms or capacities as keynes wrote in his critique of econometrics and inferential statistics already in the 1920s emphasis added the atomic hypothesis which has worked so splendidly in physics breaks down in psychics we are faced at every turn with the problems of organic unity of discreteness of discontinuity the whole is not equal to the sum of the parts comparisons of quantity fails us small changes produce large effects the assumptions of a uniform and homogeneous continuum are not satisfied thus the results of mathematical psychics turn out to be derivative not fundamental indexes not measurements first approximations at the best and fallible indexes dubious approximations at that with much doubt added as to what if anything they are indexes or approximations of the kinds of laws and relations that econometrics has established are laws and relations about entities in models that presuppose causal mechanisms being atomistic and additive when causal mechanisms operate in real world social target systems they only do it in ever changing and unstable combinations where the whole is more than a mechanical sum of parts if economic regularities obtain they do it as a rule only because we engineered them for that purpose outside man made nomological machines they are rare or even non existant unfortunately that also makes most of the achievements of econometrics as most of contemporary endeavours of mainstream economic theoretical modeling rather useless following our recent post on econometricians traditional privileging of unbiased estimates there were a bunch of comments echoing the challenge of teaching this topic as students as well as practitioners often seem to want the comfort of an absolute standard such as best linear unbiased estimate or whatever commenters also discussed the tradeoff between bias and variance and the idea that unbiased estimates can overfit the data i agree with all these things but i just wanted to raise one more point in realistic settings unbiased estimates simply don t exist in the real world we have nonrandom samples measurement error nonadditivity nonlinearity etc etc etc so forget about it we re living in the real world it s my impression that many practitioners in applied econometrics and statistics think of their estimation choice kinda like this 1 the unbiased estimate it s the safe choice maybe a bit boring and maybe not the most efficient use of the data but you can trust it and it gets the job done 2 a biased estimate something flashy maybe bayesian maybe not it might do better but it s risky in using the biased estimate you re stepping off base the more the bias the larger your lead and you might well get picked off if you take the choice above and combine it with the unofficial rule that statistical significance is taken as proof of correctness in econ this would also require demonstrating that the result holds under some alternative model specifications but p less than 05 is still key then you get the following decision rule a go with the safe unbiased estimate if it s statistically significant run some robustness checks and if the result doesn t go away stop b if you don t succeed with a you can try something fancier but if you do that everyone will know that you tried plan a and it didn t work so people won t trust your finding so in a sort of gresham s law all that remains is the unbiased estimate but hey it s safe conservative etc right and that s where the present post comes in my point is that the unbiased estimate does not exist there is no safe harbor just as we can never get our personal risks in life down to zero there is no such thing as unbiasedness and it s a good thing too recognition of this point frees us to do better things with our data right away andrew gelman share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky economics journals publishing lazy non scientific work 27 oct 2015 at 11 00 posted in economics 1 comment in a new paper andrew chang an economist at the federal reserve and phillip li an economist with the office of the comptroller of the currency describe their attempt to replicate 67 papers from 13 well regarded economics journals their results just under half 29 out of the remaining 59 of the papers could be qualitatively replicated that is to say their general findings held up even if the authors did not arrive at the exact same quantitative result for the other half whose results could not be replicated the most common reason was missing public data or code h d vinod an economics professor at fordham university noted that caution could be outweighed by the sheer amount of work it takes to clean up data files in order to make them reproducible it s human laziness he said there s all this work involved in getting the data together bruce mccullough said he thought the authors definition of what counted as replication achieving the same qualitative as opposed to quantitative results was far too generous if a paper s conclusions are correct he argues one should be able to arrive at the same numbers using the same data what these journals produce is not science he said people should treat the numerical results as if they were produced by a random number generator anna louie sussman share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky why non existence of uncertainty is such a monstrously absurd assumption 26 oct 2015 at 16 04 posted in economics 1 comment all these pretty polite techniques made for a well panelled board room and a nicely regulated market are liable to collapse at all times the vague panic fears and equally vague and unreasoned hopes are not really lulled and lie but a little way below the surface perhaps the reader feels that this general philosophical disquisition on the behavior of mankind is somewhat remote from the economic theory under discussion but i think not tho this is how we behave in the marketplace the theory we devise in the study of how we behave in the market place should not itself submit to market place idols i accuse the classical economic theory of being itself one of these pretty polite techniques which tries to deal with the present by abstracting from the fact that we know very little about the future i dare say that a classical economist would readily admit this but even so i think he has overlooked the precise nature of the difference which his abstraction makes between theory and practice and the character of the fallacies into which he is likely to be led this is particularly the case in his treatment of money and interest john maynard keynes share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky question the monetary system and you re academically dead 25 oct 2015 at 18 11 posted in economics 10 comments bernard lietaer is a former professor of international finance and president at the central bank of belgium share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky did keynes accept the is lm model 25 oct 2015 at 09 02 posted in economics comments off on did keynes accept the is lm model lord keynes has some interesting references and links for those wanting to dwell upon the question if keynes really accepted hicks s is lm model my own view is that is lm doesn t adequately reflect the width and depth of keynes s insights on the workings of modern market economies 1 almost nothing in the post general theory writings of keynes suggests him considering hicks s is lm anywhere near a faithful rendering of his thought in keynes s canonical statement of the essence of his theory in the famous 1937 quarterly journal of economics article there is nothing to even suggest that keynes would have thought the existence of a keynes hicks is lm theory anything but pure nonsense john hicks the man who invented is lm in his 1937 econometrica review of keynes general theory mr keynes and the classics a suggested interpretation returned to it in an article in 1980 is lm an explanation in journal of post keynesian economics self critically he wrote that the only way in which is lm analysis usefully survives as anything more than a classroom gadget to be superseded later on by something better is in application to a particular kind of causal analysis where the use of equilibrium methods even a drastic use of equilibrium methods is not inappropriate what hicks acknowledges in 1980 is basically that his original is lm model ignored significant parts of keynes theory is lm is inherently a temporary general equilibrium model however much of the discussions we have in macroeconomics is about timing and the speed of relative adjustments of quantities commodity prices and wages on which is lm doesn t have much to say 2 is lm forces to a large extent the analysis into a static comparative eq...
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