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description= 15 posts published by Lars Syll during October 2016;
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nal on the data a researcher when faced with multiple reasonable measures can reason perhaps correctly that the one that produces a significant result is more likely to be the least noisy measure but then decide incorrectly to draw inferences based on that one only andrew gelman eric loken mainstream economists dissing people that want to rethink economics 22 oct 2016 at 20 02 posted in economics 14 comments there s a lot of commenting on the blog now after yours truly put up a post where cambridge economist pontus rendahl in an interview compared heterodox economics to creationism and alternative medicine and totally dissed students that want to see the economics curriculum moving in a more pluralist direction sad to say rendahl is not the only mainstream economist having monumental problems when trying to argue with people challenging the ruling orthodoxy a couple of years ago paul krugman felt a similar urge to defend mainstream neoclassical economics against the critique from students asking for more relevance realism and pluralism in the teaching of economics according to krugman the students and people like yours truly are wrong in blaming mainstream economics for not being relevant and not being able to foresee crises to krugman there is nothing wrong with standard theory and economics textbooks if only policy makers and economists stick to standard economic analysis everything would be just fine i ll be dipped if there s anything the last couple of years have shown us it is that economists have gone astray krugman s standard theory mainstream neoclassical economics has contributed to causing todays s economic crisis rather than to solving it reading krugman i guess a lot of the young economics students that today are looking for alternatives to mainstream neoclassical theory are deeply disappointed rightly so but although krugman especially on his blog certainly tries to present himself as a kind of radical and anti establishment economics guy when it really counts he shows what he is a die hard teflon coated mainstream neoclassical economist perhaps this becomes less perplexing to grasp when one considers what krugman said in a speech emphasis added in 1996 i like to think that i am more open minded about alternative approaches to economics than most but i am basically a maximization and equilibrium kind of guy indeed i am quite fanatical about defending the relevance of standard economic models in many situations personally i consider myself a proud neoclassicist by this i clearly don t mean that i believe in perfect competition all the way what i mean is that i prefer when i can to make sense of the world using models in which individuals maximize and the interaction of these individuals can be summarized by some concept of equilibrium i have seen the propensity of those who try to do economics without those organizing devices to produce sheer nonsense when they imagine they are freeing themselves from some confining orthodoxy so now all young economics students that want to see a real change in economics and the way it s taught now you know where you have people like rendahl and krugman if you really want something other than the same old mainstream neoclassical catechism if you really don t want to be force fed with mainstream neoclassical theories and models you have to look elsewhere share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky econometrics and the bridge between model and reality 21 oct 2016 at 23 28 posted in statistics econometrics 1 comment trygve haavelmo the father of modern probabilistic econometrics wrote that he and other econometricians could not build a complete bridge between our models and reality by logical operations alone but finally had to make a non logical jump statistical testing of business cycle theories 1943 15 a part of that jump consisted in that econometricians like to believe that the various a priori possible sequences would somehow cluster around some typical time shapes which if we knew them could be used for prediction 1943 16 but since we do not know the true distribution one has to look for the mechanisms processes that might rule the data and that hopefully persist so that predictions may be made of possible hypothesis on different time sequences samples in haavelmo s somewhat idiosyncratic vocabulary most had to be ruled out a priori by economic theory although one shall always remain in doubt as to the possibility of some outside hypothesis being the true one 1943 18 the explanations we can give of economic relations and structures based on econometric models are according to haavelmo not hidden truths to be discovered but rather our own artificial inventions models are consequently perceived not as true representations of the data generating process but rather instrumentally conceived as if constructs their intrinsic closure is realized by searching for parameters showing a great degree of invariance or relative autonomy and the extrinsic closure by hoping that the practically decisive explanatory variables are relatively few so that one may proceed as if natural limitations of the number of relevant factors exist the probability approach in econometrics 1944 29 but why the logically conceivable really should turn out to be the case is difficult to see at least if we are not satisfied by sheer hope in real economies it is unlikely that we find many autonomous relations and events and one could of course also raise the objection that to invoke a probabilistic approach to econometrics presupposes e g that we have to be able to describe the world in terms of risk rather than genuine uncertainty and that is exactly what haavelmo 1944 48 does to make this a rational problem of statistical inference we have to start out by an axiom postulating that every set of observable variables has associated with it one particular true but unknown probability law but to use this trick of our own and just assign a certain probability law to a system of observable variables however cannot just as little as hoping build a firm bridge between model and reality treating phenomena as if they essentially were stochastic processes is not the same as showing that they essentially are stochastic processes as hicks so neatly puts it in causality in economics 1979 120 21 things become more difficult when we turn to time series the econometrist who works in that field may claim that he is not treading on very shaky ground but if one asks him what he is really doing he will not find it easy even here to give a convincing answer h e must be treating the observations known to him as a sample of a larger population but what population i am bold enough to conclude from these considerations that the usefulness of statistical or stochastic methods in economics is a good deal less than is now conventionally supposed we have no business to turn to them automatically we should always ask ourselves before we apply them whether they are appropriate to the problem in hand and as if this wasn t enough one could also seriously wonder what kind of populations these statistical and econometric models ultimately are based on why should we as social scientists and not as pure mathematicians working with formal axiomatic systems without the urge to confront our models with real target systems unquestioningly accept haavelmo s infinite population fisher s hypothetical infinite population von mises s collective or gibbs s ensemble of course one could treat our observational or experimental data as random samples from real populations i have no problem with that but modern probabilistic econometrics does not content itself with that kind of populations instead it creates imaginary populations of parallel universes and assume that our data are random samples from that kind of populations but this is actually nothing else but handwaving and it is inadequate for real science as david freedman writes in statistical models and causal inference 2010 105 111 with this approach the investigator does not explicitly define a population that could in principle be studied with unlimited resources of time and money the investigator merely assumes that such a population exists in some ill defined sense and there is a further assumption that the data set being analyzed can be treated as if it were based on a random sample from the assumed population these are convenient fictions nevertheless reliance on imaginary populations is widespread indeed regression models are commonly used to analyze convenience samples the rhetoric of imaginary populations is seductive because it seems to free the investigator from the necessity of understanding how data were generated econometricians should know better than to treat random variables probabilites and expected values as anything else than things that strictly seen only pertain to statistical models if they want us take the leap of faith from mathematics into the empirical world in applying the theory they have to really argue an justify this leap by showing that those neat mathematical assumptions that to make things worse often are left implicit as e g independence and additivity do not collide with the ugly reality the set of mathematical assumptions is no validation in itself of the adequacy of the application a crucial ingredient to any economic theory that wants to use probabilistic models should be a convincing argument for the view that there can be no harm in considering economic variables as stochastic variables haavelmo 1943 13 in most cases no such arguments are given of course you are entitled like haavelmo and his modern probabilistic followers to express a hope at a metaphysical level that there are invariant features of reality to uncover and that also show up at the empirical level of observations as some kind of regularities but is it a justifiable hope i have serious doubts the kind of regularities you may hope to find in society is not to be found in the domain of surface phenomena but rather at the level of causal mechanisms powers and capacities persistence and generality has to be looked out for at an underlying deep level most econometricians do not want to visit that playground they are content with setting up theoretical models that give us correlations and eventually mimic existing causal properties we have to accept that reality has no correct representation in an economic or econometric model there is no such thing as a true model that can capture an open complex and contextual system in a set of equations with parameters stable over space and time and exhibiting invariant regularities to just believe hope or assume that such a model possibly could exist is not enough it has to be justified in relation to the ontological conditions of social reality in contrast to those who want to give up on fallible transient and transformable truth as a relation between theory and reality and content themselves with truth as a relation between a model and a probability distribution i think it is better to really scrutinize if this latter attitude is feasible to abandon the quest for truth and replace it with sheer positivism would indeed be a sad fate of econometrics on the proper use of mathematics in economics 21 oct 2016 at 10 01 posted in economics 1 comment one must of course beware of expecting from this method more than it can give out of the crucible of calculation comes not an atom more truth than was put in the assumptions being hypothetical the results obviously cannot claim more than a vey limited validity the mathematical expression ought to facilitate the argument clarify the results and so guard against possible faults of reasoning that is all it is by the way evident that the economic aspects must be the determining ones everywhere economic truth must never be sacrificed to the desire for mathematical elegance next page recent 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