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description=15 posts published by Lars Syll during July 2017;

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are resursramar ska kunna lösa dilemmat med högre krav på meritmässigt allt mer svagpresterande studenter the conundrum of unknown unknowns 24 jul 2017 at 17 18 posted in economics 2 comments short term weather forecasting is possible because most of the factors that determine tomorrow s weather are in a sense already there but when you look further ahead you encounter the intractable problem that in non linear systems small changes in initial conditions can lead to cumulatively larger and larger changes in outcomes over time in these circumstances imperfect knowledge may be no more useful than no knowledge at all much the same is true in economics and business what gross domestic product will be tomorrow is like tomorrow s rain or the 1987 hurricane more or less already there tomorrow s output is already in production tomorrow s sales are already on the shelves tomorrow s business appointments already made big data will help us analyse this we will know more accurately and more quickly what gdp is we will be more successful in predicting output in the next quarter and our estimates will be subject to fewer revisions big data can help us understand the past and the present but it can help us understand the future only to the extent that the future is in some relevant way contained in the present that requires a constancy of underlying structure that is true of some physical processes but can never be true of a world that contains hitler and napoleon henry ford and steve jobs a world in which important decisions or discoveries are made by processes that are inherently unpredictable and not susceptible to quantitative description john kay the central problem with the present machine learning and big data hype is that so many falsely think that they can get away with analysing real world phenomena without any commitment to theory but data never speaks for itself without a prior statistical set up there actually are no data at all to process and using a machine learning algorithm will only produce what you are looking for theory matters when ignorance is bliss 22 jul 2017 at 22 49 posted in economics 3 comments the production function has been a powerful instrument of miseducation the student of economic theory is taught to write q f l k where l is a quantity of labor k a quantity of capital and q a rate of output of commodities he is instructed to assume all workers alike and to measure l in man hours of labor he is told something about the index number problem in choosing a unit of output and then he is hurried on to the next question in the hope that he will forget to ask in what units k is measured before he ever does ask he has become a professor and so sloppy habits of thought are handed on from one generation to the next joan robinson the production function and the theory of capital 1953 the ultimate insider 21 jul 2017 at 20 27 posted in varia comments off on the ultimate insider one of my absolute favourite movies great true story marvelous actors russell crowe al pacino christopher plummer fabulous music by e g lisa gerrard and jan garbarek what so many critiques of economics gets right 21 jul 2017 at 12 39 posted in economics 2 comments yours truly had a post up the other day on john rapley s twilight of the money gods in the main i think rapley is right in his attack on contemporary economics and its priesthood although he often seems to forget that there are yes it s true more than one approach in economics and that his critique mainly pertains to mainstream neoclassical economics noah smith however is not too happy about the book there are certainly some grains of truth in this standard appraisal i ve certainly lobbed my fair share of criticism at the econ profession over the years but the problem with critiques like rapley s is that they offer no real way forward for the discipline simply calling for humility and methodological diversity accomplishes little instead pundits should focus on what is going right in the economics discipline because there are some very good things happening first economists have developed some theories that really work a good scientific theory makes testable predictions that apply to situations other than those that motivated the creation of the theory slowly econ is building up a repertoire of these gems one of them is auction theory another example is matching theory which has made it a lot easier to get an organ transplant second economics is becoming a lot more empirical focusing more on examining the data than on constructing yet more theories noah smith maintains that new imaginative empirical methods such as natural experiments field experiments lab experiments rcts help us to answer questions concerning the validity of economic theories and models yours truly begs to differ although one of course has to agree with noah s view that discounting empirical evidence is not the right way to solve economic issues when looked at carefully there are in fact few real reasons to share his optimism on this so called empirical revolution in economics field studies and experiments face the same basic problem as theoretical models they are built on rather artificial conditions and have difficulties with the trade off between internal and external validity the more artificial conditions the more internal validity but also less external validity the more we rig experiments field studies models to avoid the confounding factors the less the conditions are reminicent of the real target system you could of course discuss the field vs experiments vs theoretical models in terms of realism but the nodal issue is not about that but basically about how economists using different isolation strategies in different nomological machines attempt to learn about causal relationships i have strong doubts on the generalizability of all three research strategies because the probability is high that causal mechanisms are different in different contexts and that lack of homogeneity and invariance doesn t give us warranted export licenses to the real societies or economies if we see experiments or field studies as theory tests or models that ultimately aspire to say something about the real target system then the problem of external validity is central and was for a long time also a key reason why behavioural economists had trouble getting their research results published assume that you have examined how the work performance of chinese workers a is affected by b treatment how can we extrapolate generalize to new samples outside the original population e g to the us how do we know that any replication attempt succeeds how do we know when these replicated experimental results can be said to justify inferences made in samples from the original population if for example p a b is the conditional density function for the original sample and we are interested in doing a extrapolative prediction of e p a b how can we know that the new sample s density function is identical with the original unless we can give some really good argument for this being the case inferences built on p a b is not really saying anything on that of the target system s p a b as i see it this is the heart of the matter external validity and generalization is founded on the assumption that we could make inferences based on p a b that is exportable to other populations for which p a b applies sure if one can convincingly show that p and p are similar enough the problems are perhaps surmountable but arbitrarily just introducing functional specification restrictions of the type invariance and homogeneity is at least for an epistemological realist far from satisfactory and often it is unfortunately exactly this that i see when i take part of mainstream neoclassical economists models experiments field studies by this i do not mean to say that empirical methods per se are so problematic that they can never be used on the contrary i am basically though not without reservations in favour of the increased use of experiments and field studies within economics not least as an alternative to completely barren bridge less axiomatic deductive theory models my criticism is more about aspiration levels and what we believe that we can achieve with our mediational epistemological tools and methods in the social sciences many experimentalists claim that it is easy to replicate experiments under different conditions and therefore a fortiori easy to test the robustness of experimental results but is it really that easy if in the example given above we run a test and find that our predictions were not correct what can we conclude the b works in china but not in the us or that b works in a backward agrarian society but not in a post modern service society that b worked in the field study conducted in year 2008 but not in year 2016 population selection is almost never simple had the problem of external validity only been about inference from sample to population this would be no critical problem but the really interesting inferences are those we try to make from specific labs experiments fields to specific real world situations institutions structures that we are interested in understanding or causally to explain and then the population problem is more difficult to tackle the increasing use of natural and quasi natural experiments in economics during the last couple of decades has led not only noah smith but several prominent economists to triumphantly declare it as a major step on a recent path toward empirics where instead of being a deductive philosophy economics is now increasingly becoming an inductive science in randomized trials the researchers try to find out the causal effects that different variables of interest may have by changing circumstances randomly a procedure somewhat on average equivalent to the usual ceteris paribus assumption besides the fact that on average is not always good enough it amounts to nothing but hand waving to simpliciter assume without argumentation that it is tenable to treat social agents and relations as homogeneous and interchangeable entities randomization is used to basically allow the econometrician to treat the population as consisting of interchangeable and homogeneous groups treatment and control the regression models one arrives at by using randomized trials tell us the average effect that variations in variable x has on the outcome variable y without having to explicitly control for effects of other explanatory variables r s t etc etc everything is assumed to be essentially equal except the values taken by variable x 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 real world social systems are not governed by stable causal mechanisms or capacities 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 i also think that most randomistas really underestimate the heterogeneity problem it does not just turn up as an external validity problem when trying to export regression results to different times or different target populations it is also often an internal problem to the millions of regression estimates that economists produce every year just as econometrics randomization promises more than it can deliver basically because it requires assumptions that in practice are not possible to maintain like econometrics randomization is basically a deductive method given the assumptions such as manipulability transitivity separability additivity linearity etc these methods deliver deductive inferences the problem of course is that we will never completely know when the assumptions are right and although randomization may contribute to controlling for confounding it does not guarantee it since genuine ramdomness presupposes infinite experimentation and we know all real experimentation is finite and even if randomization may help to establish average causal effects it says nothing of individual effects unless homogeneity is added to the list of assumptions real target systems are seldom epistemically isomorphic to our axiomatic deductive models systems and even if they were we still have to argue for the external validity of the conclusions reached from within these epistemically convenient models systems causal evidence generated by randomization procedures may be valid in closed models but what we usually are interested in is causal evidence in the real target system we happen to live in when does a conclusion established in population x hold for target population y only under very restrictive conditions ideally controlled experiments tell us with certainty what causes what effects but only given the right closures making appropriate extrapolations from ideal accidental natural or quasi experiments to different settings populations or target systems is not easy it works there s no evidence for it will work here causes deduced in an experimental setting still have to show that they come with an export warrant to the target population system the causal background assumptions made have to be justified and without licenses to export the value of rigorous and precise methods and on average knowledge is despairingly small so no i find it hard to share noah smith s and others enthusiasm and optimism on the value of quasi natural experiments and all the statistical econometric machinery that comes with it guess i m still waiting for the export warrant i would contrary to noah smith s optimism argue that although different empirical approaches have been more or less integrated into mainstream economics there is still a long way to go before economics has become a truly empirical science taking assumptions like utility maximization or market equilibrium as a matter of course leads to the standing presumption in economics that if an empirical statement is deduced from standard assumptions then that statement is reliable the ongoing importance of these assumptions is especially evident in those areas of economic research where empirical results are challenging standard views on economic behaviour like experimental economics or behavioura...