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description= 15 posts published by Lars Syll during July 2017;
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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 behavioural finance from the perspective of model platonism these research areas are still framed by the superior insights associated with early 20th century concepts essentially because almost all of their results are framed in terms of rational individuals who engage in optimizing behaviour and thereby attain equilibrium for instance the attitude to explain cooperation or fair behaviour in experiments by assuming an inequality aversion integrated in a fraction of the subjects preferences is strictly in accordance with the assumption of rational individuals a feature which the authors are keen to report so while the mere emergence of research areas like experimental economics is sometimes deemed a clear sign for the advent of a new era a closer look at these fields allows us to illustrate the enduring relevance of the model platonism topos and thereby shows the pervasion of these fields with a traditional neoclassical style of thought jakob kapeller ricardo s trade paradigm a formerly true theory 21 jul 2017 at 10 59 posted in economics 6 comments two hundred years ago on 19 april 1817 david ricardo s principles was published in it he presented a theory that was meant to explain why countries trade and based on the concept of opportunity cost how the pattern of export and import is ruled by countries exporting goods in which they have comparative advantage and importing goods in which they have a comparative disadvantage although a great accomplishment per se ricardo s theory of comparative advantage however didn t explain why the comparative advantage was the way it was in the beginning of the 20th century two swedish economists eli heckscher and bertil ohlin presented a theory model theorem according to which the comparative advantages arose from differences in factor endowments between countries countries have a comparative advantages in producing goods that use up production factors that are most abundant in the different countries countries would mostly export goods that used the abundant factors of production and import goods that mostly used factors of productions that were scarce the heckscher ohlin theorem as do the elaborations on in it by e g vanek stolper and samuelson builds on a series of restrictive and unrealistic assumptions the most critically important beside the standard market clearing equilibrium assumptions are 1 countries use identical production technologies 2 production takes place with a constant returns to scale technology 3 within countries the factor substitutability is more or less infinite 4 factor prices are equalised the stolper samuelson extension of the theorem these assumptions are as almost all empirical testing of the theorem has shown totally unrealistic that is they are empirically false that said one could indeed wonder why on earth anyone should be interested in applying this theorem to real world situations as so many other mainstream mathematical models taught to economics students today this theorem has very little to do with the real world using false assumptions mainstream modelers can derive whatever conclusions they want wanting to show that free trade is great just e g assume all economists from chicago are right and all economists from chicago consider free trade to be great the conclusions follows by deduction but is of course factually totally wrong models and theories building on that kind of reasoning is nothing but a pointless waste of time what mainstream economics took over from ricardo was not only the theory of comparative advantage the whole deductive axiomatic approach to economics that is still at the core...
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