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description= 15 posts published by Lars Syll during January 2025;
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good model is to be understood as a model that achieves an equilibrium between being useful and not being too wrong the usefulness of a model is clearly context dependent it may involve a combination of desired features such as being understandable for students researchers or others achieving computational tractability and other criteria not being too wrong is to be understood as not being too different from reality sylvia wenmackers danny vanpoucke this is an interesting article that emphasizes that all empirical sciences use simplifying or unrealistic assumptions in their modelling activities and that that is not the issue as long as the assumptions made are not unrealistic in the wrong way or for the wrong reasons theories are difficult to confront directly with reality therefore economists build models of their theories those models are representations that are directly examined and manipulated to indirectly say something about the target systems but models do not only face theory they also have to look to the world being able to model a credible world a world that somehow could be considered real or similar to the real world is not the same as investigating the real world even though all theories are false since they simplify they may still possibly serve our pursuit of truth but then they cannot be unrealistic or false in any way the falsehood or unrealisticness has to be qualified some of the standard assumptions made in mainstream economic theory on rationality information handling and types of uncertainty are not possible to make more realistic by de idealization or successive approximations without altering the theory and its models fundamentally if we cannot show that the mechanisms or causes we isolate and handle in our models are stable in the sense that when we export them from are models to our target systems they do not change from one situation to another then they only hold under ceteris paribus conditions and a fortiori are of limited value for our understanding explanation and prediction of our real world target system no matter how many convoluted refinements of concepts are made in the model if the successive approximations do not result in models similar to reality in the appropriate respects such as structure isomorphism etc the surrogate system becomes a substitute system that does not bridge to the world but rather misses its target share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky da pacem domine 30 jan 2025 at 15 24 posted in varia comments off on da pacem domine share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky dumb and dumber 3 premiere 29 jan 2025 at 16 34 posted in politics society comments off on dumb and dumber 3 premiere dumb dumber 3 is finally here with two new main characters dumber than ever share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky bellman style backward induction student stuff 29 jan 2025 at 11 30 posted in economics comments off on bellman style backward induction student stuff 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 a realist critique 27 jan 2025 at 22 07 posted in statistics econometrics comments off on econometrics a realist critique a popular idea in quantitative social sciences is to think of a cause c as something that increases the probability of its effect or outcome o that is p o c p o c however as is also well known a correlation between two variables say a and b does not necessarily imply that one is a cause of the other or the other way around since they may both be effects of a common cause c in statistics and econometrics we usually solve this confounder problem by controlling for c i e by holding c fixed this means that we look at different populations those in which c occurs in every case and those in which c doesn t this means that knowing the value of a does not influence the probability of c p c a p c so if there still exists a correlation between a and b in either of these populations there must be some other cause operating but if all other possible causes have been controlled for too and there is still a correlation between a and b we may safely conclude that a is a cause of b since by controlling for all other possible causes the correlation between the putative cause a and all the other possible causes d e f is broken this is of course a very demanding prerequisite since we may never actually be sure to have identified all putative causes even in scientific experiments may the number of uncontrolled causes be innumerable since nothing less will do we all understand how hard it is to actually get from correlation to causality this also means that only relying on statistics or econometrics is not enough to deduce causes from correlations some people think that randomization may solve the empirical problem by randomizing we are getting different populations that are homogeneous in regards to all variables except the one we think is a genuine cause in that way we are supposed to be able not to actually know what all these other factors are if you succeed in performing an ideal randomization with different treatment groups and control groups that is attainable but it presupposes that you really have been able to establish and not just assume that the probability of all other causes but the putative a have the same probability distribution in the treatment and control groups and that the probability of assignment to treatment or control groups are independent of all other possible causal variables unfortunately real experiments and real randomizations seldom or never achieve this so yes we may do it without knowing all the causes but it takes ideal experiments and ideal randomizations to do that not real ones that means that in practice we do have to have sufficient background knowledge to deduce causal knowledge without old knowledge we can t get new knowledge and no causes in no causes out once you include all actual causes into the original over simple model it may well be that the causes are no longer independent or linear and that a fortiori the coefficients in the econometric equations no longer are identifiable and so since all causal factors are not included in the original econometric model it is not an adequate representation of the real causal structure of the economy that the model is purportedly meant to represent unfortunately economists often hold the view that keynes s criticisms of econometrics is the conclusions of a sadly misinformed and misguided intellectual who disliked and did not understand much of it this is really a gross misapprehension to be careful and cautious is not the same as to dislike i would argue against common knowledge that keynes did not misunderstand the crucial issues at stake in the development of econometrics quite the contrary he knew them all too well and was not satisfied with the validity and philosophical underpinning of the assumptions made for applying its methods and neither was the eminent mathematical statistician david freedman who in his statistical models and causal inference wrote causal inference from observational data presents many difficulties especially when underlying mechanisms are poorly understood there is a natural desire to substitute intellectual capital for labor and an equally natural preference for system and rigor over methods that seem more haphazard these are possible explanations for the current popularity of statistical models indeed far reaching claims have been made for the superiority of a quantitative template that depends on modeling by those who manage to ignore the far reaching assumptions behind the models however the assumptions often turn out to be unsupported by the data if so the rigor of advanced quantitative methods is a matter of appearance rather than substance modelling assumptions made in statistics and econometrics are more often than not made for mathematical tractability reasons rather than verisimilitude that is unfortunately also a reason why the methodological rigour encountered when taking part in statistical and econometric research to a large degree is nothing but a deceptive appearance the models constructed may seem technically advanced and very sophisticated but that s usually only because the problems here discussed have been swept under the carpet assuming that our data are generated by coin flips in an imaginary superpopulation only means that we get answers to questions that we are not asking the inferences made based on imaginary superpopulations well they too are nothing but imaginary we should not as already aristotle noted expect more rigour and precision than the object examined allows and in econometrics it s always wise to ponder c s peirce s remark that universes are not as common as peanuts share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky vi äro tusenden 26 jan 2025 at 22 09 posted in politics society varia comments off on vi äro tusenden share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky john nash and the limits of game theory 25 jan 2025 at 15 08 posted in economics 1 comment john nash made groundbreaking contributions to game theory particularly through his development of the concept of the nash equilibrium which became a cornerstone of the analysis of strategic interactions in economics late in his life nash however also came to be aware of a fundamental methodological weakness of game theory overemphasizing the reach of instrumental rationality and abstracting away from the influence of non economic factors reduces the analysis to a pure thought experiment without any substantial connection to reality most mainstream economists still think that game theory is useful and can be applied to real life and give important and interesting results that however is a rather unsubstantiated view what game theory does is strictly seen nothing more than investigating the logic of behaviour among non existent robot imitations of humans knowing how those rational fools play games does not help us decide and act when interacting with real people knowing some game theory may actually make us behave in a way that hurts both ourselves and others decision making and social interaction are always embedded in socio cultural contexts not taking account of that game theory will remain an analytical cul de sac that never will be able to come up with useful and relevant explanations over emphasizing the reach of instrumental rationality and abstracting away from the influence of many known to be important factors reduces the analysis to a pure thought experiment without any substantial connection to reality limiting theoretical economic analysis in this way not incorporating both motivational and institutional factors when trying to explain human behaviour makes economics insensitive to social facts game theorists extensively exploit rational choice assumptions in their explanations that is probably also the reason why game theory has not been able to accommodate well known anomalies in its theoretical framework that should hardly come as a surprise to anyone game theory with its axiomatic view of individuals tastes beliefs and preferences cannot accommodate very much of real life behaviour it is hard to find really compelling arguments in favour of us continuing down its barren paths since individuals obviously do not comply with or are guided by game theory apart from a few notable exceptions it is difficult to find really successful applications of game theory why to a large extent simply because the boundary conditions of game theoretical models are false and baseless from a real world perspective and perhaps even more importantly since they are not even close to being good approximations of real life game theory lacks predictive power this should come as no surprise as long as game theory sticks to its rational choice foundations there is not much to be hoped for game theorists can of course marginally modify their toolbox and fiddle with the auxiliary assumptions to get whatever outcome they want but as long as the rational choice core assumptions are left intact it seems a pointless effort to hamper an already excessive deductive axiomatic formalism if you do believe in the real world relevance of game theoretical science fiction assumptions such as expected utility common knowledge backward induction correct and consistent beliefs etc etc then adding things like framing cognitive bias and different kinds of heuristics do not solve any problem if we want to construct a theory that can provide us with explanations of individual cognition decisions and social interaction we have to look for something else applications of game theory have on the whole resulted in massive predictive failures people simply do not act according to the theory they do not know or possess the assumed probabilities utilities beliefs or information to calculate the different subgame trembling hand perfect nash equilibria they may be reasonable and make use of their given cognitive faculties as well as they can but they are obviously not those perfect and costless hyper rational expected utility maximizing calculators game theory posits and fortunately so being reasonable makes them avoid all those made up rationality traps that game theory would have put them in if they had tried to act as consistent players in a game theoretical sense share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky invictus 25 jan 2025 at 11 02 posted in varia comments off on invictus a great poem it helped one of the greatest men that has walked this earth keep hope alive during twenty seven years in prison share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky bank of england goes mmt 23 jan 2025 at 18 41 posted in economics 3 comments share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky deconstructing uncertainty 23 jan 2025 at 18 28 posted in statistics econometrics comments off on deconstructing uncertainty share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky om detta må vi berätta 20 jan 2025 at 21 53 posted in economics politics society 2 comments vi talar ofta i dag om tilltagande kriminalitet sämre hälsa och ökade psykiska problem men nästan aldrig om vad dessa symptom i hög grad är orsakade av arbetslösheten 8 5 arbetslöshet är den högsta ...
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