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description=15 posts published by Lars Syll during October 2016;

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economics, the, and, in, what, of, is, mainstream, econometrics, science, be, svensk, universitetsutbildning, fritt, fall, to, recent, comments, lars, syll, some, unsettled, questions, macroeconomic, theory, rabbits, principle, triumph, ideology, over, non, ideological, valuefree, ll, dipped, truth, perils, calling, your, pet, cat, dog, ii, it, takes, make, real, statistical, significance, tests, do, not, validate, models, why, values, cannot, taken, at, face, value, economists, dissing, people, that, want, rethink, bridge, between, model, reality, on, proper, use, mathematics, posts, policy, reading, list, categories, archives,

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some (12), should (12), hypothesis (12), test (12), its (12), inte (11), about (11), would (11), true (11), relevance (11), för (11), 2011 (10), reality (10), rather (10), krugman (10), studenter (10), time (9), how (9), truth (9), course (9), out (9), between (9), really (9), things (9), which (9), share (9), opens (9), window (9), standard (9), wrong (9), men (9), conclusions (9), lars (8), now (8), lönebildning (8), arbetslöshet (8), mathematical (8), probability (8), just (8), variables (8), based (8), these (8), because (8), problem (8), without (8), even (8), whether (8), their (8), scientific (8), your (8), content (7), other (7), 2026 (7), will (7), same (7), must (7), those (7), who (7), over (7), haavelmo (7), also (7), random (7), often (7), populations (7), them (7), rational (7), theories (7), where (7), result (7), women (7), thought (7), tests (7), universitet (7), detta (7), off (7), comment (6), arbetslöshetssiffran (6), styr (6), ett (6), den (6), right (6), way (6), 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s i merely want to suggest that if economics is to be a science it must not only develop analytical tools but must also apply them to a world that is now observable or that can be made observable through improved methods of observation and measurement or in the words of the hungarian mathematical economist janos kornai in the real sciences the criterion is not whether the proposition is logically true and tautologically deducible from earlier assumptions the criterion of truth is whether or not the proposition corresponds to reality one of our most distinguished historians of economic thought george stigler has stated that the dominant influence upon the working range of economic theorists is the set of internal values and pressures of the discipline the subjects of study are posed by the unfolding course of scientific developments he goes on to add this is not to say that the environment is without influence but he continues whether a fact or development is significant depends primarily on its relevance to current economic theory what a curious relating of rigor to relevance whether the real world matters depends presumably on its relevance to current economic theory many if not most of today s economic theorists seem to agree with this ordering of priorities today rigor competes with relevance in macroeconomic and monetary theory and in some lines of development macro and monetary theorists like many of their colleagues in micro theory seem to consider relevance to be more or less irrelevant the theoretical analysis in much of this literature rests on assumptions that also fly in the face of the facts another related recent development in which theory proceeds with impeccable logic from unrealistic assumptions to conclusions that contradict the historical record is the recent work on rational expectations i have scolded economists for what i think are the sins that too many of them commit and i have tried to point the way to at least partial redemption this road to salvation will not be an easy one for those who have been seduced by the siren of mathematical elegance or those who all too often seek to test unrealistic models without much regard for the quality or relevance of the data they feed into their equations but let us all continue to worship at the altar of science i ask only that our credo be relevance with as much rigor as possible and not rigor regardless of relevance and let us not be afraid to ask and to try to answer the really big questions robert a gordon share on facebook opens in new window facebook share on x opens in new window x share on bluesky opens in new window bluesky svensk universitetsutbildning i fritt fall 25 oct 2016 at 17 48 posted in education school comments off on svensk universitetsutbildning i fritt fall samtidigt som urholkningen av högskolan fortsätter finns det ett politiskt tryck på fler utbildningsplatser men ensidiga satsningar på fler platser gynnar varken samhället högskolorna eller de studenter som får utbildning av tvivelaktig kvalitet i nuläget måste högskolans begränsade budgetutrymme användas till att stärka utbildningens kvalitet inte till att bygga ut högskolan ytterligare kvaliteten på högskolan är i dag ifrågasatt den tveksamma kvaliteten syns bland annat i universitetskanslersämbetets kvalitetsutvärderingar där nästan var femte utbildning underkändes en bidragande orsak till den bristande kvaliteten kan vara att antalet studenter har ökat snabbare än resurserna tillåter dessutom har det skett en urholkning av resurserna då ersättningsbeloppen inte räknas upp med de faktiska kostnadsökningarna och dessutom minskas genom ett produktivitetsavdrag samtidigt visar ifau institutet för arbetsmarknadspolitisk utvärdering att utbyggnaden av högskolan medfört sämre studentkvalitet detta är en naturlig följd av att övergången till högre studier redan är hög bland ungdomar i de högsta betygsintervallen det finns inte något överskott av högpresterande studenter som kan antas när fler platser tillkommer detta medför att studenter med allt sämre förkunskaper kommer in när högskolan växer dessutom är grundskolan och gymnasiets kvalitet ifrågasatt generellt lärarna måste lägga allt mer tid på att hjälpa studenterna genom utbildningarna vilket tar resurser från övrig undervisning det går inte heller att utesluta att kraven på studenterna sänks ökad genomströmning ger mer resurser till högskolan dagens resurssystem ger tyvärr incitament till högskolorna att godkänna studenter som inte når upp till kraven för godkänt göran arrius håkan regnér linda simonsen bra rutet svenska universitet och högskolor brottas idag med många problem två av de mer akuta är hur man ska hantera en situation med krympande ekonomi och att allt fler av studenterna är dåligt förberedda för högskolestudier varför har det blivit så här yours truly har vid upprepade tillfällen blivit approcherad av media apropå dessa frågor och har då utöver the usual suspects också försökt lyfta en problematik som sällan av rädsla för att inte vara politiskt korrekt lyfts i debatten de senaste femtio åren har vi haft en fullständig explosion av nya studentgrupper som går vidare till universitets och högskolestudier detta är på ett sätt klart glädjande idag har vi lika många doktorander i vårt utbildningssystem som vi hade gymnasister på 1950 talet men denna utbildningsexpansion har tyvärr i mycket skett till priset av försämrade möjligheter för studenterna att tillgodogöra sig högskoleutbildningens kompetenskrav många utbildningar har fallit till föga och sänkt kraven tyvärr är de studenter vi får till universitet och högskolor över lag allt sämre rustade för sina studier omstruktureringen av skolan i form av decentralisering avreglering och målstyrning har tvärtemot politiska utfästelser inte levererat i takt med den eftergymnasiala utbildningsexpansionen har en motsvarande kunskapskontraktion hos stora studentgrupper ägt rum den skolpolitik som lett till denna situation slår hårdast mot dem den utger sig för att värna de med litet eller inget kulturkapital i bagaget hemifrån mot denna bakgrund är det egentligen anmärkningsvärt att man inte i större utsträckning problematiserat vad utbildningsexplosionen i sig kan leda till eftersom vi för femtio år sedan vid våra universitet utbildade enbart en bråkdel av befolkningen är det ingen djärv gissning under antagande av att begåvning i en population är åtminstone approximativt normalfördelad att lejonparten av dessa studenter begåvningsmässigt låg till höger om mittpunkten på normalfördelningskurvan om vi idag tar in fem gånger så många studenter på våra högskolor och universitet kan vi under samma antagande knappast räkna med att en lika stor del av dessa utgörs av individer som ligger till höger om normalfördelningskurvans mittpunkt rimligen torde detta ceteris paribus innebära att i takt med att proportionen av befolkningen som går vidare till högskola och universitet ökar så ökar svårigheterna för många av dessa att uppnå traditionellt högt ställda akademiska kravnivåer här borde i så fall statsmakterna ha ytterligare en stark anledning till att öka resurserna till högskola och universitet istället för att som idag bedriva utbildningar på mager kost och med få lärarledda föreläsningar i rekordstora studentgrupper med nya kategorier av studenter som i allt större utsträckning rekryteras från studieovana hem är det svårt att se hur vi med knappare resursramar ska kunna lösa dilemmat med högre krav på meritmässigt allt mer svagpresterande studenter statistical significance tests do not validate models 25 oct 2016 at 00 20 posted in economics statistics econometrics 1 comment the word significant has a special place in the world of statistics thanks to a test that researchers use to avoid jumping to conclusions from too little data suppose a researcher has what looks like an exciting result she gave 30 kids a new kind of lunch and they all got better grades than a control group that didn t get the lunch before concluding that the lunch helped she must ask the question if it actually had no effect how likely would i be to get this result if that probability or p value is below a certain threshold typically set at 5 percent the result is deemed statistically significant clearly this statistical significance is not the same as real world significance all it offers is an indication of whether you re seeing an effect where there is none even this narrow technical meaning though depends on where you set the threshold at which you are willing to discard the null hypothesis that is in the above case the possibility that there is no effect i would argue that there s no good reason to always set it at 5 percent rather it should depend on what is being studied and on the risks involved in acting or failing to act on the conclusions this example illustrates three lessons first researchers shouldn t blindly follow convention in picking an appropriate p value cutoff second in order to choose the right p value threshold they need to know how the threshold affects the probability of a type ii error finally they should consider as best they can the costs associated with the two kinds of errors statistics is a powerful tool but like any powerful tool it can t be used the same way in all situations narayana kocherlakota good lessons indeed underlining how important it is not to equate science with statistical calculation all science entail human judgement and using statistical models doesn t relieve us of that necessity working with misspecified models the scientific value of significance testing is actually zero even though you re making valid statistical inferences statistical models and concomitant significance tests are no substitutes for doing science in its standard form a significance test is not the kind of severe test that we are looking for in our search for being able to confirm or disconfirm empirical scientific hypotheses this is problematic for many reasons one being that there is a strong tendency to accept the null hypothesis since they can t be rejected at the standard 5 significance level in their standard form significance tests bias against new hypotheses by making it hard to disconfirm the null hypothesis and as shown over and over again when it is applied people have a tendency to read not disconfirmed as probably confirmed standard scientific methodology tells us that when there is only say a 10 probability that pure sampling error could account for the observed difference between the data and the null hypothesis it would be more reasonable to conclude that we have a case of disconfirmation especially if we perform many independent tests of our hypothesis and they all give about the same 10 result as our reported one i guess most researchers would count the hypothesis as even more disconfirmed we should never forget that the underlying parameters we use when performing significance tests are model constructions our p values mean next to nothing if the model is wrong and most importantly statistical significance tests do not validate models in journal articles a typical regression equation will have an intercept and several explanatory variables the regression output will usually include an f test with p 1 degrees of freedom in the numerator and n p in the denominator the null hypothesis will not be stated the missing null hypothesis is that all the coefficients vanish except the intercept if f is significant that is often thought to validate the model mistake the f test takes the model as given significance only means this if the model is right and the coefficients are 0 it is very unlikely to get such a big f statistic logically there are three possibilities on the table i an unlikely event occurred ii or the model is right and some of the coefficients differ from 0 iii or the model is wrong so why p values cannot be taken at face value 24 oct 2016 at 09 00 posted in economics statistics econometrics 7 comments a researcher is interested in differences between democrats and republicans in how they perform in a short mathematics test when it is expressed in two different contexts either involving health care or the military the research hypothesis is that context matters and one would expect democrats to do better in the health care context and republicans in the military context at this point there is a huge number of possible comparisons that can be performed all consistent with the data for example the pattern could be found with statistical significance among men and not among women explicable under the theory that men are more ideological than women or the pattern could be found among women but not among men explicable under the theory that women are more sensitive to context compared to men a single overarching research hypothesis in this case the idea that issue context interacts with political partisanship to affect mathematical problem solving skills corresponds to many different possible choices of the decision variable at one level these multiplicities are obvious and it would take a highly unscrupulous researcher to perform test after test in a search for statistical significance given a particular data set it is not so difficult to look at the data and construct completely reasonable rules for data exclusion coding and data analysis that can lead to statistical significance thus the researcher needs only perform one test but that test is conditional 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 ...