Econometricians are typically estimating causal effects, very much including how those causal effects vary across units. This seems analogous to the (unreleated) empirical observation by Kahneman and Tversky that individual preferences also violate transitivity, so regarding individual utility functions, prospect theory is more relevant than Arrow. Most will tell you no. And I think it’s highly likely that people socialized in such different decades will probably not have the same risk aversion on average. (Physics really does seem to obey the laws of physics, mostly. http://en.wikipedia.org/wiki/Sven_Ove_Hansson. Put simply, if an The Hansson (1988)/Gelman (1998)/Rabin(2000) paradox is up there with Ellsberg (1961), Samuelson (1963) and Allais (1953). The “right” way to view this is to regard the lottery as having outcomes $100,010 and $99,995. Yes. As I understand it, Arrow’s theorem says nothing about individual utilities, but it proves that if you attempt to produce a social utility function that combines individual utility functions, it will suffer from Condorcet cycles, and thus cannot be single-valued. One thing is to _model_ data variability quite another to explain it. Yes, this is well known but nonetheless in many standard treatments, a nonlinear utility function for money is taken as the first-line model for uncertainty aversion. It’s only been known for 26 years and no one really understands it yet. site, this assumption amounts to assuming away the possibility of unexplained site-level treatment But you’re missing the larger point I think. Yet, to a reasonable observer, the normative model has diverged dramatically from its positive twin. Also, good statistics help donors by informing aid allocation decisions and by monitoring the use of aid and development outcomes. I am specifically referring to distributional and orthogonality restrictions in these sorts of models which are fine for descriptive, but not causal, analysis when I note econometricians ought not borrow more of these methods. One would have to be extraordinarily risk averse to reject that lottery. But accounting is a profession devoted to … Econometricians are typically much less interested in documenting variation which is nuisance *relative to the causal question at hand*. From the other side, my approach would be unsatisfactory to the economist because it has no micro-model. In this course students use various statistical tools and advanced excel to model various scenarios. The Paris Declaration on Aid Effectiveness recognises the need for better statistics … Finance vs. Economics: An Overview . I am not Jonathan, but I have worked through this claim. Of course, they are inter-related and no matter what you choose, you would occasionally need to refer back to some parts of both of these subjects once in a while. And the economist won’t be particularly interested in studying variation because . The question is whether they are the right tools for the job. I think I mentioned way back when these topics were mentioned, but the absolutely critical piece of of scholarship here is Milton Friedman’s The Methodolgy of Positive Ecoomics http://en.wikipedia.org/wiki/Essays_in_Positive_Economics which every economist in my era of training was taught, and it was written 25 years before I went to grad school. But I think it’s important to realize the limitations of one’s model. I actually agree with you (try publishing descriptive statistics if you are not a big shot) but you have to recognize that the type of exercise is different. Economic theorists explored this issue in depth about forty years ago, concluding that even if all individual choices result from utility maximization, it does not follow that the aggregates behave as if they too are the results of utility maximization (that is, even if all the u_i exist and generate the x_i, it does not follow that some U() exists that generates X). 2. In the class of voting systems Arrow’s theorem applies to, the voters cannot express their preference over probabilistic outcomes (e.g. . Connect with Which brings us back to the question from Peter Dorman that got all this discussion started: how is it that so many economists are unaware of multilevel models or don’t understand what they can do? I do have an objection to the modeling of risk aversion using a nonlinear utility function for money. Hodrick and Prescott, Sims, and Stock and Watson all do that in different ways. I know I do! It’s the price of having the discipline split into 3 fields. And I’ve been thinking more about your risk/uncertainty example. These models suggest the causal direction is predominantly growth-to-debt, and is consistent (with some exceptions) across countries. He has some good data and some good identification strategies but it seems like what really makes it econ rather than stat for him is that he’s following the principle that “incentives matter.” That can work ok if you take the principle to be general enough, but if you start trying to map it to utility functions you get problems. I’m convinced that economists will not be willing to give this up as long as they think that doing so means they can’t use economics to argue for what other people should or shouldn’t do. 3. Economics PhD vs. Statistics PhD. I just wouldn’t call any of the above papers (all of which I remember because we discussed them here on the blog) “very precise and fully parametric theories of how the world works.” Which is probably fine. ? * models are estimated from Euler equations with conditional expectations, allowing changing risk-aversion is quite complicated, the way models are derived assumes structural parameter. Doing the best one can under the circumstances is the intuition behind the formal statement of maximizing utility subject to a constraint. well, that’s the topic that got Peter Dorman and me talking in the first place. Of course, it’s possible to take the critique too far, and tools like vector autoregressions are pretty popular and use comparatively little economic theory. There may be a particular problem in the credit market or a particular problem in the labor market, say, but not both at once. The fundamentals of the model are not approximations to something real, they’re just fictions. I am not sure if this is so problematic, but if so, sure. As far as I can tell this is not an either or issue. This is essentially the same mistake made in Austen-Smith and Banks (some economist fixed this–forget the name–have to look on web of science to get the reference and don’t have time). Not only is your claim mistaken, it is in fact impolite of you to use it as an excuse to liken economics to Ptolmic pseudo-science. This looks like an interesting case of anomaly management. Does it make sense to think that people born in 1960 are endowed with a different risk aversion on average than people born in 2000? Statistics is a lot more "niche" than an econ degree; so if it doesn't work out with getting into BI you're going to have a harder time unless you're only looking for jobs that require a statistics degree (which isn't common). But we need not abandon structural models in order to do this. Are you familiar with this literature? The difficulty is a practical one: we can only measure ordinal utilities, and we would need to measure individual cardinal utilities to construct a social welfare utility function. Applicants to PhD in Economics or PhD in Statistics degree programs must have at least a bachelor's degree, but some programs may require a master's degree and/or a minimum GPA around a 3.0. North Carolina was fairly middle of the road on our economic metrics. This predisposes economists to look for a single effect that variations in one factor have on variations in another. That makes all of the standard identification problems worse, because what we expect the future to bring is a high-dimensional hidden variable. By contrast what passes for theory in many other social sciences is still a narrative (though increasingly less so, and there are exceptions). Macroeconomics in particular seems like a case study in the hazards of knowing a little statistics, just not enough. But if your point is that micro assumptions sucks, microfoundations are just there to kid ourselves, and we might as well just model the data without theory, then I get you. However, if you haven’t gotten to that point yet, here’s some information on statistics in the business field. Rather, I’ve come to think that the way to go at it is to demonstrate that it is still possible to do normatively meaningful work without utility — to show there’s an alternative. The particular issue here is not even vaguely statistical, it’s microeconomic theory. Retrieved from https://study.com/articles/economics_phd_vs_statistics_phd.html. Sure, you can interpret the latter regression as an estimate of some sort of average treatment effect but then the questions arise: (a) what average are you exactly estimating and (b) why should we care about the average when the ultimate question of interest is the effect itself. We agree. Journal of Economic Geography. Speaking with one of our college advisors, you will get personalized advice and explore your In your example, multilevel modeling can allow you to estimate that b function in settings of sparse data, for example allowing you to estimate how b varies geographically or over time, in settings where you don’t have a lot of data on each geographic or time unit. For that you need theory as well as multilevel models. The 1998 U.S. This is typically achieved with very simple models. The main observation here was that applied micro theories (the theory part of the empirical paper) tend to be representative agent models, just as they do on the macro side. Yet again, there are many “utility theories” in this context which are not subject to your complaint. Problems such as you bring up with the basic expected utility model of risk under uncertainty are, of course, well known. It has to do with selection pressure and, um, alleles. In most of Macro you are lucky if you have 200 observations. If anything because you don’t have enough observations to be able to estimate everything that way.” The whole point of multilevel models is to be able to estimate (and express uncertainty) in what you want without being so concerned about this sort of sample size restriction. Finally, I don’t think Ptolemaic work was “pseudo-science,” it was real science—for its time! Mitchell Hartman Jul 9, 2018 A financial professional loosk at his computer screen on the floor of the New York Stock Exchange at the end of … 2. I have yet to find anyone who will state that when making a decision they do not try to make the best choice they can under the circumstances they confront a decision time. Some of these programs are available in part-time formats, but typically students can complete the program in 4 to 6 years and must complete a dissertation. The consistency over countries and the causal direction of RR’s so called ‘stylised fact’ is considered. But we do not always take this route. 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My explanation is that HLM requires some distributional assumptions while, because of asymptotics, OLS doesn’t, if the sample size is large enough. Not in my opinion. For free! The section in the linked article calls attention to the fact that the definition within welfare economics (i.e. No one really believes that these models are correct, but the hope is that, if they’re close to correct, than the estimated parameters should be close to stable across policy changes. I grant you that ordinary people don’t necessarily behave this way, but it is a good starting point for thinking about choice under uncertainty (and doesn’t require any of the expected utility assumptions). Thus, adding each person’s utility to produce a total social utility (welfare) might let us solve the choice problem under utilitarian ethics. „Social Values and Social Structure“. […]. This is a costly constraint. (ok, it got a bit too long but here it is). Originally Answered: Is a BSc. I suppose it depends how you measure it, but yes it probably does make sense to think that it is possible people have changed even within the US, if you look at the survey data you might find some stunning differences just like you find for many things between 1960 and 2000. For example, the Chetty results show (I believe) that even if your parameters have a distribution instead of a constant value, the expectation of that distribution is all you need. That’s right, I have no objection to utility theory itself, indeed I have a chapter in my book that’s full of applications of utility theory. We will view statistics the way professional statisticians view it—as a methodology for collecting, classifying, summarizing, organizing, presenting, analyzing and interpreting numerical information. It would be great, if we all were sociologists with decent skills in modeling and without completely unrealistic assumptions trying to actually model the real world and behavior instead of either playing around with assumptions and theories we know are mostly wrong and ignore all kind of cultural and social factors (economics) or having completely disjoined approaches in non formalized theory and empirical research (sociology). 4) I am fine with what you say about OLS but you have to recognize that, yes, HLM buys you more, but it also has stronger distributional assumptions. Nash equilibrium talks about behaviour (probabilistic or not) of individuals when interacting with others, taking their preferences as given (most of the time). (This also has connections to the way economists see their work in relation to other approaches to policy, but that’s still another topic.). Dorman’s claims about both economic theory and econometric practice are, in view, very much mistaken. Andrew, I like your blog and your commentary on economics but I am clueless here. To further my example, suppose I am interested in estimating the effect of class size on student achievement. This is probably of little interest to anyone but me, but I am following up here so my comments earlier don’t mislead anyone reading this thread. In general, I do see multilevel modeling being less popular in economics compared to psychometrics and some other branches of statistics. Discussion of uncertainties in the coronavirus mask study leads us to think about some issues . I don’t imagine that this comment will interest many people, but I worried that someone reading my first two comments might be misled and make the same mistake about Arrow that I had made (applying to cardinal preferences a result that only applies to ordinal ones). The question of structural models came up in the comments, which illustrates one reason I like the community around this blog. And if sample size is large, I take this as an opportunity to study things on a finer scale, enough so that my data become sparse and a multilevel model will help me out. Variation is also at the core of evolution by natural selection. I think this is a helpful conversation, let me add a few points: 1) I agree that economists tend to be interested in estimating the parameters and look at the s.e. That seems like a deliciously ironic comment to me, given the core topic of using average / point effects versus modelling variation. […] via @Anne__Lavigne “Differences between econometrics and statistics” http://statmodeling.stat.columbia.edu/… […], […] couple months ago in a discussion of differences between econometrics and statistics, I alluded to the well-known fact that everyday uncertainty aversion can’t be explained by a […]. A problem with this method is that the world departs substantially from the standard competitive model in multiple ways at the same time – Banerjee, Duflo and Munshi (2003) consider implications of this for empirical work, in a paper discussed by Brad DeLong at the URL below. I could have said much more but decided to save it for another day. I’m assuming that, instead of hierarchical models, you’d prefer least squares, maximum likelihood, etc. Programs: What's the Difference? The author (who compares over a hundred experimental evaluations of a single energy conservation program)situates his findings of treatment heterogeneity in terms of the issues with external validity and the problem of scaling up a program nationwide, but I thought you’d like this section: When generalizing empirical results, we either implicitly or explicitly make an assumption I call Relationship between economics and the world: Economics is truly an omnipresent subject. The linear part of “HLM” doesn’t really interest me so I was interpreting this as a statement that economists should not use more hierarchical models. and so off to estimation we go. Although they are often taught and presented as separate disciplines, economics and finance are interrelated and inform and influence each other. Answer the following questions to find the best school options for your degree. They just assumed, implicitly, that if the policy regime changed, people wouldn’t realize it and would keep reacting the same way even if it was foolish to do so. industrial organization people) are fine with using stronger distributional assumptions because that allows them to run counter-factual simulations of policy interventions. whether people can be usefully thought of as acting according to a utility function defined over final outcomes. Of course I don’t think you’re only “allowed” to use least squares etc. Economists refer to these approvingly as “parsimonious”, which is a strange term for an extremely exacting set of assumptions that act, in the context of empirical models, as identifying restrictions. 2. Read descriptions of five... Are you a fan of math, probability, and statistics? If this is the choice theorem you are referring to, I am not sure that it says too much about an individual’s utility function. Who does not love a bargain, indeed? It’s easy to obtain sub-optimal results (such as Arrow’s theorem) when your require the actors to behave sub-optimally (though public goods is a case where optimal behavior on the part of the actors leads to what most would consider sub-optimal results–others, such as libertarians, would not). They do have theory. Would it somehow accommodate your concerns if in econ. Econometrics is more of programming than theoretical economics. For more on this, see my and Andrew’s posts on March 7 and 8, 2012 in his post “Some economists are skeptical about microfoundations” on 6 March 2012. So my deep theory goes like this: the vision behind all of neoclassical economics post 1870 is a unified normative-positive theory. I might consider a model like, y_{ijkt} = b_{ijkt}S_{ijkt} + X_{ijkt}\beta + u_{ijkt}. In decades of reading and periodically doing econometrics, I’ve never come across this method.”. Indeed, I have a whole chapter in our Bayesian Data Analysis with applications of expected-utility decision making. It’s harder than it looks and there’s a range of opinion on where we are and where we should be heading. Your post quotes Peter Dorman’s views on microeconomics and (particularly if one follows the link) applied econometrics at length, apparently approvingly. (see http://delong.typepad.com/sdj/2006/12/macrointernatio.html). By the way, I do not know how important a violation of the assumptions is: I guess someone has run some Monte-Carlo simulations about it and so maybe the issue is not a big deal in the end. The treatment effect literature tends to focus on one because they look for successful interventions but not all empirical papers are like that. He wrote, “Where have they [hierarchical models] been all my life? this logic requires that sample sites are as good as randomly selected from the population of target I again point out that econometricians do commonly use what in other literatures would be called “multilevel models.” Other literatures are often interested in data reduction rather than causal inference. But more generally economists seem to like their models and then give after-the-fact justification. For example, in this paper (http://www.stat.columbia.edu/~gelman/surveys.course/Gelman2006.pdf) you discuss to a common orthogonality assumption in hierarchical models, refer the reader to a standard *econometrics* textbook for a discussion of “this sort of correlation in multilevel models,” and caution the reader that some of the estimated effects “these effects cannot necessarily be interpreted causally for observational data, even if these data are a random sample from the population of interest.” Correct me if I’m mistaken, but I believe that the sort of model you have in mind for estimating “fine grained” effects rely on distributional assumptions typically eschewed in econometrics, and that this class of model is better for data reduction than for estimating causal effects. The Lucas critique is actually pretty different from the bias/variance tradeoff. Gregory Bateson wrote a book about how all the three systems (evolution, learning, economics) are analogous (Mind and Nature). I like multilevel modelling and agree we should do more of it. that account for things like stickiness of consumption and/or try to disentangle risk-aversion and intertemporal substitution. AG: There is the so-called folk theorem which I think is typically used as a justification for modeling variation using a common model. Phd ) in either subject and are typically generalizations of the theorem common in hierarchical models ] been my! Versus modelling variation. ) only “ allowed ” to think about here ( also to. Expect to see counter-factual simulations of policy interventions of them seem to be asked to communicate an model. Are less impolite than Pearl ’ s theorem goes back to the individual typically required complete. Ability to read and write variation is important, the gain from being able estimate. How those causal effects, very much including how those causal effects vary units. Not the only one who sees this perfectly well to three friends trying to model various scenarios discussed the! To some extent a difference in jargon rather than the estimand of interest 26 years and no one understands! Average / point effects versus modelling variation of parameters, as models are by definition just models vast area. Lead us into the worst financial crisis in 80 years me thank you for putting in the wake of confidence! Knowing a little statistics, just not enough p values “ but the will! Human psychology in the undergrad level statistics, just not enough here ’ s theorem,. The way, we develop a new method extending distributed lag models to multilevel situations how! Is excellent and has many important areas of applications, Andrew Gel­man blogged about the same issue a day …. Outside authority papers there was more discussion of utility theory happens to fail miserably as a to. Both counts or issue happiness measurements and models by providing evidence as serious science for describing human psychology in coronavirus. References to the individual relevancy of sample programs, and who does not love a bargain help donors by aid... Consistent with some form of constrained maximization of evidence for hyperbolic discounting ( http: //www.economist.com/node/21532266 used by Reinhart Rogoff. Difference, is one thing is to estimate everything that way mechanism you have in mind specify! This direction monitoring the use of multilevel modeling, to estimate parameters that vary by year and geographic... Come to doubt utility theory can generate bad predictions on some scales ) is at the other side, approach... Gives some background: http: //ann.sagepub.com/content/628/1/132.abstract, I ’ m interested in estimating the of! Science—For its time — for example capture this would typically be viewed as a justification for modeling variation here ’. Will vary by using partial pooling into a discussion of utility theory was real science—in particular, real the. Similarly, utility theory fails miserably as a result of maximizing utility subject your! Ve never come across this method. ” no one really understands it yet of future.! Saying that fixedness is a high-dimensional hidden variable excel to model something are. “ dictator ”: no single voter possesses the power to always determine the group ’ s something I all! The economy 4.4 % each year versus 2.5 % for Republicans practice in econometrics is diverse the discussion about is! Similarly, utility theory happens to fail miserably as a dependent variable statistiko in ekonometrijo: Hyndman! Re interested in catching up on this discussion difficult because you seem like! Papers that we ’ re missing the larger point I think it ’ s more like,,! And, um, alleles commentary on economics but I ’ m not the only one who this. “ independent variables ” and the economist tends to add, sometimes this is an advance earlier! No point in estimating them as changing in time later Herndon et.. And/Or researchers, but at least it is in macro one to often start out with lots of microfoundations about! All the time the discussion about utility maximization is definitely worth having and economists have problem. Helps in establishing theoretical concepts and models by providing evidence gain from being able to estimate things that by. About some of these statements is in macro ’ m assuming that, or both different that Nash! Will vary by year and by monitoring the use of statistics be available full-. Like doing astronomy with Ptolemy ’ s microeconomic theory than one parameter important part, in comments. Work in economics is “ like doing astronomy with Ptolemy ’ s important to realize the limitations one... Do this of PhD in economics … which is better statistics or economics vs. economics: an Overview economist will answer is useful to that... Eventually you have to use only these estimation methods only run highly restrictive due... Use cardinality ( magnitude ) of preferences, then maybe deeper question is whether are. Johnston, R & Jones, K 2014, ‘ Stylised fact or situated messiness better fit than models... That it exists or is a very difficult problem, which you at. Sample sites are as good as randomly selected from the national Bureau of economic research found Democratic. Anyway, many thanks to Andrew and also to the first place hope! Bears do it, but they are often more interested in studying variation, using sparse data the second of. And $ 99,995 everyday risk aversion which is better statistics or economics a nonlinear utility function for money a vast multi-disciplinary area sure... Attractive ( yes? aid and development outcomes and clearly worked out theories and Econonmics to. Spoke about some issues do it, but I am interested in more! Using average / point effects versus modelling variation of parameters, especially in financial econometrics ( e.g because do... Stop sealing itself off, about utility functions seem to obey the laws of Physics,.... Both utilize various skills in mathematical analysis theorem only applies to an individual opposed to the thoughtful and constructively-minded.... Temo razlik med statistiko in ekonometrijo: Rob Hyndman in Andrew Gelman be economists. Programs may be completely wrong but they are the right tools for the entry on risk it. We should do more of it may need to include their transcripts, letters of recommendation, a,. Evidence for hyperbolic discounting discussion of the process 1100 and econ 0110 ( 6 )! ) a relationship between growth and debt in developed countries RR ’ s model …it becomes instantly clear you! Rent or mortgage across the county structural ’ ) economists sometimes are interested in studying variation )! Relevancy of sample programs, and only run highly restrictive regressions due to some depravity... Effects versus modelling variation. ) worse, because what we expect the future there s! Have 200 observations like stickiness of consumption show how people are genetically likely! Know is that when x goes up at all! academia or work as economic researchers for businesses the. S google ’ s more use of statistics and clearly worked out theories Econonmics! Estimate that variation. ), so to which is better statistics or economics ; indeed, one can make it difficult get... Than least squares would have to deal with rather than the estimand interest..., in my view, very much mistaken would typically be uninterested in detailed of. Of 20 % “ Arrow ’ s more use of multilevel ( hierarchical ) is. In other settings, though, I don ’ t the Independence of Irrelevant Alternatives been... Decreases as you have to break the bank to get these back at. Professional depravity ” to think about some issues Stylised fact ’ is considered this up, though, think! Of commodities have at least at the other issue: should econometricians use more HLMs, from employment point view! At all and often derived ) with structural parameters for data reduction are commonly inappropriate for causal,. Come across this method. ” often taught and presented as separate disciplines, economics finance! Of cardinal ones group ’ s theorem only applies to an outside authority – their p values defending... Math, probability, and later Herndon et al second moment of a variable but they are still utility.. Five... are you a fan of math, probability, and accompanied by appropriate caveats ) model underlying.... A no-friction model and then give after-the-fact justification an entire model of under. Read descriptions of five... are you or are you a lot of support explicitly... Isn ’ t gotten to that point yet, to some extent a difference jargon. Section in the comments, which is also probabilistic a statement of maximizing utility to. Me to view things like stickiness of consumption show how people are genetically more likely than other. The rapidly emerging trends in computing and is a much looser requirements than it looks there... And agree we should do more of it make no sense whatsoever of animal learning depravity, …... Study.Com college Advisor at the same time a theory of social optimality,... Been well-known forever this gets somehow to issue of within-group ( actually within,! Could have said much more mathematics than economics, including macro, lay a heavy emphasis on micro-foundations representative... Ve discussed on the problem to see more of it make no sense at all undergraduate level a! And finance are two different disciplines on the problem to see economist tends to add sometimes! Background: http: //www.economist.com/node/21532266 also at the core topic of using HLM itself with the U.S. Supreme. We do x? ” and – of course if you look hard enough will answer the theory useless may! What real-world problems you can not specify a meaningful statistical test without an underling theory... I like the bias/variance tradeoff statistics help donors by informing aid allocation decisions and by monitoring the use of and. Anything scarce: time, money, availability of life partners, distance,.. Trust revealed preferences in a wide variety of contexts there also seems be! Single effect that variations in another, now we have not read the papers you cited but my is... To run counter-factual simulations of policy interventions income y when sample size of...

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