Levinovitz likens modern-day macroeconomics to mathematical astrology in the early Chinese empire. And in fact, the parallel sounds pretty accurate. The article is worth reading just to learn about classical Chinese astrology, actually.
But anyway, Levinovitz draws heavily on the econ disses of Paul Romer:
‘I’ve come to the position that there should be a stronger bias against the use of math,’ Romer explained to me. ‘If somebody came and said: “Look, I have this Earth-changing insight about economics, but the only way I can express it is by making use of the quirks of the Latin language”, we’d say go to hell, unless they could convince us it was really essential. The burden of proof is on them.’...and Paul Pfleiderer:
Pfleiderer called attention to the prevalence of ‘chameleons’ – economic models ‘with dubious connections to the real world’...Like Romer, Pfleiderer wants economists to be transparent about this sleight of hand. ‘Modelling,’ he told me, ‘is now elevated to the point where things have validity just because you can come up with a model.’He also rightly (in my opinion) identifies Robert Lucas as a key figure in the turn away from empiricism in macro:
Lucas’s veneration of mathematics leads him to adopt a method that can only be described as a subversion of empirical science:
"The construction of theoretical models is our way to bring order to the way we think about the world, but the process necessarily involves ignoring some evidence or alternative theories – setting them aside. That can be hard to do – facts are facts – and sometimes my unconscious mind carries out the abstraction for me: I simply fail to see some of the data or some alternative theory."A lot of what Levinovitz is writing is just a synthesis of things that smart economists have been complaining about in private for decades, and in public since the 2008 crisis. I think econ needs more critics like this, who are willing and able to go talk to the smart dissidents within the econ mainstream, rather than just accepting at face value the arguments of "heterodox" outsiders due to political affinity (as some econ critics sadly do).
Levinovitz, however, leaves out what I think is the most important development: the empirical revolution in econ. This has been most important in micro fields, since data is much more abundant, but it's also starting to influence macro. "Micro-focused macro" - using firm-level or area-level data to test the assumptions of macro models directly, rather than just throwing in a bunch of obviously wrong assumptions and hoping they yield aggregate results you like - is a big deal these days, and getting bigger. Soon, we may even see people insisting in seminars that DSGE models only use assumptions that have been rigorously tested on high-quality micro data! That dream is still far off, but it seems to be getting closer.
I also think Levinovitz should have given a shout-out to the successes of applied micro theory - auction theory, matching theory, discrete choice models, and the rest. He writes:
Unlike engineers and chemists, economists cannot point to concrete objects – cell phones, plastic – to justify the high valuation of their discipline.But that's actually not right. Econ theory powers lots of useful technology, from Google's ad auctions to kidney transplant allocation systems. Economic engineering isn't a term people use, but it's a real thing, and mathematical econ theories sometimes do an excellent job of describing human behavior in ways that can be consistently applied.
But anyway, Levinovitz' article is very good (and very well-written), and is worth a read. Just remember that econ is a lot more than macro, that it has become much more data-centric, and that it has produced a number of useful engineering applications.
This is so clueless. Testing individual assumptions for complex system is pointless. The question is not if the assumption is wrong, but how false is it and how much it matters. It's the expansion around the true model that matters.ReplyDelete
Define "complex system" :DDelete
Have you got any nice examples of macro models that have been overturned by empirics?ReplyDelete
Yeah, every single one of em. :-)Delete
The problem is that things that get "overturned" don't die.
If models won't die in the face of opposing evidence, what's the point of evidence? What's the point of the models for that matter?Delete
Then one might as well ask - what is the point of economics?Delete
A flippant answer, but also one worthy of some serious meditation is -
Economics exists to provide a [quasi-] rational appologia for the existence and continuing privileged condition of a small, wealthy elite class; and a parallel justification for keeping the majority in poverty.
To be clear, I am speaking of macro.Delete
There is only one problem with this empirical revolution.ReplyDelete
It still has not proved one thing which the common man thinks is both surprising and convincing.
Let me tell you a secret. It never will.
The common man was never convinced by econ theory either, as surveys show. The common man is only convinced of what his parents tell him when he's a common boy of 5. Maybe true for the uncommon man as well.Delete
Point is economic theory arrives when you prove one such thing. That is all it takes. But it will take an impressive idea. The empirical proving thing will be easy. Hence, it is not correct to put empirical and revolution in one sentence.Delete
What you call empirical revolution is simply Economists going about their day jobs intelligently, since theory is not for everyone and not everyone can be a revolutionary.
Comparative advantage. As Samuelson said, its both nontrivial and nonobviousDelete
While I do understand the notion of how empirical research has helped economics as a field of engineering and the micro department... I still cannot understand how will it help the macro department. As in, I think macro has some far more fundamental issues.ReplyDelete
To prove a point, I've yet to see any pressing macroeconomic question that has been solved through econometrics. Technological unemployment, minimum wages, fiscal multiplier... where is the consensus?
These three problems are quite apart from each other in nature. Fiscal multiplier has been studied probably the most and so far, I would argue that least is known about it.
Minimum wages and their effects has been studied to some extent and still, instead of consensus (such as the impact is of small magnitude to any direction), there seems to be a polarization.
Technological unemployment and the 'Luddite' fears. Now one can hardly say that there has been much empirical research in this subject. Why not? Because nobody really knows could we could offer a plausible path that leads to the "worst outcome" in the first place. And as a consequence, there is little research that would contest the actual possibility and rather there is some research that tries to instead offer a possible path (or paths) to explain how the 'Luddite' fears are unjust.
Research on fiscal multiplier is really telling. So far we know that it matters (eg. is not 0) and we know that it affects just about everything as much as it's affected by just about anything. So we know that we know nothing about something that matters in much of policymaking that deals with government spending. And to top this off — even if we would know, for example, that it matters where and how it's directed, Lucas would still intervene before we would conclude that government should not just build bridges to nowhere.
In minimum wage issue, I would suspect (but not conclude) that ideology seems to be playing it's part. And the research, so far, has not been able to do much about it.
Technological unemployment instead is just the matter that people are concerned about something that seems to be very real to us in qualitative terms, yet something that hardly can be addressed through quantitative terms. And one could very well imagine that if it is coming our way, we cannot actually know about it, because nobody could actually formulate the possibility while some, through statistics, convinced us of another path that never happened.
And thus, I unfortunately can't see much light of this empirical revolution in macro and related policymaking. And to be honest, it's not necessarily all that nice and tight in other areas either: https://www.gwern.net/docs/dnb/2013-ioannidis.pdf
i hear you. for the foreseeable future, there will remain pressing economics questions for which quantitative theories and quantitative data are not enough, by themselves. i am curious, what methods for inquiry into macro topics do you consider most useful/promising?Delete
That's a good question. Unfortunately, if I would even think that I had the slightest clue, I'd be probably studying economics myself.Delete
Only thing that really concerns me right now though is this wave of (apparent?) confidence that the "empirical revolution" is providing. Same goes with the experimental variant. I'm certain that both provide a healthy direction for research, but "revolution" doesn't really seem to translate into macro.
Actually, cell phones are good example *for* economics, because they aren't very useful unless the spectrum is efficiently and effectively used. And auction theory has been instrumental in determining the allocation of the spectrum (in ways that seem, to me, to have increased the effectiveness and efficiency of its use).ReplyDelete
hi don, I hear a lot that auction theory has been an empirical success. How does it increase the effectiveness and efficiency of the electromagnetic spectrum licensing process? I'm curious about this, and would like to be pointed in the direction of evidence.Delete
In the UK auctions companies overreached and encountered serious financial troubles, with BT having to sell off the yellow pages. I don't think that's particularly efficient. See Backhouse 'economics: science or ideology?'Delete
See also 'a tale of two auctions' (http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=1655400), which talks about how uncritically the success of the auctions has been accepted among economists.
Efficient doesn't mean we always get it right, does it? It'd be nice if it did.Delete
kookymonster--lots of good stuff here:
Besides Chinese astrology, Western medieval scholasticism comes to mind. And parts of it had some applications, too: the "latitude of forms" was the graphic precursor to the calculus, for example.ReplyDelete
But I tend to think that Daniel Davies got it right when he wrote that economics is a dept. of local control theory that got too big for its britches.
It is useful in applications where allocation decisions are an issue (kidneys; memory, bandwidth & time in infotech) but it strikes me that it will become less useful in the age of the oversupply of nearly everything, including money.
It may find new wheels once neuroscience gets around to the point of asking Ernst Mach's old questions of why it is that things like language and science themselves are efficient. Or why there exist physical minimal principles like the principle of least action. Sort of micro-micro cognitive economics, or perhaps nanoeconomics or femtoeconomics.
On the other hand, macroeconomists appear to be engaged in propping-up a system of debt finance born in the 17th Century and which is really useless today. Except as a sort of social engineering to keep the poor people unhappy and in line. Indeed it appears to be total B.S. and an increasing impediment to nearly everyone. Good luck with that!
1. As I keep telling you, you have to stop thinking there's a divide between micros and macros. That distinction went away with generation that was young in 1980, basically. The methods are basically the same.ReplyDelete
2. This "empirical revolution" is in your mind. Economists have always been interested in empirical issues - even the game theorists.
3. "He also rightly (in my opinion) identifies Robert Lucas as a key figure in the turn away from empiricism in macro:" What a load of nonsense! You and Levinovitz clearly haven't read Lucas's work. Example: Expectations and the Neutrality of Money is a piece of theory, but it's motivated by an empirical observation: looks like there's a Phillips curve correlation in the data. Lucas's paper gives you a theoretical explanation for the empirical regularity, and the theory makes testable predictions about how the Phillips curve will shift around. In other work, Lucas estimates labor supply elasticities (Lucas and Rapping), money demand functions, and the costs of inflation. We can argue about the value of the work, of course, but to say he somehow turned us away from empirical work is false.
Probably at least as guilty as Lucas, and probably more so in all this, is the late Paul Samuelson. He certainly successfully led the charge for mathematizing econ theory in a big way, but it is an old (and apparently true) wisecrack that he never ran a regression in his life.Delete
1. As I keep telling you, you have to stop thinking there's a divide between micros and macros. That distinction went away with generation that was young in 1980, basically. The methods are basically the same.Delete
Really? Macro people are always using GE, and most other fields rarely use GE these days, from what I've seen.
But more importantly, the difference between macro and micro is not (just) a methodological difference, it's a difference in the phenomena they study and the data they have to study them.
This "empirical revolution" is in your mind.
A picture is worth a thousand words in this case.
1. "Macro people are always using GE..."Delete
You'll never get it.
2. "A picture is worth a thousand words in this case."
Bad empirical work. That's not a revolution in empirical work, it's a profession that had a flurry of big theoretical developments - math in economics, econometric methods, information economics, game theory - and then ran out of theoretical things to do. What else but to apply them? That's not some demonstration of the superiority of empirics over theory.
"it's a profession that had a flurry of big theoretical developments - math in economics, econometric methods, information economics, game theory - and then ran out of theoretical things to do. What else but to apply them? "Delete
I do not think is the right away you go about trying to understand the real causes behind phenomena. So evidence is found that validates a theory. So what? I'm sure it does. That is probably going to depend on how you specify your econometric model, if you call that proper empirical investigation. See response to Luis Augusta 12.24
I've long thought that economists should pay more attention to what ecologists do, and regarding this post, let me suggest a 2011 article by James S Clark et al. in Ecology Letters: "Individual-scale variation, species-scale differences: inference need to understand diversity." As they show, analysis of aggregated (e.g., species-level) data often leads to mistaken conclusions, for example about ecological responses to climate change, because the action is at the individual level: "Species do not respond to climate, individuals respond to weather."ReplyDelete
I doubt there's an economist in the world with greater physics envy than Noah Smith. He wants so badly to validate his chosen profession that he'll repeat this "revolution in empirics" until we all cry mercy.ReplyDelete
I have an idea Noah - rather than constantly bashing other people and regurgitating everyone elses research why don't you go out and try to establish some empirics of your own? You talk a lot, but you haven't produced a single relevant piece of academic work. Get to it. Validate your profession with the work you do rather than simply screaming at people on the internet all day.
Although part of my daily routine is to bash economists, I think people also don't give enough credit to economic engineering (an expression I often use). Howver, don't you think you're not giving theoretical work enough credit? At the end of the day, what we want is theoretical work that is supported by robust empirical research.ReplyDelete
"At the end of the day, what we want is theoretical work that is supported by robust empirical research."Delete
No we do not. That is where economists are an odd bunch who don't really understand what empirical investigation really is. What you want to do is investigate the evidence first. And that means QUALITATIVE as well as quantitative evidence. It is not the job of a social scientist to validate a theory.
For example if you are investigating a liquidity trap you want documentary evidence from banks etc that says in words why they are putting their deposits at the central bank. It is a very time consuming exercise, but this is how it works in other disciplines.
And then you conclude after going through the primary documentation (which does not involve gimmicks like Granger causation tests etc) that "the weight of the evidence investigated here suggests that the reasons for high historical levels of cash deposits held at central banks is...."
Whether you have validated a theory or not by doing this is entirely secondary in importance.
First, I'm not an economist, I'm a mathematician. Second, I agree that theory should be built to explain and understand the data, as opposed to build data to support our theories. However, I also believe that raw data without proposals of plausible mechanisms are not particularly good.Delete
What economists actually need is to learn to let their theories go when they don't match the data anymore, in many respects, especially macro, it seems like economists are not willing to do so.
"However, I also believe that raw data without proposals of plausible mechanisms are not particularly good."Delete
I'm in complete agreement. But identifying that causal mechanism requires qualitative evidence. The raw data identifying large amounts of cash held by banks and restricted lending is not enough. It does not give you the cause. But a model or theory will not necessarily give you the real cause either. You don't want proposals, you want the real thing.
Eg, you go through bank reports and make the relevant interviews, see what they say about why they are cutting back on bank lending despite large amounts of cash and conclude that "the majority of banks are cutting back on lending because ..."
And you have got the causal mechanism without any irrelevant information or gimmick. This is how historians and other social scientists work.
I agree that this was a very good article. Having thought about almost every point in the article at some point in the last 8 years, it is fun to read someone that sees the same problems in the same way.ReplyDelete
I'm not sure why 'Economic Engineering' is not used in describing macro models very often. I suspect few individual economists have any reason to engage in such activity. Other than awards and prestige, what would be the motivation?
It is easy to see how micro economic engineering could bring great value to individual businesses or isolated processes that everyone agrees requires an efficiency makeover (like traffic patterns).
Unfortunately, macro seems to affect the most people but it is the least understood branch. It is vastly dominated by banking and finance, and there's just no way to make a career out of fighting that kind of power. So perhaps it needs to be taken out of academia and pursued in a different way.
I do expect that any new progress in macro must be heavily empirical also. Unfortunately, the data really is somewhat limited and hard to find. Hopefully this will improve.
I think economics is engineering. While all of engineering has a scientific basis, the goal should not be absolute precision as it is in physics. The first goal as I see it should be at least some kind of predictive ability, and precision should be a distant second goal.
As I've posted before, I'm all for the Noah-endorsed empirical turn -- not because models are bad but because data are good. I don't think economists can or should become "problematique"-oriented Annales historians, but that's not the point.ReplyDelete
However, I'm not sure Robert Lucas deserves to be considered the bete noir of mathiness. I do find his stuff prickly, but when Paul Romer attacked the Lucas and Moll article last year, he completely ignored the very empirical rationale given by the authors for not adopting Romer's increasing returns/monopolistic competition approach: in their view, intellectual property just isn't important enough in a large enough sector of the economy to justify abandoning core neoclassical assumptions. William Nordhaus has made very similar structure-of-the-economy arguments (though in a very different context) in recent work.
I would vote for Romer's model, probably, in a two-way election, but I'm very tired of Romer's long, aggrieved truth-seeker, Nobel campaign.
Economics exists to provide a [quasi-] rational appologia ...
Nah. Economics exists to hand out (quasi-) Nobel prizes to mathematicians. Any interesting branch of math - game theory, statistical inference, time series analysis, stochastic process theory - can be magically transformed to "economics" this way. And that is why economics will never rid itself of its math dependency.
It's too bad von Neumann died before the economics Nobels were invented; he would happily have accepted one (even as he privately dripped contempt.) At least Shapley had the grace to roll his eyes.
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I like astrologers because they warn people on possible ways.ReplyDelete
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Noah, what is your view on this, is Labini wrong? If so, why?ReplyDelete
You seem to think Romer gets it right. I guess you think he is one of these 'smart insiders'. But Romer has played a central role in this whole problem. If you really want to find out why some countries have grown (and others haven't) you are not going to find out anything from reading Romer - because he does exactly the same thing. Farmer in his latest post also does not have a very glowing view on Romer's contribution.
The people who really got it right about the economics profession were the likes of Maddison, Myrdal, Tobin and Morgenstern - and a long time ago.
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