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Economics Is A Lost Field (thisviewoflife.com)
38 points by goodmachine 1393 days ago | hide | past | web | 57 comments | favorite

Like supposedly scientists are split on Evolution, Global Warming and the Age of the Earth?

I am a bit unfair, but economists agree on a lot of things like free trade, public health care (for it, since the 60s), price floors and ceilings, carbon taxes, even in Central banks people broadly agree on a 'Taylor rule'-type behavior of managing inflation over the medium term.

There is a poll by the University of Chicago of a broad pool of economists from Ivies on a set of propositions and you can see that there is broad agreement on a lot of issues:



The reason why there appears to be a lot of disagreement is because of at least three reasons:

* economists with a esoteric position are more likely to search for the limelight and the media are happy to give them a platform.

* special interests are willing to hire economists to agree with them.

* Most importantly people don't like to admit they are wrong. Especially if they are vested ideologically or by religion.

Exactly - there is broad consensus, and the controversy is manufactured.

Anybody remember Bush's tax rebate?


Or all the times Republicans talk about how we can't cut defense spending because of the jobs that would be lost?


When push comes to shove, they're all Keynesians, anything to the contrary is just populistic rhetoric or opportunistic bashing of things they don't approve of. Pretty much everyone agrees spending boosts GDP in the short run, they may disagree about the size of the fiscal multiplier, what government should spend on, how big it should be, whether it will cause inflation, how much unemployment is structural, what the non-accelerating inflation rate of unemployment is, etc.


>When push comes to shove, they're all Keynesians...

But that has nothing to do with economics. That's because they want to spend money, same as the Democrats. There's precious little reason to believe anything good has come from monetary policy in recent years.

There are no atheists in foxholes, and there are no conservatives when the pork is being passed out.

But regardless, everybody believes spending raises GDP. But one side is afraid it will work too well, and will have undesirable side effects for their constituencies, and finds bashing on the grounds it doesn't work has populist appeal.

>There are no atheists in foxholes, and there are no conservatives when the pork is being passed out.

Well, no conservative politicians. Conservative voters aren't happy about it, but we consider it better than the alternative.

>But regardless, everybody believes spending raises GDP.

Well, sure, spending raises GDP in the short run. Because GDP includes that spending. I can raise my personal GDP this month by running up my credit cards, too, but that's not necessarily a good thing.

The "broad consensus" for Keynesianism is political in nature, not economic. The linked article is correct - you know what an economist is going to find before he starts looking based purely on his politics, and since the academy is far to the left you find lots of support for government solutions to whatever ails the economy.

I think the author's point is that economists are split on one of the most important issues. In that sense, it's not unlike physicists being split on the relative value of string theory. The only difference is that the economic issue is politically charged, so the tribal forces unsure the split endures. For physics, there are strong bandwagon incentives for everyone to do the same thing, so you swing from a huge multi-decade investment in an untested theory, to a complete vanishing of strings jobs.

In both cases, it's not the fact that something is unknown that's the problem. It's that smart people can't come to a Bayesian agreement, so it's a flag that people are being massively irrational.

I wouldn't call string theory an issue of major importance with respect to physics compared to monetary policy in economics. I'm not a physics buff, but my understanding is string theory hasn't yet made any predictions that would result in different outcomes than the standard model. On the other hand, the variety of monetary policy viewpoints among economists would certainly make different predictions, and their magnitude would be significant.

More analogous would be if physicists were split on whether gravity exists.

No, gravity is something for which there is overwhelming, unambiguous evidence. Macroeconomics is something that by its very nature is difficult to gather convincing evidence about. (No controlled experiments, very small observational data set.) Strings is much more like a macroeconomic question, because neither can be definitively tested.

How to formulate a quantum theory of gravity is the most important outstanding question in fundamental physics. Strings is the best guess. Policy-wise, the effects of government spending is the most important outstanding question in economics.

I think it's pretty analogous actually.

except economists aren't actually split on the effects of government spending in general, just on the relative importance of those effects in specific situations.

Wikipedia's collection of unsolved problems in economics - http://en.wikipedia.org/wiki/List_of_unsolved_problems_in_ec...

This is so true, the key takeaway is that you can hire a scientist to 'prove your agenda' with science, you can hire an economist to 'prove your monetary policy' with economics, and you can hire a mathematician to 'prove your trend/point' with statistics. And once demagogues figured out that having a [profession] type person on board improved the reception of their rhetoric they went off to find such people.

So what is the chance we could create some sort of Guild of Objectivity or some such. Basically membership in the guild for person of profession X requires that all of their output as a professional person be complete and without omission or slant. The proof of said objectivity to be created by review of at least 3 other Guild members of the same profession. Where the Guild removes members who violate their oath, and operates on constant self evaluation.

Not going to happen of course, but it would an interesting plot point in a fantasy story I suspect.

About creating your guild : it's very simple.

We return to the situation in the Roman empire, or the middle ages : politicians should no longer listen to scientists at all, so there is nothing to be gained by having scientific analysis turn out one way or the other. Ideally not just politicians, but everybody. Then your club would get back to normal.

The problem is that these scientific analyses carry a lot of weight, and affect monetary outcomes of individuals and organisations by influencing the government.

I would say the big victim of this thinking is not so much the science that goes one way or the other, but rather scientific theories that point out that it's impossible to know certain things. A lot of important sciences exhibit chaotic behavior, like economics, biology, medicine, even climate. This means there are stringent limits to how much we will ever know about them, and that it is perfectly explainable why statistics will (to varying degrees) suddenly fail to work on numbers from those sciences.

But while you can get a lot of money, researchers and positions for investigating why something is true, or why something is false, it's almost impossible to get resources when you claim that humanity as a whole can never make progress on investigating some phenomenon because there's some mathematical rule preventing that. Even in cases where it's effectively an undisputed fact that the central limit theorem doesn't apply, people refuse to accept that things like average do not have a well-defined meaning for things like stock prices, or economic indicators.

This seems to have become a central axiom of modern thinking, that science predicts everything. Even when people know the various basic principles preventing that, like Godel's theorems, or the basic axioms of statistics, they will deny the obvious consequences. Even if we do find the famous theory of everything, we are hardly done. Mathematics leaves a lot of real situations "undecided", and of course reality doesn't leave anything undecided. And even people knowing that you absolutely need the central limit theorem for any statistical rule to apply, refuse to give up their numbers when you demonstrate that it does not apply to their dataset. In most cases, that's easy : you demonstrate that at least one reasonable approximation for their data is a divergent series. At that point you've proven statistics doesn't apply to the dataset. It's easy to do this for lots of data, like stocks (because bad news amplifies, and can kill companies if the amplifier can be > 1, which is easy to find in the dataset), and it's easy to do that once you're outside of a trivially small range, the values of, say, solar irradiance are divergent, which means that whatever the statistical average is up to now, contains exactly zero information. You may as well roll the dice. The confusing thing is that it "generally" works in the short term, which is to say it's a huge effect that has lots of mass and needs time to move around, so it looks like a trend, but it isn't. It's a sudden change taking effect. Like when you have an approaching storm, the variance in any specific location looks like a smooth change, a trend, that lasts days or weeks, but it isn't. It's just the effect of a binary event that is the storm passing through, there is no trend.

We have collectively decided as a species that science answers every question definitively. Even if science itself proves that to be false.

Scientists are not split on those issues. Uneducated people disagree with the scientists. Big difference.

If economists have a handle on things, why did the IMF have to apologize to Greece for giving them bad advice? Why did the Black-Scholes Model fail?

You mischaracterize the disagreement. Scientists disagreeing with each other is not the same kind as anti science derps claiming that global warming is a conspiracy. Climate scientists, for example, can agree that the planet is warming, but they can't agree on whether it is warming at a 12C/century rate or a 1C/century rate. Most estimates fall somewhere in between, but the range of disagreement is HUGE in terms of impact and policy response.

And he is right...economists agree on plenty of policy matters. That they disagree on some of the major problems of our time is not a problem witn the field. Disagreement on major problems is a tautology.

Well, I'm not claiming that everything is just fine - the opposite of complete disarray. My point is that economics so burdened with controversy that its better to dismiss it.

Austrian economists will beg to differ.

The problem with those studies is that it's cherry-picking economists. Who cares about concensus? The measuring stick should be how correctly they can predict future events.

I wouldn't say Austrians as a whole disagree, though some of them certainly do. If you look at F.A. Hayek's expressed positions, he agrees with a reasonable number of those listed as consensus above. Yes to free trade, yes to public healthcare, yes to taxing pollution (rather than regulating it), no to price floors/ceilings, etc. Monetary policy and how to manage the business cycle are some of the points of strong disagreement, though.

Yeah, but Austrian economists are a tiny minority, and were much tinier before January 2009. The political/media system gives them 50% weight, not the success, or lack thereof, of their ideas.

"broad pool of economists from Ivies"

What are Ivies? At first I thought you meant Ivy League but more than half of the experts polled are not from Ivy League schools. (Chicago, MIT, Berkeley, Stanford)

Oh, sample size is 40! And it's only US economists. And only economists in academia.

That poll is not biased at all and represents the point of view of all economists in the world!

I'm sure the 40 economists will Strongly Agree on this with a high confidence.

There are two major counterpoints here. The first, which has already been mentioned, is that economists do agree on many things.

The second big point is that the profession actually does (mostly) agree on monetary policy when interest rates are comfortably positive. In the mainstream, it's widely agreed that when interest rates are positive, a) the fed controls inflation and b) the Taylor rule is a good approximation of what the fed should do.

When interest rates hit 0 in 2008-9, the field was thrown in disarray. Roughly, neo-Keynesians like Krugman believe the fed no longer controls inflation (or controls it less well) and so fiscal stimulus is necessary to supplement monetary policy. Neo-monetarists like Sumner believe the Fed continues to control inflation, via QE, so the Fed should just continue to use the Taylor rule but use QE instead of interest rates and basically just pump out money as long as the Taylor rule calls for negative rates, echoing Milton Friedman's advice for Japan in the 90's (which Krugman agreed with at the time!!).* According to both those views, monetary or fiscal stimulus have been inadequate.

Due to the unprecedented nature of QE an opposing camp has strengthened, arguing that the fed's actions have been reckless and ineffectual. These have been joined by dissenting voices, such as the Austrian real business cycle theorists which have always been opposed to fed intervention in the money supply.

The recent crisis raised new problems that the field has yet to grapple with. But finding good answers is likely to be very important. As events proceed, it will hopefully become obvious which concerns and predictions are warranted. I see the process as a healthy scientific debate, not a reason to throw out the whole field.

* To be more technical, they actually call for an abandonment of the Taylor rule and its replacement with NGDP level targeting, but in effect those are actually quite similar. One important motivation is to move away from equating interest rates with monetary policy, since interest rates aren't useful at the ZLB.

This is a solid snapshot of the actual state of affairs. What it really does is demonstrate how nuanced economics is, and how the article ignores these subtleties which make or break "good" economic policy. For instance, there is a massive difference between keynesian and neo-keynesian policy which the article completely ignores.

The basic problem with economics is mathematical. Economists keep acting like the economy is normally distributed when it is not. For example, the "Black Scholes Model", assumed that the system was normally distributed, differentiable at all points, continuos, etc., which of course was not true. What's worse is that every economist knows this, but they continue to use these faulty formulas because they are afraid of the alternative, chaos.

The economy is governed by chaos theory. Just like the weather or earthquakes. Chaotic systems don't have nice little formulas. They are extremely complex, and the slightest miscalculation can produce large changes in outcome. At least with the weather, the core principles are well understood. Scientists can perform experiments on how heat affects pressure and other properties. We can't experiment in economics. The core principles are not well understood. Therefore, economic models are hopelessly lost. Admitting that makes economists look dumb though, so they stick with Calculus and pretend the world is normal.

You do not understand stochastic analysis. What Black & Scholes did was to notice that all the randomness can be taken away if all you want to do is

    * Price a specific type of option under specific conditions.
Those conditions DO assume and include randomness. The funny thing is, just like in the physics of heating (which is the same as brownian motion), there are values which are deterministic, despite the intrinsic randomness of the process.

Really, it is not that the Black-Scholes model is differentiable (which is not).

You missed the whole point. Randomness exists in both normal and chaotic systems. The difference is that in normally distributed systems, randomness can be predicted.

I think you're just spouting a lot of buzzwords, and you're actually conflating (a) the relevance of chaos theory and (b) criticisms of normal distributions in economics.

A major recent criticism is of some economic models which have assumptions to the effect of "returns on this investment will be normally distributed." The criticism is that evidence seems to suggest that returns are not actually normally distributed; rather they have "fat tails," meaning that extreme events are more likely than with a normal distribution. And this error causes economic models to discount the role of these unlikely extreme events.

The Black-Scholes model effectively models stock prices as Brownian motion. This boils down to a single assumption: stock prices are the buildup of lots of very small INDEPENDENT random events (with FINITE variance) that occur over short times periods; this leads straight to Brownian motion. Brownian motion is indeed continuous; however, it is nowhere differentiable with probability 1. Because of the assumptions of finite variance and independence, the CLT tells us that returns will be normally distributed. So here, people pretty much agree that it's always these assumptions of independence that cause these models to predict poorly.

This is totally different from chaos theory. First of all, chaotic systems are not necessarily complex. Here's a chaotic map with a "nice little formula":

  f : [0,1) -> [0,1)
  f(x) = 2*x (mod 1)
While this is chaotic, we can understand much about this map. For example, each application produces an entropy of 1 bit (see entropy of dynamical systems...). So this is a map that "produces randomness" in a way. This is philosophically nice, because probability theory itself doesn't at all explain how randomness comes about.

You can create a chaotic map with a simple formula, but those don't appear often in the real world. Give me the formula for the weather, or to predict the next earthquake, or to model turbulence.

If the stock market movements were normally distributed, crashes would be extremely rare. Something like 1 every 10,000 years. Virtually all economic models assume something to be true that we know isn't.

Once again, don't confuse predictability with ability to understand a system. We actually have a fairly good understanding of weather dynamics and turbulence - and I can give you the formula for both of these - the Navier-Stokes equation! Not the simplest equation, but something understandable (yes, I know there's a Millenium Prize problem to see if we always get a smooth solution). We do understand how turbulence arises from this. And we understand the weather very well.

However, we can't predict the weather, nor can we predict the earthquakes. And as you correctly point out, the reason for this is chaos. The reason is not that we don't understand the underlying processes that govern these dynamics. Rather, the uncertainties in our initial conditions increase exponentially with time (due to chaos) and make long-term predictions unreliable.

No, not at all: what can be predicted can because it is essentially free from that randomness.

The fact that it is easy because the distribution is normal has nothing to do with the randomness. Really.

You cannot 'predict' randomness in a normal distribution as you cannot in a geometric or uniform.

Yes, you can predict the amount of randomness in a normally distributed system. If you could not, standard deviations would have no meaning, and all branches of statistics built thereon would be false.

In chaos theory, the best you can hope for is strange attractors. Unfortunately, economics doesn't even seem to have these.

Fluid dynamics is tough. There are a bunch of little particles each doing their own thing with no shits given for the greater cause of their laminar flow. Yet we can still make statistical generalisations that are useful in many cases. We can also make flying toothpaste tubes. We aren't quite sure precisely how those work, but we understand the parametric space well enough to keep clear of the holes in our knowledge. None of this means that we can predict extreme weather, though we have gotten better over the years. Neither does it prevent daredevil pilots and engineers from regularly pushing the flight envelope (and, once in a while, from breaking through).

Economics is tough. There are lots of little factors each doing their own thing with no shits given for the greater economy (or theory). Yet we can still make statistical generalisations that are useful in many cases. We can also design and manage monetary and financial systems that allow for unprecedented levels of human wealth and complexity. We aren't quite sure precisely how these work, hell economists can't figure out what the traders and bankers are up to half the time, but we do know where we cross from solidly-footed theory to still-debated hypotheses (even if nobody else cares for the delineation). None of this means that we can fix financial storms, though we have gotten much better over the decades. Neither does it prevent bankers and traders from innovating at the brink of theory.

what do you mean 'we have gotten better at fixing financial storms'? The financial magnitude of swing in the recent financial crises has been as bad or worse than the great depression, and to me, it seems like the only reason we aren't starving in the streets like they were in the 30s is because the green revolution has made it so that feeding people is no longer largely a productive capacity problem.

I've been impressed by the reasoning behind market monetarism (mainstream credibility: good and rising). They also seem to have a pretty good ante facto grasp on events, in the sense that when e.g. Japan commits to a less tight monetary policy the results (amazingly rising real GDP with little inflation) do not seem like the sort of the sort of thing other pundits would expect, while being the sort of thing you would expect from reading market monetarist blogs. It gives the impression of being the theory that takes the last few years in stride (or earlier decades too of course) whereas the other economic stories I know are busy manufacturing new special explanations for each successive event.

Check the sidebar of "The Money Illusion" for an introduction or Google market monetarism.

Relevant judgments here: Fiscal policy can't do anything monetary policy can't, so you should generally prefer QE to increased government debt, unless a separate case is made for government investment qua investment; with a properly behaving central bank the fiscal multiplier is exactly zero because the central bank is already stabilizing NGDP. Money is 'tight' or 'loose' in the general economy depending on NGDP growth rates; looking at interest rates or money supply will be exceedingly misleading as to what the effective policy is right now, never mind what it should be going forward.

-- Eliezer Yudkowsky

Economists, like most people, want to defend their reputations. When they are proven wrong by events, they find it painful to admit they were wrong. Paul Krugman wrote about this in a recent blog post:


it's funny, because he's never admitted he was wrong, himself. Go ahead, search for it.

Ok... I'll bite.

He predicted deflation as part of the economic crisis, which hasn't happened. He's mentioned that in several posts, most significantly in this one:


He also frequently writes about the state of macro economics, the politics involved, the different camps in the debate and what can be done about it. For example:

  So here’s what should have happened: economists propounding these other 
  approaches should have said, “Gosh, I seem to have been wrong. I need to 
  rethink my approach.”

  Oh, and by the way, I have done that. As I’ve written before, I rethought my 
  views about liquidity traps and currency crises after the Asian crisis of the 
  late 1990s; I rethought my views about advanced country debt and deficits 
  after making a wrong prediction in 2003 (although in that case my mistake was 
  in not taking my own model seriously enough).


And that same search will turn up many, many posts where he talks about intellectual honesty and validity of different arguments, ranging from "this guy is lying" to "I disagree, but this is a reasonable point of view".

"Notice how Keynesians responded to the partial failure of a prediction: by asking what they got wrong, and how their model of the world needed to be adjusted."

One could make that argument about the ptolemaic system and epicycles. While krugman admits his prediction was wrong, it is a subjective argument as to whether what Krugman did in the end was to admit his model is really wrong, or if he decided it needed mere "adjustment". I know where I stand on that judgment.

I am a physicist working on complex systems. When I read Krugman I get the vibe of a scientific peer using the scientific method within the constraints of the information available. Pretty much all other economists that make it into the mainstream press fall very much short of that. Most don't even have a falsifiable model.

I'm a biochemist engineering an enzyme, when I read Krugman I get the vibe of someone who uses the veneer of the structure of the scientific method to delude himself into thinking that he isn't operating in the realm of confirmation bias.

I could also be biased: When I was a (math major) undergrad holding study sessions for lower-level mathematicians at a school with a very prestigious econ department, I recall the econ students coming to me with problems that seem to be specifically concocted to satisfy a culture that valued 'make a model such that you can take the gnarliest derivative possible so that you can remind everyone that you actually could pass calculus'. Gnarly derivatives, of course, rarely correspond to honestly measurable quantities (up to error). There was also NO dimensional analysis, so often equations would have the same term in an exponent, as a sum, and as a divisor.

In the real sciences for 90% of useful things, we take advantage of taylor's theorem and call everything locally linear.

I stand corrected, he has said "I was wrong". Once. On the same day that he posted the I was wrong article. And about a topic that's not economics:


"Lost" implies some kind of regression. The truth is that economics has always been exactly the way the author describes. The economy is full of human actors who are irrational, who act based on their expectation of how others will act, and many of whom study economic theory and follow the pronouncements of economists.

Imagine how difficult astronomy would be if stars adjusted their spectra according to their anticipation of spectral trends, which was informed by emotion and by their reading of physics papers. Now imagine astronomers beaming spectral fashion magazines at the sun and being held responsible for skin cancer rates and crop yields. Imagine interest groups representing growers of different crops at different latitudes, as well as sunscreen industry groups, all beaming their own spectral fashion magazines at the sun. If that were the case, I doubt physicists would have had enough confidence in their understanding of the solar spectrum to deduce the existence of a new element from it [1].

[1] http://www.universetoday.com/53563/who-discovered-helium/

What a lame article. I don't even see what the point is. It's just random whining that people in a certain field don't know all the answers. There wouldn't be much point in studying economics (or anything, for that matter) if all the problems were solved and everybody knew all the answers.

There was an article on HN just the other day about Voyager 1 entering some unknown region of the universe. The physicists involved had no idea what was going on and all of their predictions turned out to be incorrect. So why no whiny article titled "Physics is a Lost Field"?

Macroeconomics is hard. It's nearly impossible to perform experiments validating large scale macroeconomic theories. If there were a way to accurately test the impact of the government borrowing and spending money, then it would be carried out. But realistically there's no feasible way to do that.

What's more, the author doesn't propose any solutions. Anybody can say this or that is screwed up. But that doesn't help anything. I'm sure the econ world would love to hear his theories that unquestionably solve the problems once and for all, but of course he didn't offer any.

Also, his mention of Freakonomics has me doubting his understanding of economics. The sumo example he mentions is a pretty straightforward application of microeconomics. He then goes on to say, "Freakonomics is, however, silent on monetary or fiscal policy." Monetary and fiscal policy are macroeconomic concepts. Economics is about making decisions and choosing between alternatives - how will people spend their money, what will they choose in this situation, etc. There's more to econ than just growing the national economy.

the problem with economics is its self-conscious insistence on being taken seriously as a rigorous, hard(ish) science which leads to an over use of complex, fancy looking mathematical models that, given the subject, require a great many assumptions to "work". in a dynamic, human-created system with constantly changing rules (society) those assumptions are often massive over simplifications or quickly made obsolete with the passage of time. better to think of economics as philosophy with which statistics might be applied rather than a science in and of itself...(i have a graduate degree in economics)

And don't forget that the object of study is actually sensible to predictions about it, in multiple ways, which gives a new dimension to that can of worms.

I'd say that the main problem is that economists are using numbers, and they really want to use them, but they're using them blindly. They'd love to be treated as physicists, but, sorry, they aren't yet. Economy is a very green field with little actual prediction capabilities (at least on a macro scale), and the sooner we accept it, the better.

And the bottom line: never ever trust anyone trying to justify the application of some economic policy based on mid-term or long-term predictions, no matter how many numbers may they throw at you.

Economists are no different than the prophets of old. Everyone claims to be speaking the truth. What's sad is that they live off the 1 correct prediction while disregarding the 20 that they completely failed on.

The field simply is not a science. It has no predictive value.

Mistaking Economics with Finantial Engineering is a big fail.

And blaming Merton & Scholes for the Long-Term Capital Management fiasco is another error:

The fact that they (actually Meriwether, but anyway) invested where they should have not (Russian bonds, look at that! like investing in Greek bonds right now) is just an indicator that we are human. Also, it is quite disputable that the intervention was necessary. The Fed acted short-term (which is one of the big mistakes of modern governments) and it might have gone better than predicted.

You can just take a look at the performance of Renaissance Technologies along the years to realize that you can make a lot of money if you really invest (human & technological capital) on it. It is hard, but it can be done. And using maths & CS, little more.

This doesn't prove that economics is wrong. It just proves that something like one of every two economists is wrong. This is not a hard problem to figure out the answer to by looking at historic data either. Read both sides closely, and if you're paying enough attention, you'll figure out which one is right pretty fast.

IMO - The underpinning issue with the subject of Economics is that it's often misconstrued as a science. A science implies that what you are studying and testing is reproducible (i.e. the scientific method). However the issue with many of the theories of economics is they are subject to change. Let's say for example you state a theory that says "If X happens, Y will happen". Often in economics, once X happens to a certain point (let's say everyone catches on to the idea that X will always yield Y, so everyone simply goes and does it), Y may no longer happen at the same rate. So really the issue for me is - the people who make fiscal decisions are basing them on unproven (or let's say slightly proven) theories. It's better than nothing (which is the alternative), but still doesn't make it an absolute science.

I don't think your understanding of the word science is universal. For example, I think it is perfectly scientific to study things that do not repeat very often, like the big bang or extinction events caused by large objects striking planets.

When I say science, I just mean the gathering of knowledge through systematic, empirical means. I think that's what a lot of people mean by it. The problem with economics is that the empirical tools we have at our disposal are not very powerful, the data is noisy, and the factor-space is huge.

My point is the definition of science gets misconstrued. The general populous assumes that something that is scientific is a "truth". We often say "Big Bang Theory" not the "Big Bang Truth". In economics the line between truth and theory gets massively blurred (for reasons I'm not going to begin debating here).

So when the Fed decides to drop the interest rates or a Harvard economics professor writes a report on how X will cause Y, we consider these to be absolutes. Meaning, if for every time X happens, there is a reactionary Y that needs to happen to keep growth consistent. We just believe because they've created an economy theory to support it, that is must be true.

This is "a pox on both houses" disingenuous pablum. Consider their description of the Reinhart-Rogoff affair:

This intellectual disagreement over the impact of fiscal decisions has spilled into the public domain with the fight between Nobel Prize winner Paul Krugman and the Harvard Duo of Carmen Reinhart and Kenneth Rogoff. Here is the letter written by Reinhart and Rogoff labeling Krugman‘s comments on their work as “spectacularly uncivil behavior.” The spat is over the impact of debt on economic growth.

What the author must have known, but fails to mention, is that Reinhart-Rogoff was wrong due their selective data usage and spreadsheet errors.

Due to the too frequent economic crises, during my education I considered getting a Ph.D. in economics. I got some famous texts on economics, read some chapters, talked to a famous economics professor, did a big upchuck, concluded that the field was hopeless, and stayed with applied math.

Why hopeless? Here are my guesses:

Data and Reality. Historically the people studying economies just had far too little data on their subject. By analogy they were trying to understand, repair, or re-engineer a car but had never looked under a car, never popped the hood, didn't know what piston rings were, and still were in doubt if the thing had front wheel or rear wheel drive. In a medical analogy, they had no cadavers to dissect, X-rays, MRIs, blood tests, etc. In an astronomical analogy, they had no telescopes.

So, they never did well with what is usually one of the first steps forward for a science -- the descriptive part where we just give a good description of the subject. Astronomy, biology, thermodynamics, chemistry, electricity and magnetism, and more all started with good descriptions of their subjects.

Or, for cars, start tinkering, as Henry Ford did, with a lot of time with dirty hands, and only later use finite element analysis to build models of stress and strain in continuum mechanics. Or naval architects had a lot of experience before they moved to towing tanks and the Navier-Stokes equations.

Bluntly I had to conclude that the academic economists really just didn't have even a first, good descriptive understanding of a real economy.

During WWII for war production planning, Leontief worked on 'input-output' models of the US economy. Good for him. But I was told that the US academic economics community very much did not like his work because it was not 'theoretical' enough as in, say, 'political economy'. So, it looked like academic economics wanted to stay with pomp, pretense, prestige, ignorance, and incompetence.

One of my Ph.D. advisors wanted me to take a course in economics so that if I did any work on a committee on a 'public sector' problem, then I could defend myself from attacks by floods of gibberish from academic economists. I've had no desire to do any such 'public sector' work and have not, but I signed up for the suggested course.

I wanted to be nice to the professor and not cause trouble. So, during his lecture with a lot of hand waving and free hand curves but no data and nothing convincing, I just took notes and said nothing. Then after class I asked him what he was assuming about his curves -- continuity, uniform continuity, differentiability, continuous differentiability, monotonicity, concavity, pseudo-concavity, quasi-concavity (e.g., in case he was intending to use constraint qualifications for the Kuhn-Tucker conditions for optimality). He was unhappy. Later in the day, I got a message to see my advisor. I was out of the economics course -- the professor claimed that I might disrupt the class. That was not my intention, but good riddance! But that professor's reaction seemed to be a special case of a major 'feature' of academic economics -- have a tightly knit 'club' that wants only true believers and pushes out any skeptics. Or the first rule of Economics Club is never talk about the rules of Economics Club!

Net, academic economists know next to nothing important about any real economy. Real economic policy needs much more in data on real economies, insight into reality, good judgment, and real effectiveness with applied math than is common in academic economics.

Lest we forget though, there is Hayek's "information problem". Econometric data are by their very nature aggregated, and that fundamentally introduces bias. How do you choose how to aggregate your data? How do you choose what relevance that particular aggregation means (from a policy standpoint, or from a fundamental standpoint)?

A number such as "unemployment", for example, is loaded. Are parents that could have a job but choose to stay home to take care of children "unemployed"?

Common problem. E.g., how to "aggregate" data in astronomy? For a simple first cut answer, work hard, get a lot more data, work hard, have some good ideas, get a lot more data, work hard, etc. So, for astronomy, use spectroscopy to identify the elements in the star. Use the brightness of the star and the red shift. Get empirical distributions of various characteristics of the stars and begin to guess that stars go through stages and where the distributions are low the stages are short.

So, start by observing, getting a lot of data, and being just descriptive; economics didn't and still doesn't do nearly enough here. Then look a little deeper and start to make some sense of it; economics has done next to nothing here, necessarily so since they didn't get a good grade in the first grade with the descriptive work. For something with a little promise, e.g., Leontief's work , they don't like that and regard it as not acceptable in Economics Club.

So, with such work, in astronomy get Hertzsprung–Russell diagrams. Nice progress.

Now, continue: Take what is known about weights in the periodic table and observe that if press together two deuterium atoms to make one helium 4 atom, then lose some mass and, thus, get some energy. Keep this up across the periodic table and see that iron has the least such energy. Observe that can keep pressing light atoms together to get heavier ones, e.g., carbon, oxygen, ..., iron and get off energy. Do a lot of model building of the reactions in the centers of distant stars. Check with the data, e.g., the Hertzsprung–Russell diagrams.

Eventually come up with a well tested, apparently quite solid, model of stars. A lot work, bright ideas, spectroscopy, expansion rate of the universe and red shift, nuclear physics, etc. Didn't say it was easy.

Much the same in other fields of science that have been successful.

So, if economics wants to copy that methodology, then they need to get their hands on more data. Then, say, they need to look at the flows that, intuitively, appear to be generating the data. I know; I know; too soon want a lot of curves on propensities, and will have a tough time there. Not guaranteed to be easy. But neither were the other sciences that were successful.

My view of academic economics is that they sit in small, dark rooms with the doors closed, hope for a single stroke success comparable with E = mc^2 in physics, dream up models, essentially of imaginary economies, hope, but not get very far. So, they don't want to do the first, observational, low level grunt work of data collection and basic description that astronomy, chemistry, biology, etc. did.

There have been suggestions that the Princeton econ department has two halves with one half, then with Bernanke, the more empirical. If so, good for the Fed and the US since we will be less likely to be stuck with crack pot ideas from "defunct economists".

A danger here: So, with such work with imaginary economies, some to be defunct economist makes a lot of absurd assumptions and finds some optimal solution -- maybe he studied some linear programming (Kantorovich, Solow), Kuhn-Tucker theory (Arrow), Lagrange multiplier theory (Debreu), or dynamic programming (Samuelson). Then, seeing a real economy and an opportunity for fame, status, prestige, tenure, lots of undergraduate co-eds for secretaries, he takes the solution from his imaginary economy and says that that is what the real economy should do. Bummer. Good way to kill tens of thousands of people from unemployment, busted homes, street crime, infant mortality, drug abuse, suicide, etc. Incompetence is a bad thing; incompetent economists are really ugly things.

Your point about unemployment is an example: Early on I looked at it and asked, where the heck is the definition, that is, the empirical or operational definition? Next, one level deeper, what the heck are we really counting? E.g., might we be partitioning the data in some way that would be better? So here what do we want for better? Sure, we want something that can help us with reductionism, that is, clear causality. But the actual unemployment data is so poorly defined and so "aggregated" that our hope for anything causal is just smoking funny stuff, like the astronomers calling stars just points of light and not looking deeper with spectroscopy, the periodic table, nuclear physics, etc.

Finally I understood what the empirical economists intended to do with data such as unemployment: They just said, it's a measurement; hopefully it is done in a consistent way month by month; we agree we don't have a good definition and that the data is too aggregated and has basic problems in measurement, but we just take the data as it is; with the data, we will do just empirical statistical modeling. Then, recognized or not, they have essentially given up making unemployment data an input to anything reductionist, causal, or scientific. Suckage. Meanwhile academic economists are driving late model cars, and millions of people are suffering from unemployment likely for no very good reasons. Suckage.

It's also worth searching youtube for "Ben Bernanke was wrong" to see how utterly clueless some of our 'leading' economists can be.

I have the impression that economists (the real ones, not the politicians that use that title) need an esoteric terminology to protect their field. That'll decouple macroeconomics from policy while it's developed (and it's still embryonic) until nobody can deny their claims anymore.

Economics is broken in a number of other ways.

The biggest questions to me are growth and sustainability. In the neoclassical world (I studied and degreed in the study) growth factors are all engogenous to economics:

The Neoclassical Growth Model, where output is a function of current stocks of capital and labor: Y = A K^α L^(1-α ), and capital accumulation is simply a function of investment and captial depreciation: K = sY - δK

The AK theory, which reduces growth to aggregate capital: Y = AK.

The product-variety model (Romer, Dixit & Stiglitz): production as a function of summed intermediate production functions based on capital

The Schumpeterian model, output is based on a productivity function (technology, assumed to be increasing without limit, and capital.

Technology increases. Inputs are perfectly substitutable. Innovation will produce substitutes.

And that's straight out of the first chapter of a graduate level text in economic growth (Aghion & Howitt, The Economics of Growth, ISBN 978-0-262-01263-8).

Then there's the whole class of heterodox economics: http://en.wikipedia.org/wiki/Heterodox_economics

Among these, the fields of thermoeconomics / biophysical economics / ecological economics, in which a, if not the primary factor relating to economic growth is energy. Many of the contributions to this field come from outside the field of economics, particularly from ecology, biology, and physics, but there are also a number of classically trained economists: Kenneth Boulding, Robert Ayres, Charles A.S. Hall, Robert Costanza, Herman Daly, H.T. Odum, and others. http://en.wikipedia.org/wiki/Heterodox_economics http://en.wikipedia.org/wiki/Thermoeconomics

Further work is being done by a wide range of people, some with training in finance and business, but "unbrainwashed" (in their own words) by economic orthodoxy. Gail Tverberg of Our Finite world (http://www.ourfiniteworld.com/) is key among these. Joesph Tainter has an extensive study of collapse of complex societies with profound implications for the Western European, now global, civilization.

When I look at the predictions and statements of mainstream economists, I see huge amounts of wishful and/or fuzzy thinking, and a long string of disappointments. When I look at the track record of the energy-oriented heterodoxy, I see a much stronger record. I tend to consider my own degree "economic woo" -- more similar to astrology and alchemy than astronomy and physics.

Not that it's _all_ bunk: markets are useful (though highly imperfect, and rare) concepts. Changing the relationship of money to underlying real wealth (which I'm increasingly convinced should be measured in fungible energy units, localized (and yes, that reads "FUEL"), and even predictions of how people generally _do_ behave (though not how they _should_) can be useful. But in planning and plotting a long-term path through the future, I'm increasingly fearful that economics is the wrong tool for the job, and that collectively we're going to have an Alan Greenspan moment, in which we find we've been grossly mislead by our belief system.

First, one should not rely on consensus or general agreement. Historically, the "consensus" or prevailing theory has been wrong or substantially flawed many times. Furthermore in most scientific fields one can find a number of highly qualified dissidents who do not accept the "consensus." They are often small in absolute number, but an absolute consensus is quite rare. Finally, periods of rapid scientific and technological progress are often characterized by a lack of consensus.

Ben Bernanke's Federal Reserve policies are largely the prescription of Milton Friedman and the monetarists. Friedman argued that the Great Depression was caused by allegedly tight monetary policy in the 1930's that resulted in a massive series of runs on banks and crashes. He argued that the Great Depression could have been averted by loose monetray policy along the lines of quantitative easing.

For many years, until recently, conservative, business, and libertarian groups embraced Friedman's ideas probably in part because quoted out of context, they shifted the blame for the Great Depression from misconduct and bad decisions by private corporations and wealthy individuals to the federal government and civil servants who provide little funding to conservative, business, and libertarian lobbying groups. Friedman's arguments also argued that the government need only have provided cheap money to prevent/cure the Great Depression rather than activist government programs such as Social Security and the alphabet soup of public works programs such as the Works Progress Administration (WPA).

Keynesian economics strongly disagreed with the Friedman/monetarist theory. Keynesians argue that the United Staes did have loose monetary policy in the 1930's and it did not work. They argue that the United States and much of the world was in a liquidity trap, an unusuall situation in which interest rates reach or nearly reach zero but a negative interest rate is needed to produce a revival of consumption and demand. Pouring money into the economy through the Federal Reserve or other central bank won't work. Nor will there be much inflation, because the money just sits in bank accounts unused.

In Keynesian economics, absent some extreme positive economic shock like the invention of a new energy source, the government must borrow heavily and spend heavily to restart the economy, pulling it out of the liquidity trap, which it is argued is what World War II finally did in the 1940s.

Keynesian economists like Paul Krugman and Dean Baker argue that the United States has been in a liquidity trap since the crash in 2008. The liquidity trap theory makes a prediction that has so far been borne out, that inflation will remain low despite the huge infusion of money from quantitative easing and huge budget deficits. These other folks such as John Taylor, Peter Schiff, Ron Paul, and various other cricits of both Ben Bernanke and the Keynesians like Krugman have been consistently wrong about inflation for the last five years.



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