Economist's View

"Trumped by Darwin?"

Robert Frank returns to the point he made in Alpha Markets, i.e. that Charles Darwin provides the "true intellectual foundation" for economics. Though the example this time is male elk rather than bull elephant seals, the central point - and it's one worth giving more thought to - is that "Individual and group interests are almost always in conflict when rewards to individuals depend on relative performance." In these situations, which occur frequently in economic and social relationships, the assumption in neoclassical economic models that the maximization of self-interest is consistent with the maximization of social interest does not hold, and failure to recognize this has " undermined regulatory efforts ... causing considerable harm to us all":

The Invisible Hand, Trumped by Darwin?, by Robert Frank, Commentary, NY Times: If asked to identify the intellectual founder of their discipline, most economists today would probably cite Adam Smith. But that will change. ... Charles Darwin ... tracks economic reality much more closely. ...

Smith’s basic idea was that business owners ... have powerful incentives to introduce improved product designs and cost-saving innovations. These moves bolster innovators’ profits in the short term. But rivals respond by adopting the same innovations, and the resulting competition gradually drives down prices and profits. In the end, Smith argued, consumers reap all the gains.

The central theme of Darwin’s narrative was that competition favors traits and behavior according to how they affect the success of individuals, not species or other groups. As in Smith’s account, traits that enhance individual fitness sometimes promote group interests. For example, a mutation for keener eyesight in hawks benefits not only any individual hawk that bears it, but also makes hawks more likely to prosper as a species.

In other cases, however, traits that help individuals are harmful to larger groups. For instance, a mutation for larger antlers served the reproductive interests of an individual male elk, because it helped him prevail in battles ... for access to mates. But as this mutation spread, it started an arms race that made life more hazardous for male elk over all. The antlers of male elk can now span five feet or more. And despite their utility in battle, they often become a fatal handicap when predators pursue males into dense woods.

In Darwin’s framework, then,... [c]ompetition, to be sure, sometimes guides individual behavior in ways that benefit society as a whole. But not always.

Individual and group interests are almost always in conflict when rewards to individuals depend on relative performance, as in the antlers arms race. In the marketplace, such reward structures are the rule, not the exception. The income of investment managers, for example, depends mainly on the amount of money they manage, which in turn depends largely on their funds’ relative performance. Relative performance affects many other rewards in contemporary life. ...

In cases like these, relative incentive structures undermine the invisible hand. To make their funds more attractive to investors, money managers create complex securities that impose serious, if often well-camouflaged, risks on society. But when all managers take such steps, they are mutually offsetting. No one benefits, yet the risk of financial crises rises sharply. ...

It’s the same with athletes who take anabolic steroids. ...

If male elk could vote to scale back their antlers by half, they would have compelling reasons for doing so, because only relative antler size matters. Of course, they have no means to enact such regulations.

But humans can and do. ... Darwin has identified the rationale for much of the regulation we observe in modern societies — including steroid bans in sports, safety and hours regulation in the workplace, product safety standards and the myriad restrictions typically imposed on the financial sector.

Ideas have consequences. The uncritical celebration of the invisible hand by Smith’s disciples has undermined regulatory efforts to reconcile conflicts between individual and collective interests in recent decades, causing considerable harm to us all. ...

[And, again, for those who might be interested, see also Paul Krugman's: What Economists Can Learn from Evolutionary Theorists Synopsis.]

Economists are Seeking Remedies to the Crisis

Francesco Caselli of the London School of Economics rebuts a recent attack on the economics profession:

Economists are actively engaged in seeking remedies to the crisis, by Francesco Caselli, CIF: Larry Elliott's claim that "as a profession, economics not only has nothing to say about what caused the world to come to the brink of financial collapse last autumn, but also a supreme lack of interest", deserves a rebuttal.

The alleged lack of interest is belied by the outpouring of commentary and discussion that has swept the profession over the last couple of years and shows no sign of abating. I can think of few of the top academic stars in macroeconomics who have not been busy editorialising, blogging, and participating in discussions and policy events.

The evidence for the lack-of-interest charge is that "if, for example, you scroll down the list of papers scheduled for publication by the Review of Economic Studies, one of the prestigious UK journals, there is not the slightest sense that the world of general equilibrium and real business cycle models has been turned upside down in the past two years".

Whats New in Econometrics: Time Series

This won't interest many of you I don't think, but I didn't realize these lectures were available on Google Video so I thought I'd pass them along to anyone - like me - who is interested (if you click through to the Google Video page and select "original size" for viewing, the picture is a bit better):

"The Economic Crisis and Its Implications for The Science of Economics"

Sound/video from a recent conference:

The Perimeter Institute conference on economics is being organized in an effort to better evaluate the state of economics as a predictive and descriptive science in light of the current market crisis. We believe that this requires careful, dispassionate discussion, in an atmosphere governed by the modesty and open mindedness that characterizes the scientific community. To do this we aim to bring leading economists and theorists of finance together with physicists, mathematicians, biologists and computer scientists to evaluate current theories of markets, and identify key issues that can motivate new directions for research. ...

Collection URL:http://pirsa.org/C09006

"Rats Outperform Humans in Interpreting Data"

Bill Easterly sent me a link to the post The Vortex of Vacuousness that I posted the other day, but I like this one better:

Maybe we should put rats in charge of foreign aid research, by William Easterly: Laboratory experiments show that rats outperform humans in interpreting data... The amazing finding on rats is described in an equally amazing book by Leonard Mlodinow. The experiment consists of drawing green and red balls at random, with the probabilities rigged so that greens occur 75 percent of the time. The subject is asked to watch for a while and then predict whether the next ball will be green or red. The rats followed the optimal strategy of always predicting green (I am a little unclear how the rats communicated, but never mind). But the human subjects did not always predict green, they usually want to do better and predict when red will come up too, engaging in reasoning like “after three straight greens, we are due for a red.” As Mlodinow says, “humans usually try to guess the pattern, and in the process we allow ourselves to be outperformed by a rat.”

Unfortunately, spurious patterns show up in some important real world settings, like research on the effect of foreign aid on growth. Without going into any unnecessary technical detail, research looks for an association between economic growth and some measure of foreign aid, controlling for other likely determinants of economic growth. Of course, since there is some random variation in both growth and aid, there is always the possibility that an association appears by pure chance. The usual statistical procedures are designed to keep this possibility small. The convention is that we believe a result if there is only a 1 in 20 chance that the result arose at random. So if a researcher does a study that finds a positive effect of aid on growth and it passes this “1 in 20” test (referred to as a “statistically significant” result), we are fine, right?

Alas, not so fast. A researcher is very eager to find a result, and such eagerness usually involves running many statistical exercises (known as “regressions”). But the 1 in 20 safeguard only applies if you only did ONE regression. What if you did 20 regressions? Even if there is no relationship between growth and aid whatsoever, on average you will get one “significant result” out of 20 by design. Suppose you only report the one significant result and don’t mention the other 19 unsuccessful attempts. You can do twenty different regressions by varying the definition of aid, the time periods, and the control variables. In aid research, the aid variable has been tried, among other ways, as aid per capita, logarithm of aid per capita, aid/GDP, logarithm of aid/GDP, aid/GDP squared, [log(aid/GDP) - aid loan repayments], aid/GDP*[average of indexes of budget deficit/GDP, inflation, and free trade], aid/GDP squared *[average of indexes of budget deficit/GDP, inflation, and free trade], aid/GDP*[ quality of institutions], etc. Time periods have varied from averages over 24 years to 12 years to to 8 years to 4 years. The list of possible control variables is endless. One of the most exotic I ever saw was: the probability that two individuals in a country belonged to different ethnic groups TIMES the number of political assassinations in that country. So it’s not so hard to run many different aid and growth regressions and report only the one that is “significant.”

This practice is known as “data mining.” It is NOT acceptable practice, but this is very hard to enforce since nobody is watching when a researcher runs multiple regressions. It is seldom intentional dishonesty by the researcher. Because of our non-rat-like propensity to see patterns everywhere, it is easy for researchers to convince themselves that the failed exercises were just done incorrectly, and that they finally found the “real result” when they get the “significant” one. Even more insidious, the 20 regressions could be spread across 20 different researchers. Each of these obediently does only one pre-specified regression, 19 of whom do not publish a paper since they had no significant results, but the 20th one does publish their spuriously “significant” finding (this is known as “publication bias.”)

But don’t give up on all damned lies and statistics, there ARE ways to catch data mining. A “significant result” that is really spurious will only hold in the original data sample, with the original time periods, with the original specification. If new data becomes available as time passes you can test the result with the new data, where it will vanish if it was spurious “data mining”. You can also try different time periods, or slightly different but equally plausible definitions of aid and the control variables.

So a few years ago, some World Bank research found that “aid works {raises economic growth} in a good policy environment.” This study got published in a premier journal, got huge publicity, and eventually led President George W. Bush (in his only known use of econometric research) to create the Millennium Challenge Corporation, which he set up precisely to direct aid to countries with “good policy environments.”

Unfortunately, this result later turned out to fail the data mining tests. Subsequent published studies found that it failed the “new data” test, the different time periods test, and the slightly different specifications test.

The original result that “aid works in a good policy environment” was a spurious association. Of course, the MCC is still operating, it may be good or bad for other reasons.

Moral of the story: beware of these kinds of statistical “results” that are used to determine aid policy! Unfortunately, the media and policy community don’t really get this, and they take the original studies at face value (not only on aid and growth, but also in stuff on determinants of civil war, fixing failed states, peacekeeping, democracy, etc., etc.) At the very least, make sure the finding is replicated by other researchers and passes the “data mining” tests. ...

I saw Milton Friedman provide an interesting example of avoiding data mining. I was at a SF Fed conference where he was a speaker, and his talk was about a paper he had written 20 years earlier on "The Plucking Model." From a post in January 2006, New Support for Friedman's Plucking Model:

Friedman found evidence for the Plucking Model of aggregate fluctuations in a 1993 paper in Economic Inquiry. One reason I've always liked this paper is that Friedman first wrote it in 1964. He then waited for more than twenty years for new data to arrive and retested his model using only the new data. In macroeconomics, we often encounter a problem in testing theoretical models. We know what the data look like and what facts need to be explained by our models. Is it sensible to build a model to fit the data and then use that data to test it to see if it fits? Of course the model will fit the data, it was built to do so. Friedman avoided this problem since he had no way of knowing if the next twenty years of data would fit the model or not. It did.

The other thing I'll note is that there is a literature on how test statistics are affected by pretesting, but it is ignored for the most part (e.g. if you run a regression, then throw out an insignificant variable, anything you do later must take account of the fact that you could have made a type I or type II error during the pretesting phase). The bottom line is that the test statistics from the final version of the model are almost always non-normal, and the distribution of the test statistics is not generally known.

[One more note. I wrote a paper on Friedman's Plucking Model, and had a revise and resubmit at a pretty good journal. I satisfied all the referee's objections, at least I thought I had, and it was all set to go. I had sent the first version of the paper to Friedman, and he wrote back with a long, multi-page letter that was very encouraging, and I incorporated his suggestions into the revision (a reason I'll always have a soft spot for him, his time was valuable, yet he took the time to do this). But the final results weren't robust, and had come about through trying different specifications until one worked. The final specification worked well, very well in fact, but the results were pretty fragile. As a result, I pulled the paper and did not resubmit it. The paper was completely redone and rewritten, but after thinking it over I decided it wasn't robust enough to publish. I find myself regretting that sometimes, the referees would have probably taken the paper since the final version satisfied all their objections, and it was a good journal - I told myself I had simply done what everyone else does, etc. But, hard as it was for an assistant professor in need of publications to pull a paper, especially one Friedman himself had endorsed - this was just before going up for tenure so it could have mattered a lot - pulling the paper was the right thing to do. The only way to solve this problem - and data mining in economics is a problem - is for the people involved in the research to self-police the integrity of the process.]

Update: Seems like a good time to rerun this graph on publications in political science journals:

Lies, Damn Lies, and....: Via Kieran Healy, ...It is, at first glance, just what it says it is: a study of publication bias, the tendency of academic journals to publish studies that find positive results but not to publish studies that fail to find results. ...

The chart on the right shows G&M's basic result. In statistics jargon, a significant result is anything with a "z-score" higher than 1.96, and if journals accepted articles based solely on the quality of the work, with no regard to z-scores, you'd expect the z-score of studies to resemble a bell curve. But that's not what Gerber and Malhotra found. Above a z-score of 1.96, the results fit the bell curve pretty well, but below a z-score of 1.96 there are far fewer studies than you'd expect. Apparently, studies that fail to show significant results have a hard time getting published.

So far, this is unsurprising. Publication bias is a well-known and widely studied effect, and it would be surprising if G&M hadn't found evidence of it. But take a closer look at the graph. In particular, take a look at the two bars directly adjacent to the magic number of 1.96. That's kind of funny, isn't it? They should be roughly the same height, but they aren't even close. There are a lot of studies that just barely show significant results, and there are hardly any that fall just barely short of significance. There's a pretty obvious conclusion here, and it has nothing to do with publication bias: data is being massaged on wide scale. A lot of researchers who almost find significant results are fiddling with the data to get themselves just over the line into significance. ... Message to political science professors: you are being watched. And if you report results just barely above the significance level, we want to see your work....

"The Failure of the Economy & the Economists"

A much shortened version of Benjamin Friedman review of Akerlof and Shiller's Animal Spirits: and Shiller's The Subprime Solution:

The Failure of the Economy & the Economists, by Benjamin M. Friedman, NYRB, Review of Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism by George A. Akerlof and Robert J. Shiller; and The Subprime Solution: How Today's Global Financial Crisis Happened, and What to Do About It by Robert J. Shiller: By now there are few people who do not acknowledge that the major American financial institutions and the markets they dominate turn out to have served the country badly in recent years. ...

But despite the universal agreement that no one wants any more such failures once this one has passed, there is a troubling lack of attention to reforms that might prevent such a crisis from recurring. ... As in past financial declines, what is sorely missing in this discussion is attention to what function the financial system is supposed to perform in the economy and how well it has been doing it. ... Another fundamental issue that the current discussion has overlooked almost entirely is the distinction between the losses to banks and other lenders that reflect genuine losses of wealth to the economy, and other losses that don't. ...

Why has there been so little discussion of fundamental issues like this distinction among losses? Why is so little said about the trade-off between the goal of allocating the economy's capital efficiently and the need to shrink the enormous costs of the financial industry in doing so? One obvious reason is political. There is a long arc from Roosevelt's acceptance of a useful role for government institutions and government regulation to the conviction of Reagan and Thatcher that the government is never the solution but actually the problem. A second, closely related reason is ideological: the faith, personified by Alan Greenspan with his early dedication to the writings of Ayn Rand and his staunch opposition to regulations while chairman of the Federal Reserve, that private, profit-driven economic activity is self-regulating and, when necessary, self-correcting.

"Austrian Business Cycle Theory"

John Quiggin explains why Austrian business cycle theory "hasn’t developed in any positive way" since the 1920's, and has since become "ossified dogma":

Austrian Business Cycle Theory, by John Quiggin: I’ve long promised a post on Austrian Business Cycle Theory, and here it is. For those who would rather get straight to the conclusion, it’s one I share in broad terms with most of the mainstream economists who’ve looked at the theory, from Tyler Cowen, Bryan Caplan and Gordon Tullock at the libertarian/Chicago end of the spectrum to Keynesians like Paul Krugman and Brad DeLong.

To sum up, although the Austrian School was at the forefront of business cycle theory in the 1920s, it hasn’t developed in any positive way since then. The central idea of the credit cycle is an important one, particularly as it applies to the business cycle in the presence of a largely unregulated financial system. But the Austrians balked at the interventionist implications of their own position, and failed to engage seriously with Keynesian ideas.

The result (like orthodox Marxism) is a research program that was active and progressive a century or so ago but has now become an ossified dogma. Like all such dogmatic orthodoxies, it provides believers with the illusion of a complete explanation but ceases to respond in a progressive way to empirical violations of its predictions or to theoretical objections. To the extent that anything positive remains, it is likely to be developed by non-Austrians such as the post-Keynesian followers of Hyman Minsky. ... [...continue reading...]

"The Twenty-First Century Will be the Age of Inductive Economics"

So says Barry Eichengreen:

The Last Temptation of Risk, by Barry Eichengreen, National Interest: The Great Credit Crisis has cast into doubt much of what we thought we knew about economics. ... The question is how we could have been so misguided. One interpretation, understandably popular given our current plight, is that the basic economic theory informing the actions of central bankers and regulators was fatally flawed. The only course left is to throw it out and start over. But another view, considerably closer to the truth, is that the problem lay not so much with the poverty of the underlying theory as with selective reading of it... That ... encouraged financial decision makers to cherry-pick the theories that supported excessive risk taking. It discouraged whistle-blowing, not just by risk-management officers in large financial institutions, but also by the economists whose scholarship provided intellectual justification for the financial institutions’ decisions. The consequence was that scholarship that warned of potential disaster was ignored. ...

[I]t was not that economic theory had nothing to say about the kinds of structural weaknesses and conflicts of interest that paved the way to our current catastrophe. In fact, large swaths of modern economic theory focus squarely on the kind of generic problems that created our current mess. The problem was not an inability to imagine that conflicts of interest, self-dealing and herd behavior could arise, but a peculiar failure to apply those insights to the real world. ...

What got us into this mess, in other words, were not the limits of scholarly imagination. It was not the failure or inability of economists to model conflicts of interest, incentives to take excessive risk and information problems that can give rise to bubbles, panics and crises. It was not that economists failed to recognize the role of social and psychological factors in decision making or that they lacked the tools needed to draw out the implications. In fact, these observations and others had been imaginatively elaborated by contributors to the literatures on agency theory, information economics and behavioral finance. Rather, the problem was a partial and blinkered reading of that literature. The consumers of economic theory, not surprisingly, tended to pick and choose those elements of that rich literature that best supported their self-serving actions. ... It is in this light that we must understand how it was that the vast majority of the economics profession remained so blissfully silent and indeed unaware of the risk of financial disaster. ...

[A]mid the pervading sense of gloom and doom, there is at least one reason for hope. The last ten years have seen a quiet revolution in the practice of economics. For years theorists held the intellectual high ground. ... The methods of empirical economists seeking to analyze real data were rudimentary by comparison. ...

But the IT revolution has altered the lay of the intellectual land. ... The data sets used in empirical economics today are enormous, with observations running into the millions. Some of this work is admittedly self-indulgent... But now it is on the empirical side where the capacity to do high-quality research is expanding most dramatically... And, revealingly, it is now empirically oriented graduate students who are the hot property when top doctoral programs seek to hire new faculty.

Not surprisingly, the best students have responded. The top young economists are, increasingly, empirically oriented. ... To the extent that their work is rooted concretely in observation of the real world, it is less likely to sway with the latest fad and fashion. Or so one hopes.

The ... twenty-first century will be the age of inductive economics, when empiricists hold sway and advice is grounded in concrete observation of markets and their inhabitants. Work in economics, including the abstract model building in which theorists engage, will be guided more powerfully by this real-world observation. It is about time.

Should this reassure us that we can avoid another crisis? Alas, there is no such certainty. ... [entire article]

Blogginheads: Economics 2.0

The economy as a broken spaceship (08:02)
Are macroeconomic models just hogwash? (14:10)
Resizing and recasting the financial sector (30:46)
Did we have to bail out the banks? (37:35)
Why statistics can’t predict economic future (yet) (41:16)
Czar for a day: Mark and Arnold fix the economy (47:32)
Play entire video (56:51)

Update: New York Times Extract (2:53)

"There were Exactly Five People Who Foresaw This Crisis"

Daniel Kahneman on economic models:

Irrational everything, by Guy Rolnik, Haaretz: Prof. Daniel Kahneman has dozens, perhaps hundreds, of stories about people's irrational behavior when it comes to making economic decisions. ... But the story Kahneman recalls when asked about the economic models at the root of the current financial crisis is actually taken from history, not an experiment. It concerns a group of Swiss soldiers who set out on a long navigation exercise in the Alps. The weather was severe and they got lost. After several days, with their desperation mounting, one of the men suddenly realized he had a map of the region.

They followed the map and managed to reach a town. When they returned to base and their commanding officer asked how they had made their way back, they replied, "We suddenly found a map." The officer looked at the map and said, "You found a map, all right, but it's not of the Alps, it's of the Pyrenees."

According to Kahneman, the moral of the story is that some of our economic models, perhaps those of the investment world, are worthless. But individual investors need security - maps of the Pyrenees - even if they are, in effect, worthless. ...

"In the last half year, the models simply didn't work. So the question arises: Why do people use models? I liken what is happening now to a system that forecasts the weather, and does so very well. People know when to take an umbrella when they leave the house, or when it will snow. Except what? The system can't predict hurricanes. Do we use the system anyway, or throw it out? It turns out they'll use it."

Okay, so they use it. But why don't they buy hurricane insurance?

"The question is, how much will the hurricane insurance cost? Since you can't predict these events, you would have to take out insurance against many things. If they had listened to all the warnings and tried to prevent these things, the economy would look a lot different than it does now. So an interesting question arises: After this crisis, will we arrive at something like that? It's hard for me to believe."

The financial world's models are built on the assumption that investors are rational. You have shown that not only are they not rational, they even deviate from what is rational or statistical, in predictable, systematic ways. Can we say that whoever recognized and accepted these deviations could have seen this crisis coming?

"It was possible to foresee, and some people did. ... I have a colleague at Princeton who says there were exactly five people who foresaw this crisis, and this does not include ... Ben Bernanke. One of them is Prof. Robert Shiller, who also predicted the previous bubble. The problem is there were other economists who predicted this crisis, like Nouriel Roubini, but he also predicted some crises that never came to be."

He was one of those who predicted 10 crises out of three.

"Ten out of three is a pretty good record, relatively. But I conclude from the fact that only five people predicted the current crisis that it was impossible to predict it. In hindsight, it all seems obvious: Everyone seemed to be blind, only these five appeared to be smart. But there were a lot of smart people who looked at the situation and knew all the facts, and they did not predict the crisis." ...

The interesting psychological problem is why economists believe in their theory, but this is the problem with the theory, any theory. It leads to a certain blindness. It's difficult to see anything that deviates from it."

We only look for information that supports the theory and ignore the rest. "Correct..." ...

Let's end with your story of the Swiss soldiers and the map of the Pyrenees. I know why the map helped the soldiers: it gave them confidence. But why didn't they use a map of the Alps? Why don't we use the right economic models, ones that are relevant to extreme cases as well?

"Look, it's possible that there simply is no map of the Alps, that there is nothing that can predict hurricanes." 

[full interview]

Macroeconomic Meltdown?

The state of macroeconmics:

Are those who sweat the big stuff in meltdown?, by Tim Harford, Commentary, Financial Times: ...I am struck by the soul-searching that has gripped the [macroeconomics] profession in the face of the economic crisis. The worry is not so much that macroeconomists did not forecast the problem – bad forecasts are more a sign of a complex world than intellectual bankruptcy – but that macroeconomics seems unable to provide answers. Sometimes it cannot even ask the right questions.

Willem Buiter ... complains that macroeconomists have simply discarded the difficult stuff to make their models more elegant: “They took these non-linear stochastic dynamic general equilibrium models into the basement and beat them with a rubber hose until they behaved.”

He is not alone in his frustration. Paul Krugman ... thinks macroeconomics is in a dark age, in the sense that rather than discovering new insights, we are actually going backwards and forgetting what we used to know. Mark Thoma ... opines: “I think that the current crisis has dealt a bigger blow to macroeconomic theory and modelling than many of us realise.”

We shall see. While many commentators have reached for Keynes – or some caricature of Keynes – as a solution to this crisis, this is not because he is the fount of all knowledge, but because he was asking good questions about problems that now seem relevant again.

Economists now understand much more than Keynes ever could about networks and complex interactions (thanks to agent-based modelling), psychology (thanks to behavioural economics) and the real world (thanks to econometrics). In principle, these advances should inform our understanding of the crisis. An early attempt is Animal Spirits, a book by George Akerlof, a Nobel laureate, and Robert Shiller, who identified the housing bubble early. But macroeconomics has a lot of momentum and it will take time to turn the oil tanker around.

Justin Wolfers,... an unabashed microeconomist, says that, “formally elegant but empirically irrelevant macroeconomists had a much harder time getting hired this year,” while Buiter reckons that the central banks have already jettisoned conventional macroeconomics in favour of a pragmatic combination of hunches and judgment calls. If so, the market for macroeconomic ideas seems to be self-correcting – much like the market for financial weapons of mass destruction. It is just a shame, in both cases, that the correction did not come more smoothly and much, much earlier.

Let me a bit more specific, and add something more to problems with macroeconomics I discussed in The Great Multiplier Debate and "The Unfortunate Uselessness of Most 'State of the Art' Academic Monetary Economics". The main mechanism generating fluctuations and policy effects in modern New Keynesian models is Calvo type sluggish price adjustment. I think this model is useful for “normal” times as a way of understanding economic fluctuations, and for learning about optimal policy, and it represents a step forward in understanding monetary policy in particular. But do people really think that all would be fine right now if prices – and they must have housing prices in mind when they think about sticky prices as an explanation for the current episode – had only adjusted faster? If housing prices had dropped even faster than they have already, all would be well in the world?

Okay, so maybe they don’t have housing prices in mind. Still, do we really think that sluggish price adjustment is the main mechanism at work in the present crisis? If not, then what use is the evidence from those models? Why do we keep hearing about theoretical simulations that give values for the multiplier that are small, large, zero, less than one, whatever? Do we really think that sluggish price adjustment captures the essence of the factors driving the present crisis? I don't.

The fundamental mechanism driving the economic fluctuations is wrong, and people seem to be missing that when they try to use the evidence from this model to comment on the present situation. There are two big problems. First, we have very little data from episodes like the current one to calibrate these models. What should, say, the elasticity of labor supply be in a severe recession? Do we know? That's a key parameter in these models, and we can only guess what it's value ought to be. Second, even if we have good data from similar episodes, why run it through a model that does not capture the fundamental problem driving the downturn?

Again, I think the New Keynesian model is very useful for understanding "normal" business cycles, but I am very hesitant to use this model as the basis for policy advice in the present crisis.

So where does that leave us? We do not have either the theoretical models or the empirical evidence we need to understand this episode thoroughly and completely, and to provide the policy advice that will cure the problem with any degree of certainty. Without solid theoretical models and the associated empirical evidence, we really have no choice but to fall back upon older models that were "built to answer the questions that are important at the moment," i.e. the old-fashioned Keynesian model, and to rely upon loose, but solid theoretical principles rather than a tightly constructed model and vast amounts of empirical evidence. It's quite understandable that economists who have been striving to push the profession in a positive, scientific, solidly theoretical and evidence based direction would resist going backward, and resist strongly, but what choice do we have? Until we have a better mousetrap, the simple, old fashioned one will have to suffice.

Palley: "The Outlook for Macroeconomics and Macroeconomic Policy"

Heterodox economist Thomas Palley says:

I noticed that I posted Simon Johnson’s “Quiet Coup” and Dani Rodrik’s (mild) response. Here’s an alternative hypothesis. The economics profession has been party to the capture of economic policy and government by the financial oligarchy. I hope you will consider discussing this alternative hypothesis on your blog.

Here's the preface to his paper, "After the Bust: The Outlook for Macroeconomics and Macroeconomic Policy," outlining his arguments:

Preface, by Dimitri B. Papadimitriou, January 2009: “Change” was the buzzword of the U.S. presidential campaign, in response to a political agenda precipitated by financial turmoil and a global economic crisis. According to Research Associate Thomas I. Palley, the neoliberal economic policy paradigm underlying the current agenda must itself change if there is to be a successful policy response to the crisis. He observes that the financial downturn has exposed the faulty economics of the existing policy paradigm, thus presenting the opportunity for real change, but that there are profound political, intellectual, and sociological obstacles to such change.

The ideology of the economics profession—mainstream economic theory—remains unreformed, says Palley, and he warns of a return to failed policies if a deep crisis is averted. Since Post Keynesians accurately predicted that the U.S. economy would implode from within, there is an opportunity for Post Keynesian economics to replace neoliberalism with a more successful approach.

Palley outlines the policy challenges, noting that there is significant disagreement among economic paradigms about how to ensure full employment and shared prosperity. A salient feature of the neoliberal economy, which is supported by mainstream economic theory (e.g., free trade, deregulation, and the notion of a natural rate of unemployment), is the disconnect between wages and productivity growth that explains widening income inequality. Workers are boxed in on all sides by globalization, labor market flexibility, concern with inflation rather than with full employment, and a belief in “small government” that has eroded economic rights and government services. Financialization, the economic foundation of neoliberalism, serves the interests of financial markets and top management. Thus, reversing the neoliberal paradigm requires a policy agenda that addresses financialization and ensures financial markets and corporations are more closely aligned with the greater public interest.

Palley outlines several major obstacles to changing both economics and economic policy. Social democratic political parties are divided in terms of the merits of the neoliberal economic paradigm.Other obstacles include the dominance of neoliberal economics within the academic community and among policymakers, which is supported by a misplaced belief that neoclassical economics is a scientific fact. This belief is used by the academic establishment to block alternative points of view.

New Keynesian economics is a form of real-business-cycle theory in the tradition of Arthur C. Pigou rather than John Maynard Keynes, says Palley. Though mainstream economists are willing to recommend Keynesian policies in times of economic crisis, they are unwilling to change the core analytical assumptions driving modern neoclassical macroeconomics (an example of so-called“cuckoo” economics).The only satisfactory escape from this intellectual and political stew is the creation of a new, progressive Keynesian consensus. That will require placing economics at the center of the political stage.

"The End of Universal Rationality"

Yochai Benkler discusses the use of the "assumption of universal rationality and a sub-assumption that what that rationality tries to do is maximize returns to the self" as a primary analytical foundation for our models of sociological, political, and economic behavior:

The End of Universal Rationality, The Edge: The big question I ask myself is how we start to think much more methodically about human sharing, about the relationship between human interest and human morality and human society. The main moment at which I think you could see the end of an era was when Alan Greenspan testified before the House committee and said, "My predictions about self-interest were wrong. I relied for 40 years on self-interest to work its way up, and it was wrong." For those of us like me who have been working on the Internet for years, it was very clear you couldn't encounter free software and you couldn't encounter Wikipedia and you couldn't encounter all of the wealth of cultural materials that people create and exchange, and the valuable actual software that people create, without an understanding that something much more complex is happening than the dominant ideology of the last 40 years or so. But you could if you weren't looking there, because we were used in the industrial system to think in these terms.

A lot of what I was spending my time on in the 90s and the 2000s was to understand why it is that these phenomena on the Net are not ephemeral. Why they're real. But I think in the process of understanding that, I had to go back and ask, where are we really in between this what's-in-it-for-me versus the great altruists and the stories of Stahanovich and the self-sacrifice for the community?

Both of them are false. But the question is, how do we begin to build a new set of stories that will let us understand both? The stories are actually relatively easy. How we build actual, tractable analysis that allows us to convert what in some sense we all know, that some of us are selfish and some of us aren't. That actually most of us are more selfish some of the time and less selfish other of the time and in different relations. That we don't all align according to the standard economic model of selfish rationality, but that we're also not saints. Mother Teresa wouldn't be Mother Teresa if everybody were like her.

So this is the puzzle that I'm really trying to chew on now, which is how we move from knowing this intuitively and having a folk wisdom about it to something that probably won't in any immediate future have the tractability and precision of mainstream economics. Not, by the way, that as we sit here today, mainstream economics necessarily enjoys the high status that it might have a few years ago, but nonetheless so that we will be able to start building systems in the same way that we thought about building organizational systems around compensation, like options that ties the incentives of the employees to that of the business, like we thought with regard to political science that's completely pervaded today by the understanding of, how does politics happen? Well, it depends on what the median voter wants and what the median Senator wants, and all of that.

We have a lot of sophisticated analyses that try, with great precision, to predict and describe existing systems in terms of an assumption of universal rationality and a sub-assumption that what that rationality tries to do is maximize returns to the self. Yet we live in a world where that's not actually what we experience. The big question now is how we cover that distance between what we know very intuitively in our social relations, and what we can actually build with. ... [...continue reading or watch the video...]

"Why Bother with Adam Smith?"

Gavin Kennedy reacts to some of the recent criticism of economists for reading and citing the sacred texts and ancient tomes:

Thought for the Day - 3, Adam Smith's Lost Legacy: ...There is a debate underway among historians of economic thought on whether economists really need to study the history of ideas in what we may loosely term our discipline. Those economists who take the view that the history of economic ideas really has nothing to do with modern economics, point to it being unnecessary for ‘real scientists’ to read the works of Isaac Newton, and his lesser luminaries, so why bother with Adam Smith and the rest?

My views on this debate (I have not joined in, so far) are predictable. The physical world is fairly constant – each and every carbon atom is assumed to behave the same way, and has done so through the ages, and unless that changes in known circumstances, its properties and relationships with other atoms are not expected to change. Knowledge gains in hard sciences build upon earlier knowledge gains, and future knowledge gains continue the process.

Turning to economics – part of human sciences – it is quite different. We hardly know about past economic history; even recent history is controversial and is well short of arriving at a settled view. There are political views of economic behaviours – as far as I know, we do not have ‘leftwing’ or ‘rightwing’ carbon atoms – and we do not have a settled view on what constitutes economic society or on what would constitute a society that could be said to be the basis for all further societies without (controversial) changes.

"What Use is Economic Theory?"

Given the discussion below, it seems like a good time to rerun this, a post that was suggested in a comment from Hal Varian:

I've weighed in on this debate in this essay. My thesis is that economics should not be compared to physics but to engineering. Or, alternatively, not to biology but to medicine. That is, economics is inherently a "policy science" where the value of an economic theory should be judged according to its contribution to economic policy.

There are many who disagree with this view, but hey, let a thousand flowers bloom.

Here it is:

What Use is Economic Theory?, by Hal R. Varian, August, 1989: Why is economic theory a worthwhile thing to do? There can be many answers to this question. One obvious answer is that it is a challenging intellectual enterprise and interesting on its own merits. A well-constructed economic model has an aesthetic appeal well-captured by the following lines from Wordsworth:

Mighty is the charm
Of these abstractions to a mind beset
With images, and haunted by herself
And specially delightful unto me
Was that clear synthesis built up aloft
So gracefully.

No one complains about poetry, music, number theory, or astronomy as being ‘‘useless,’’ but one often hears complaints about economic theory as being overly esoteric. I think that one could argue a reasonable case for economic theory on purely aesthetic grounds. Indeed, when pressed, most economic theorists admit that they do economics because it is fun.

But I think purely aesthetic considerations would not provide a complete account of economic theory. For theory has a role in economics. It is not just an intellectual pursuit for its own sake, but it plays an essential part in economic research. The essential theme of this essay that economics is a policy science and, as such, the contribution of economic theory to economics should be measured on how well economic theory contributes to the understanding and conduct of economic policy.

Mathematical Formalism in Economics

Roman Frydman responds to the response to the Anatole Kaletsky article, Goodbye, homo economicus:

Your posting of Kaletsky’s article has led to a much overdue discussion of the usefulness of mathematical formalism for understanding market outcomes. This is particularly important as the recent discussions of failures of economic models have focused on specific assumptions, such as incompleteness of markets, contracts or nonlinearities (Willem Buiter), or neo-Keynesian versus new classical approaches (Paul Krugman).

The attached note, which draws heavily on my recent book and subsequent papers with Michael Goldberg, argues that the question of whether and what type of mathematical formalism can help us understand market outcomes in modern capitalism is more subtle than Kaletsky’s critics might have realized.

Here's the note:

What type of mathematical formalism can help us understand market outcomes in modern capitalism?

Mark Thoma reports that the article by Anatole Kaletsky Goodbye, homo economicus, calling for an intellectual revolution in economics, “did not get the best reception here and elsewhere, and there were also protests that arrived by email.”

What really irked Kaletsky’s antagonists was his attack on the use of mathematical formalism in economics. But what has gone completely unnoticed in the subsequent discussion is that Kaletsky’s attack on mathematical formalism focused not on the use of mathematics in economics as such, but on the portrayal by contemporary models of the “market economy as a mechanical system.”

This characterization of contemporary macro and finance models seems uncontroversial. Regardless of whether these models are based on REH or behavioral considerations, they represent the causal mechanisms that supposedly underpin change on individual and aggregate levels through mechanical rules. Thus, they ignore the key feature of modern economies: the fact that individuals and companies engage in innovative activities, discovering new ways of using existing physical and human capital and technology, as well as new technologies and new capital in which to invest.

Moreover, the institutions and the broader social context within which this entrepreneurial activity takes place also change in novel ways. Innovation in turn influences future returns from economic activity in ways that no one, including economists, and market participants, can fully foresee, and thus that do not conform to any rule that can be prespecified in advance.

In our recent book, Imperfect Knowledge Economics (IKE), Michael Goldberg and I trace the empirical failures and fundamental epistemological flaws within the contemporary models of “rational” or “irrational” behavior to a common source: in modeling aggregate outcomes, contemporary economists fully prespecify the causal mechanism that underpins change in real-world markets.

To remedy this flaw, IKE jettisons mechanical models of change and attempts to construct economic models of individual behavior and aggregate outcomes on the basis of qualitative regularities that can be formalized with mathematical conditions. An aggregate model based on such micro-foundations generates only qualitative predictions of market outcomes.

This brings us back to the key question: whether, and if so, some mathematical formalism might be useful in our quest to understand individual behavior and market outcomes.

The “Zig Zag Windings of the Flowery Path of Literature”

The article by Anatole Kaletsky I posted earlier today, Goodbye, homo economicus, did not get the best reception here and elsewhere, and there were also protests that arrived by email. Here's a follow-up on one aspect of the article, the use of formal mathematical models in economics. This article is by David Colander:

Marshallian General Equilibrium Analysis, by David Colander: In an assessment of Alfred Marshall, Paul Samuelson (1967) writes that “The ambiguities of Alfred Marshall paralyzed the best brains in the Anglo-Saxon branch of our profession for three decades.“ In making this assessment he carried on a tradition of Marshall-bashing that has a long history in economics, dating back to Stanley Jevons and F. Y. Edgeworth, who accused Marshallian economists of being seduced by “zig zag windings of the flowery path of literature.” (Edgeworth, 1925)

These harsh assessments of Marshall and his approach to economics have had their influence on the modern profession and, other than historians of economic thought, few young economists know much about him. Fewer still would see themselves as Marshallians.[1]

Today, Marshall is best remembered for his contribution to partial equilibrium supply and demand analysis.[2] For the true economic theorists of the 1990s, however, this contribution is de minimus; the partial equilibrium approach is for novice economists with no stomach for real economic theory—general equilibrium. The profession’s collective view of Marshall in the 1990s is that Marshall is passé--at most a pedagogical stepping stone for undergraduate students, but otherwise quite irrelevant to modern economics.

"Goodbye, Homo Economicus"

Via an email suggestion (there's much, much more in the full version):

Goodbye, homo economicus, by Anatole Kaletsky:  Was Adam Smith an economist? Was Keynes, Ricardo or Schumpeter? By the standards of today’s academic economists, the answer is no. Smith, Ricardo and Keynes produced no mathematical models. Their work lacked the “analytical rigour” and precise deductive logic demanded by modern economics. And none of them ever produced an econometric forecast (although Keynes and Schumpeter were able mathematicians). If any of these giants of economics applied for a university job today, they would be rejected. As for their written work, it would not have a chance of acceptance in the Economic Journal or American Economic Review. The editors, if they felt charitable, might advise Smith and Keynes to try a journal of history or sociology.

If you think I exaggerate, ask yourself what role academic economists have played in the present crisis. Granted, a few mainstream economists with practical backgrounds—like Paul Krugman and Larry Summers in the US—have been helpful explaining the crisis to the public and shaping some of the response. But in general how many academic economists have had something useful to say about the greatest upheaval in 70 years? The truth is even worse than this rhetorical question suggests: not only have economists, as a profession, failed to guide the world out of the crisis, they were also primarily responsible for leading us into it. ...

Academic economists have thus far escaped much blame for the crisis. Public anger has focused on more obvious culprits: greedy bankers, venal politicians, sleepy regulators or reckless mortgage borrowers. But why did these scapegoats behave in the ways they did? Even the greediest bankers hate losing money so why did they take risks which with hindsight were obviously suicidal? The answer was beautifully expressed by Keynes 70 years ago: “Practical men, who believe themselves to be quite exempt from any intellectual influence, are usually the slaves of some defunct economist. Madmen in authority, who hear voices in the air, are distilling their frenzy from some academic scribbler of a few years back.”

What the “madmen in authority” heard this time was the distant echo of a debate among academic economists begun in the 1970s about “rational” investors and “efficient” markets. This debate began against the backdrop of the oil shock and stagflation and was, in its time, a step forward in our understanding of the control of inflation. But, ultimately, it was a debate won by the side that happened to be wrong. And on those two reassuring adjectives, rational and efficient, the victorious academic economists erected an enormous scaffolding of theoretical models, regulatory prescriptions and computer simulations which allowed the practical bankers and politicians to build the towers of bad debt and bad policy. ...

Which brings us to the causes of the present crisis. The reckless property lending that triggered this crisis only occurred because rational investors assumed that the probability of a fall in house prices was near zero. Efficient markets then turned these assumptions into price-signals, which told the bankers that lending 100 per cent mortgages or operating with 50-to-1 leverage was safe. Similarly, regulators, who allowed banks to determine their own capital requirements and private rating agencies to establish the value at risk in mortgages and bonds, took it as axiomatic that markets would automatically generate the best possible information and create the right incentives for managing risks. ...

The scandal of modern economics is that these two false theories—rational expectations and the efficient market hypothesis—which are not only misleading but highly ideological, have become so dominant in academia (especially business schools), government and markets themselves. While neither theory was totally dominant in mainstream economics departments, both were found in every major textbook, and both were important parts of the “neo-Keynesian” orthodoxy, which was the end-result of the shake-out that followed Milton Friedman’s attempt to overthrow Keynes. The result is that these two theories have more power than even their adherents realise: yes, they underpin the thinking of the wilder fringes of the Chicago school, but also, more subtly, they underpin the analysis of sensible economists like Paul Samuelson.

The rational expectations hypothesis (REH), developed by two Chicago economists, Robert Lucas and Thomas Sargent in the 1970s, asserted that a market economy should be viewed as a mechanical system that is governed, like a physical system, by clearly-defined economic laws which are immutable and universally understood. Despite its obvious implausibility and the persistent attacks on it, especially from the left, REH has continued to be regarded by universities and funding bodies as the most acceptable foundation for serious academic research. In their recent book Imperfect Knowledge Economics, two American professors, Roman Frydman and Michael Goldberg, complain that “all graduate students of economics—and increasingly undergraduates too—are taught that to capture rational behaviour in a scientific way they must use REH.” In Britain too the REH orthodoxy has remained far more powerful than is often realised. As David Hendry, until recently head of the Oxford economics department, has noted: “Economists critical of the rational expectations based approach have had great difficulty even publishing such views, or maintaining research funding. For example, recent attempts to get ESRC funding for a project to test the flaws in rational expectations based models was rejected. I believe some of British policy failures have been due to the Bank accepting the implications [of REH models] and hence taking about a year too long to react to the credit crisis.” ...

To make matters worse, rational expectations gradually merged with the related theory of “efficient” financial markets. ... This was the efficient market hypothesis (EMH), developed by another group of Chicago-influenced academics, all of whom received Nobel prizes just as their theories came apart at the seams. EMH, like rational expectations, assumed that there was a well-defined model of economic behaviour and that rational investors would all follow it; but it added another step. In the strong version of the theory, financial markets, because they were populated by a multitude of rational and competitive players, would always set prices that reflected all available information in the most accurate possible way. Because the market price would always reflect more perfect knowledge than was available to any one individual, no investor could “beat the market”—still less could a regulator ever hope to improve on market signals by substituting his own judgment. ...

Why did such discredited theories flourish? Largely because they justified whatever outcomes the markets happened to decree—laissez-faire ideology, big salaries for top executives and billions in bonuses for traders. And, conveniently, these theories were regarded as the gold-standard by academic economists who won Nobel prizes.

So what is to be done? There are two options. Either economics has to be abandoned as an academic discipline, becoming a mere appendage to the collection of industrial and social statistics. Or it must undergo an intellectual revolution. ...

Economics today is a discipline that must either die or undergo a paradigm shift—to make itself both more broadminded, and more modest. It must broaden its horizons to recognise the insights of other social sciences and historical studies and it must return to its roots. Smith, Keynes, Hayek, Schumpeter and all the other truly great economists were interested in economic reality. They studied real human behaviour in markets that actually existed. Their insights came from historical knowledge, psychological intuition and political understanding. Their analytical tools were words, not mathematics. They persuaded with eloquence, not just formal logic. One can see why many of today’s academics may fear such a return of economics to its roots.

Academic establishments fight hard to resist such paradigm shifts, as Thomas Kuhn, the historian of science who coined the phrase in the 1960s, demonstrated. Such a shift will not be easy, despite the obvious failure of academic economics. But economists now face a clear choice: embrace new ideas or give back your public funding and your Nobel prizes, along with the bankers’ bonuses you justified and inspired.

Update: Paul Krugman comments on the use of models in Keynes' General Theory.

"Neoclassical Economics: Mad, Bad, and Dangerous to Know"

I can't say I agree with every word of this, but given what just happened to the economy and our general failure to see the signs that it was coming, it's a good time to hear alternative viewpoints about the state of the discipline:

Neoclassical Economics: mad, bad, and dangerous to know, by Steven Keen: The whole of the most recent Real World Economics Review (formerly known as the Post-Autistic Economics Review) is devoted to the question of “How should the collapse of the world financial system affect economics?”. My paper, which led volume 49, is reproduced below. ...

The most important thing that global financial crisis has done for economic theory is to show that neoclassical economics is not merely wrong, but dangerous, by Steven Keen: Neoclassical economics contributed directly to this crisis by promoting a faith in the innate stability of a market economy, in a manner which in fact increased the tendency to instability of the financial system. With its false belief that all instability in the system can be traced to interventions in the market, rather than the market itself, it championed the deregulation of finance and a dramatic increase in income inequality. Its equilibrium vision of the functioning of finance markets led to the development of the very financial products that are now threatening the continued existence of capitalism itself.

Simultaneously it distracted economists from the obvious signs of an impending crisis—the asset market bubbles, and above all the rising private debt that was financing them. Paradoxically, as capitalism’s “perfect storm” approached, neoclassical macroeconomists were absorbed in smug self-congratulation over their apparent success in taming inflation and the trade cycle, in what they termed “The Great Moderation”... [...continue reading...]

"Blame Economists, Not Economics"

Dani Rodrik says economics is fine, but its practitioners are not (the full version points to macroeconomists in particular):

Blame economists, not economics, by Dani Rodrik, Project Syndicate: As the world economy tumbles off the edge of a precipice, critics of the economics profession are raising questions about its complicity in the current crisis. Rightly so: economists have plenty to answer for. ...

So is economics in need of a major shake-up? Should we burn our existing textbooks and rewrite them from scratch? Actually, no. Without recourse to the economist's toolkit, we cannot even begin to make sense of the current crisis.

Why, for example, did China's decision to accumulate foreign reserves result in a mortgage lender in Ohio taking excessive risks? If your answer does not use elements from behavioral economics, agency theory, information economics, and international economics, among others, it is likely to remain seriously incomplete.

The fault lies not with economics, but with economists. The problem is that economists (and those who listen to them) became over-confident in their preferred models of the moment: markets are efficient, financial innovation transfers risk to those best able to bear it, self-regulation works best, and government intervention is ineffective and harmful.

They forgot that there were many other models that led in radically different directions. Hubris creates blind spots. If anything needs fixing, it is the sociology of the profession. The textbooks -- at least those used in advanced courses -- are fine.

Non-economists tend to think of economics as a discipline that idolizes markets and a narrow concept of (allocative) efficiency. ... But ... spend some time in advanced seminar rooms, and you will get a different picture. ... Advanced training in economics requires learning about market failures in detail, and about the myriad ways in which governments can help markets work better. ...

Economics is really a toolkit with multiple models -- each a different, stylized representation of some aspect of reality. One's skill as an economist depends on the ability to pick and choose the right model for the situation.

Economics' richness has not been reflected in public debate because economists have taken far too much license.

Instead of presenting menus of options and listing the relevant trade-offs -- which is what economics is about -- economists have too often conveyed their own social and political preferences. Instead of being analysts, they have been ideologues, favoring one set of social arrangements over others.

Furthermore, economists have been reluctant to share their intellectual doubts with the public, lest they 'empower the barbarians.' ...

Paradoxically, then, the current disarray within the profession is perhaps a better reflection of the profession's true value added than its previous misleading consensus. Economics can at best clarify the choices for policymakers; it cannot make those choices for them.

When economists disagree, the world gets exposed to legitimate differences of views on how the economy operates. It is when they agree too much that the public should beware.

"Equilibrium and Meltdown"

George Waters of Illinois State University on the economic crisis and the state of macroeconomics:

Equilibrium and Meltdown, by George A. Waters: Equilibrium in economics is such a ubiquitous concept some might be surprised to hear that it is also controversial. It is hard to imagine doing much economic analysis without examining the intersection of supply and demand, but whether we should focus exclusively on equilibrium outcomes is a critical question. Though the importance of equilibrium might seem like an esoteric debate, the attitude toward this question has deep implications for economists’ views on the correct policy response to the current economic crisis.

Milton Friedman believed in equilibrium. An example of the intensity of his belief was his argument against requiring medical licenses for doctors on the grounds that more doctors would be allowed to practice, and market forces would weed out poor doctors and improve the quality of care. This argument makes perfect sense if we focus on the equilibrium outcome, but most people are instinctively repelled by this proposal. The concern arises from the consideration of how the world gets to such an equilibrium. To find out who the bad doctors are, some patients have to try them, get bad treatment and tell others about it. Since patients have little expertise in making judgments about doctors, a poor doctor could practice for many years without detection. I know this happens even with licensing requirements, but the situation could easily be worse without them. An equilibrium outcome cannot be divorced from the path to arrive at that state.

"The Unfortunate Uselessness of Most 'State of the Art' Academic Monetary Economics"

Willem Buiter on "'state of the art' academic monetary economics":

The unfortunate uselessness of most ’state of the art’ academic monetary economics, by Willem Buiter: The Monetary Policy Committee of the Bank of England I was privileged to be a ‘founder’ external member ... contained, like its successor..., quite a strong representation of academic economists and other professional economists with serious technical training and backgrounds. This turned out to be a severe handicap when the central bank had to switch gears and change from being an inflation-targeting central bank under conditions of orderly financial markets to a financial stability-oriented central bank under conditions of widespread market illiquidity and funding illiquidity.; Indeed, it may have set back by decades serious investigations of aggregate economic behaviour and economic policy-relevant understanding .; It was a privately and socially costly waste of time and other resources.

Most mainstream macroeconomic theoretical innovations since the 1970s (the New Classical rational expectations revolution associated with such names as Robert E. Lucas Jr., Edward Prescott, Thomas Sargent, Robert Barro etc, and the New Keynesian theorizing of Michael Woodford and many others) have turned out to be self-referential, inward-looking distractions at best.; Research tended to be motivated by the internal logic, intellectual sunk capital and esthetic puzzles of established research programmes; rather than by a powerful desire to understand how the economy works - let alone how the economy works during times of stress and financial instability.; So the economics profession was caught unprepared when the crisis struck.

"The Gratuitous Ignorance of Many of our Economists"

Paul Krugman with more on the failure of academic economics:

Equilibrium decadence (wonkish), by Paul Krugman: Brad DeLong is exercised about William Poole’s technological regress. I was getting at something like the same thing in my Dark Age post. Here are some further thoughts about the sad intellectual history of the past few decades.

What Brad calls technological regress and I call a Dark Age actually began with some profound and productive questioning of conventional wisdom. In the late 1960s macroeconomists began a search for microeconomic foundations — above all, an attempt to explain why nominal shocks seem to have real effects rather than merely affecting the price level. The 1970 Phelps volume, which suggested that imperfect information could explain a lot of what we see, had a huge impact on the profession. And when Lucas married this insight to rational expectations, it seemed to shake the foundations of Keynesian ideas about monetary and fiscal policy. Business cycles, Lucas suggested, last only as long as price- and wage-setters can’t disentangle nominal from real shocks — and monetary or fiscal policy can’t stabilize the economy, at most they add noise.

But it became clear after a few years that this approach wasn’t going to work: actual business cycles last too long to rely on imperfect information. And at that point the profession divided. One group went down the “new Keynesian” route, arguing that something such as small costs of changing prices must explain the rigidity we actually seem to see. This group isn’t averse to putting a lot of rationality into its models, but it’s willing to accept aspects of the world that seem clear in the data, even if it can’t (yet?) be fully explained in terms of deep foundations.

The other group decided that since they couldn’t come up with a rigorous microfoundation for price stickiness, there must not be any price stickiness: recessions are the result of adverse technological shocks, not demand shocks.

And the latter group, the equilibrium macro side, was so convinced of the logical correctness of its position that schools dominated by that view stopped teaching demand-side economics. (Schools dominated by new Keynesians, on the other hand, did teach real business cycle theory.) I haven’t been able to dig up the quote, but somewhere along the line Ed Prescott declared that his students wondered who Keynes was, because he was never mentioned in their courses.

And those trained according to this dogma were and are utterly ignorant of what Keynes, or modern Keynesians, have to say. They know that Keynesianism is stupid nonsense, because that’s what they remember having been told. But they don’t actually know why they’re supposed to believe that; the serious debates the profession had in the 70s about the microfoundations of inflation and unemployment theory are lost in the mist.

And as a result we have the spectacle of well-known economists offering what they think are profound arguments, but are actually long-refuted fallacies. Most important is the “Treasury view” that government spending can’t affect demand. But there’s also the astonishing belief that Ricardian equivalence means that consumer spending automatically falls to offset even a temporary increase in government spending, which seem to be part of that Poole quote. (New Keynesian models in which consumers fully anticipate future taxes still leave room for fiscal policy — but they don’t know that.)

And the sad thing is that all of this matters. Our ability as a nation to respond to the current economic crisis is being seriously hampered by the gratuitous ignorance of many of our economists.

Roman Frydman emails:

In connection with your post of Paul’s text on the failure of economics, Ned Phelps argues this is not about Neo-Keynesians or new Classicals, it is about economics that ignores the key feature of modern economies: the way they unfold over time cannot be represented by fully predetermined models (those modeling the economy with fixed rules implying a single probability distribution for the past and the future).

In fact the problem is the Rational Expectations Hypothesis, which MIT and Chicago happily share. As we argue in "Financial Markets and the State: Price Swings, Risk, and the Scope of Regulation" (and a number of recent academic papers) the mechanical nature of “scientific” models, which economists construct, prevents us from understanding the swings and design of regulatory policies. It is also dangerous, because it may lead to regulation that throws out the baby with the bath water. I think it is time that we leave “the dream of mechanical markets”, something truly difficult for both Paul and Bob Lucas.

"The Financial Crisis and the Systemic Failure of Academic Economics"

Via email:

The Financial Crisis and the Systemic Failure of Academic Economics, by David Colander, Hans Föllmer, Armin Haas, Michael Goldberg, Katarina Juselius, Alan Kirman, and Thomas Lux: [From the conclusion] ..."We believe that economics has been trapped in a sub-optimal equilibrium in which much of its research efforts are not directed towards the most prevalent needs of society. Paradoxically self-reinforcing feedback effects within the profession may have led to the dominance of a paradigm that has no solid methodological basis and whose empirical performance is, to say the least, modest. Defining away the most prevalent economic problems of modern economies and failing to communicate the limitations and assumptions of its popular models, the economics profession bears some responsibility for the current crisis. It has failed in its duty to society to provide as much insight as possible into the workings of the economy and in providing warnings about the tools it created. It has also been reluctant to emphasize the limitations of its analysis. We believe that the failure to even envisage the current problems of the worldwide financial system and the inability of standard macro and finance models to provide any insight into ongoing events make a strong case for a major reorientation in these areas and a reconsideration of their basic premises."

"Cognitive Hierarchy Theory"

I was trying to figure out how you would react to my reaction to this article, and how I should react in return. But I wasn't sure how you would react if I did:

Making a game of economic theory, EurekAlert: ...[G]ame theory and insights from cognitive psychology can shed light on the economic choices people and corporations make...

"Economics is the field that has used game theory the most broadly to understand bargaining, pricing, firm competition, incentive contracts, and more," explains [Colin] Camerer,... Professor of Behavioral Economics in Caltech's Division of Humanities and Social Sciences. "Almost all the analysis, however, assumes people plan ahead and carefully figure out what others will do, which often results in mathematical claims that are highly unrealistic cognitively."

"Time for a Revolution in Economic Thought"

I don't think Anatole Kaletsky is very impressed with the models used by financial economists:

Now is the time for a revolution in economic thought, by Anatole Kaletsky, Commentary, Times Online: ...In this article I will outline some of the unorthodox approaches to economics which conventional economists have ignored and which might have helped to avert the present crisis...

While some economists had warned for years about global trade imbalances, escalating house prices, of excessive consumer borrowing, none of them remotely foresaw the ... total breakdown of financial markets caused by the unforced blunders by investors and banks. Modern economists were inherently incapable of understanding such a problem because they assumed that investors were “rational” and markets “efficient”. These assumptions led inevitably to disaster once they were blown apart. ...

Benoît Mandelbrot,..., who invented fractal geometry and pioneered the mathematical analysis of chaos and complex systems, ... found fruitful applications in the study of earthquakes, weather, galaxies and biological systems from the 1960s onward, but the field that originally inspired his ideas turns out ... to have been finance and economics. Yet 40 years of effort by Mandelbrot to interest economists in the new mathematical methods, which appear to work far better in modelling extreme movements in financial markets than the conventional methods based on statistically “normal” distributions, have been either ridiculed or ignored.

At the other end of the academic spectrum, we find economists treating ideas from sociology, psychology or philosophy with the same derision and disdain. George Soros is no mathematician like Mandelbrot, but he has ... explained convincingly how false beliefs among investors can create self-reinforcing boom-bust cycles of exactly the kind afflicting the world today. But the reaction to these ideas has been the same as to Mandelbrot's:... refusal among ... economists, regulators and central bankers even to think seriously about approaches that challenge the central orthodoxies of ... “efficient” markets inhabited by “rational” investors send price signals which, in some sense, are always right. Reality is very different...

One reason why such fruitful insights have been ignored is the convention adopted by academic economists some 30 years ago that all serious ideas must be expressed in equations, not words. ... But even if we accept the mathematical formalism of modern economics, there is vast scope for new ideas.

A control theory approach, used by serious mathematicians such as Nicos Christofides and Shahid Chaudhri ... has applied advanced mathematics from aerodynamics and control engineering to analyse financial turbulence without the over-simplified assumptions, such as continuous liquidity, which have caused the recent disasters in risk management and regulation.

But the challenge that existing economic orthodoxy may find most disconcerting is Imperfect Knowledge Economics (IKE), the name of a path-breaking recent book by Roman Frydman and Michael Goldberg... Building on ideas of Edmund Phelps, one of the few Nobel Laureate economists who rejected the consensus view on rational expectations, IKE uses similar tools to conventional economics to generate radically different results. It insists that the future is inherently unknowable...

With this obvious, but critically important, change in assumptions, IKE demolishes most of the conclusions of rational expectations. More importantly, it shows that reasonable assumptions about economic uncertainty can produce financial models that ... are statistically far closer to what happens in the real world.

These are just a few examples of the creative thinking that has started again in economics after 20 years of stagnation. But the academic establishment ... will fight hard against new ideas. The outcome of this battle does not just matter to academic economists. Without a better understanding of economics, financial crises will keep recurring and faith in capitalism and free markets will surely erode. ...

"The Great Multiplier Debate"

This is very good. I have some follow-up comments at the end:

Why Can't We All Just Get Along? The Great Multiplier Debate, by Menzie Chinn: I've been thinking about why the numbers that are typically bandied about in policy circles (at least that I'm familiar with) have so little impact on the overall general and blogosphere debate (see some examples here and here). I think it's part ideological, and part methodological. I can't do much about the first (e.g., tax cuts good, spending on goods and services bad -- unless on defense; or alternatively "let the market adjust no matter how long it takes"). But at least I can lay out why reasons why there is disagreement on the size of the multipliers. ...

The starting point in the analysis is to realize that there are three key ways in which to obtain "multipliers".

• Estimation of structural macroeconometric models, with identification a la the Cowles Commission approach.
• Calibration of microfounded models (including real business cycle models, and New Keynesian dynamic stochastic general equilibrium models).
• Estimation of vector autoregressions (VARs) and associated impulse-response functions, with identification achieved by a variety of means.

Traditional macroeconometric models. Most of the estimates I have cited [1] [2] are based upon the first approach. One estimates a model with many equations, including the components of aggregate demand (C, I, G, X, M), supply side (price setting, wage setting), and potential GDP. The framework most popular in policy circles is one that might be characterized as "the neoclassical synthesis", wherein wherein prices are sticky in the short run, and perfectly flexible in the long run. ... Now even within this category, there is a wide diversity of specifications...

A key reason for the academic disenchantment with these types of models included the view that the identification schemes used were untenable (e.g., why is income in the consumption function but not in the investment?). Another source is the combined impact of the inflationary 1960's and 1970's, and the Lucas Critique. On the latter point, I'd point out that unless policy changes are really massive, the Lucas Critique (a.k.a. Econometric Policy Evaluation Critique) isn't really relevant (see [1]).

Models with micro-foundations in general equilibrium Micro-founded models are often associated with real business cycle models. However, the association is not one-for-one. It's true the early real business cycle models worked off of utility functions and production functions. But the modern generation of dynamic stochastic general equilibrium (DSGE) models in the new Keynesian mode incorporate microfoundations as well (utility functions, production functions, investment functions, etc.) but also incorporate rigidities such as price stickiness. Purists will say everything has to be microfounded. Well, that's a matter of taste, but the fact of the matter is that it's very hard to calibrate simple real business cycle models without rigidities to match the moments of actual real world data, even after the data's been HP-filtered (I'm sure this blanket statement will get me in trouble, but I think that that's a fair assessment). So DSGEs do better at mimicking real data, especially after numerous rigidities are incorporated. ... For a survey of how DSGEs have been incorporated into policy analysis, see the survey by UW PhD Camilo Tovar.

It's useful at this point to ask how are these models calibrated? For the deep parameters (intertemporal rate of substitution, for instance), one can rely upon some estimates -- then pick the one that you like (and is in the range of estimates). Oftentime, the combination of parameter values is selected to mimic the time series properties of actual (filtered) data. So say one believes one should not appeal to ad hoc Keynesian models. It's not clear that RBCs or DSGEs get you away from the problem that one has to appeal to the data to get multipliers since the models are calibrated to mimic real world data. In other words, while the theoretical bases of the models may differ,... the differences in terms of multipliers might not be as big as one might think.

VARs Vector autoregressions are regressions of multiple variables on lags of themselves. The underlying shocks can be identified by putting them in a recursive ordering (called a Cholesky decomposition), or using restrictions based on theory (say, money has no contemporaneous impact on prices; or money has no impact on output in the long run). VARs were initially proposed as a way of getting around "incredible identifying assumptions", in the Cowles Commission approach to econometrics embodied in the old style macroeconometric models. But of course, people can disagree about which restrictions make the most economic sense. (For instance money is neutral in the long run seems natural, but not all theoretical models have that implication.)

The much cited Romer and Romer model of fiscal policy impacts is a particular sort of VAR, in which only one equation is focused on, and extra-model information is used to identify exogenous tax changes (remember, they don't analyze government spending changes). ... A good summary of where these types of fiscal multipliers come from was in Box 2.1 in Chaper 2 of the April 2008 World Economic Outlook.

My bottom line There are indeed a wide variety of estimates regarding the size of multipliers. Different models -- and assumptions within those model categories -- lead to different estimates. It's important to understand the underpinnings of those estimates (and this is where many of the people who cited the Romer and Romer study went wrong). Hence, one has to have an understanding of the very complicated models before taking strong stands in favor of one estime over another.

In my experience, as far as policy organizations such as central banks, government agencies and multilateral agencies go, reference is made to a number of models. Their assessments of multiplier magnitudes will then reflect some weighting of the various model predictions. That is why I will put more wieght upon assessments by organizations (that have to make decisions upon these judgments) than a single academic study, regardless of how well I respect the academics involved (and sometimes, these academics are working outside their area of research expertise...)

As an aside, here are the impacts of various fiscal experiments in response to a negative shock in a DSGE developed by the IMF... Notice that the public investment shows the biggest impact, while under the base assumptions the impact of transfers and tax cuts are about the same.

Models are built to answer specific questions. If you are interested in traveling to an unknown area of the city, then a street map - a model of the world that answers the how do I get there question - is useful. It is even more useful if it is built specifically for your question. If I am traveling by car, I want to know where the roads are, a map showing all of the underground conduits in the city and nothing else is useless. But suppose I try to use a map designed for a car to find the best route for traveling by bicycle. I can probably find a way there using this map, but it may not give the best possible answer. Some roads may be hard to travel on, it may not show smaller roads that a bicycle rider might want to take, and if it only shows, say, freeways where bikes are prohibited, then it isn't much use at all. But more importantly, it may omit bike routes. I don't know how it is where you live, but here there is a fairly extensive set of bike paths that are separate from the roads used by cars. And these routes can save you lots of time - if you know about them, i.e. if your map shows them. So the best map would show bike routes and roads suitable for bikes, and omit everything else, and it could also show things like elevation changes if it's an areas with lots of hills (which isn't usually part of a road map).

My point is this. Since the Great Moderation, and since Lucas convinced everyone that growth is where all the action is, the questions we have been asking have been mainly about growth and, where stabilization is concerned, about the use of optimal monetary policy rules to offset economic fluctuations (and whether monetary policy was responsible for the Great Moderation). Thus, the models were built to look at these particular questions. Nobody, or hardly anybody, was asking questions about the use of fiscal policy to stabilize the economy. Hence very few models were built to look at this issue. Because of that, because we are essentially using a map designed to guide cars to ask questions about the best way to travel by bicycle, we may not get the best answer to the question (that is, the answer to the question of what's the fastest way to get there - akin to asking about the fastest way for the economy to recover - may be wrong).

Why was fiscal policy ignored? Two reasons come to mind. First, we thought the economy was much more flexible than ever before. If a shock hit, even a big one, it might cause a bit of a pause, but the economy would quickly recover and keep on growing. It was the Terminator economy, and there was no shock big enough to keep it from quickly reassembling itself and picking up where it left off. And the two recessions during that time period, along with the experience of 9-11 and Katrina, all led people to believe that the economy had, in fact, undergone a shift and was now more robust than ever. The exact source of this shift was the subject of great debate, was it monetary policy, financial innovation, just good luck, better technology such as computers, the list was very long, but whatever the cause, the shift itself was taken to be permanent. Thus, the need for stabilization policy, fiscal policy in particular, was believed to be greatly diminished. The fact that fiscal policy might be needed in a deep recession because monetary policy would be rendered ineffective was discounted and ignored because the the belief was that a deep recession couldn't occur, the economy was too robust and flexible for that.

The second factor was the belief that if stabilization policy is needed, monetary policy was superior in every way to fiscal policy. Monetary policy could be implemented faster, with less distortions, it could be reversed quickly, it was in the hands of independent, public minded shepherds, there wasn't any dimension, or so it was thought, upon which fiscal policy would be better than monetary policy, and vast amounts of research were devoted to getting the monetary policy component of stabilization policy correct. In the process, fiscal policy was dismissed as irrelevant, at least as a stabilization tool, and largely ignored by researchers  (fiscal policy was still used to try to promote growth - that's the whole supply-side argument about cutting taxes, but not as a stabilization tool). That's not to say government spending and taxes weren't included in models and analyzed theoretically, or even empirically, but to the extent that happened, the questions were not focused on how fiscal policy could be used as a stabilization tool -- the models were not constructed to answer this question.

So it shouldn't surprise us that most of the estimates on multipliers come from the old style, many equation, structural macroeconometric models, the traditional approach described above. These models were built at a time when questions about fiscal policy were in the forefront, so answers to fiscal policy questions come out of this framework easily. For this reason, because the models were built with this question in mind, there is an abundance of evidence about fiscal policy multipliers, particularly government spending multipliers, from research conducted during this time period. The next approaches to macro modeling and estimation, the micro-founded models and the VAR models, came into being as the fiscal policy question was falling by the wayside (most VAR models do not even include government spending and taxes). Thus, as you may have noticed, there isn't much in the way of evidence from these models that we can reply upon (and that's not even considering the fact that we have very little data from recessionary episodes to inform us on these issues). The models will be built - I guarantee you they are being built presently - but for now we have what we have.

"Economists, Ideology, and Stimulus"

Paul Krugman says what I've been trying to say:

Economists, ideology, and stimulus, by Paul Krugman: Mark Thoma and Brad DeLong are both, in slightly different ways, perturbed by the state of debate over fiscal stimulus. So am I. This has not been one of the profession’s finest hours.

There are certainly legitimate arguments against spending-based fiscal stimulus. You can worry about the burden of debt; you can argue that the government will spend money so badly that the jobs created are not worth having; and I’m sure there are other arguments worth taking seriously.

What’s been disturbing, however, is the parade of first-rate economists making totally non-serious arguments against fiscal expansion. You’ve got John Taylor arguing for permanent tax cuts as a response to temporary shocks, apparently oblivious to the logical problems. You’ve got John Cochrane going all Andrew-Mellon-liquidationist on us. You’ve got Eugene Fama reinventing the long-discredited Treasury View. You’ve got Gary Becker apparently unaware that monetary policy has hit the zero lower bound. And you’ve got Greg Mankiw — well, I don’t know what Greg actually believes, he just seems to be approvingly linking to anyone opposed to stimulus, regardless of the quality of their argument.

Needless to say, everyone I’ve mentioned is politically conservative. That’s their right: economists are citizens too. But it’s hard to avoid the conclusion that all of them have decided on political grounds that they don’t want a spending-based fiscal stimulus — and that these political considerations have led them to drop their usual quality-control standards when it comes to economic analysis.

Has there been any comparable outbreak of mass bad economics from good liberal economists? I can’t think of one, although maybe that’s my own politics showing. In any case, what’s happening now is pretty disturbing.

Greg Mankiw's response is:

Let me make clear: When I link to another economist here on this blog, it is typically because I think his or her arguments are worth hearing and thinking about, not necessarily because I agree with all of them. I don't have the time to offer a refereeing service for every article I mention. So when I say, "Here is an article by Professor X," I mean "Here is an article by Professor X," not "Here is an article by Professor X, and I approve of everything he says."

I don't think this is satisfactory (and I've told Greg that by email in the past, though it's been awhile). If he has read something and disagrees with it, why not say so (e,g, "I think this is interesting, but don't necessarily agree with the point about whatever"). It only takes a few seconds to add this, and it alerts readers who wouldn't know otherwise that there may be flaws in the argument. He doesn't have to say why he disagrees, that can take a long time, but he can state that a disagreement exists. Basically Greg has given himself a free hand to post things that support his point of view - further his political agenda - without having to take responsibility for what is said or how it is presented (and the excuse that he doesn't have time to vet everything he posts because he's such a busy, important guy doesn't cut it). I used to think I could post things without comment that were decent arguments, but that I disagreed with, but I found that people attribute the views posted here to me whether I like it or not (hence, for example, when I posted the recent Borjas piece, I italicized the word his in the introduction, "George Borjas with his advice for the incoming administration," and even then I worried I wasn't clear enough that I didn't necessarily agree). If I post something and disagree, then I think I need to say so. If I don't state disagreements and post something anyway, then I shouldn't be surprised if people think it's a view I endorse.

But this misses the biggest part of the problem. The problem isn't Greg Mankiw linking to Paul Krugman even though he disagrees and having people believe that Greg endorses Paul's views. Those cases are pretty clear, and the disagreement is usually stated pretty clearly anyway (or it doesn't get posted). The problem comes when you post things that support your point of view, but you don't necessarily agree with the theory, methodology, etc. used to arrive at the supporting conclusion. This is where the confusion is the greatest. People know, for example, that Greg has been a skeptic on stimulus spending, so when he posts an argument against government spending as a stimulus tool, people naturally think it's an argument he endorses. And they should, why else would it be posted if not as supporting evidence? Declaring that you might post things that support your agenda without any comment at all, even when you have questions about how the conclusion was derived, is a license to mislead.

Update: Also see Robert Waldmann with What's in the Water in Chicago? and The Effect of Government Spending on GNP in the Classical model.

How Far Can You Throw an Economist?

I wasn't completely happy with my discussion in Can Economists Be Trusted? Are There Any Wrong Answers in Economics?. I talked about cherry picking results to serve political aims, but I didn't talk about or come down hard enough on the misrepresentation of results for political purposes. So I'm glad to see Andrew Gelman continuing the discussion:

"Can economists be trusted?," by Andrew Gelman: Mark Thoma has an interesting discussion of the challenge that the economics profession, and individual economists, have when they give policy recommendations.

Mark's basic point goes as follows. Consider the following four stages of a model:

(a) assumptions about fundamental principles of how the world works,
(b) normative principles (that is, fundamental goals, views about how the world should be),
(c) conclusions about the likely effects on policy,
(d) recommendations about policies.

In any rigorous economic model, there should be a mapping leading from (a) to (c). Further reasoning (possibly mathematical modeling, as in cost-benefit analysis) will take you from (b) and (c) to (d).

That's all fine. But Mark's point is that the reasoning can go the other way too: start with (b) and (d), and then you can figure out what (c) needs to be, and then you can go back one more step and figure out what model (a) you need to get started! Even if economists are not doing this reasoning-from-conclusions-to-assumptions explicitly, you could well believe it's going on implicitly as well as being induced by various pressures such as the selection of what research results to report and even what problems to work on.

This is inevitable, and I discuss it in ... Bayesian Data Analysis. We call it the garbage-in-garbage-out problem: If you can come with any decision you'd like by just altering the inputs of your analysis, then what's the point of decision analysis (or, by extension to the above-linked example, economic modeling) at all?

My answer is something that I call "institutional decision analysis," which has two principles:

1. It can be a good idea to provide reasoning to justify your decisions. ...[A]n institution--whether it be a business, a government agency, a nonprofit organization, or some other grouping--often needs some path of bread crumbs connecting assumptions to recommendations. ...

2. As Mark noted, an overall decision recommendation on anything important is likely to be so dependent on assumptions to such an extent that it's probably fair to say that the analyst is reasoning from conclusions to assumptions (from (d) to (c) and then to (a), in my above notation). But, even then, formal decision analysis can be useful in making relative recommendations. This is the point that we made in our article about decision making for home radon. In the economics context, this might suggest that economists of different political persuasions could still give useful recommendations about how to spend money or cut taxes, or where in the economy such policies would make more or less sense.

There's always a temptation to act as a lawyer - to use theory and empirical evidence, your own if necessary, to make the best possible case for the policies you would like to see enacted. Lobbyists certainly do this, consultants do this in some cases (though they ought to advise their clients of the full spectrum of evidence), politicians don't hesitate to shade things to make themselves look good, and some think tanks are also fully engaged in this type of activity (in a few cases, to the point of blatantly misrepresenting theory or evidence in order topromote their point of view ).

But lawyer like advocacy for preferred policies is not how academic economists ought to present evidence to policymakers and to the public. This does not mean economists should always end up in some wishy-washy, on the one hand, on the other hand position due to unavoidable uncertainty involved in the decision-making process, they can still come to firm policy recommendations. And in this regard point 1 above - connecting assumptions to recommendations - is helpful in explaining the basis for the decision (I'd add the connection between the empirical evidence and the recommendations as well). But I'd also like to see a bit more than that, including how robust the recommendations are to changes in the assumptions, whether there are other common assumptions that lead to different outcomes, and if so, why these assumptions were ruled out, and the strength of the empirical evidence being used to support the policy position.

"Can Economists Be Trusted?" "Are There Ever Any Wrong Answers in Economics?"

Uwe Reinhardt:

Can Economists Be Trusted?, by Uwe E. Reinhardt, Economix: ...[W]ittingly or unwittingly, economists infuse their analysis with their own (or a political client’s) preferred ideology.

Consider, for example, President Bill Clinton’s 1993-94 health-reform plan. In this plan, President Clinton proposed a mandate on employers to provide their employees with health insurance.

Politically conservative economists predicted that the mandate ... would lead to vast unemployment. Economists supporting the Clinton health plan predicted that the ... mandate ... might even ... increase employment.

It can be shown with a simple mathematical model that an economist’s prediction in this regard is powerfully driven by two assumptions about the behavioral responses to mandated employer-paid health insurance. ... Unfortunately, the empirical literature on this responsiveness offers economists a wide range of estimates from which they can choose...

This example starkly illustrates how easy it is for economists to infuse their own ideology – or that of their clients – into what may appear to outsiders as objective, scientific analysis.

We are now seeing a replay of this tendency in the debate on the relative merits of added government spending versus added tax cuts as measures to stimulate the economy.

Writing in The New York Times, for example, the Harvard professor N. Gregory Mankiw, former chief of President George W. Bush’s Council of Economic Advisers, makes a case for stimulating the economy through tax cuts rather than added government spending. ...

To buttress his case..., he then cites an empirical study by Valerie A. Ramey, according to which the $1 of added government spending will ultimately increase gross domestic product (G.D.P.) by only $1.40, while according to another recent study by Christina and David Romer, $1 of tax cuts over time increases G.D.P. by $3.

Non-economists may ask, of course, exactly how a $1 cut in taxes would translate itself into a $3 increase in G.D.P. at a time when traumatized households, whose wealth has been eroded, might use any new tax savings merely to pay down debt or rebuild their wealth through added savings, rather than spend it, and when business firms unable to sell their output even from existing capacity might hesitate to invest such tax savings in more capacity.

But never mind this fine point.

More interesting is the fact that Christina Romer is to be the head of President-elect Barack Obama’s Council of Economic Advisers. In that capacity, last Saturday she released an analysis of fiscal stimulus alternatives, with a co-author, Jared Bernstein. Curiously — or perhaps not — for that analysis, the two authors assume a much larger four-year multiplier effect for added government spending (1.55) than for tax cuts (0.98), although they do confess to a high degree of uncertainty on the actual sizes of these multipliers.

So there you have the flexibility, shall we say, that economists enjoy when they apply their professional skills to affairs of state in what may seem, to outsiders, like purely scientific analyses.

In the first lecture of my freshman economics course at Princeton entitled “The Art of Siffing Among Seasoned Adults,” I demonstrate how seasoned adults routinely structure information felicitously (i.e., “sif”) to further their own agenda, and I point out that economists can be among the most skillful practitioners of this art. ... When economists advise on public policy, the operative mantra is Caveat Emptor!” ...

The answer to this, of course, is that economists should acknowledge the range of estimates, and, if they are committed to one set of estimates over another, if they want to get past the "on the one hand, on the other hand" construction, why they think one set is better or worse than another (let me admit to being less than perfect at this myself).

Brad DeLong:

Fama's Fallacy V: Are There Ever Any Wrong Answers in Economics?: Montagu Norman here, back from my grave once again. This time it is Greg Mankiw whose words have summoned me...

One thing that used to give me nightmares--and that provoked several of my nervous breakdowns--was how you could never get any economist (except for John Maynard Keynes) to take a definite position. They were always "on the one hand--on the other hand." This was what led Harry Truman in later days to wish for a one-handed economist, a wish that has never been fulfilled...

The "on the one hand--on the other hand" nature of discourse raises the question of whether in economics--a "science" where there is enormous intellectual and ideological and political disagreement about how the world works--there can ever be any wrong answers?. I believe that there can be wrong answers in economics, because examinations in economics tend to take a particular form: instead of asking (i) "do expansionary fiscal policies increase output and employment?" we ask (ii) "in models where there are idle resources and high unemployment, do expansionary fiscal policies increase output and employment?" (ii) is a question about a particular class of models of the economy, and so has a definite right answer--"yes, in that class of models they do"--and a definite wrong answer--"no, in that class of models they don't."

Eugene Fama claimed that "when there are idle resources--unemployment" expansionary fiscal policies had no effect in models in which the NIPA savings-investment identity:

investment = (private savings) - (government deficit)

held.

Now the NIPA savings-investment identity holds in all models--it is, after all, an identity, true by definition and construction. And every single model that has been built in which there is a possibility of high unemployment and idle resources is a model in which fiscal policy works because increases in government spending lead to unexpected declines in inventories and unexpected declines in inventories lead to firms to expand production, which leads to increases in income and saving.

I would, therefore, say that Fama's claim is "wrong". Not only does it not hold in all models in the class, it does not hold in any models in the class.

Greg Mankiw disagrees:

Greg Mankiw's Blog: Fama's arguments make sense in the context of the classical model... presented in Chapter 3 of my intermediate macro textbook.... I would go on to the Keynesian model.... But whether one leaves the classical model behind to embrace the Keynesian model is a judgment call...

Mankiw thinks that Fama is not wrong but is, rather, making a "judgment call."

But Mankiw writes in his chapter 3 that the classical model "assume[s] that the labor force is fully employed." And so Greg gets himself into Cretan Liars' Paradox territory here: Fama says that there is high unemployment and idle resources, while Mankiw says that Fama is not wrong because he makes sense as long as the labor force is fully employed and there are no idle resources.

Is Mankiw's answer here a "wrong" answer, or is he too making a "judgment call"? I seek an empirical test. I seek a Harvard undergraduate to take Greg Mankiw's course this spring, to write the following in an appropriate place:

the classical model of chapter 3 shows us that expansionary fiscal policies have no effect on output even where there are idle resources--unemployment.

and to report back on the reaction of the course instructors.

Let's ask another question. Does Greg Mankiw believe in the classical model he is using to defend Fama (in the classical model, the LM curve is vertical, and a vertical LM curve leads to a vertical supply curve, and to the result that demand side policies such as a change in government spending or taxes cannot change real output)?:

I disagree ... that the LM curve is vertical... Introspection is not a particularly reliable way to measure elasticities. There is a substantial empirical literature on money demand that demonstrates that it is interest-elastic. ... According to Ball, the interest semi-elasticity of money demand is -0.05: This means that an increase in the interest rate of one percentage point, or 100 basis points, reduces the quantity of money demanded by 5 percent.

How far off is the vertical LM case as a practical matter? One way to answer this question is to look at the fiscal-policy multiplier. In chapter 11 of my intermediate macro text, I give the government-purchases multiplier from one mainstream econometric model. If the nominal interest rate is held constant, the multiplier is 1.93. If the money supply is held constant, the multiplier is 0.60. If the LM curve were completely vertical, the second number would be zero. ...

Greg has been pretty good at saying there is a lot of uncertainty about the fiscal policy multipliers, and about explaining why estimates differ across studies, and why he favors one set of estimates over another, so I don't want to come down too hard on his disagreement with the 1.93 figure in his "favorite textbook", but it does seem like he is defending Fama with a model that he does not believe in.

Rational or Not?

Was the financial crisis a fully rational response to a poorly structured environment, or is irrationality a fundamental characteristic of economic behavior? I've always leaned toward the poorly structured environment side of the argument:

Managing fads, frenzies and finance markets, by Xavier Vives, Project Syndicate: The financial crisis ... severely damaged the credibility of financial markets, institutions and traders. More and more people are claiming that markets are characterized by irrationality, bubbles, fads and frenzies, and that economic actors are driven by behavioral biases. ...

I believe, however, that there is another explanation ... based on rational calculation ... by institutions and traders. The problems ... in the financial markets have very much to do with lack of good information, misaligned incentives, and, in fact, rational responses to the environment. When information is scarce and unevenly distributed, prices may well depart from the reality of fundamentals.

We see this when new technologies arrive... The Internet bubble is the most recent example, but a similar phenomenon occurred with the construction of railways more than a century ago. It can be argued that the sophisticated loan packages created ... in recent years are, likewise, a new and unknown product, so information and experience to aid pricing has been scarce and dispersed.

In such circumstances, prices may well move far from the fundamentals as assessed by a hypothetical collective wisdom that would pool all information in the market. Trading on the momentum of price movements may then become a rational activity that becomes self-fulfilling, as investors decide to "ride the bubble" while it lasts. ...

This means that important and relatively persistent departures of prices from fundamental values are possible..., but ... a correction ... will always follow. ... This explains why the market can look like Keynes's casino in the short term and like Hayek's marvel in the long term. ...

The debate over the irrationality of financial markets is no mere academic argument. If we believe that economic actors are irrational, then we will enact paternalistic policies aimed at controlling behavior or bailing out failed agents and institutions, which could be self-defeating and even dangerous. This may include restrictions on investments by institutions and individuals and intrusive regulation that limits, or dictates, their conduct in the market. The calls to curb speculation in derivatives markets or short sales have this flavor.

If, on the other hand, we believe that economic actors will respond rationally to incentives and information, then we can usefully reform regulatory frameworks with well-targeted measures, including restrictions on off-balance sheet vehicles, tougher disclosure requirements and controls on rating agencies' conflicts of interests.

The Austrian and Chicago Schools

This is from History of Economic Thought: A Critical Perspective, by E.K. Hunt, a long out of print textbook I had when I was an undergraduate at CSU Chico [update: it is has been published again by M E Sharpe]. It explains how the "Austrian and Chicago schools reduce all human behavior to rational maximizing exchanges and hence are able to prove that in every respect, economic and non-economic, a free market, capitalist system is the best of all possible worlds," and gives some of the critical reactions to that point of view:

The Austrian and Chicago Schools

The school of neoclassical economists that advocates extreme laissez-faire Capitalism represents the contemporary counterparts of Senior and Bastiat. In a sense this group really represents two separate but similar schools - the Austrian School and the Chicago School. The Austrian School traces its lineage directly back to Carl Menger (Chapter Eleven), Menger's extreme methodological individualism is the basis of the social philosophy of the Austrian School.

While Menger's first generation of disciples included both social reformers and conservatives, the ultraconservative nature of the Austrian School is more properly thought of as the product of two of Menger's second-generation disciples, Ludwig von Mises and Friedrich A. Hayek. Both von Mises and Hayek taught at various times at the University of Chicago. Together with Frank H. Knight, who taught for many years at the University of Chicago, they were the most important influences in the formation of the Chicago School. For the past generation, Milton Friedman has been the most influential member of the Chicago School. In 1976, Friedman was awarded the Nobel Prize in economics.

The problem with classifying the Austrian and Chicago schools together is that although they both emphasize the universal beneficence of exchange, extreme individualism, and a doctrinaire advocacy of laissez-faire, they have methodological differences. The Austrians generally advocate a rationalist approach to economic theory, while Milton Friedman and his followers generally advocate an empiricist approach. Although it is currently very common in the academic economics profession to hear all extremely individualistic advocates of laissez-faire referred to as the "Chicago School," it is probably more accurate to say that the more conservative wing of contemporary neoclassicism is about evenly divided between those who on methodological grounds follow the Austrian School and those who follow Friedman's Chicago School. We do not believe these methodological differences to be terribly significant,17 so we shall consider these contemporary advocates of extreme laissez-faire together.

"Correspondence, Abstraction, and Realism"

Philosopher of social science Daniel Little on "realists" versus "instrumentalists":

Correspondence, abstraction, and realism: Science is generally concerned with two central semantic features of theories: truth of theoretical hypotheses and reliability of observational predictions. ... Truth involves a correspondence between hypothesis and the world; while predictions involve statements about the observable future behavior of a real system. Science is also concerned with epistemic values: warrant and justification. The warrant of a hypothesis is a measure of the degree to which available evidence permits us to conclude that the hypothesis is approximately true. A hypothesis may be true but unwarranted (that is, we may not have adequate evidence available to permit confidence in the truth of the hypothesis). Likewise, however, a hypothesis may be false but warranted (that is, available evidence may make the hypothesis highly credible, while it is in fact false). And every science possesses a set of standards of hypothesis evaluation on the basis of which practitioners assess the credibility of their theories--for example, testability, success in prediction, inter-theoretical support, simplicity, and the like. ...

Whatever position we arrive at concerning the possible truth or falsity of a given economic hypothesis, it is plain that this cannot be understood as literal descriptive truth. Economic hypotheses are not offered as full and detailed representations of the underlying economic reality. For a hypothesis unavoidably involves abstraction, in at least two ways.

"Economists' Pretensions About Science"

Gavin Kennedy continues his crusade against the myth of the invisible hand:

An Evolutionist Speaks Out About Economists' Pretensions About Science, by Gavin Kennedy: Massimo Pigliucci, professor in the departments of Ecology and Evolution, Stony Brook, NY, contributes an important piece of work in the Blog, Rationallyspeakingout.org (‘a site devoted to positive scepticism') (here):

Economics learns a thing or two from evolutionary biology

Economics is supposed to be a solid discipline, founded on complex mathematical models (and we all know math is really, really difficult). They even give Nobel prizes to economists, for crying out loud! And yet, economics has always had to fight off the same reputation of being a “soft” science that has plagued sociology, psychology, and to some extent even some of the biological sciences, like ecology and evolutionary biology. Indeed, like practitioners in those other fields of inquiry, some economists admit of being guilty of “physics envy,” that is, of using the physical sciences as the model for what their field ought to be like. Turns out even the assumption that a good science should be modeled on physics is “flawed,” to use Greenspan’s apt phrase.

A recent article by Chelsea Wald in Science (12 December 2008) puts things in perspective by asking how it is possible that so many smart people in the financial sector made irrational decisions over a period of years, despite clear data showing there was a problem, and eventually leading to a worldwide economic crisis that is at the least poking at, if not shaking, the foundations of capitalism itself.

Part of the answer is to be found in the persistent idea in economics that “markets” work because people are rational agents who act in their own self-interest and have perfect, instantaneous access to relevant information about the businesses they are considering investing in. Economists are not stupid, and they know very well that perfect rationality, complete information and instant access are all light years away from the reality of how markets operate. And in fact recent models have relaxed these assumptions to some extent. But it is so much more tractable to model things that way! After all, physicists do it too: remember those problems in Physics 101 that started “consider a spherical cow…”?

Quantitative Methods and the Financial Crisis

Nassim Taleb and Pablo Triana don't pull any punches:

Bystanders to this financial crime were many, by Nassim Nicholas Taleb and Pablo Triana, Commentary, Financial Times: ...A crime has been committed. Yes, we insist, a crime. There is a victim (the helpless retirees, taxpayers funding losses, perhaps even capitalism and free society). ... And there was a robbery (overcompensated bankers who got fat bonuses hiding risks; overpaid quantitative risk managers selling patently bogus methods). ...

Almost everyone in risk management knew that quantitative methods – like those used to measure and forecast exposures, value complex derivatives and assign credit ratings – did not work... Almost everyone would accept that the failure in 1998 of Long Term Capital Management discredited the quantitative methods of the Nobel economists involved with it (Robert Merton and Myron Scholes) and their school of thought called “modern finance”. LTCM was just one in hundreds of such episodes.

Yet a method heavily grounded on those same quantitative and theoretical principles, called Value at Risk, continued to be widely used. It was this that was to blame for the crisis. ... Indeed, the same Nobel economists who helped blow up the system at least once, Professors Scholes and Merton, could be seen lecturing us on risk management, to the ire of one of the authors of this article. Most poignantly, the ... regulators were using the same arguments. They, too, were responsible.

So how can we displace a fraud? Not by preaching nor by rational argument (believe us, we tried). Not by evidence. Risk methods that failed dramatically in the real world continue to be taught to students in business schools... As we are writing these lines, close to 100,000 MBAs are still learning portfolio theory... The fraud can be displaced only by shaming people, by boycotting the orthodox financial economics establishment and the institutions that allowed this to happen. ...

So when you see a quantitative “expert”, shout for help, call for his disgrace, make him accountable. Do not let him hide be-hind the diffusion of responsibility. Ask for the drastic overhaul of business schools (and stop giving funding). Ask for the Nobel prize in economics to be withdrawn from the authors of these theories, as the Nobel’s credibility can be extremely harmful. Boycott professional associations that give certificates in financial analysis that promoted these methods. Remove Value-at-Risk books from the shelves – quickly. Do not be afraid for your reputation. Please act now. Do not just walk by. Remember the scriptures: “Thou shalt not follow a multitude to do evil.”

[See also: How Software Models Doomed the Markets and The State of Financial Engineering.]

"Frequentists vs Bayesians"

Steve Hsu:

Frequentists vs Bayesians, by Steve Hsu: Noted Berkeley statistician David Freedman recently passed away. I recommend the essay below if you are interested in the argument between frequentists (objectivists) and Bayesians (subjectivists). I never knew Freedman, but based on his writings I think I would have liked him very much -- he was clearly an independent thinker :-)

In everyday life I tend to be sympathetic to the Bayesian point of view, but as a physicist I am willing to entertain the possibility of true quantum randomness.

I wish I understood better some of the foundational questions mentioned below. In the limit of infinite data will two Bayesians always agree, regardless of priors? Are exceptions contrived?

Some issues in the foundation of statistics Abstract: After sketching the conflict between objectivists and subjectivists on the foundations of statistics, this paper discusses an issue facing statisticians of both schools, namely, model validation. Statistical models originate in the study of games of chance, and have been successfully applied in the physical and life sciences. However, there are basic problems in applying the models to social phenomena; some of the difficulties will be pointed out. Hooke’s law will be contrasted with regression models for salary discrimination, the latter being a fairly typical application in the social sciences.

"Imperfect Knowledge and Post-Crisis Reform of the Financial System"

In a recent interview with CNN, President-elect Obama says:

"[The] top priority may ... be continuing to stabilize the financial system. We don't know yet what's [going to] happen in January," he said. "None of this can be accomplished if we continue to see a potential meltdown in the banking system and financial system. So that's priority number one — making sure the plumbing works."

Since stabilizing financial markets and reforming the financial system will be a top priority for the new administration, what types of reforms should be enacted? The paper below argues that it is crucial that the administration and policymakers consider these reforms within the context of models that recognize the importance of imperfect knowledge.

The paper also examines whether policymakers should intervene to stabilize asset prices, i.e. whether the Fed should try to pop bubbles before they get too big. To examine this issue, the paper responds to a speech given by Ben Bernanke in October of 2002 that explains the conventional view, a view that has come to be known as Greenspanism. The paper argues that this approach is misguided, and offers a new approach based upon the assumption of imperfect knowledge on the part of market participants, the Fed, and other policy officials. In doing so, the paper also counters recent criticism of Alan Greenspan that says he kept interest rates too low after the dot.com crash. But, the paper does blame his ideology for contributing in an important way to the crisis:

Imperfect Knowledge and Post-Crisis Reform of the Financial System: A Sketch of the Conceptual Framework and Policy Proposals, by Roman Frydman and Michael D. Goldberg [note: podcast] In an interview with Wolf Blitzer in Des Moines, Iowa, the then Democratic nominee Senator Barack Obama was asked to name his top priority from a list of issues, which included taxes, health care, education, energy policy, and immigration.

“[The] top priority may not be any of those five. It may be continuing to stabilize the financial system. We don’t know yet what's gonna happen in January,” he said. “None of this can be accomplished if we continue to see a potential meltdown in the banking system and financial system. So that’s priority number one – making sure the plumbing works.”

Fortunately for the country and, indeed, the world, the now President-elect Obama understands that getting the financial system right must be one of the top priorities he addresses [1]

There are two key issues that need to be tackled:

1) Stabilizing the financial system in the short-term and repairing the plumbing – the flow of credit. (Policy makers have already done much in addressing this issue...)

2) Re-regulation of markets and formulation of policy in order to reduce the magnitude and frequency of crises in the future. How do we avoid throwing out the baby with the bath water? That is, how do we regulate and formulate policy while preserving capitalist economies’ key feature – their powerful incentives to individuals to devise new ways of doing things?

To deal with the second issue requires a new conceptual framework. The origin of the current crisis lies in the sharp upswing in equity and house prices, followed by a sharp downswing. ...

To develop the appropriate policy response to the current financial crisis, we need to understand such fluctuations. The problem is that current policy thinking is based on economic models that do not provide an adequate account of asset price fluctuations.

The key flaw of the contemporary framework is that it does not recognize the important role of imperfect knowledge in driving outcomes in asset markets. Indeed, contemporary models view market outcomes as arising from equilibria that ignore the imperfection of knowledge on the part of market participants and policymakers. Financial markets are normally viewed as being in these equilibria, which can be thought as determining the benchmark level. Swings away from benchmark levels treated as bubbles, which occur because of factors – irrationality or market psychology – that are unrelated to market fundamentals.

But, treating price swings as bubbles, largely driven by non-fundamental factors over which only God may have control, offers very little guidance about which policies can limit the system’s vulnerability to crisis. It limits the regulatory response to ensuring transparency of information. Of course, if a sudden reversal in the market occurs, leading to a crisis, policy officials act strongly to restore liquidity and confidence in the financial system. Lacking guidance from economists’ models, they can only hope that markets return to their normal equilibrium behavior, and that another bubble will not form anytime soon. 

A more theoretically-sound and empirically-relevant account of asset market fluctuations comes from a new approach to economics that places imperfection of knowledge at the center of analysis.[4] This approach, which we have dubbed Imperfect Knowledge Economics (IKE), does not presume that individuals are irrational, but that they have imperfect knowledge of how asset prices are related to market fundamentals. Indeed, news about fundamentals – e.g., interest rates, earnings, GDP growth rates, central bank announcements – move markets. Asset prices often undergo long swings away from historical benchmark levels, followed by “corrections,” because this is how markets “discover” a sensible range of values. Once one recognizes that upswings and downswings depend on how market participants, with their imperfect knowledge, interpret fundamentals, new channels for policy action open up.

Econ Bloggers

From Tyler Cowen:

Econ bloggers gain clout in financial crisis, Marginal Revolution: Here is the article, there is lots from me and from Mark Thoma, among others.

On a more casual note, I've enjoyed blogging the same topic week after week after week.  I wonder at what point I will feel like cracking?

I'm not sure the quote about doctors came out quite right:

Are the econ bloggers able to better explain and analyze the often-complex factors that have led to the current crisis?

"I'm in academics," he replied. "On the academics side, you don't ever diagnose the patient. It's all theoretical, and what I'm doing now, especially with the financial crisis, is like having a patient show up at the doctor's office and say, 'I've got these symptoms, what's wrong with me?' And the doctor sticks him. That's a completely different use of economics -- a real time analysis -- that I haven't seen before."

Instead of "and the doctor sticks him," I meant that the doctor is asked to diagnose what is wrong and recommend a prescription - a cure of some sort - that will fix the problem (or explain why no cure is available and the patient will have to suffer through the problem until it fixes itself). You don't have the luxury  you have as an academic of waiting until it's all over, looking at the data, and then figuring out how well the policy worked, what could have been done better, etc. Part of real-time policymaking is learning what to look at ("Get me a TED spread, stat!"), and then learning how to interpret the diagnostics that you get so that you can understand what is happening and recommend a course of action. Real-time policy making is not easy, and you find out very fast just how good your models really are, and I've gained a lot of respect for those who do it and do it well since I've started doing this.

As in the medical profession, we need an interface between theory and practice - in economics the gulf has been too wide for too long - and I think blogs are one way the profession has started to close the gap between the theoretical community and policymakers. Practitioners have a lot to learn from the theoretical research in medicine and in economics, but there also has to be a feedback in the other direction where the practitioners can say, "this treatement doesn't work, has the following flaws, etc., and it would work better if..." so that the theorists can provide better tools for polcymakers and other practitioners. The Fed and other policymaers have always had to do this - make policy decisions in real-time - but the process wasn't very visible. With blogs, it's starting to come out into the open, e.g. look what Krugman did on his as policies to abate the financial crisis were proposed, and I think that's a very healthy development.

"But Have We Learned Enough?"

Greg Mankiw would like to say we know enough to guarantee we won't repeat the mistakes that the led to the Great Depression, but he can't rule out the possibility that it will happen again:

But Have We Learned Enough?, by N. Gregory Mankiw, Economic View, NY Times: ...[W]hen Olivier Blanchard, the I.M.F.’s chief economist, was asked about the possibility of the world sinking into another Great Depression, he reassuringly replied that the chance was “nearly nil.” He added, “We’ve learned a few things in 80 years.”

Yes, we have. But ... have we learned enough to avoid doing the same thing again? ...

Perhaps the most troubling study of the 1930s economy was written in 1988 by the economists Kathryn Dominguez, Ray Fair and Matthew Shapiro; it was called “Forecasting the Depression: Harvard Versus Yale.” ...

The three researchers show that the leading economists at the time, at competing forecasting services run by Harvard and Yale, were caught completely by surprise by the severity and length of the Great Depression. What’s worse, despite many advances in the tools of economic analysis, modern economists armed with the data from the time would not have forecast much better. In other words, even if another Depression were around the corner, you shouldn’t expect much advance warning from the economics profession.

Let me be clear: Like Mr. Blanchard at the I.M.F., I am not predicting another Great Depression. We have indeed learned a lot over the last 80 years. But you should take that economic forecast, like all others, with more than a single grain of salt.

Heuristic Optimization

How to overcome numerical optimization problems such as the presence of discontinuities and getting stuck at local optima:

Heuristic optimisation in economics and econometrics, by Manfred Gilli and Peter Winker, Vox EU: Economics has a long tradition of relying on quantitative models for both presenting its theory and testing it empirically. In fact, Joseph Schumpeter, in the first edition of Econometrica in 1933, described economics as the most quantitative of all sciences. Optimisation is an inherent part of this methodology. In theoretical models, agents are presented as utility maximisers and firms try to maximise profit or to minimise cost. Selecting and estimating models for given data sets amounts to optimisation as well – sums of squares are minimised and likelihoods are maximised so routinely today that often researchers may not even be aware that fitting a model means optimising it.

When building models, economists are often limited by the fact that the model later needs to be solved, ideally in a closed-form. Some researchers have abandoned relying on “representative agents” and opted for more complex models, relying on computer simulations to obtain results. Such agent-based models, if they are to be a viable alternative to more standard approaches, need to be “tuned” such that the results from these models coincide with empirical facts. This, again, is an estimation – and hence optimisation – problem. In this column, we will primarily discuss estimation problems in econometrics, but the problem is much more general and applies to many areas in economics (see Winker (2001), chapter 2).

More formally, optimisation problems in estimation and modelling are typically expressed as  max f(x) where f may be a likelihood function and x the model’s parameters (of course numerically, max f(x) is the same as min -f(x)). Interestingly, the problem max f(x) is often considered synonymous with the solution x^opt, which tacitly assumes that a solution exists and is unique. As McCullough and Vinod (1999, p. 635) state, “Many textbooks convey the impression that all one has to do is use a computer to solve the problem, the implicit and unwarranted assumptions being that the computer’s solution is accurate and that one software package is as good as any other”. Goffe et al. (1994) were amongst the first to recognise that many optimisation problems in econometrics cannot be solved with standard methods because of the existence of multiple optima and discontinuities. These are not pathological examples. These problems even occur for widely used models such as generalised autoregressive conditional heteroscedasticity (GARCH) regressions (see Doornik and Ooms, 2008)). Another example comes from robust (‘resistant’) regression. Figure 1 shows the objective function for estimating a linear regression by minimising the Least Median of Squares (LMS), instead of the Least (Mean of) Squares. The function has many local optima and does not look very smooth.

Figure 1. Least median of squares objective function

These two examples illustrate different problems in optimisation. The GARCH model shows that even widely applied models are not necessarily easy to estimate, and researchers are sometimes not even aware of the computational difficulties. The LMS model serves as an example where possibly superior models are not used because they seem difficult to estimate.

Arrow: Crisis a Challenge to Standard Economic Theory

Kenneth Arrow:

Risky business, by Kenneth Arrow: The current financial crisis ... presents ... a challenge to standard economic theory, a challenge all the more important since the development of policies to prevent future financial crises will depend on a deeper understanding of the processes at work.

That economic decisions are made without certain knowledge of the consequences is pretty self-evident. But, although many economists were aware of this elementary fact, there was no systematic analysis of economic uncertainty until about 1950. There have been two developments in the economic theory of uncertainty in the last 60 years, which have had opposite implications for the radical changes in the financial system. One has made explicit and understandable a long tradition that spreading risks among many bearers improves the functioning of the economy. The second is that there are large differences of information among market participants and that these differences are not well handled by market forces. The first point of view tends to argue for the expansion of markets, the second for recognising that they may fail to exist and, if they do come into being, may fail to work for the benefit of the general economic situation.

The value of spreading risks has, of course, been recognized as the basis of conventional insurance as well as the issue of company shares that spread corporate risks widely. The central element of standard economic analysis since the 1870s has been the concept of general economic equilibrium, which, under competitive conditions, leads to an optimal allocation of resources. In the 1950s, it was shown how to incorporate uncertainty into general equilibrium, which suggests, at least, that increasing the number and coverage of risk-bearing instruments would improve the running of the economy. Not only would risks be more efficiently borne, but, more importantly, additional socially valuable risky enterprises would be undertaken. Research showed how derivative securities should be priced, how individuals should choose portfolios to minimise their variability, and how individual contracts, such as mortgages, could be bundled so as to distribute the risks for different parts of the market with different risk tolerances.

The second strand of analysis was a growing recognition of the importance of information in governing reactions to uncertainties. If individuals in the market have different degrees of information, the ability to create securities or engage in other forms of contracts becomes limited; the less informed understand that the more informed will take advantage and react accordingly. This situation was long recognized by insurance companies under such terms as, "moral hazard" ... and "adverse selection"... Economists began to realise that "asymmetric" information was the key to understanding the limits of health insurance and the incentive problems of socialism and then that these concepts found their most important application in financial markets, precisely in the complex securities that the first strand of analysis had called for.

There is obviously much more to the full understanding of the current financial crisis, but the root is this conflict between the genuine social value of increased variety and spread of risk-bearing securities and the limits imposed by the growing difficulty of understanding the underlying risks imposed by growing complexity.

Arrow has the credentials to speak on these issues, that's for sure. Simply recognizing the market failures that are present in these markets due to asymmetric information and other problems is a first step to taking corrective action. For too long it was assumed that these markets would self-correct for any problems due to information asymmetries, agency problems, excessive market concentration and power, etc., but we know that that is not always the case. When these problems are large and persistent, regulatory intervention to correct the market failures can improve how these markets function.  As Arrow notes, "increasing the number and coverage of risk-bearing instruments would improve the running of the economy," but only if these markets are working properly.

"Fundamentalists versus Realists"

Paul Romer says some fundamentalists need to get real:

Fundamentalists versus Realists, by Paul Romer: Debate among economists about the $700 billion Paulson plan reveals a deep divide between realists and fundamentalists. ...

The formal, model-based approach of the fundamentalists has contributed much to progress in economic analysis. At key junctures, it has also made important contributions to policy. The challenge is to maintain an intellectual environment that leaves space for ... realists as well. In complicated policy contexts where models don't yet capture key forces, the realists have much to offer...

The key difference lies in the relative weight each side gives to formal models as opposed to judgment.

Fundamentalists have an unswerving faith in models. Policies should always be derived from the best available model. Data should be filtered through a model. If an observation does not fit within the context of a model, it should be excluded from consideration. Realists are more conscious of the limits of models and more comfortable with a division of labor between the researcher who improves the models and the clinician who makes policy decisions. They recognize that the power of models comes precisely from a commitment to abstraction that filters out potentially important complexity. They believe that useful evidence can accumulate with direct experience as well as through the research process of testing and refining models. They believe that researchers should consider the possibility that the fault lies with the model when its predictions diverge from clinical judgment and that policies should draw on both sources of evidence.

Many times, the confidence fundamentalists have had in abstract models turned out to be well founded and the objections raised by realists who were more focused on details were misplaced. The fundamentalists were right that an airline industry could still function even if airlines could set their own fares; that people could still talk to each other even if they purchased phone service from different companies. The realists pointed to all the complicated details that arise in such markets, details that simple models could not capture. Fundamentalists, correctly, ignored the detail and pushed prescriptions based on the textbook model of competition.

Other times, the models are missing something that is too important. In the study of macroeconomic fluctuations, real business cycle theorists and their descendants, the dynamic stochastic general equilibrium modelers, are the quintessential fundamentalists. Their models are a useful way to make research progress, but in macroeconomic policy making, the great depression, which these models cannot explain, is a decisive data point warning us that the models are incomplete and have to be supplemented by clinical judgment.

In the current crisis, the astonishing and unexpected consequences of the Lehman Brothers bankruptcy should serve as a similarly decisive data point. On the Thursday and Friday before Lehman filed for protection, I was at a conference on the financial crisis. Everyone there expected them to file on Monday. We repeated for each other all the fundamentalist arguments: "Everyone had been given time to prepare." "The courts handle bankruptcies all the time." None of us expected that putting Lehman through a court managed bankruptcy would be much different from arranging a forced sale of Bear Stearns. We were all wrong. Within days, AIG was insolvent. Runs were developing on Goldman Sachs, Morgan Stanley, and the entire money market fund industry. Banks had stopped lending to each other in the Fed Fund market. Rates on Treasuries approached zero.

In response, the Treasury, Fed, and market regulators took drastic steps that the fundamentalists would surely have opposed had there been time for debate. ... Looking back, it appears that they had enough sand bags to hold back the flood and stop the panic, but perhaps just barely enough. This is not a data point that can be dismissed as an outlier. It is the kind of observation that should make the fundamentalists just a bit less confident in their models and a bit more willing to listen to the realists who are willing to defer to the policy makers on the front lines. ...

Chaoplexity and Complexitarians

On non-traditional approaches to economics:

• A Brave Army of Heretics, David Warsh, Economics Principles
• John Horgan on "Can Chaoplexology Save Economics?", by Barkley Rosser
• Can Chaoplexity Save Economics?, by John Horgan

Numbers Racket?

The argument in this piece is that over time, a series of "opportunistic" changes in the statistics describing the economy have led to a biased and overly rosy view of the health of our economic system. You can read it for yourself, there's a link to the article below along with a brief passage, but my take is a bit different.

There are answers to each of the claims in the article - none are new - but let me take a more general approach. The economists in the agencies that prepare our national economic statistics are dedicated individuals whose only goal is to make the statistics as accurate as possible. They are not political hacks willing to distort the picture of the economy to help the administration. Far from it. Their goal is to provide the most accurate statistics possible and there are always improvements they would like to see made. But due to factors such as data compatibility and the cost of redefining and recalculating a measurement, statistics are not generally adjusted until it is believed the improvement is large enough to justify the change (though sometimes the statistics can be adjusted backward or spliced together in a way that preserves data compatibility).

However, even when it is clear that the measurements could be improved, and the improvements are substantial, the political process may prevent definitional changes. When are we most likely to see desired changes implemented? At some points in time, the changes may work against the administration in power, in others the changes may be helpful, and it is unlikely that the administration in power would approve of a chance unless it was helpful.

This means that changes in the definitions of statistics will, looking back, generally appear to have been put into place to help the administration in power, i.e. it will appear that they were manipulated for political purposes since the changes almost always make the economy look better. But that's not the motivation - the reason for the change is to improve the measurements - and the politics surrounding such changes dictate that they will occur most often when the changes are politically favorable.

This does impart a bias, but it is not a bias in the measurements themselves, it is a bias in the types of improvements that can be made. All of the changes improve the measurements, they don't distort the picture of the economy they make it more accurate, at least that's the intent, but the changes do not generally occur unless they are politically favorable. (Let me acknowledge that there could be some bias toward a better than true picture if this is how it works. If the politics only allow definitional changes that make the economy look better, then there could be some changes that are known to be needed, but left undone because they would make the economy look worse. This would make the reported statistics biased toward a healthier looking economy, and this is why the agencies that measure the economy should be as free as possible from political influence, so they can adjust the measurements in either direction as needed.):

Numbers Racket: Why the economy is worse than we know, by Kevin Phillips, Harper's Magazine v.316, n.1896 1may2008: If Washington's harping on weapons of mass destruction was essential to buoy public support for the invasion of Iraq, the use of deceptive statistics has played its own vital role in convincing many Americans that the U.S. economy is stronger, fairer, more productive, more dominant, and richer with opportunity than it actually is.

The corruption has tainted the very measures that most shape public perception of the economy—the monthly Consumer Price Index (CPI), which serves as the chief bellwether of inflation; the quarterly Gross Domestic Product (GDP), which tracks the U.S. economy's overall growth; and the monthly unemployment figure, which for the general public is perhaps the most vivid indicator of economic health or infirmity. Not only do governments, businesses, and individuals use these yardsticks in their decision-making but minor revisions in the data can mean major changes in household circumstances—inflation measurements help determine interest rates, federal interest payments on the national debt, and cost-of-living increases for wages, pensions, and Social Security benefits. And, of course, our statistics have political consequences too. An administration is helped when it can mouth banalities about price levels being "anchored" as food and energy costs begin to soar.

The truth, though it would not exactly set Americans free, would at least open a window to wider economic and political understanding. Readers should ask themselves how much angrier the electorate might be if the media, over the past five years, had been citing 8 percent unemployment (instead of 5 percent), 5 percent inflation (instead of 2 percent), and average annual growth in the 1 percent range (instead of the 3–4 percent range). We might ponder as well who profits from a low-growth U.S. economy hidden under statistical camouflage. Might it be Washington politicos and affluent elites, anxious to mislead voters, coddle the financial markets, and tamp down expensive cost-of-living increases for wages and pensions?

Let me stipulate: the deception arose gradually, at no stage stemming from any concerted or cynical scheme. There was no grand conspiracy, just accumulating opportunisms. As we will see, the political blame for the slow, piecemeal distortion is bipartisan—both Democratic and Republican administrations had a hand in the abetting of political dishonesty, reckless debt, and a casino-like financial sector. To see how, we must revisit forty years of economic and statistical dissembling. ...

The U.S. Economy Ex-Distortion

The real numbers, to most economically minded Americans, would be a face full of cold water. Based on the criteria in place a quarter century ago, today's U.S. unemployment rate is somewhere between 9 percent and 12 percent; the inflation rate is as high as 7 or even 10 percent; economic growth since the recession of 2001 has been mediocre, despite a huge surge in the wealth and incomes of the superrich, and we are falling back into recession. ...

The question is which gives the more distorted picture, the old definitions from 25 or 30 years ago, or the newer definitions. I'm sticking with the newer definitions, though sometimes it doesn't matter much, e.g. take the unemployment rate figure. The figure above is simply the broadest definition that the BLS measures (U6 in Table A12), and this measure adds several percentage points to the standard measure (it's available every month - there's no secret here). But the difference is fairly constant over time so that while the number is higher, the relative picture doesn't change much in terms of when unemployment was lower or higher, i.e. when things were better or worse for labor market participants.

Or take core inflation, one of the things criticized in the article. As explained here many times, there are theoretical reasons for preferring the core measure, and some of the discussions criticizing the Fed's use of core inflation don't seem to realize that the "alpha-trimming" is symmetric, i.e. both large increases and large decreases in prices are excluded from the preferred inflation measures used for policy (that's not true of CPI les food and energy, but that's not what the Fed uses for policy). Nor do they realize that the Fed is not trying to measure the cost of living. (Just to say this once more, one use of a price index is to measure the cost of living, but another is to determine the course of monetary policy, and it turns out the best price index for the Fed to use for policy excludes highly volatile prices. The Fed is not trying to measure the cost of living, it is trying to find the best signal for the course of monetary policy - see here). The CPI less food and energy measures of prices reported in the news  aren't the best measures of "core inflation," and I'd prefer that the headline number be the symmetrically trimmed PCE figure, but the two measures aren't that far apart, generally, and making such a change would likely create as much confusion and suspicion (see above) as it would improvement in communication about economic conditions. As for how to measure prices, the old way which gives the higher inflation figure in the last paragraph (does the author really want the Fed to increase the federal funds rate that much?), or the new way, again, I prefer the new way.

"Breaking the Neoclassical Monopoly in Economics"

Thomas Palley says not to forget about heterodox economists:

Breaking the Neoclassical Monopoly in Economics, by Thomas Palley, Project Syndicate: For the last 25 years, the so-called "Washington Consensus" - comprising measures aimed at expanding the role of markets and constraining the role of the state - has dominated economic development policy. ...

Not anymore. Dani Rodrik ... is the latest to challenge the intellectual foundations of the Washington Consensus in a powerful new book titled One Economics, Many Recipes: Globalization, Institutions, and Economic Growth. Rodrik's thesis is that though there is only one economics, there are many recipes for development success.

Rodrik has rendered a major service by stating so openly the claim of "one economics." ... The ... claim of "one economics" is misguided, for it implies that mainstream neoclassical economics is the only true economics.

Part of the difficulty of exposing this narrowness is that there is a family split among neo-classical economists between those who believe that real-world market economies approximate perfect competition and those who don't. Believers are identified with the "Chicago School," whose leading exponents include Milton Friedman and George Stigler. Non-believers are identified with the "MIT School" associated with Paul Samuelson. Rodrik is of the MIT School, as are such household names as Paul Krugman, Joseph Stiglitz, and Larry Summers. This split obscures the underlying uniformity of thought.

The Chicago School claims that real-world market economies produce roughly efficient (so-called "Pareto optimal") outcomes on which public policy cannot improve. Thus, any state intervention in the economy must make someone worse off.

The MIT School, by contrast, argues that real-world economies are afflicted by pervasive market failures, including imperfect competition and monopoly, externalities associated with problems like pollution, and an inability to supply public goods such as street lighting or national defense. Consequently, policy interventions that address market failures - as well as widespread information imperfections and the non-existence of many needed markets - can make everyone better off.

None of this is about fairness, which is a separate issue. Indeed, neither the Chicago School nor the MIT School say that market outcomes are fair, because actual market outcomes depend on the initial distribution of resources. If that distribution was unfair, current and future outcomes will be unfair, too.

Chicago economists seem to believe that real-world outcomes are acceptably unfair and, more importantly, that attempts to remedy unfairness are too costly...

MIT economists tend to espouse the opposite: fairness is important, the real world is unacceptably unfair, and government failure can be prevented by good institutional design, including democracy.

These differences reflect the intellectual richness of neo-classical economics, but they provide no justification for the claim that there is one economics. On the contrary, heterodox economists like Thorsten Veblen and Joseph Schumpeter long ago raised many of today's cutting-edge issues in neoclassical economics, including the role of social norms and the relationship between technological innovation and business cycles.

Heterodox economics includes core theoretical concepts that are fundamentally incompatible with neoclassical economics in either of its two contemporary forms. These concepts result in significantly different explanations of the real world, including income distribution and the determinants of economic activity and growth. Moreover, they often result in different policy prescriptions. ...

Just as philosophers are divided on the nature of truth and understanding, economics is divided on the workings of the real world. Paradigms should co-exist in economics, just as in other social sciences. Yet, in practice, the dominance of the belief in "one economics," particularly in North America and Europe, has led increasingly to a narrow and exclusionary view of the discipline.

This reality is difficult to convey. One reason is that liberal neo-classical economists like Stiglitz and Krugman share values with heterodox economists, and shared values are easily conflated with shared analysis. Another reason is that heterodox and MIT School economists also often agree on policy, even if their reasoning is different. Finally, most people are incredulous that economists could be so audacious as to enforce one view of economics. ...

By repeating the claim of "one economics," Rodrik inadvertently reveals the censorship embedded in contemporary economics. The great challenge is not to admit that there are many recipes, but rather to create space for other perspectives on economic analysis and policy.

Economists would like to find the set of laws that will allow us to explain the great diversity of economic behavior we see in the world, and the neoclassical model is one such attempt. It is a hard model to beat. One reason the neoclassical model has survived as long as it has is because it is pliable, maybe too pliable as it is difficult to find economic behavior that can't be explained by tweaking some element of the model. Pretty much any maximizing behavior can be rationalized using some variant of the neoclassical model. But the model is not perfect and there are certainly things it cannot explain very well.

In our quest to discover the laws of economics, we propose and use many different models. Those that work best survive and their inventors become well-known within the economics community, and those models that don't work are discarded. It's an imperfect process, but the process moves us forward and, over time, our models have improved.

I think there is "one economics," a set of core economic principles that apply anywhere and everywhere and, when embedded within the existing institutions, customs, power relationships, technical knowledge, etc., these principles can explain the world we see around us. Unfortunately, however, we don't know what that "one economics" is, not for sure - we're not even close in some ways - and because of that there is room for many variations of the core neoclassical model (e.g. fixed price and wage macro models with monopolistically competitive players as an alternative to real business cycle models), and for challenges to the core model itself.

It's always hard for the new (heterodox) model to upset and eventually displace the traditional theoretical model. One reason, of course, is that there is lots of resistance from those vested in the current model and they will not let go easily. But it's not impossible and if the heterodox economists really do have a better model, they should keep sounding the horn, improving their models as much as possible so the superiority of the new model becomes more evident, and be persistent until people begin to notice and want see for themselves if the claims have any validity. If the heterodox economists are right, if they really do have a better model, then they will eventually carry the day, become entrenched as the new establishment, and be the target of a new set of heterodox economists upset that they cannot get a proper hearing for their ideas.

Faithful to Science

I haven't had much time to think about this, but posts are getting stale amid the rush of the holiday weekend, so, staying in "echo mode":

Taking Science on Faith, by Paul Davies, Commentary, NY Times: Science, we are repeatedly told, is the most reliable form of knowledge about the world because it is based on testable hypotheses. Religion, by contrast, is based on faith. ...

The problem with this neat separation into “non-overlapping magisteria,” as Stephen Jay Gould described science and religion, is that science has its own faith-based belief system. All science proceeds on the assumption that nature is ordered in a rational and intelligible way. You couldn’t be a scientist if you thought the universe was a meaningless jumble of odds and ends haphazardly juxtaposed. ...

The most refined expression of the rational intelligibility of the cosmos is found in the laws of physics, the fundamental rules on which nature runs. The laws of gravitation and electromagnetism, the laws that regulate the world within the atom, the laws of motion — all are expressed as tidy mathematical relationships. But where do these laws come from? And why do they have the form that they do?

When I was a student, the laws of physics were regarded as completely off limits. The job of the scientist, we were told, is to discover the laws and apply them, not inquire into their provenance. The laws were treated as “given” — imprinted on the universe like a maker’s mark at the moment of cosmic birth — and fixed forevermore. Therefore, to be a scientist, you had to have faith that the universe is governed by dependable, immutable, absolute, universal, mathematical laws of an unspecified origin. You’ve got to believe that these laws won’t fail, that we won’t wake up tomorrow to find heat flowing from cold to hot, or the speed of light changing by the hour.

Over the years I have often asked my physicist colleagues why the laws of physics are what they are. The answers vary... The favorite reply is, “There is no reason they are what they are — they just are.” The idea that the laws exist reasonlessly is deeply anti-rational. After all, the very essence of a scientific explanation of some phenomenon is that the world is ordered logically and that there are reasons things are as they are. ...

Although scientists have long had an inclination to shrug aside such questions concerning the source of the laws of physics, the mood has now shifted considerably. Part of the reason ... that the laws of physics have now been brought within the scope of scientific inquiry is the realization that what we long regarded as absolute and universal laws might not be truly fundamental at all, but more like local bylaws. They could vary from place to place on a mega-cosmic scale. A God’s-eye view might reveal a vast patchwork quilt of universes, each with its own distinctive set of bylaws. ...

The multiverse theory is increasingly popular, but it doesn’t so much explain the laws of physics as dodge the whole issue. There has to be a physical mechanism to make all those universes and bestow bylaws on them. This process will require its own laws, or meta-laws. Where do they come from? The problem has simply been shifted up a level from the laws of the universe to the meta-laws of the multiverse.

Clearly, then, both religion and science are founded on faith — namely, on belief in the existence of something outside the universe, like an unexplained God or an unexplained set of physical laws... For that reason, both monotheistic religion and orthodox science fail to provide a complete account of physical existence. ...

It seems to me there is no hope of ever explaining why the physical universe is as it is so long as we are fixated on immutable laws or meta-laws that exist reasonlessly or are imposed by divine providence. The alternative is to regard the laws of physics and the universe they govern as part and parcel of a unitary system, and to be incorporated together within a common explanatory scheme.

In other words, the laws should have an explanation from within the universe and not involve appealing to an external agency. The specifics of that explanation are a matter for future research. But until science comes up with a testable theory of the laws of the universe, its claim to be free of faith is manifestly bogus.

Very quick (and probably wrong) reaction: I guess I don't see why falsifiability isn't enough to distinguish science from faith. The argument - I think- is that a statement like "this object is blue," which appears falsifiable isn't since if the laws of the universe change the object may be red instead of blue tomorrow. So I have to take it on "faith" that blue will stay blue forever. Fine, but as I look at the object it's either blue or it isn't. If it changes from blue to red someday, then that is an indication that either the hypothesis itself or one of the maintained hypotheses (i.e. that the laws of physics are constant, at least locally) is false. So I don't see why the scientific method fails us in this particular instance. But as I said, I didn't give this the thought it deserves, so feel free to explain why I've totally missed the point. It wouldn't be the first time that has happened.

Frydman and Goldberg: Imperfect Knowledge Economics and Exchange Rate Dynamics

Continuing with the subject of how to model exchange rate dynamics, this is Roman Frydman and Michael Goldberg describing how their work on imperfect knowledge economics can help us to understand exchange rate movements, and how policymakers can use this knowledge to reduce deviations of exchange rates from parity:

Currency fluctuations cannot be eliminated, but they can be limited, by Roman Frydman and Michael D. Goldberg, Project Syndicate: "Dollar denial," that state of willful blindness in which bankers and central bankers claim not to be worried about America's falling currency, seems to be ending. Now even European Central Bank Governor Jean Claude Trichet has joined the chorus of concern. ... Every day seems to bring a new low against the euro.

In the face of the dollar's ongoing fall, policymakers have seemed paralyzed. The reasons for inaction are many, but it is difficult to avoid the impression that they are related to the current state of academic theorizing about exchange rates. Simply put, economists believe either that nothing should be done or that nothing can be done. Their so-called "rational expectations models" predict that exchange rates should not deviate from parity in any lasting way. Believing that..., they see no need for intervention because, save for temporary deviations, markets always get currency values right.

"Behavioral economists," by contrast, acknowledge that currencies can depart from parity for a long period. But they attribute this to market psychology and irrational trading, not to the attempts of currency traders to interpret changing macroeconomic fundamentals. This implies that intervention is not only unnecessary; it is ineffective: Faced with wide swings and trading volumes of $2 trillion per day, central banks are helpless to counteract traders' irrational zeal.

But both the "rational expectations" and the "behavioral" models are flawed, because they seek to generate exact predictions of human behavior. Both disregard the fact that rationality depends as much on individuals' imperfect understandings of history and society as on their motivation.

If we place "imperfect knowledge" at the heart of economic analysis, the implications of our limited ability to predict market outcomes becomes clear. When it comes to currency markets, parity levels based on international trade are merely one of many factors that traders consider. In attempting to cope with imperfect knowledge, they are not irrational when they pay attention to other macroeconomic fundamentals and thereby bid an exchange rate away from its parity level.

Comment on "Tests of Statistical Significance in Economics"

This comment scrolled down the sidebar fairly quickly, so many of you may have missed Deirdre McCloskey's response to your comments to the post "Tests of Statistical Significance in Economics." As you'll recall, the post highlighted comments by Andrew Gelman on a debate between McCloskey/Zilliak and Hoover/Siegler over the use of classical statistical methodology in economics. Here's the comment:

Dears,

I can't keep all your monickers straight, so let me "reply" in a general way. Ziliak and I are to get the page proofs of a book about all this in a couple of week, out in I think December: The Cult of Statistical Significance (University of Michiagn Press).

(1.) There we tell how R. A. Fisher resisted calls to make his procedures relevant to scientific hypotheses (by Neyman and Pearson, for example, or by the inventor of the t test, Gossett; or by later exponents of statistics with loss functions such as Wald). He stuck with 5% and tests of one kind of scepticism, supposing (as is very frequently not the case) that the only source of scientific error is one of inference from a sample to a population.

(2.) But the basic point, which some of you-all are not quite seeing, is that good fit is not the same thing as importance. In fact, usually it has nothing to do with importance. Yet SPSS-sciences have thoroughly confused the two. As one of you said, irrelevant reporting of standard errors (when for example the issue is not one of sampling anyway!) is used as a referee-enforced entry fee to journals, and makes no contribution to the scientific oomph of the argument.

(3.) It's rather important to understand (see the book or any of the articles we wrote) that we are making a very old and elementary point. So it just won't do to say, "Wow, this is crazy. Who are these people anyway?" We're merely reporting on scores of the leading minds on statistics from the beginning who make the same point. See for example Bill Kruskal's devastating article on "significance" in The old Encyclopedia of Statistics. It's not our point. It's Savage's point, or Freedman's point (Freedman, Pisani, and Purvis).

In other words, some fields---not physics and engineering and chemistry---have made a dreadful mistake, which vitiates most of their statistical work.

Sincerely,

Deirdre McCloskey

More on Significance Testing in Economics

More for the "Regression-Heads". Andrew Gelman responds to on comments on his post Significance testing in economics: McCloskey, Ziliak, Hoover, and Siegler from me, Justin Wolfers, and others. Here's his response:

More on significance testing in economics, by Andrew Gelman

Tests of Statistical Significance in Economics

This one's for the "regression-heads". Andrew Gelman comments on the McCloskey, Ziliak, Hoover, and Siegler debate over the use of tests of statistical significance in economics:

Significance testing in economics: McCloskey, Ziliak, Hoover, and Siegler, by Andrew Gelman: Scott Cunningham writes,

Today I was rereading Deirdre McCloskey and Ziliak's JEL paper on statistical significance, and then reading for the first time their detailed response to a critic who challenged their original paper. I was wondering what opinion you had about this debate. Is statistical significance and Fisher tests of significance as maligned and problematic as McCloskey and Ziliak claim? In your professional opinion, what is the proper use of seeking to scientifically prove that a result is valid and important?