The teaching of economics has recently been in the news. One reason is the activities of Manchester University undergraduates who have formed the Post-Crash Economics Society to protest the monopoly of mainstream neoclassical economics in university lecture halls. A second reason is criticism of the neoclassical reasoning in Thomas Piketty’s runaway best seller Capital in the Twenty-First Century.
This criticism and calls for including heterodox economic theory in the curriculum have prompted a defense of mainstream economics from Princeton University’s Paul Krugman and Oxford University’s Simon Wren-Lewis. Both hail from the mainstream’s liberal wing, which muddies the issue because it is easy to conflate the liberal wing with the critics. In fact, the two are significantly different and their defense of mainstream economics is pure flimflam …
The mainstream’s flimflam defense involves a two-pronged response. The first prong is an assertion that mainstream economics is already a big tent that incorporates Keynesian economics. The second prong is the oversights that led mainstream economists to miss the crisis have been fully corrected. There was no deep conceptual failure, only a myopic failure to observe the real-world rise of shadow banking …
Krugman’s freshwater – saltwater characterization is profoundly misleading regarding the intellectual state of mainstream economics. Whereas the freshwater metaphor makes sense, the saltwater metaphor does not. The true saltwater school is the now eviscerated Cambridge (UK) School of economics that was home to the likes of Joan Robinson and Nicholas Kaldor. The MIT School is better described as brackish (or even putrid) water.
Why brackish? Because it has retained the nonsense of marginal productivity distribution theory while discarding the foundations of Keynesian economics. The essence of Keynes’ economics was the liquidity preference theory of interest rates and rejection of the claim that price and nominal wage flexibility would ensure full employment. New Keynesians abandon both. They replace liquidity preference theory with loanable funds interest rate theory and they use price and nominal wage rigidity to explain cyclical unemployment.
I have long argued that the new Keynesian nomenclature is a cuckoo tactic because it captures the Keynesian label while having nothing to do with Keynes, in a manner similar to the cuckoo which lays its eggs in other birds’ nests. In my view, it is better labeled new Pigovian economics since it relies on market imperfections and frictions, which were the hallmarks of Pigou’s economic thinking. That makes for bitter irony as Pigou was Keynes’ greatly respected intellectual opponent in the 1930s and his thinking now passes under the Keynesian banner, displacing Keynes’ own ideas.
Yours truly har idag, tillsammans med några andra medlemmar i Junilistans förtroenderåd, en artikel i Aftonbladet där vi argumenterar mot att allt mer av den politiska makten flyttas över till EU-institutioner utan egentlig demokratisk förankring i de europeiska folken.
Knowing the contents of a toolbox, of course, requires statistical thinking, that is, the art of choosing a proper tool for a given problem. Instead, one single procedure that I call the “null ritual” tends to be featured in texts and practiced by researchers. Its essence can be summarized in a few lines:
The null ritual:
1. Set up a statistical null hypothesis of “no mean difference” or “zero correlation.” Don’t specify the predictions of your research hypothesis or of any alternative substantive hypotheses.
2. Use 5% as a convention for rejecting the null. If signiﬁcant, accept your research hypothesis. Report the result as p < 0.05, p < 0.01, or p < 0.001 (whichever comes next to the obtained p-value).
3. Always perform this procedure …
The routine reliance on the null ritual discourages not only statistical thinking but also theoretical thinking. One does not need to specify one’s hypothesis, nor any challenging alternative hypothesis … The sole requirement is to reject a null that is identiﬁed with “chance.” Statistical theories such as Neyman–Pearson theory and Wald’s theory, in contrast, begin with two or more statistical hypotheses.
In the absence of theory, the temptation is to look ﬁrst at the data and then see what is signiﬁcant. The physicist Richard Feynman … has taken notice of this misuse of hypothesis testing. I summarize his argument:
To report a signiﬁcant result and reject the null in favor of an alternative hypothesis is meaningless unless the alternative hypothesis has been stated before the data was obtained.
Feynman’s conjecture is again and again violated by routine signiﬁcance testing, where one looks at the data to see what is signiﬁcant. Statistical packages allow every difference, interaction, or correlation against chance to be tested. They automatically deliver ratings of “signiﬁcance” in terms of stars, double stars, and triple stars, encouraging the bad afterthe-fact habit. The general problem Feynman addressed is known as overﬁtting … Fitting per se has the same
problems as story telling after the fact, which leads to a “hindsight bias.” The true test of a model is to ﬁx its parameters on one sample, and to test it in a new sample. Then it turns out that predictions based on simple heuristics can be more accurate than routine multiple regressions … Less can be more. The routine use of linear multiple regression exempliﬁes another mindless use of statistics …
We know but often forget that the problem of inductive inference has no single solution. There is no uniformly most powerful test, that is, no method that is best for every problem. Statistical theory has provided us with a toolbox with effective instruments, which require judgment about when it is right to use them … Judgment is part of the art of statistics.
To stop the ritual, we also need more guts and nerves. We need some pounds of courage to cease playing along in this embarrassing game. This may cause friction with editors and colleagues, but it will in the end help them to enter the dawn of statistical thinking.
In his latest blog, Paul Krugman slings off at non-mainstream Economists …
Krugman trash what he accurately sees as “an upwelling of frustration on the part of heterodox economists” …
No need for change, boys and girls: mainstream economics has everything under control. We missed the crisis just because we failed to observe the shenanigans in the shadow banking system. Once we realised our observational errors, we had all the necessary tools and knew what to do. (Oh, and what the rebels said would happen didn’t anyway, so there!)
As usual, Krugman’s reasoning is neat, plausible, and wrong …
[T]he real frustration heterodox economists feel is the frustration that comes from trying to make an almost immoveable intellectual object move. In the 1960s, critics successfully exposed fundamental flaws in Neoclassical economics, as Samuelson himself admitted:
“If all this causes headaches for those nostalgic for the old-time parables of neoclassical writing, we must remind ourselves that scholars are not born to live an easy existence. We must respect, and appraise, the facts of life.”
But what happened? Nothing!
Decades later, the same childish parables are still taught in textbooks like Krugman’s that are derivatives of Samuelson’s original, with no evidence that these “old-time parables” were ever even challenged.
My take from this history was that the only real chance to cause fundamental change in economics comes during crises. But the experience of the Great Recession has shown that even that isn’t necessarily enough to dislodge the orthodoxy.
A major factor here is the existence of progressive economists on the fringe of the orthodoxy, especially mainstreamers like Krugman himself …
Krugman might rightly rail against this nonsense in print and sensibly argue for expansionary policy during a deleveraging crisis, but apart from the IS-LM model itself, the tools he uses were first developed by ultra-orthodoxers like Barro: rational expectations, “Dynamic Stochastic General Equilibrium” models, the whole kaboodle.
Had these ultra-orthodoxers been the mainstream, then the need for drastic change to the core of economics would have been obvious. But instead, the far more reasonable Krugman is the public face of orthodox economics. He still uses the orthodox core, but is skilled at adding kinks — imperfect competition, “frictions” that slow down the march to equilibrium, and so on — to better match real world data. The impact is that once the crisis passes, the core of economics survives the crisis, with a few added kinks.
The Conservative belief that there is some law of nature which prevents men from being employed, that it is “rash” to employ men, and that it is financially ‘sound’ to maintain a tenth of the population in idleness for an indefinite period, is crazily improbable – the sort of thing which no man could believe who had not had his head fuddled with nonsense for years and years… Our main task, therefore, will be to confirm the reader’s instinct that what seems sensible is sensible, and what seems nonsense is nonsense. We shall try to show him that the conclusion, that if new forms of employment are offered more men will be employed, is as obvious as it sounds and contains no hidden snags; that to set unemployed men to work on useful tasks does what it appears to do, namely, increases the national wealth; and that the notion, that we shall, for intricate reasons, ruin ourselves financially if we use this means to increase our well-being, is what it looks like – a bogy.
J. M. Keynes (1929)
The Neoclassical Production Function (NPF) makes sense in a simple context. Suppose you are an entrepreneur with a fruit orchard. You can pay to have fruit trees planted. That is your capital. After a while the fruit trees mature, and you hire workers to pick and sell the fruit. That is your labor. The function Y = f(K,L), which says that output is a function of capital and labor, is a reasonable model that can help to predict your decisions and the share of income that goes to your workers.
Economists from Ricardo to Piketty have wanted to describe the relationship between economic growth and income distribution in terms of simple laws. For the past fifty years or so, the NPF has been the go-to tool for economists trying to do this. Mathematically, it is very elegant for that purpose.
But thinking of the economy in terms of an aggregate NPF has many problems, including the following:
1. Capital aggregation. There is a huge, huge literature on this (see “Cambridge capital controversies”). The result was that the economists who claimed that you cannot construct a meaningful aggregate out of different types of capital equipment won the theoretical battle but lost the practical war. That is, those who use capital aggregation admit that it is bogus, but they go ahead and do it anyway. It’s a matter of “I need the eggs” …
4. Capital proliferation. Over the past fifty years, economists have conceptualized many types of capital. We now have human capital, social capital, organizational capital, institutional capital, environmental capital, network capital, consumer capital, cultural capital, knowledge capital, innovation capital, and so on … But these multiple forms of capital mess with the simple NPF and with the correspondence between theoretical concepts and real world data …
So, should we use the NPF to guide economic policy to try to achieve the best balance among growth and the distribution of income? Some possibilities:
(1) The criticisms of the aggregate NPF are not important, so that policy conclusions are still sound.
(2) Some of the criticisms are devastating, but we need some tool to guide policy, and until something better comes along our best choice is the aggregate NPF.
(3) Some criticisms are devastating, and as a result we should be very cautious and humble about making policy pronouncements based on our understanding of the NPF.
To me, (3) makes the most sense. But that is not a popular position at the moment.
If you have an apple and I have an apple and we exchange these apples then you and I will each have one apple.
But if you have an idea and I have an idea and we exchange these ideas, then each of us will have two ideas.
George Bernard Shaw