One of the main ideas underlining the book is that “being an economist” in the XXI century requires a radical change in the training of economists and such change requires a global effort. A new economics curriculum is needed in order to improve the understanding of the deep interactions between economics and the political forces and the historical processes of social change. The need for trans-disciplinary and interdisciplinary work is highlighted.
Discussions include the following. Main critiques of current practices on theory, methods and structures. Current gaps in the economics curriculum. What should economics graduates know? The contributors are: Nicola Acocella, Sheila Dow, David Hemenway, Arturo Hermann, Grazia Ietto-Gillies, Maria Alejandra Madi, Lars Pålsson Syll, Constantine Passaris, Paul Ormerod, Jack Reardon, Alessando Roncaglia, Asad Zaman.
Yours truly’s contribution to the collection is on “Economics textbooks – anomalies and transmogrification of truth.”
Balliol Croft, Cambridge
27. ii. 06
My dear Bowley,
I have not been able to lay my hands on any notes as to Mathematico-economics that would be of any use to you: and I have very indistinct memories of what I used to think on the subject. I never read mathematics now: in fact I have forgotten even how to integrate a good many things.
But I know I had a growing feeling in the later years of my work at the subject that a good mathematical theorem dealing with economic hypotheses was very unlikely to be good economics: and I went more and more on the rules — (1) Use mathematics as a short-hand language, rather than as an engine of inquiry. (2) Keep to them till you have done. (3) Translate into English. (4) Then illustrate by examples that are important in real life. (5) Burn the mathematics. (6) If you can’t succeed in 4, burn 3. This last I did often.
I believe in Newton’s Principia Methods, because they carry so much of the ordinary mind with them. Mathematics used in a Fellowship thesis by a man who is not a mathematician by nature — and I have come across a good deal of that — seems to me an unmixed evil. And I think you should do all you can to prevent people from using Mathematics in cases in which the English language is as short as the Mathematical …
I cannot offer a course in mathematics in this slim volume, but I will do what I can to hit a few of the highlights, when genuinely needed. I will issue one early warning: do not be intimidated by what you don’t completely understand. Statistical Science is not really very helpful for understanding or forecasting complex evolving self-healing organic ambiguous social systems – economies, in other words.
A statistician may have done the programming, but when you press a button on a computer keyboard and ask the computer to find some good patterns, better get clear a sad fact: computers do not think. They do exactly what the programmer told them to do and nothing more. They look for the patterns that we tell them to look for, those and nothing more. When we turn to the computer for advice, we are only talking to ourselves. This works in a simple setting in which there is a very well-defined set of alternative theories and we can provide the computer with clear instructions. But in complex nonexperimental settings, Sherlock Holmes admonishes: “Never theorize before you have all the evidence. It biases the judgments” …
Mathematical analysis works great to decide which horse wins, if we are completely confident which horses are in the race, but it breaks down when we are not sure. In experimental settings, the set of alternative models can often be well agreed on, but with nonexperimental economics data, the set of models is subject to enormous disagreements. You disagree with your model made yesterday, and I disagree with your model today. Mathematics does not help much resolve our internal intellectual disagreements.
I have lost count of the number of times I have heard students and faculty repeat the idea in seminars, that “all models are wrong”. This aphorism, attributed to George Box, is the battle cry of the Minnesota calibrator, a breed of macroeconomist, inspired by Ed Prescott, one of the most important and influential economists of the last century.
All models are wrong … all models are wrong …
Of course all models are wrong. That is trivially true: it is the definition of a model. But the cry has been used for three decades to poke fun at attempts to use serious econometric methods to analyze time series data. Time series methods were inconvenient to the nascent Real Business Cycle Program that Ed pioneered because the models that he favored were, and still are, overwhelmingly rejected by the facts. That is inconvenient.
Ed’s response was pure genius. If the model and the data are in conflict, the data must be wrong. Time series econometrics, according to Ed, was crushing the acorn before it had time to grow into a tree. His response was not only to reformulate the theory, but also to reformulate the way in which that theory was to be judged. In a puff of calibrator’s smoke, the history of time series econometrics was relegated to the dustbin of history to take its place alongside alchemy, the ether, and the theory of phlogiston.
How did Ed achieve this remarkable feat of prestidigitation? First, he argued that we should focus on a small subset of the properties of the data. Since the work of Ragnar Frisch, economists have recognized that economic time series can be modeled as linear difference equations, hit by random shocks. These time series move together in different ways at different frequencies …
After removing trends, Ed was left with the wiggles. He proposed that we should evaluate our economic theories of business cycles by how well they explain co-movements among the wiggles. When his theory failed to clear the 8ft hurdle of the Olympic high jump, he lowered the bar to 5ft and persuaded us all that leaping over this high school bar was a success.
Keynesians protested. But they did not protest loudly enough and ultimately it became common, even among serious econometricians, to filter their data with the eponymous Hodrick Prescott filter …
By accepting the neo-classical synthesis, Keynesian economists had agreed to play by real business cycle rules. They both accepted that the economy is a self-stabilizing system that, left to itself, would gravitate back to the unique natural rate of unemployment. And for this reason, the Keynesians agreed to play by Ed’s rules. They filtered the data and set the bar at the high school level …
We don’t have to play by Ed’s rules … Once we allow aggregate demand to influence permanently the unemployment rate, the data do not look kindly on either real business cycle models or on the new-Keynesian approach. It’s time to get serious about macroeconomic science and put back the Olympic bar.
Thomas Piketty’s book Capital in the Twenty-First Century has already attracted more serious attention than any economics book published in the last 75 years. This collection of 17 essays by some of the world’s most prominent economists explores Piketty’s book in depth and from various vantage points.
Yours truly’s contribution to the collection is on “Piketty and the limits of marginal productivity theory.”
Endogeneity problems are of course nothing new in growth regressions. But what is special here is that policy endogeneity is not just an econometric nuisance, but typically an integral part of the null hypothesis that is being tested. The supposition that governments are trying to achieve some economic or political objective is at the core of the theoretical framework that is subjected to empirical tests. In such a setting, treating policy as if it were exogenous or random is problematic not just from an econometric standpoint, but also conceptually …
The cross-national variation we observe in government ownership is unlikely to be random by the very logic of the theories that are tested. Under the developmental perspective, this variation will be driven by the magnitude of the financial market failures that need to be addressed and the governments’ capacity to do so effectively. Under the political motive, the variation will be generated by the degree of “honesty” or “corruption” of political leaders. I show in this paper that the cross-national association between performance and policy will have a very different interpretation depending on which of these fundamental drivers dominate. Unfortunately, none of these drivers is likely to be observable to the analyst. In such a setting the estimated coefficient on state ownership is not informative about either the positive or the normative questions at stake. It cannot help us distinguish between the develop-mental and political views, because the estimated coefficient on government ownership will be negative in both cases.
At last something worth watching for our youngsters — a website on Keynes for kids!
It is generally recognised that the Ricardian analysis was concerned with what we now call long-period equilibrium. Marshall’s contribution mainly consisted in grafting on to this the marginal principle and the principle of substitution, together with some discussion of the passage from one position of long-period equilibrium to another. But he assumed, as Ricardo did, that the amounts of the factors of production in use were given and that the problem was to determine the way in which they would be used and their relative rewards. Edgeworth and Professor Pigou and other later and contemporary writers have embroidered and improved this theory by considering how different peculiarities in the shapes of the supply functions of the factors of production would affect matters, what will happen in conditions of monopoly and imperfect competition, how far social and individual advantage coincide, what are the special problems of exchange in an open system and the like. But these more recent writers like their predecessors were still dealing with a system in which the amount of the factors employed was given and the other relevant facts were known more or less for certain. This does not mean that they were dealing with a system in which change was ruled out, or even one in which the disappointment of expectation was ruled out. But at any given time facts and expectations were assumed to be given in a definite and calculable form; and risks, of which, though admitted, not much notice was taken, were supposed to be capable of an exact actuarial computation. The calculus of probability, though mention of it was kept in the background, was supposed to be capable of reducing uncertainty to the same calculable status as that of certainty itself; just as in the Benthamite calculus of pains and pleasures or of advantage and disadvantage, by which the Benthamite philosophy assumed men to be influenced in their general ethical behaviour.
Actually, however, we have, as a rule, only the vaguest idea of any but the most direct consequences of our acts. Sometimes we are not much concerned with their remoter consequences, even though time and chance may make much of them. But sometimes we are intensely concerned with them, more so, occasionally, than with the immediate consequences. Now of all human activities which are affected by this remoter preoccupation, it happens that one of the most important is economic in character, namely, wealth. The whole object of the accumulation of wealth is to produce results, or potential results, at a comparatively distant, and sometimes indefinitely distant, date. Thus the fact that our knowledge of the future is fluctuating, vague and uncertain, renders wealth a peculiarly unsuitable subject for the methods of the classical economic theory. This theory might work very well in a world in which economic goods were necessarily consumed within a short interval of their being produced. But it requires, I suggest, considerable amendment if it is to be applied to a world in which the accumulation of wealth for an indefinitely postponed future is an important factor; and the greater the proportionate part played by such wealth accumulation the more essential does such amendment become.
By ‘uncertain’ knowledge, let me explain, I do not mean merely to distinguish what is known for certain from what is only probable. The game of roulette is not subject, in this sense, to uncertainty; nor is the prospect of a Victory bond being drawn. Or, again, the expectation of life is only slightly uncertain. Even the weather is only moderately uncertain. The sense in which I am using the term is that in which the prospect of an European war is uncertain, or the price of copper and the rate of interest twenty years hence, or the obsolescence of a new invention, or the position of private wealth-owners in the social system in 1970. About these matters their is no scientific basis on which to form any calculable probability whatever. We simply do not know.
J M Keynes “The General Theory of Employment” Quarterly Journal of Economics, February 1937.
On the theoretical side, there is a long tradition in economics arguing that acting to reduce inequality could be counterproductive. Yale University economist Arthur Okun summarized this view in his 1975 book, Equality and Efficiency: The Big Tradeoff, where he posited that income equality and economic efficiency are in tension. Inequality provides incentives for work and investment …
Okun’s view is based on the idea that monetary rewards and penalties drive productive activity, that is, if you pay people more (or, perhaps, pay them at all), they will work harder and be more productive. These rewards and penalties are optimal for growth. In this view, any intervention is distortionary and will, therefore, lower economic growth …
To be clear, Okun was not opposed to policymakers acting to reduce inequality. “The market needs a place, and the market needs to be kept in its place,” he said. Rather, he was concerned with how policymakers should act, given the economic realities of the supposed trade-off. His main concern was what he termed, “the leaky bucket,” that is, how much of redistributive policy leaks out of the system due to administrative costs, reduction in work effort, effects on saving and investment, and “socio-economic leakages” such as claims that extending unemployment benefits will reduce efforts to find a job …
While the idea that there is a trade-off between equality and efficiency as Okun put forth in 1975 may have been a widely accepted idea at the time, it is not the case that theory points entirely to this conclusion … However, strong simplifying assumptions limit the utility of the predictions from many of these theories and economists have been developing new approaches to account for a more realistic level of complexity … It is not the purpose of this paper to summarize this sub-field of economics, yet it is critical to understand that inequality may not always provide sufficient incentives for people to work harder despite the implications from some branches of theory.