Re-reading the Lucas & Sargent manifesto

5 August, 2015 at 13:42 | Posted in Economics | 12 Comments

wrongwayRe-reading the Lucas & Sargent New Classical manifesto ‘After Keynesian Economics’ (1979) some macroeconomists seem to be überimpressed by its “quality” and “persuasiveness.”

Quality and persuasiveness?

Hmm …

Let’s listen to what James Tobin had to say on the Lucas & Sargent kind of macroeconomic analysis:

They try to explain business cycles solely as problems of information, such as asymmetries and imperfections in the information agents have. Those assumptions are just as arbitrary as the institutional rigidities and inertia they fins objectionable in other theories of business fluctuations … I try to point out how incapable the new equilibrium business cycles models are of explaining the most obvious observed facts of cyclical fluctuations … I don’t think that models so far from realistic description should be taken seriously as a guide to policy … I don’t think that there is a way to write down any model which at one hand respects the possible diversity of agents in taste, circumstances, and so on, and at the other hand also grounds behavior rigorously in utility maximization and which has any substantive content to it.

Or listen to what Willem Buiter has to say about the kind of macroeconomics that Lucas & Sargent inaugurated:

The Monetary Policy Committee of the Bank of England I was privileged to be a ‘founder’ external member of during the years 1997-2000 contained, like its successor vintages of external and executive members, 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, the typical graduate macroeconomics and monetary economics training received at Anglo-American universities during the past 30 years or so, 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 aesthetic 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.

Contrary to what some überimpressed macroeconomists seem to argue, I would say the recent economic crisis and the fact that Chicago economics has had next to nothing to contribute in understanding it, shows that New Classical economics — in Lakatosian terms — is a degenerative research program in dire need of replacement.

Neoclassical economic theory today is in the story-telling business whereby economic theorists create make-believe analogue models of the target system – usually conceived as the real economic system. This modeling activity is considered useful and essential. Since fully-fledged experiments on a societal scale as a rule are prohibitively expensive, ethically indefensible or unmanageable, economic theorists have to substitute experimenting with something else. To understand and explain relations between different entities in the real economy the predominant strategy is to build models and make things happen in these “analogue-economy models” rather than engineering things happening in real economies.

In business cycles theory these models are constructed with the purpose of showing that changes in the supply of money “have the capacity to induce depressions or booms” [Lucas 1988:3] not just in these models, but also in real economies. To do so economists are supposed to imagine subjecting their models to some kind of “operational experiment” and “a variety of reactions”. “In general, I believe that one who claims to understand the principles of flight can reasonably be expected to be able to make a flying machine, and that understanding business cycles means the ability to make them too, in roughly the same sense” [Lucas 1981:8]. To Lucas models are the laboratories of economic theories, and after having made a simulacrum-depression Lucas hopes we find it “convincing on its own terms – that what I said would happen in the [model] as a result of my manipulation would in fact happen” [Lucas 1988:4]. The clarity with which the effects are seen is considered “the key advantage of operating in simplified, fictional worlds” [Lucas 1988:5].

On the flipside lies the fact that “we are not really interested in understanding and preventing depressions in hypothetical [models]. We are interested in our own, vastly more complicated society” [Lucas 1988:5]. But how do we bridge the gulf between model and “target system”? According to Lucas we have to be willing to “argue by analogy from what we know about one situation to what we would like to know about another, quite different situation” [Lucas 1988:5]. Progress lies in the pursuit of the ambition to “tell better and better stories” [Lucas 1988:5], simply because that is what economists do.

We are storytellers, operating much of the time in worlds of make believe. We do not find that the realm of imagination and ideas is an alternative to, or retreat from, practical reality. On the contrary, it is the only way we have found to think seriously about reality. In a way, there is nothing more to this method than maintaining the conviction … that imagination and ideas matter … there is no practical alternative” [Lucas 1988:6].

Lucas has applied this mode of theorizing by constructing “make-believe economic systems” to the age-old question of what causes and constitutes business cycles. According to Lucas the standard for what that means is that one “exhibits understanding of business cycles by constructing a model in the most literal sense: a fully articulated artificial economy, which behaves through time so as to imitate closely the time series behavior of actual economies” [Lucas 1981:219].

To Lucas business cycles is an inherently systemic phenomenon basically characterized by conditional co-variations of different time series. The vision is “the possibility of a unified explanation of business cycles, grounded in the general laws governing market economies, rather than in political or institutional characteristics specific to particular countries or periods” [Lucas 1981:218]. To be able to sustain this view and adopt his “equilibrium approach” he has to define the object of study in a very constrained way. Lucas asserts, e.g., that if one wants to get numerical answers “one needs an explicit, equilibrium account of the business cycles” [Lucas 1981:222]. But his arguments for why it necessarily has to be an equilibrium is not very convincing. The main restriction is that Lucas only deals with purportedly invariable regularities “common to all decentralized market economies” [Lucas 1981:218]. Adopting this definition he can treat business cycles as all alike “with respect to the qualitative behavior of the co-movements among series” [1981:218]. As noted by Hoover [1988:187]:

Lucas’s point is not that all estimated macroeconomic relations are necessarily not invariant. It is rather that, in order to obtain an invariant relation, one must derive the functional form to be estimated from the underlying choices of individual agents. Lucas supposes that this means that one must derive aggregate relations from individual optimization problems taking only tastes and technology as given.

Postulating invariance paves the way for treating various economic entities as stationary stochastic processes (a standard assumption in most modern probabilistic econometric approaches) and the possible application of “economic equilibrium theory.” The result is that Lucas business cycle is a rather watered-down version of what is usually connoted when speaking of business cycles.

Based on the postulates of “self-interest” and “market clearing” Lucas has repeatedly stated that a pure equilibrium method is a necessary intelligibility condition and that disequilibria are somehow “arbitrary” and “unintelligible” [Lucas 1981:225]. Although this might (arguably) be requirements put on models, these requirements are irrelevant and totally without justification vis-à-vis the real world target system. Why should involuntary unemployment, for example, be considered an unintelligible disequilibrium concept? Given the lack of success of these models when empirically applied, what is unintelligible, is rather to pursue in this reinterpretation of the ups and downs in business cycles and labour markets as equilibria. To Keynes involuntary unemployment is not equatable to actors on the labour market becoming irrational non-optimizers. It is basically a reduction in the range of working-options open to workers, regardless of any volitional optimality choices made on their part. Involuntary unemployment is excess supply of labour. That unemployed in Lucas business cycles models only can be conceived of as having chosen leisure over work is not a substantive argument about real world unemployment.

The point at issue [is] whether the concept of involuntary unemployment actually delineates circumstances of economic importance … If the worker’s reservation wage is higher than all offer wages, then he is unemployed. This is his preference given his options. For the new classicals, the unemployed have placed and lost a bet. It is sad perhaps, but optimal [Hoover 1988:59].

Sometimes workers are not employed. That is a real phenomenon and not a “theoretical construct … the task of modern theoretical economics to ‘explain’” [Lucas 1981:243].

All economic theories have to somehow deal with the daunting question of uncertainty and risk. It is “absolutely crucial for understanding business cycles” [Lucas 1981:223]. To be able to practice economics at all, “we need some way … of understanding which decision problem agents are solving” [Lucas 1981:223]. Lucas – in search of a “technical model-building principle” [Lucas 1981:1] – adapts the rational expectations view, according to which agents’ subjective probabilities are identified “with observed frequencies of the events to be forecast” are coincident with “true” probabilities. This hypothesis [Lucas 1981:224]

will most likely be useful in situations in which the probabilities of interest concern a fairly well defined recurrent event, situations of ‘risk’ [where] behavior may be explainable in terms of economic theory … In cases of uncertainty, economic reasoning will be of no value … Insofar as business cycles can be viewed as repeated instances of essentially similar events, it will be reasonable to treat agents as reacting to cyclical changes as ‘risk’, or to assume their expectations are rational, that they have fairly stable arrangements for collecting and processing information, and that they utilize this information in forecasting the future in a stable way, free of systemic and easily correctable biases.

To me this seems much like putting the cart before the horse. Instead of adapting the model to the object – which from both ontological and epistemological considerations seem the natural thing to do – Lucas proceeds in the opposite way and chooses to define his object and construct a model solely to suit own methodological and theoretical preferences. All those – interesting and important – features of business cycles that have anything to do with model-theoretical openness, and a fortiori not possible to squeeze into the closure of the model, are excluded. One might rightly ask what is left of that we in a common sense meaning refer to as business cycles. Einstein’s dictum – “everything should be made as simple as possible but not simpler” falls to mind. Lucas – and neoclassical economics at large – does not heed the implied apt warning.

The development of macro-econometrics has according to Lucas supplied economists with “detailed, quantitatively accurate replicas of the actual economy” thereby enabling us to treat policy recommendations “as though they had been experimentally tested” [Lucas 1981:220]. But if the goal of theory is to be able to make accurate forecasts this “ability of a model to imitate actual behavior” does not give much leverage. What is required is “invariance of the structure of the model under policy variations”. Parametric invariance in an economic model cannot be taken for granted, “but it seems reasonable to hope that neither tastes nor technology vary systematically” [Lucas 1981:220].

The model should enable us to posit contrafactual questions about what would happen if some variable was to change in a specific way. Hence the assumption of structural invariance, that purportedly enables the theoretical economist to do just that. But does it? Lucas appeals to “reasonable hope”, a rather weak justification for a modeler to apply such a far-reaching assumption. To warrant it one would expect an argumentation that this assumption – whether we conceive of it as part of a strategy of “isolation”, “idealization” or “successive approximation” – really establishes a useful relation that we can export or bridge to the target system, the “actual economy.” That argumentation is neither in Lucas, nor – to my knowledge – in the succeeding neoclassical refinements of his “necessarily artificial, abstract, patently ‘unreal’” analogue economies [Lucas 1981:271]. At most we get what Lucas himself calls “inappropriately maligned” casual empiricism in the form of “the method of keeping one’s eyes open.” That is far from sufficient to warrant any credibility in a model pretending to explain the complex and difficult recurrent phenomena we call business cycles. To provide an empirical “illustration” or a “story” to back up your model do not suffice. There are simply too many competing illustrations and stories that could be exhibited or told.

As Lucas has to admit – complaining about the less than ideal contact between theoretical economics and econometrics – even though the “stories” are (purportedly) getting better and better, “the necessary interaction between theory and fact tends not to take place” [Lucas 1981:11].

The basic assumption of this “precise and rigorous” model therefore cannot be considered anything else than an unsubstantiated conjecture as long as it is not supported by evidence from outside the theory or model. To my knowledge no in any way decisive empirical evidence have been presented. This is the more tantalizing since Lucas himself stresses that the presumption “seems a sound one to me, but it must be defended on empirical, not logical grounds” [Lucas 1981:12].

And applying a “Lucas critique” on Lucas own model, it is obvious that it too fails. Changing “policy rules” cannot just be presumed not to influence investment and consumption behavior and a fortiori technology, thereby contradicting the invariance assumption. Technology and tastes cannot live up to the status of an economy’s deep and structurally stable Holy Grail. They too are part and parcel of an ever-changing and open economy. Lucas hope of being able to model the economy as “a FORTRAN program” and “gain some confidence that the component parts of the program are in some sense reliable prior to running it” [Lucas 1981:288] therefore seems – from an ontological point of view – totally misdirected. The failure in the attempt to anchor the analysis in the alleged stable deep parameters “tastes” and “technology” shows that if you neglect ontological considerations pertaining to the target system, ultimately reality kicks back when at last questions of bridging and exportation of model exercises are laid on the table. No matter how precise and rigorous the analysis is, and no matter how hard one tries to cast the argument in “modern mathematical form” [Lucas 1981:7] they do not push science forwards one millimeter if they do not stand the acid test of relevance to the target. No matter how clear, precise, rigorous or certain the inferences delivered inside these models are, they do not per se say anything about external validity.

Neoclassical economics has since long given up on the real world and contents itself with proving things about thought up worlds. Empirical evidence only plays a minor role in economic theory, where models largely function as a substitute for empirical evidence. Hopefully humbled by the manifest failure of its theoretical pretences, the one-sided, almost religious, insistence on mathematical-deductivist modeling as the only scientific activity worthy of pursuing in economics will give way to methodological pluralism based on ontological considerations rather than formalistic tractability.


Hoover, Kevin (1988), The New Classical Macroeconomics. Oxford: Basil Blackwell.

– (2002), Econometrics and reality. In U. Mäki (ed.), Fact and fiction in economics (pp. 152-177). Cambridge: Cambridge University Press.

– (2008), “Idealizing Reduction: The Microfoundations of Macroeconomics. Manuscript, 27 May 2008.

Lucas, Robert (1981), Studies in Business-Cycle Theory. Oxford: Basil Blackwell.

– (1986), Adaptive Behavior and Economic Theory. In Hogarth, Robin & Reder, Melvin (eds) Rational Choice (pp. 217-242). Chicago: The University of Chicago Press.

– (1988), What Economists Do.

Syll, Lars (2015), On the use and misuse of theories and models in economics.



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  1. “Lucas hope of being able to model the economy as “a FORTRAN program”

    Funnily enough a programming language that lacks structure and modelling tools for dealing with the real world.

    Which why it isn’t much used any more.

  2. I have read somewhere that Lucas himself admitted he did not understand Keynes’ GT. (It may have been in this paper, ‘After Keynesian Economics’, appalling as it is for its “attitude”, I’m not certain.) I have a pet theory which says that because many of the main proponents of the REH were not trained in economics early on in their academic careers and came from engineering/science backgrounds, they would naturally be drawn to microeconomic theory. Micro theory, which is essentially classical theory (and its various brands), has a clear set of structured axioms and assumptions which lend themselves to abstraction and mathematization – the fundamental building blocks are, in essence, very simple models. Whereas Keynesian theory, as it developed, was a complex, convoluted, contradictory (in its various shades and colours) competing corpus of concepts and notions. It’s no surprise that the micro foundations of macro developed as it has given the backgrounds of many people taking on economics. Given all this, it is also no surprise that the insights and subtleties of Keynes have been trammeled upon.

    • “I have a pet theory which says that because many of the main proponents of the REH were not trained in economics early on in their academic careers and came from engineering/science backgrounds, they would naturally be drawn to microeconomic theory. ….. Micro theory, which is essentially classical theory (and its various brands), has a clear set of structured axioms and assumptions which lend themselves to abstraction and mathematization – the fundamental building blocks are…”

      Many people might agree with you coming from the background of studying geometry but not the optional courses physics and chemistry.

      My opinion from a technical background we might see structured axioms and assumptions as a weakness of the field if they are contradicted by the real world.

      In the US only two years of math and science are required. Every one has to take algebra and geometry.

      Geometry could appears more as rule following than experimental.

      But, geometry is easiest to understand by doing, experiment. The great success of geometry is it always works. Geometric axioms are based on fact or experiment if you will. And never ever fail! It isn’t the axiom that is important. If they ever failed the axiom would be wrong and gone.

      Students who prepared for engineering school or to study science added two experimental and quantitative science classes, physics and chemistry. They are based on real world observations and experiments of nature. Never made up ideas. Nature can always win over theory and ideas.

      If axioms applied to any thing like economics and are held higher than experimental results and observation it should be ridiculous to them. But, they could make that mistake for a little while. In fact in my micro class there was no observations or experiment.

      I never saw an axiom in engineering, science, or accounting.

      It appears that some economists have attempted to passed off assumptions as axioms.

      Science and engineering is not axiom based. They are fundamentally based on nature.

    • What I think Lucas said (and Lars can correct this) was that there were substantial aspects of the GT which over his career he was unable to improve on. Lucas was in many ways the more circumspect of the New Classicists. He would be rare among the big names in recent macro-economics in that he actually read the GT. I also I understand he was an historian by training, and learned the maths while studying economics.

      Sargent, Fama and Prescott are by far the more gung-ho of the group.

  3. “It appears that some economists have attempted to passed off assumptions as axioms.”

    I would agree my use of the word axiom may not be strictly kosher in this case. I was meaning to say more what you have said in the quote from your post directly above.

    “Never made up ideas.”

    I would think science is replete with made up ideas – which ultimately, as you say, have to be tested against our observations of nature.

    And just in case you might think I am prejudiced against science/engineering types, I was a physics/chemistry/maths student at secondary school level heading for engineering until one day….. As an undergraduate, micro came more easily to me than macro so perhaps I am just projecting my experience on to others .

  4. “What I think Lucas said (and Lars can correct this) was that there were substantial aspects of the GT which over his career he was unable to improve on.”

    I’ll have to find the reference.

    ” I also I understand he was an historian by training, and learned the maths while studying economics.”

    He studied science/maths in high school and intended to study engineering, but, as you say, studied history as an undergrad.

  5. At a Council on Foreign Relations Symposium in 2009, Lucas gave a post luncheon talk followed by a question and answer session. In response to a question he said…..”Schumpeter and Keynes are two economists I’ve always had trouble understanding.”

    See (first question):

  6. “…..thereby contradicting the invariance assumption……”

    Lucas himself contradicted the policy invariance corollary of his early papers. In an WSJ interview, he supported the Fed’s pumping of money into the economy and the administration’s stimulus package post the 2008 slump. Perhaps we are all Keynsians now?

  7. An engineer, a physicist and an economist are stranded on a deserted island
    with nothing to eat. A crate containing many cans of soup washes ashore and
    the three ponder how to open the cans.
    Engineer: Let’s climb that tree and drop the cans on the rocks.
    Physicist: Let’s heat each can over our campfire until the increase in internal
    pressure causes it to open.
    Economist: Let’s assume we have a can opener.

    • Thanks Henry. If I find the reference Lucas made referring to his work and the General Theory – I will post it on here. I have seen it come up a few times on various blogs.

  8. This is why companies whose boards have gender diversity do better than 100% male run firms.
    A billion math nerds all share the same blind spots. Add a billion more to the freshwater or the saltwater, they keep criticizing each other’s math.
    Math isn’t economic’s problem. Math nerds are the problem.

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