How evidence is treated in macroeconomics

from Lars Syll

“New Keynesian” macroeconomist Simon Wren-Lewis has a post up on his blog, discussing how evidence is treated in modern macroeconomics (emphasis added):

It is hard to get academic macroeconomists trained since the 1980s to address this question, because they have been taught that these models and techniques are fatally flawed because of the Lucas critique and identification problems. But DSGE models as a guide for policy are also fatally flawed because they are too simple. The unique property that DSGE models have is internal consistency. Take a DSGE model, and alter a few equations so that they fit the data much better, and you have what could be called a structural econometric model. It is internally inconsistent, but because it fits the data better it may be a better guide for policy.

Being able to model a credible world, a world that somehow could be considered real or similar to the real world, is not the same as investigating the real world.

Noah Smith thinks p-values work. Read my lips — they don’t!

from Lars Syll

Noah Smith has a post up trying to defend p-values and traditional statistical significance testing against the increasing attacks launched against it:

Suddenly, everyone is getting really upset about p-values and statistical significance testing. The backlash has reached such a frenzy that some psych journals are starting to ban significance testing. Though there are some well-known problems with p-values and significance testing, this backlash doesn’t pass the smell test. When a technique has been in wide use for decades, it’s certain that LOTS of smart scientists have had a chance to think carefully about it. The fact that we’re only now getting the backlash means that the cause is something other than the inherent uselessness of the methodology.

Hmm …

That doesn’t sound very convincing.

Maybe we should apply yet another smell test … 

Some Issues Re-visited

from Peter Radford

Hmmm.

It seems that some people misunderstood my comments regarding neoclassical economics.

Allow me to reiterate and, perhaps, clarify.

I want to say that I regard neoclassical economics as a triumph. A wonderful achievement. Brilliant.

Please read the fine print: that brilliance has nothing to do with relevance, reality, or any other such yardstick.

All I am saying is that within its own confines, with regard to its own rules, and with respect to the limits placed upon it by its multitude of excellent practitioners, neoclassical economics has been an extraordinary success.

Further, and more to the point, I am saying that the number of instances of economies we find within the space of all possible economies described by neoclassical economics is tiny. So tiny we are unlikely ever to experience one.

Macroeconomic ad hocery

from Lars Syll

Robert Lucas is well-known for condemning everything that isn’t microfounded rational expectations macroeconomics as “ad hoc” theorizing. 

But instead of rather unsubstantiated recapitulations, it would be refreshing and helpful  if the Chicago übereconomist — for a change — endeavoured to clarify just what he means by “ad hoc.”

The standard meaning — OED — of the term is “for this particular purpose.” But in the hands of New Classical–Real Business Cycles–New Keynesians it seems to be used more to convey the view that modeling with realist and relevant assumptions is somehow equivalent to basing models on “specifics” rather than the “fundamentals” of individual intertemporal optimization and rational expectations.

Some Issues

from Peter Radford

First:

I have finally arrived at the point where I can give orthodox simple economics its due. It is a triumph. A system of thought well conceived, brilliantly executed, coherent, consistent, and pretty much complete. Bravo. I love it.

As long as we are trying to examine economies consisting of one or two prescient households, a couple of firms of exquisite accounting excellence, one or two products that are easily substituted for one another, as long as there is no uncertainty, no relevant time, and as long as these various actors can calculate everything at warp speed, we know everything we need to know about economics. The game is over.

As I say: well done everyone.

These unbelievably simple little economies, I assume, must exist somewhere. And wherever they do we can explain them easily.

Where they don’t is another matter.

Orthodox economics is simple economics. Simple.

Second:

RBC theory — willfully silly obscurantism

from Lars Syll

Lucas and his school … went even further down the equilibrium rabbit hole, notably with real business cycle theory. And here is where the kind of willful obscurantism Romer is after became the norm. I wrote last year about the remarkable failure of RBC theorists ever to offer an intuitive explanation of how their models work, which I at least hinted was willful:

“But the RBC theorists never seem to go there; it’s right into calibration and statistical moments, with never a break for intuition. And because they never do the simple version, they don’t realize (or at any rate don’t admit to themselves) how fundamentally silly the whole thing sounds, how much it’s at odds with lived experience.”

Paul Krugman

Yours truly, of course, totally agrees with Paul on Lucas’ rabbit hole freshwater school.

And so does Truman F. Bewley:

The microfoundationalist cyborg dream

from Lars Syll 

Are macro-economists doomed to always “fight the last war”? Are they doomed to always be explaining the last problem we had, even as a completely different problem is building on the horizon? Well, maybe. But I think the hope is that microfoundations might prevent this. If you can really figure out some timeless rules that describe the behavior of consumers, firms, financial markets, governments, etc., then you might be able to predict problems before they happen. So far, that dream has not been realized. But maybe the current round of “financial friction macro” will produce something more timeless. I hope so.

Noah Smith

So there we have it! This is nothing but the age-old machine dream of neoclassical economics — an epistemologically founded cyborg dream that disregards the fundamental ontological fact that economies and societies are open — not closed — systems. If we are going to be able to show that the mechanisms or causes that we isolate and handle in our models are stable in the sense that they do not change when we “export” them to our “target systems,” they do only hold under ceteris paribus conditions and are a fortiori of limited value for understanding, explaining or predicting real economic systems. Or as the always eminently quotable Keynes wrote in Treatise on Probability(1921):

On the poverty of microfoundationalist fantasies

from Lars Syll

The microfoundationalist’s fantasy has a powerful hold on macroeconomists. They recognize that an agent-by-agent reconstruction of the economy is not feasible, but they argue that it is something that we could do “in principle,” and that the in-principle claim warrants a particular theoretical strategy. The strategy is to start with the analysis of a single agent and to build up through ever more complex analyses to a whole economy …

The implicit argument in favor of representative-agent models as empirically relevant to aggregate economic data runs something like this: a representative-agent model is not itself an acceptable representation of the whole economy … but it is a first step in a program which step by step will inevitably bring the model closer to the agent-by-agent microeconomic model of the whole economy … I call this argument eschatological justification: it is the claim that there is a plausible in-principle game plan for a reductionist program and that the conclusions of early stages of that program are epistemically warranted by the presumed, but undemonstrated, success of the future implementation of the program in the fullness of time …

Why Real Business Cycle models can’t be taken seriously

from Lars Syll

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 find 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.

James Tobin

Real Business Cycle theory basically says that economic cycles are caused by technology-induced changes in productivity. It says that employment goes up or down because people choose to work more when productivity is high and less when it’s low. This is of course nothing but pure nonsense — and how on earth those guys that promoted this theory (Thomas Sargent et consortes) could be awarded The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel is really beyond comprehension.

On rational expectations and playing games of whack-a-mole (wonkish)

The Keynes-Ramsey-Savage debate on probability

from Lars Syll

Neoclassical economics nowadays usually assumes that agents that have to make choices under conditions of uncertainty behave according to Bayesian rules, axiomatized by Ramsey (1931) and Savage (1954) – that is, they maximize expected utility with respect to some subjective probability measure that is continually updated according to Bayes theorem. If not, they are supposed to be irrational, and ultimately – via some “Dutch book” or “money pump”argument – susceptible to being ruined by some clever “bookie”.

Bayesianism reduces questions of rationality to questions of internal consistency (coherence) of beliefs, but – even granted this questionable reductionism – do rational agents really have to be Bayesian? As I have been arguing elsewhere (e. g. here, here and here) there is no strong warrant for believing so.

In many of the situations that are relevant to economics one could argue that there is simply not enough of adequate and relevant information to ground beliefs of a probabilistic kind, and that in those situations it is not really possible, in any relevant way, to represent an individual’s beliefs in a single probability measure. 

Noah Smith is wrong on the experimental turn in empirical economics

from Lars Syll

The increasing use of natural and quasi-natural experiments in economics during the last couple of decades has led Noah Smith to — on his blog Noahpinion today — triumphantly declare it as a major step on a recent path toward empirics, where instead of being a “deductive, philosophical field,” economics is now increasingly becoming  an “inductive, scientific field.”

Smith is especially apostrophizing the work of Joshua Angrist and Jörn-Steffen Pischke, so lets start with one of their later books and see if there is any real reason to share Smith’s optimism on this ’empirical turn’ in economics.

In their new book, Mastering ‘Metrics: The Path from Cause to Effect, Angrist and Pischke write:

Rational expectations — only for Gods and idiots

from Lars Syll

In a laboratory experiment  run by James Andreoni and Tymofiy Mylovanov — presented here — the researchers induced common probability priors, and then told all participants of the actions taken by the others. Their findings is very interesting, and says something rather profound on the value of the rational expectations hypothesis in standard  neoclassical economic models:

Ditch ‘ceteris paribus’!

from Lars Syll

When applying deductivist thinking to economics, neoclassical economists usually set up “as if” models based on a set of tight axiomatic assumptions from which consistent and precise inferences are made. The beauty of this procedure is of course that if the axiomatic premises are true, the conclusions necessarily follow. The snag is that if the models are to be relevant, we also have to argue that their precision and rigour still holds when they are applied to real-world situations. They often don’t. When addressing real economies, the idealizations necessary for the deductivist machinery to work — as e. g. IS-LM and DSGE models — simply don’t hold.

If the real world is fuzzy, vague and indeterminate, then why should our models build upon a desire to describe it as precise and predictable? The logic of idealization is a marvellous tool in mathematics and axiomatic-deductivist systems, but a poor guide for action in real-world systems, in which concepts and entities are without clear boundaries and continually interact and overlap.

Consistency and validity is not enough!

from Lars Syll

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.

Formalistic deductive “Glasperlenspiel” can be very impressive and seductive. But in the realm of science it ought to be considered of little or no value to simply make claims about the model and lose sight of reality. As Julian Reiss writes: 

In search of causality

from Lars Syll

One of the few statisticians that I have on my blogroll is Andrew Gelman.  Although not sharing his Bayesian leanings, yours truly finds  his open-minded, thought-provoking and non-dogmatic statistical thinking highly recommendable. The plaidoyer here below for “reverse causal questioning” is typical Gelmanian:

When statistical and econometrc methodologists write about causal inference, they generally focus on forward causal questions. We are taught to answer questions of the type “What if?”, rather than “Why?” Following the work by Rubin (1977) causal questions are typically framed in terms of manipulations: if x were changed by one unit, how much would y be expected to change? But reverse causal questions are important too … In many ways, it is the reverse causal questions that motivate the research, including experiments and observational studies, that we use to answer the forward questions … 

Validating assumptions

from Lars Syll

Piketty uses the terms “capital” and “wealth” interchangeably to denote the total monetary value of shares, housing and other assets. “Income” is measured in money terms. We shall reserve the term “capital” for the totality of productive assets evaluated at constant prices. The term “output” is used to denote the totality of net output (value-added) measured at constant prices. Piketty uses the symbol β to denote the ratio of “wealth” to “income” and he denotes the share of wealth-owners in total income by α. In his theoretical analysis this share is equated to the share of profits in total output. Piketty documents how α and β have both risen by a considerable amount in recent decades. He argues that this is not mere correlation, but reflects a causal link. It is the rise in β which is responsible for the rise in α. To reach this conclusion, he first assumes that β is equal to the capital-output ratio K/Y, as conventionally understood. From his empirical finding that β has risen, he concludes that K/Y has also risen by a similar amount. According to the neoclassical theory of factor shares, an increase in K/Y will only lead to an increase in α when the elasticity of substitution between capital and labour σ is greater than unity. Piketty asserts that this is the case. Indeed, based on movements α and β, he estimates that σ is between 1.3 and 1.6 (page 221). 

Macroeconomic ad hocery

from Lars Syll

Robert Lucas is well-known for condemning everything that isn’t microfounded rational expectations macroeconomics as “ad hoc” theorizing.

But instead of rather unsubstantiated recapitulations, it would be refreshing and helpful  if the Chicago übereconomist — for a change — endeavoured to clarify just what he means by “ad hoc.”

The standard meaning — OED — of the term is “for this particular purpose.” But in the hands of New Classical–RBC–New Keynesians it seems to be used more to convey the view that modeling with realist and relevant assumptions is somehow equivalent to basing models on “specifics” rather than the “fundamentals” of individual intertemporal optimization and rational expectations.

This is of course pure nonsense, simply because there is no — as yours truly has argued at length e. g. here — macro behaviour that consistently follows from the RBC–New Keynesian microfoundations. The only ones that succumb to ad hoc assumptions here are macroeconomists like Lucas et consortes, who believe that macroeconomic behaviour can be adequately analyzed with a fictitious rational-expectations-optimizing-robot-imitation-representative-agent.

Bayesianism — a dangerous scientific cul-de-sac

from Lars Syll

The bias toward the superficial and the response to extraneous influences on research are both examples of real harm done in contemporary social science by a roughly Bayesian paradigm of statistical inference as the epitome of empirical argument. For instance the dominant attitude toward the sources of black-white differential in United States unemployment rates (routinely the rates are in a two to one ratio) is “phenomenological.” The employment differences are traced to correlates in education, locale, occupational structure, and family background. The attitude toward further, underlying causes of those correlations is agnostic … Yet on reflection, common sense dictates that racist attitudes and institutional racism must play an important causal role. People do have beliefs that blacks are inferior in intelligence and morality, and they are surely influenced by these beliefs in hiring decisions … Thus, an overemphasis on Bayesian success in statistical inference discourages the elaboration of a type of account of racial disadavantages that almost certainly provides a large part of their explanation.

The message: from austerity to prosperity

from Asad Zaman

Modern history is largely driven by the battle of the rich (top 0.01%) against the masses (bottom 90%). Over the past few decades, the rich have been tremendously successful in having it all their way. A previous blog post on “Deception and Democracy” illustrates by examples their successful conversion of democracy into plutocracy in the USA. As pointed out by Polanyi, unregulated markets create disastrous outcomes for the majority. Therefore, in a democratic environment, theories which misrepresent facts and justify massive inequalities are essential pillars of support for the plutocrats. Spreading these theories via media and educational channels helps create an environment where people support policies which go against their common interests.