In 1969 Robert Wilson, director of the National Accelerator Laboratory, was testifying before the US Congress. He sought funding for a particle accelerator (forerunner of the Large Hadron Collider at Cern where the Higgs boson was discovered in 2012). Asked by Senator John Pastore how his project would help defeat the Russians, he responded: “It only has to do with the respect with which we regard one another . . . are we good painters, good sculptors, great poets . . . new knowledge has nothing to do directly with defending our country except to help make it worth defending.”
Thursday, February 20, 2014
Why we do things... John Kay
Not everything we do, not even most of it, is done for profit, or with other practical aims in mind. John Kay:
Friday, February 14, 2014
Mike Woodford: why we need to model expectations realistically
I just read an essay by Mike Woodford from 2012, and I thought I might pass on a few interesting observations he made. He was responding to a criticism of rational expectations based DSGE modelling made by John Kay. What he says seems to make quite a bit of sense to me, especially about the need to model how people form expectations in a realistic way, going beyond the naive assumption of rational expectations, looking to empirical evidence instead (those comments come toward the end):
"There is... an important respect in which I do believe that much model-based economic
analysis imposes a requirement of internal consistency that is unduly strong, and that may result in unnecessary fragility of the conclusions reached; and I suspect that this has a fair amount to do with the unease that Kay expresses about modern economic analysis. It has been standard for at least the past three decades to use models in which not only does the model give a complete description of a hypothetical world, and not only is this description one in which outcomes follow from rational behavior on the part of the decision-makers in the model, but the decision-makers in the model are assumed to understand the world in exactly the way it is represented in the model.
This postulate of “rational expectations,” as it is commonly though rather misleadingly known, is the crucial theoretical assumption behind such doctrines as “efficient markets” in asset pricing theory and “Ricardian equivalence” in macroeconomics. It is often presented as if it were a simple consequence of an aspiration to internal consistency in one’s model and/or explanation of people’s choices in terms of individual rationality, but in fact it is not a necessary implication of these methodological commitments. It does not follow from the fact that one believes in the validity of one’s own model and that one believes that people can be assumed to make rational choices that they must be assumed to make the choices that would be seen to be correct by someone who (like the economist) believes in the validity of the predictions of that model. Still less would it follow, if the economist herself accepts the necessity of entertaining the possibility of a variety of possible models, that the only models that she should consider are ones in each of which everyone in the economy is assumed to understand the correctness of that particular model, rather than entertaining beliefs that might (for example) be consistent with one of the other models in the set that she herself regards as possibly correct."
"...the mainstream alternative developed in response to [the Lucas] critique --- according to which aggregate consumer expenditure is modeled as the solution to the Euler equation (a condition for intertemporal optimality) of a representative household, under the hypothesis of rational expectations, has difficulty matching the statistical properties of aggregate data too closely. In order to avoid making strongly counter-factual predictions, current-vintage empirical DSGE models commonly assume preferences for the representative household that incorporate a high degree of “habit persistence,” so that even when solved under the assumption of intertemporal optimization under rational expectations, consumer spending will not jump sharply in response to events that (at least according to the model) should predictably change the future path of household income. But the postulate of strong habit persistence has not found much support from studies of the behavior of individual households. An alternative explanation for the observation of persistent departures from the predictions of the rational expectations Euler-equation model under more standard preferences would be the existence of persistent departures of actual household expectations from those implied by the rational-expectations solution of the economists’ model."
"The macroeconomics of the future, I believe, will... have to go beyond conventional late-twentieth-century methodology as well, by making the formation and revision of expectations an object of analysis in its own right... A prudent use of such an approach for economic policy analysis would surely need to consider a variety of possible assumptions about the forecasting approaches used by economic agents, quite apart from the consideration that would be given to uncertainty about the correct specification of the economic environment.
This absence of a single clear prediction about how people should forecast is often considered to be a reason not to entertain such hypotheses, and instead to prefer the hypothesis of rational expectations, which aims to provide a unique prediction about expectations in a given economic environment. But a more sensible approach may be to accept that one should only expect one’s model of the economy to deliver a range of plausible outcomes, rather than a unique prediction...
Allowance for a set of possible outcomes under a given policy would lead to an approach to policy design that would focus on the robustness of policy to possible variations in the way that the consequences of the policy are understood by people in the economy, rather than focusing solely on the optimality of the policy if events unfold precisely as planned. It should lead, for example, to a concern to design policies that make it more difficult for asset bubbles to occur, or that should reduce the economic distortions that result from them when they do occur, rather than ignoring these issues on the ground that in a rational-expectations equilibrium the bubbles should not occur. It should also lead to greater attention to the communication policies of central banks and other governmental actors, rather than assuming that official explanations of policy are irrelevant given that economic agents can be expected to have rational expectations --- and that these “rational” expectations depend only on governmental actions, not upon speech."
"... What we should outgrow... is the aspiration to build models that can not only be regarded (at least provisionally) as correct representations of reality for purposes of policy analysis, but that can be assumed to be self-evidently valid to everyone in the economy as well."
From "What’s Wrong with Economic Models?", Michael Woodford, July 2012
http://ineteconomics.org/sites/inet.civicactions.net/files/Note-9-Woodford.pdf
Is inequality approaching a tipping point?
As with my last post, I'm trying to catch up here in linking to my recent Bloomberg pieces. This is my last one from two weeks ago. Given all the recent discussion of rising inequality, I wanted to point to a really fascinating paper from about 15 years ago that almost no one (in economics, at least) seems to know about. The paper looks at a very general model of how wealth flows around in an economy, and points to the existence of a surprising phase transition or tipping point in how wealth ends up being distributed. It shows that, beyond a certain threshold (see text below), the usual effect of wealth concentration (a small fraction of people owning a significant fraction of all wealth) becomes much worse: wealth "condenses" into the hands of just a few individuals (or, in the model, they might also be firms), not merely into the hands of a small fraction of the population.
Are we approaching such a point? I've mentioned some evidence in the article that we might be. But the important thing, I believe, is that we have good reason to expect that such a threshold really does exist. We are likely getting closer to it, although we may still have a ways to go.
****
We know that inequality is on the rise around the world: The richest 1 percent command almost half the planet’s household wealth, while the poorest half have less than 1 percent. We know a lot less about why this is happening, and where it might lead.
Some argue that technological advancement drives income disproportionately to those with the right knowledge and skills. Others point to the explosive growth in the financial sector. Liberals worry that extreme inequality will tear society apart. Conservatives argue that the wealth of the rich inspires others to succeed.
What if we could shed all our political prejudices and take a more scientific approach, setting up an experimental world where we could test our thinking about what drives inequality? Crazy as the idea might sound, it has actually been done. The results are worth pondering.
Imagine a world like our own, only greatly simplified. Everyone has equal talent and starts out with the same wealth. Each person can gain or lose wealth by interacting and exchanging goods and services with others, or by making investments that earn uncertain returns over time.
More than a decade ago some scientists set up such a world, in a computer, and used it to run simulations examining fundamental aspects of wealth dynamics. They found several surprising things.
First, inequality was unavoidable: A small fraction of individuals (say 20 percent) always came to possess a large fraction (say 80 percent) of the total wealth. This happened because some individuals were luckier than others. By chance alone, some peoples’ investments paid off many times in a row. The more wealth they had, the more they could invest, making bigger future gains even more likely.
For those who worry about the corrosive effects of wealth inequality on social cohesion and democracy, the idea that it follows almost inexorably from the most basic features of modern economies might be unnerving. But there it is. A small fraction owning most of everything is just as natural as having mountains on a planet with plate tectonics.
Suppose we reach into this experimental world and, by adjusting tax incentives or other means, boost the role of financial investment relative to simple economic exchange. What happens then? The distribution of wealth becomes more unequal: The wealth share of the top 20 percent goes from, say, 80 percent to 90 percent.
If you keep boosting the role of finance and investment, something surprising happens. Inequality doesn’t just keep growing in a gradual and continuous way. Rather, the economy crosses an abrupt tipping point. Suddenly, a few individuals end up owning everything.
This would be a profoundly different world. It’s one thing to have much of the wealth belonging to a small fraction of the population -- 1 percent is still about 70 million people. It’s entirely another if a small number of people -- say, five or eight -- hold most of the wealth. With such a chasm between the poor and rich, the idea that a person could go from one group to the other in a lifetime, or even in a number of generations, becomes absurd. The sheer numbers make the probability vanishingly small.
Are we headed toward such a world? Well, data from Bloomberg and the bank Credit Suisse suggest that the planet’s 138 richest people currently command more wealth than the roughly 3.5 billion who make up the poorest half of the population. Of course, nobody can say whether that means we’ve reached a tipping point or are nearing one.
Experimental worlds are useful in that they exploit the power of computation to examine the likely consequences of complex interactions that would otherwise overwhelm our analytical skills. We can get at least a little insight into what might happen, what we ought to expect.
Our experimental world suggests that today’s vast wealth inequality probably isn’t the result of any economic conspiracy, or of vast differences in human skills. It’s more likely the banal outcome of a fairly mechanical process -- one that, unless we find some way to alter its course, could easily carry us into a place where most of us would rather not be.
Are we approaching such a point? I've mentioned some evidence in the article that we might be. But the important thing, I believe, is that we have good reason to expect that such a threshold really does exist. We are likely getting closer to it, although we may still have a ways to go.
****
We know that inequality is on the rise around the world: The richest 1 percent command almost half the planet’s household wealth, while the poorest half have less than 1 percent. We know a lot less about why this is happening, and where it might lead.
Some argue that technological advancement drives income disproportionately to those with the right knowledge and skills. Others point to the explosive growth in the financial sector. Liberals worry that extreme inequality will tear society apart. Conservatives argue that the wealth of the rich inspires others to succeed.
What if we could shed all our political prejudices and take a more scientific approach, setting up an experimental world where we could test our thinking about what drives inequality? Crazy as the idea might sound, it has actually been done. The results are worth pondering.
Imagine a world like our own, only greatly simplified. Everyone has equal talent and starts out with the same wealth. Each person can gain or lose wealth by interacting and exchanging goods and services with others, or by making investments that earn uncertain returns over time.
More than a decade ago some scientists set up such a world, in a computer, and used it to run simulations examining fundamental aspects of wealth dynamics. They found several surprising things.
First, inequality was unavoidable: A small fraction of individuals (say 20 percent) always came to possess a large fraction (say 80 percent) of the total wealth. This happened because some individuals were luckier than others. By chance alone, some peoples’ investments paid off many times in a row. The more wealth they had, the more they could invest, making bigger future gains even more likely.
For those who worry about the corrosive effects of wealth inequality on social cohesion and democracy, the idea that it follows almost inexorably from the most basic features of modern economies might be unnerving. But there it is. A small fraction owning most of everything is just as natural as having mountains on a planet with plate tectonics.
Suppose we reach into this experimental world and, by adjusting tax incentives or other means, boost the role of financial investment relative to simple economic exchange. What happens then? The distribution of wealth becomes more unequal: The wealth share of the top 20 percent goes from, say, 80 percent to 90 percent.
If you keep boosting the role of finance and investment, something surprising happens. Inequality doesn’t just keep growing in a gradual and continuous way. Rather, the economy crosses an abrupt tipping point. Suddenly, a few individuals end up owning everything.
This would be a profoundly different world. It’s one thing to have much of the wealth belonging to a small fraction of the population -- 1 percent is still about 70 million people. It’s entirely another if a small number of people -- say, five or eight -- hold most of the wealth. With such a chasm between the poor and rich, the idea that a person could go from one group to the other in a lifetime, or even in a number of generations, becomes absurd. The sheer numbers make the probability vanishingly small.
Are we headed toward such a world? Well, data from Bloomberg and the bank Credit Suisse suggest that the planet’s 138 richest people currently command more wealth than the roughly 3.5 billion who make up the poorest half of the population. Of course, nobody can say whether that means we’ve reached a tipping point or are nearing one.
Experimental worlds are useful in that they exploit the power of computation to examine the likely consequences of complex interactions that would otherwise overwhelm our analytical skills. We can get at least a little insight into what might happen, what we ought to expect.
Our experimental world suggests that today’s vast wealth inequality probably isn’t the result of any economic conspiracy, or of vast differences in human skills. It’s more likely the banal outcome of a fairly mechanical process -- one that, unless we find some way to alter its course, could easily carry us into a place where most of us would rather not be.
Wall St shorts economists
I've been remiss in not providing links to my last two Bloomberg pieces. Active web surfers may have run across them, but if not -- below is the full text of this essay from January. It looks at the question -- first raised here by Noah Smith -- of why, if DSGE models are so useful for understanding an economy, i.e. for gaining insights which can be had in no other way, no one on Wall St. actually seems to use them. Good question, I think:
****
In 1986, when the space shuttle Challenger exploded 73 seconds after takeoff, investors immediately dumped the stock of manufacturer Morton Thiokol Inc., which made the O-rings that were eventually blamed for the disaster. With extraordinary wisdom, the global market had quickly rendered a verdict on what happened and why.
Economists often remind us that markets, by pooling information from diverse sources, do a wonderful job of valuing companies, ideas and inventions. So what does the market think about economic theory itself? The answer ought to be rather disconcerting.
Blogger Noah Smith recently did an informal survey to find out if financial firms actually use the “dynamic stochastic general equilibrium” models that encapsulate the dominant thinking about how the economy works. The result? Some do pay a little attention, because they want to predict the actions of central banks that use the models. In their investing, however, very few Wall Street firms find the DSGE models useful.
I heard pretty much the same story in recent meetings with 15 or so leaders of large London investment firms. None thought that the DSGE models offered insight into the workings of the economy.
This should come as no surprise to anyone who has looked closely at the models. Can an economy of hundreds of millions of individuals and tens of thousands of different firms be distilled into just one household and one firm, which rationally optimize their risk-adjusted discounted expected returns over an infinite future? There is no empirical support for the idea. Indeed, research suggests that the models perform very poorly.
Economists may object that the field has moved on, using more sophisticated models that include more players with heterogeneous behaviors. This is a feint. It isn’t true of the vast majority of research.
Why does the profession want so desperately to hang on to the models? I see two possibilities. Maybe they do capture some deep understanding about how the economy works, an “if, then” relationship so hard to grasp that the world’s financial firms with their smart people and vast resources haven’t yet been able to figure out how to profit from it. I suppose that is conceivable.
More likely, economists find the models useful not in explaining reality, but in telling nice stories that fit with established traditions and fulfill the crucial goal of getting their work published in leading academic journals. With mathematical rigor, the models ensure that the stories follow certain cherished rules. Individual behavior, for example, must be the result of optimizing calculation, and all events must eventually converge toward a benign equilibrium in which all markets clear.
A creative economist colleague of mine told me that his papers have often been rejected from leading journals not for being implausible or for conflicting with the data, but with a simple comment: “This is not an equilibrium model.”
Knowledge really is power. I know of at least one financial firm in London that has a team of meteorologists running a bank of supercomputers to gain a small edge over others in identifying emerging weather patterns. Their models help them make good profits in the commodities markets. If economists’ DSGE models offered any insight into how economies work, they would be used in the same way. That they are not speaks volumes.
Markets, of course, aren’t always wise. They do make mistakes. Maybe we’ll find out a few years from now that the macroeconomists really do know better than all the smart people with “skin in the game.” I wouldn’t bet on it.
****
In 1986, when the space shuttle Challenger exploded 73 seconds after takeoff, investors immediately dumped the stock of manufacturer Morton Thiokol Inc., which made the O-rings that were eventually blamed for the disaster. With extraordinary wisdom, the global market had quickly rendered a verdict on what happened and why.
Economists often remind us that markets, by pooling information from diverse sources, do a wonderful job of valuing companies, ideas and inventions. So what does the market think about economic theory itself? The answer ought to be rather disconcerting.
Blogger Noah Smith recently did an informal survey to find out if financial firms actually use the “dynamic stochastic general equilibrium” models that encapsulate the dominant thinking about how the economy works. The result? Some do pay a little attention, because they want to predict the actions of central banks that use the models. In their investing, however, very few Wall Street firms find the DSGE models useful.
I heard pretty much the same story in recent meetings with 15 or so leaders of large London investment firms. None thought that the DSGE models offered insight into the workings of the economy.
This should come as no surprise to anyone who has looked closely at the models. Can an economy of hundreds of millions of individuals and tens of thousands of different firms be distilled into just one household and one firm, which rationally optimize their risk-adjusted discounted expected returns over an infinite future? There is no empirical support for the idea. Indeed, research suggests that the models perform very poorly.
Economists may object that the field has moved on, using more sophisticated models that include more players with heterogeneous behaviors. This is a feint. It isn’t true of the vast majority of research.
Why does the profession want so desperately to hang on to the models? I see two possibilities. Maybe they do capture some deep understanding about how the economy works, an “if, then” relationship so hard to grasp that the world’s financial firms with their smart people and vast resources haven’t yet been able to figure out how to profit from it. I suppose that is conceivable.
More likely, economists find the models useful not in explaining reality, but in telling nice stories that fit with established traditions and fulfill the crucial goal of getting their work published in leading academic journals. With mathematical rigor, the models ensure that the stories follow certain cherished rules. Individual behavior, for example, must be the result of optimizing calculation, and all events must eventually converge toward a benign equilibrium in which all markets clear.
A creative economist colleague of mine told me that his papers have often been rejected from leading journals not for being implausible or for conflicting with the data, but with a simple comment: “This is not an equilibrium model.”
Knowledge really is power. I know of at least one financial firm in London that has a team of meteorologists running a bank of supercomputers to gain a small edge over others in identifying emerging weather patterns. Their models help them make good profits in the commodities markets. If economists’ DSGE models offered any insight into how economies work, they would be used in the same way. That they are not speaks volumes.
Markets, of course, aren’t always wise. They do make mistakes. Maybe we’ll find out a few years from now that the macroeconomists really do know better than all the smart people with “skin in the game.” I wouldn’t bet on it.
Wednesday, February 12, 2014
Peter Dorman, bluntly, on the crappiness of today's microfoundations
This is a bit old, but I just happened onto this interesting post at Econospeak contributed by Peter Dorman. It pulls no punches, and suggests that the stamp above might be appropriately applied to most of the highly "insightful" and "sophisticated" papers of modern micro-founded macroeconomics:
... Microfoundations for macroeconomics are fine in principle—not indispensable, but useful. The problem is that what passes for microfoundations in the universe of orthodox macro is crap.
There. I said it. I used the “c” word. But not the “s” word.
It’s nothing more than robotic imitation of teaching exercises to improve math skills, without any consideration for such mundane matters as empirical verisimilitude. I will mention three crushing faults, each sufficient by itself to blow a wide hole in a supposedly useful model.
1. Utility theory. Andrew Gelman calls this “folk psychology”; that may be generous. It is rife with anomalies (see “behavioral economics”), and, most important, it is oblivious to the last several decades of work in psychology, evolutionary biology, neuropsychology, organization theory—all the disciplines where people study behavior in a scientific way.
2. Mono-equilibrium assumptions. There are no interaction effects to generate multiple equilibria in the microfoundations macro theorists use. Every individual, firm and product is an isolated atom, floating uninterrupted through space until it bumps into another such atom in the marketplace. Social psychology, ecology, nonconvex production and consumption spaces? Forget about it. In evolutionary biology, by contrast, fitness surfaces are assumed nonconvex from the get-go; it’s central to the discipline. Failure to recognize the interactive character of economic life leads economists to ask fundamentally wrong questions, like “what’s the equilibrium?” and “what’s the optimum?” If this isn’t obvious to you already, you can get a longer version of the argument here. (Note for those who are wondering: no, nonconvexity stemming from interaction effects has nothing to do with market failure. The existence of externalities is neither necessary nor sufficient for these effects. See for yourself.)
3. Path dependence. Microfoundations means general equilibrium theory, but the flavor it uses is from the mid-1950s. The Sonnenschein-Debreu-Mantel demonstration (update to the 1970s) that initial conditions and out-of-equilibrium trades alter the equilibrium itself (they assume away problem #2) has turned GET upside down.
Notice that I haven’t mentioned the standard heterodox criticisms of representative agents and ergodicity. You can add those if you want.
Now here’s the clincher. As Krugman points out, faced with the choice between addressing the evidence or maintaining consistency with their microfounded models, macroeconomists as a herd have gone for the second. This is because they believe that the micro theory they use is really, really, really true, and that no model that cannot be yoked to it can be considered scientific. And if we actually knew with certainty that mid-50s general equilibrium theory with optimizing agents and no interactions outside the market was the only acceptable framework for thinking coherently about economics, they’d be right. But they’re not.
Like I said, their microfoundations are crap.
Damned with faint praise
I posted yesterday on the new book by Kartik Athreya, Big ideas in Macroeconomics: a non-technical view. There's a blurb on the back by Herb Gintis, who I think is a very smart guy and worth listening to. I noticed he also has written a review on Amazon, which is titled: At Last! A Serious Presentation and Defense of Modern Macroeconomic Theory. That sounds really positive, doesn't it? I thought, wow, Gintis thinks the theory is in great shape? I'm shocked, and I have to think hard about what he says. The review starts out saying nice things about the book. But then look at the parts I've highlighted below:
It is easy to find excellent, accurate, accessible, and entertaining books that present the current theories and ideas in many fields, including law, physics, and biology. It is virtually impossible to find such books in economics. Sadly, when someone writes a book about economics, it almost always is an attempt to convince the reader that some politically motivated partial truth is the whole truth.
There are some books that present basic economic theory in an unbiased manner, and I review the ones I have found in an entry on my web site (http://people.umass.edu/gintis). Click on You Must Read This! and look for "Books on Economics for Serious Beginners: Very Introductory Readings."
But for the sort of advanced macroeconomic that guided policy makers and central bankers leading up to the financial meltdown of 2008, there has been virtually no serious accessible exposition without a political bone to pick. I love this book because it treats the reader as intelligent and discerning, presents the theory ably and in great detail, but avoids the mathematical detail that makes the material quite impenetrable to all but the expert who spends the bulk of his time devoted to the subject.
The reader who even cursorily inspects this book might consider me a biased observer because I contributed a blurb to the book jacket and the author graciously thanks me for my support in the introductory pages. The fact is that I consider this an exemplary exposition of modern macroeconomics, and I think his defense of the theory is as good as one can find anywhere, the theory is in fact so weak that nothing can save it. People continue doing it not because it is good theory, but because it is the only game in town. I believe a complete revolution in macroeconomic theory is in the process of being born, although it will take some years to take over as the mainstream theory.
Change in macroeconomic theory can be extremely rapid. Keynesianism displaced classical macroeconomics in just a few years after the end of WWII, and the reigning "rational expectations" macro displaced Keynesianism in just a few breathtaking years. This is a credit to economics as a discipline--given new evidence and given new economic conditions, young Ph.D. economists are quite willing to throw over the past, and in the best graduate schools, hiring of new faculty is based on how productive they are as researchers, not whether or not they agree with the reigning orthodoxy.
Macroeconomics has always been deeply political. After WWII in Europe and the US, the growth in organized labor led to cost-push inflation (higher wages --> higher prices) and unemployment caused by wages above the market-clearing level. Keynesianism blamed the unemployment on the market system itself and suggested deficit spending as the way to restore full employment and accommodating higher prices by increasing the money supply. Of course, this is a stupid theory because it leads to chronic deficit spending and chronic inflation. With the decline in the power of organized labor (caused mainly by increased international competition eliminating domestic monopolies in internationally traded goods such as steel, mining, and automobiles), a resurgent right-wing macroeconomics, called rational expectations theory, displaced Keynesian macro by recognizing the fatal flaws in its reasoning, which contradicted economic rationality. Keynesianism remains today in an attenuated form that recognizes coordination failures and price inertia, but is mainly a liberal profession of faith.
The only virtue of rational expectations macro (RA macro), which Athreya explains so nicely in this book, is that it killed Keynesian macro. The theory itself is nothing but smoke and mirrors. It purports to be solidly based on widely-accepted microeconomic principles that accurately describe the market economy (the "rational" in rational expectations), but this is simply false. The market economy is in fact a complex dynamic system whose behavior can be simulated, much as the weather is simulated by supercomputers, but cannot be captured in a few recursive equations, as the RA macro supporters claim. Instead of a large number of economic actors, RA macro assumes there is one "representative agent," and instead of large numbers of firms and industries, RA macro assumes there is one "production function." The only source of volatility in such a world is technology shocks and the vagaries of "expectations" (which of course cannot be measured, because they don't really exist). All we end up with is smoke and mirrors, plus lots of abstruse equations.
Among the more bizarre modeling choices of RA macro is to assume that all markets clear instantaneously. This of course assumes away the coordination failures that really underlie macroeconomic fluctuations. Especially exotic is the assumption that there is always full employment! "Unemployed" workers are simply people who temporarily prefer not to work (they prefer "leisure," in the parlance of macro theory). In fact what happens in a recession is that millions of jobs disappear. The displaced workers prefer their old or equivalent jobs at their accustomed wages, but these are gone. Of course, many could find work at a lower wage, but that is not always the rational thing to do because the worker may get locked into the lower wage occupational level.
This absurd sort of macro modeling would be okay if the resulting models predicted well, but they do not. RA macro long ago gave up econometric testing their equations in favor of "calibrating" them, which means just get the best fit you can, however poor. An poor they are.
Of course, prediction is not everything. Engineers cannot predict when a car will go over a bump, but they can model the effects of such a shock on the car and proposed mechanisms (shock absorbers) that allow the system (the car) to survive the shock with minimal damage. The same is true, to a much more limited extent in macroeconomics, where "automatic stabilizers" can lessen the effects of shocks to the economy.
The real problem with RA macro (and similarly of Keynesian macro) is the theory cannot deal with finance at all, and financial markets lie at the heart of contemporary economic instability. The Walrasian micro model on which RA macro is built simply has no place for money or finance. Graduate students in economics do not even study finance---that is left to the business schools.
Of course, all of that is now changing. Economists around the world are revamping their theories and developing the empirical data on finance so that a more useful theory is likely to be forthcoming. It is a very exciting time for macroeconomics. Athreya's defense of the current theory is quite brilliant and I urge the reader to learn from him. However, we all know the story of the silk purse and the sow's ear.
In short, nice attempt on an impossible task: giving a coherent defense of modern rational expectations macroeconomics.
Tuesday, February 11, 2014
Economists with hurt feelings
Kartik Athreya is an economist at the Federal Reserve Bank of Richmond. He is a true believer in the modern methods of macroeconomics, and has written a new book entitled Big ideas in Macroeconomics: a non-technical view. I've just had a partial read of the first 50 pages or so on google books.
Athreya is really irritated at all the criticism that macroeconomists have had to endure since the onset of the financial crisis. He famously expressed his irritation a few year ago, demanding that bloggers and non-economists in general shut up and leave discussion of economics to himself and other experts in the field. It seems that the purpose of the new book is to correct all the confusion and explain to everyone why modern macro is so wonderful and right and beyond criticism. I don't think it is going to succeed. Anyone who reads his section on the Walrasian Clearinghouse -- an imaginary mechanism to explain how an economy reaches Walrasian equilibrium -- will pretty quickly come to the conclusion that Athreya's beloved picture of how an economy works is mostly mathematical fantasy.
But actually, I think the book may in this way provide a great service. Anyone who reads it carefully will be able to see for themselves just how fragile and artificial the modern rational expectations approach to macroeconomics really is. I'm going to order the book because, from what I have seen, there will be much to learn, although possibly not about how a real economy works. Readers will experience a close encounter with the reality-defying attitude and arrogance of mainstream macroeconomics. Reading from one who holds it in such high esteem, the reader can also trust that he or she is not being deceived by some ignorant blogger who is setting up straw man arguments (a common response from wounded macroeconomists).
David Glasner has read the book and offers an informative review. One section deserves highlighting, regarding Athreya's tendency to dismiss whole realms of real economic phenomena as irrelevant simply because they don't fit into his preferred modelling methodology:
As Athreya acknowledges in chapter 5, an important issue separating certain older macroeconomic traditions (both Keynesian and Austrian among others) is the idea that macroeconomic dysfunction is a manifestation of coordination failure. It is a property – a remarkable property – of Walrasian general equilibrium that it achieves perfect (i.e., Pareto-optimal) coordination of disparate, self-interested, competitive individual agents, fully reconciling their plans in a way that might have been achieved by an omniscient and benevolent central planner. Walrasian general equilibrium fully solves the coordination problem. Insofar as important results of modern macroeconomics depend on the assumption that a real-life economy can be realistically characterized as a Walrasian equilibrium, modern macroeconomics is assuming that coordination failures are irrelevant to macroeconomics. It is only after coordination failures have been excluded from the purview of macroeconomics that it became legitimate (for the sake of mathematical tractability) to deploy representative-agent models in macroeconomics, a coordination failure being tantamount, in the context of a representative agent model, to a form of irrationality on the part of the representative agent. Athreya characterizes choices about the level of aggregation as a trade-off between realism and tractability, but it seems to me that, rather than making a trade-off between realism and tractability, modern macroeconomics has simply made an a priori decision that coordination problems are not a relevant macroeconomic concern.A similar argument applies to Athreya’s defense of rational expectations and the use of equilibrium in modern macroeconomic models. I would not deny that there are good reasons to adopt rational expectations and full equilibrium in some modeling situations, depending on the problem that theorist is trying to address. The question is whether it can be appropriate to deviate from the assumption of a full rational-expectations equilibrium for the purposes of modeling fluctuations over the course of a business cycle, especially a deep cyclical downturn. In particular, the idea of a Hicksian temporary equilibrium in which agents hold divergent expectations about future prices, but markets clear period by period given those divergent expectations, seems to offer (as in, e.g., Thompson’s “Reformulation of Macroeconomic Theory“) more realism and richer empirical content than modern macromodels of rational expectations.
Athreya offers the following explanation and defense of rational expectations:[Rational expectations] purports to explain the expectations people actually have about the relevant items in their own futures. It does so by asking that their expectations lead to economy-wide outcomes that do not contradict their views. By imposing the requirement that expectations not be systematically contradicted by outcomes, economists keep an unobservable object from becoming a source of “free parameters” through which we can cheaply claim to have “explained” some phenomenon. In other words, in rational-expectations models, expectations are part of what is solved for, and so they are not left to the discretion of the modeler to impose willy-nilly. In so doing, the assumption of rational expectations protects the public from economists.
This defense of rational expectations plainly belies the methodological arrogance of modern macroeconomics. I am all in favor of solving a model for equilibrium expectations, but solving for equilibrium expectations is certainly not the same as insisting that the only interesting or relevant result of a model is the one generated by the assumption of full equilibrium under rational expectations. (Again see Thompson’s “Reformulation of Macroeconomic Theory” as well as the classic paper by Foley and Sidrauski, and this post by Rajiv Sethi on his blog.) It may be relevant and useful to look at a model and examine its properties in a state in which agents hold inconsistent expectations about future prices; the temporary equilibrium existing at a point in time does not correspond to a steady state. Why is such an equilibrium uninteresting and uninformative about what happens in a business cycle? But evidently modern macroeconomists such as Athreya consider it their duty to ban such models from polite discourse — certainly from the leading economics journals — lest the public be tainted by economists who might otherwise dare to abuse their models by making illicit assumptions about expectations formation and equilibrium concepts.
See also Noah Smith's comments on the book.
Subscribe to:
Posts (Atom)