Faust, Keynes and the DSGE Approach to Macroeconomics

DSGE models have been the subject of much attention recently on the blogs. Simon Wren-Lewis suggests that DSGE modelers made a Faustian bargain and offers a partial defense.  David Glasner is distinctly uneasy with the DSGE approach and although Paul Krugman remains eclectic he wants to retain the IS-LM model as part of his portfolio.

Like it or not, DSGE models are here to stay. I made the following argument in the First Edition of The Macroeconomics of Self-Fulfilling Prophecies in 1993.

In this book I take a point of view that is becoming less controversial but is by no means universally accepted. I will argue that the future of macroeconomics is as a branch of applied general equilibrium theory. 

Believe it or not; twenty one years ago, that was a controversial statement. I argued then that the problem with DSGE models is not the assumption that the economy is in equilibrium. The problem with DSGE models is the implication of some of these models that the equilibrium is optimal. Since then, I have consistently argued that the way forward is to reformulate Keynesian ideas with modern mathematics; that is what the DSGE agenda is all about.

For example, I have constructed a DSGE model where 25% unemployment is an equilibrium. That model does not use, or need, the concept of sticky wages or sticky prices to explain why high unemployment  persists; persistence is implicit in the notion of an equilibrium. Unlike classical or new-Keynesian DSGE models, my work explains why 25% unemployment is a very bad thing from the point of view of society.

The use of multiple equilibrium models to understand Keynesian economics is part of a research agenda that began at the University of Pennsylvania in the 1980s. That agenda has accelerated recently and the use of multiple equilibrium models to understand data has become mainstream. Jim Bullard uses the work of Benhabib-Schmitt-Grohé and Uribe to understand the liquidity trap. Narayana Kocherlakota applies my work on incomplete factor markets to understand unemployment and the top economics journals are routinely publishing research on the importance of animal spirits as a driver of economic activity. We have moved past the IS-LM model as the true guardian of Keynesian thought.

So what’s wrong with middle brow theorizing? The IS-LM model made the best use of techniques available in 1936 when Hicks introduced it as a way of making logical sense of the General Theory. We’ve moved on since then and we now have tools for bringing dynamics into the picture and for understanding how expectations interact with realized outcomes in ways that respect the methods that have proven successful in so many other branches of economics.

The IS-LM model says nothing about inflation. It says nothing about the passage of time and it does not account for the inability of firms and workers to engage in apparently mutually beneficial trades. We now have the tools to put all of those pieces together and, despite Paul’s claims to the contrary, the result is not a simple regurgitation of 1950s macroeconomics. If a smart theorist like Krugman struggles with formalizing his intuition the problem is not with the mathematics; the problem is with the intuition.

Mathematical formalism is an indispensable tool that has been with us since the late nineteenth century. There was a major leap forward in 1947 with Samuelson’s Foundations of Economic Analysis and a further methodological surge in 1989, when Stokey-Lucas released Recursive Methods in Economic Dynamics. With the publication of Stokey-Lucas, the bar for becoming a practitioner of economics became significantly higher than it was when Adam Smith wrote The Wealth of Nations.

Some in the blogging community hearken for the days when an economist could slap together a verbal argument and publish the result in the Quarterly Journal of Economics. Paul Krugman for example, wants his…

ad hockery back — not as an exclusive approach, but as a permissible one. And that’s not a small thing, given the almost total exclusion of middlebrow modeling from academic macro for the past three decades.

The use of ‘ad hockery’ has not been acceptable in economics for quite a while. And for good reason. As Marshall argued in his 1906 letter to Bowley, mathematics is a language; nothing more. I drew attention to Marshall’s instructions in an earlier post but they are worth repeating;

1. Use mathematics as shorthand 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 I do often

Bloggers and researchers have each ignored Marshall’s dictum; but in different ways. Ph.D. economists have published a huge amount of mathematical junk that bears little or no relevance to any real world problem.1  Some, but not all, economic bloggers have ignored the call to check the logic with mathematics before writing down a verbal argument.

The research community ignored points (3) and (4). Paul would have us ignore points (1) and (2) and that is at least as bad.

The IS-LM model is static. It cannot explain inflation and it has no well developed theory of expectations. DSGE models are a huge methodological advance that gives us logical tools to integrate all of these pieces. There is simply no substitute for the use of mathematics to make sure that an argument hangs together.

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1. Don’t get me wrong; mathematics for mathematics sake does play a role in economics journals.  Sometimes, the real world examples come later.  A good example of this process is Lloyd Shapley’s work on stable matches that was used by Al Roth to create markets for kidney exchanges. But the best and most enduring economics papers use the mathematics to explain real world phenomena.  

Keynes and Sticky Prices: Time to Think Outside the Box

Several recent excellent posts have appeared on Keynesian economics and sticky wages and prices. David Glasner points out that

...the sticky-wages explanation for unemployment was exactly the “classical” explanation that Keynes was railing against in the General Theory.

and quoting David again

it’s really quite astonishing — and amusing — to observe that, in the current upside-down world of modern macroeconomics, what differentiates New Classical from New Keynesian macroeconomists is that macroecoomists of the New Classical variety, dismissing wage stickiness as non-existent or empirically unimportant, assume that cyclical fluctuations in employment result from high rates of intertemporal substitution by labor in response to fluctuations in labor productivity, while macroeconomists of the New Keynesian variety argue that it is nominal-wage stickiness that prevents the steep cuts in nominal wages required to maintain employment in the face of exogenous shocks in aggregate demand or supply. 

Quite!

Paul Krugman takes off from David's post and argues that

...even if you don’t think wage flexibility would help in our current situation (and like Keynes, I think it wouldn’t), Keynesians still need a sticky-wage story to make the facts consistent with involuntary unemployment. For if wages were flexible, an excess supply of labor should be reflected in ever-falling wages. 

Simon Wren-Lewis  takes up the torch.  He argues that

“the evidence that prices are not flexible is ... overwhelming”.

Lets look at some facts. In contrast to Simon's assertion; the evidence from the Great Depression is that wages and prices are remarkably flexible. During the first six years of the Great Depression, nominal wages and nominal prices fell by thirty percent.  Here is a graph of the normalized CPI and a normalized wage index that I constructed using aggregate data on compensation to employees (the details are in my book Expectations Employment and Prices and you can download the data here)

Of course the fact that the CPI and the wage moved in lock step means that the real wage did not fall and that, I would guess, is the fact that Paul and Simon would point to.  But that is very different from there being "overwhelming evidence" in favor of sticky prices.

The new-Keynesians have tried to discipline their models by looking at micro data on the frequency of price changes.  Here again; the NK model falls short. Klenow and Malin find that prices in the micro data are simply not rigid enough to explain the aggregate data.  Keynesians often cite Truman Bewley's 1999 study as evidence in favor of downwardly rigid nominal wages but a piece by Tomas Hirst (posted over at Pieria by Marco Nappolini) draws our attention to recent work by Elsby Shin and Solon which casts serious doubt on the relevance of Bewley's  finding. ESS find, that in the US, the wage data

...show a surprisingly high frequency of nominal wage reductions.

and for the UK,

...like the authors of previous British studies of nominal wage change, [the authors]  are struck by the apparent flexibility of British wages.

So lets get back to what's really important. High and persistent unemployment is a problem.  But it has nothing to do with inflexible wages or sticky prices. Both Classical AND new-Keynesian models are broken. It's time to think outside the box!

Rational Expectations and Animal Spirits

Along with the rest of modern macroeconomics, the rational expectations (RE) assumption has gotten quite a bit of flack lately. I don’t think all of it is deserved.  It is not the rational expectations (RE) assumption that is at fault: It is the rational expectations assumption in conjunction with the assumption of a unique equilibrium. 

In standard dynamic stochastic general equilibrium (DSGE) models there is a single rational expectations equilibrium. In the models I work with there are many rational expectations equilibria. Not just one, or two or three: but an infinite dimensional continuum of them. That is not a problem. It is an opportunity that I exploit to model the idea that beliefs matter. In my work, I close my models by adding an equation that I call a 'belief function'. The belief function is an effective way of operationalizing the Old Keynesian assumption of ‘animal spirits’. It is a forecasting rule that explains how people use current information to predict the future. That rule replaces the classicalassumption that the quantity of labor demanded is always equal to the quantity of labor supplied.

You might think that adding a belief function to operationalize animal spirits allows me to dispense with the rational expectations assumption since the belief function could be arbitrary. Not so. Even though we do not live in a stationary environment, our beliefs should be consistent with the outcomes that we would observe in a stationary world.  In such a world, beliefs should obey Abraham Lincoln’s dictum that “you can fool all of the people some of the time or some of the people all of the time but you can’t fool all of the people all of the time.”  In my view, that is the rational expectations assumption.

Suppose you are building a rational expectations model with a unique equilibrium. In that model, you wouldnot need to independently model a ‘belief function’.  The people in your model would need to forecast the future somehow, and presumably they would use some kind of forecasting rule.  But you would not need to know the parameters of that rule.  Whatever rule they use; it would have to be correct ‘on average’.

Stick with the unique RE assumption and suppose that the fundamentals change.  Perhaps there is a new Fed Chairperson, or perhaps someone invents a new technology. In a standard DSGE model, the rule that people use to forecast the future would need to change. The belief function in this world is endogenous.

Now move to my parallel universe where there is a continuum of RE equilibria.  In my universe the rule that people use to forecast the future is critical.  It is the belief function that selects the equilibrium. If people believe that there will be high unemployment; that belief will be self-fulfilling.

In my world, ask what happens if the fundamentals change.  Perhaps there is a new Fed Chairperson or perhaps there is a new technology.  In this world, the belief function selects a new equilibrium. Beliefs are fundamental!

Are beliefs really fundamental?  I think so. This is a not a radical idea; it is a new way of understanding an old one. Central bankers have known for a long time that expectations of future inflation are highly persistent. That persistence is often cited as one of the strikes against either the rational expectations assumption or the equilibrium assumption. I believe that both of those accusations are misplaced. Persistent expectations is a strike against rational expectations PLUS the uniqueness assumption. It is the uniqueness assumption that needs to go; not the rational expectations assumption which simply reflects a fact that we have known for a long time: Expectations are incredibly persistent. Welcome to my alternate reality!

Download my Data on the Stock Market and Unemployment

The recent drop in the stock market, if it persists, will present serious challenges for the Yellen Fed.

In a couple of recent academic papers, The Stock Market Crash of 2008 caused the Great Recession: Theory and Evidence here and The Stock Market Crash Really Did Cause the Great Recession here I showed that changes in the value of the stock market cause changes in the unemployment rate three months later. Here is a link to a Freakonomics post that features my work.
I continue to receive requests for the data that I used in those studies. That data is available here. These are important empirical findings that establish a strong and stable relationship between changes in the value of the S&P and changes in the U.S. unemployment rate.

Quote of the Day

This piece is widely known, but I never tire of reading it. It comes from a 1906 letter by Alfred Marshall to his student Arthur Bowley (of the Edgworth-Bowley Box)

1. Use mathematics as shorthand 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 I do often.