Thought for the Day: Animal Spirits as a New Fundamental

 In IS-LM models there is always something in the background shifting the IS curve.  What is it?  

In my view that 'something' is Keynes' animal spirits that we should add to our models as a new fundamental.

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 classical assumption that the quantity of labor demanded is always equal to the quantity of labor supplied.

Here is a link to the blog I wrote on that topic last year.

Multiple Equilibria and Financial Crises

Models of sunspots and multiple equilibria were developed in the 1980s as an alternative to the dominant Real Business Cycle agenda. For the last couple of decades, these models have taken a backstage role as explanations of the macroeconomy. Now they are back with a vengeance. 

On Thursday and Friday of this week, Jess Benhabib and I are running a conference at the San Francisco Fed that showcases new research on multiple equilibria and financial crises. The papers at this conference trace their roots to an agenda on sunspots, developed at the University of Pennsylvania in the 1980s.

The sunspot agenda began with the seminal paper by David Cass and Karl Shell, Do Sunspots Matter?, the pathbreaking paper on Self-Fulfilling Prophecies by Costas Azariadis and a paper by myself and Michael Woodford in which we developed techniques that form the basis for dynamic models of indeterminacy that are now widely used to understand monetary policy regimes. 

Another important landmark was the 1994 conference at NYU, published in the Journal of Economic Theory as a symposium on Growth Fluctuations and Sunspots.  Here is a link to a survey paper that explains the history of the sunspot agenda and its connection to endogenous business cycles.

I'm looking forward to the dinner talk on Thursday night by Karl Shell and I'm also looking forward to seeing the tremendous range of papers that are moving this agenda forwards in new and exciting directions. Here is a link to the conference papers. 

The Unit Root of the Matter: Is it Demand or Supply?

John Cochrane responds to my piece on why there is no evidence that the economy is self-correcting with an excellent blog post

on unit roots. John's post raises two issues. The first is descriptive statistics. What is a parsimonious way to describe the time series properties of the unemployment rate? Here we agree. Unemployment is the sum of a persistent component and a transitory component.

The second is economics. How should we interpret the permanent component?

I claim that the permanent component is caused by shifts from one equilibrium to another and that each of these equilibria is associated with a different permanent unemployment rate. I’ll call that the “demand side theory”. (More on the data here and here and my perspective on the theory here and here ).

Modern macroeconomics interprets the permanent component as shifts in the natural rate of unemployment. I’ll call that the “supply side theory”. That theory is widely accepted and, in my view, wrong. As I predicted in the Financial Times back in 2009, "the next [great economic idea] to fall will be the natural rate hypothesis". 

Lets start with the statistics.

In the comments section, (always worth reading beyond the main post) John and I are in complete agreement that unemployment has two components. One is highly persistent, and well approximated by a random walk. The other is stationary.

Here is John

Hi Roger. We’re converging. Yes, there is an interesting low frequency component in unemployment, that might be modeled well in a short sample with a random walk (unit root = random walk plus stationary component). And unit root asymptotics might be a better approximation to finite sample distributions, plus warn of biases like the AR(1) coefficient.

A random walk, as its name suggests, has an equal chance of going up or down. A stationary variable always returns to a constant number. What about a series that is the sum of a random walk and a stationary component? The stationary bit is always pulling the unemployment rate back to something: but that something is not a number, it’s the random walk component. Unemployment is aiming at a moving target.

John has his own unit root tests. In John's words

"Look at the plot" and "think about the units"

I like that. Here is my “look at the plot” diagram seen through the lens of John’s comment that a unit root equals a “random walk plus stationary component”

John's Unit Root Test: 

"Look at the Plot":

The blue line is the unemployment rate since 1949, the grey shaded areas are the eleven post-war NBER recessions, and the red lines are the means of the unemployment rate for each of the eleven post-war expansions. Because unemployment has a “low frequency component”, the number the economy converges to is different after every recession. It is not a single number. It is a moving target.

So much for the statistics: What about the economics? The central question for policy makers and their academic advisors should be: Why is the target moving? My answer is that aggregate demand, driven by animal spirits, is pulling the economy from one inefficient equilibrium to another. My theoretical work  explains how that idea is consistent with the rest of economic theory. 

The orthodox answer, one we have taught to graduate and undergraduate students alike for the past fifty years is that aggregate supply is shifting from one decade to the next, pushed by changing demographics, shifting tax policies and technological change.  

If permanent movements in the unemployment rate are caused by shifts in aggregate demand, as I believe, we can and should be reacting against these shifts by steering the economy back to the socially optimal unemployment rate. If instead, these movements are caused by shifts in aggregate supply, the moving target is  the socially optimal unemployment rate.

John has not yet staked out a position. On this point he says…

I don't have a definite opinion. There is lots of interesting, new, and unexplored economics on that one. I'll read your paper!

Paul Krugman weighed in on this debate and he claims to agree with John about the statistics, although I’m not sure he read the comments section. 

John and I are in complete agreement: there is  a permanent component in the unemployment rate. That component requires an explanation. Is it demand or is it supply? The answer to that question has huge implications for policy. 

Tired old 1950's theory would attribute the permanent component in unemployment to unavoidable natural rate shifts. Shiny new Neo-Paleo-Keynesian theory would attribute the permanent component to avoidable shifts in animal spirits. Which is it Paul: Demand or Supply?

Beyond 1950's Economic Theory: Nonlinearity, Multiple Equilibria and Sticky Prices

David Glasner has a very nice post on Price Stickiness and Economics with great comments from Rajiv Sethi,  Richard Lipsey and Kevin Donoghue among others. David reacts to a post from Noah Smith: this is all classic stuff

 

Here is David

While I am not hostile to the idea of price stickiness — one of the most popular posts I have written being an attempt to provide a rationale for the stylized (though controversial) fact that wages are stickier than other input, and most output, prices — it does seem to me that there is something ad hoc and superficial about the idea of price stickiness and about many explanations, including those offered by Ball and Mankiw, for price stickiness. I think that the negative reactions that price stickiness elicits from a lot of economists — and not only from Lucas and Williamson — reflect a feeling that price stickiness is not well grounded in any economic theory.

 Let me offer a slightly different criticism of price stickiness as a feature of macroeconomic models, which is simply that although price stickiness is a sufficient condition for inefficient macroeconomic fluctuations, it is not a necessary condition. It is entirely possible that even with highly flexible prices, there would still be inefficient macroeconomic fluctuations. And the reason why price flexibility, by itself, is no guarantee against macroeconomic contractions is that macroeconomic contractions are caused by disequilibrium prices, and disequilibrium prices can prevail regardless of how flexible prices are.

This is my response, first posted as a comment on David's blog,

I have a somewhat different take. I like Lucas’ insistence on equilibrium at every point in time as long as we recognize two facts. 1. There is a continuum of equilibria, both dynamic and steady state and 2. Almost all of them are Pareto suboptimal.

The Arrow-Hahn distaste for RBC models was as much a distaste for the policy implication as it was for the method. At least that’s what I gleaned from conversations with Frank. Perhaps Ken Arrow reads blogs and will jump in and prove me wrong.

David replies...

Roger, I think equilibrium at every point in time is ok if we distinguish between temporary and full equilibrium, but I don’t see how there can be a continuum of full equilibria when agents are making all kinds of long-term commitments by investing in specific capital. Having said that, I certainly agree with you that expectational shifts are very important in determining which equilibrium the economy winds up at. I would certainly be curious to know what Arrow makes of RBC theory, but it would be shocking to me if he had anything positive to say about it. I thought that he always tried to emphasize the ways in which the assumptions of the Arrow-Debreu model deviated from real world conditions.

I agree with much of this. My response to David, which I have also posted on Uneasymoney....

I am comfortable with temporary equilibrium as the guiding principle, as long as the equilibrium in each period is well defined. By that, I mean that, taking expectations as given in each period, each market clears according to some well defined principle. In classical models, that principle is the equality of demand and supply in a Walrasian auction. I do not think that is the right equilibrium concept.

Hicks wanted to separate ‘fix price markets’ from ‘flex price markets’. I don't think that is the right equilibrium concept either. I prefer to use competitive search equilibrium for the labor market. Search equilibrium leads to indeterminacy because there are not enough prices for the inputs to the search process. Classical search theory closes that gap with an arbitrary Nash bargaining weight. I prefer to close it by making expectations fundamental.

Once one treats expectations as fundamental, there is no longer a multiplicity of equilibria. People act in a well defined way and prices clear markets. Of course ‘market clearing’ in a search market may involve unemployment that is considerably higher than the unemployment rate that would be chosen by a social planner. And when there is steady state indeterminacy, as there is in my work, shocks to beliefs may lead the economy to one of a continuum of steady state equilibria.

That brings me to the second part of an equilibrium concept. Are expectations rational in the sense that subjective probability measures over future outcomes coincide with realized probability measures? That is not a property of the real world. It is a consistency property for a model. And yes: if we plop our agents down into a stationary environment, their beliefs should eventually coincide with reality. If the environment changes in an unpredictable way, it is the belief function, a primitive of the model, that guides the economy to a new steady state. And I can envision models where expectations on the transition path are systematically wrong.

The recent ‘nonlinearity debate’ on the blogs confuses the existence of multiple steady states in a dynamic model with the existence of multiple rational expectations equilibria. Nonlinearity is neither necessary nor sufficient for the existence of multiplicity. A linear model can have a unique indeterminate steady state associated with an infinite dimensional continuum of locally stable rational expectations equilibria. A linear model can also have a continuum of attracting points, each of which is an equilibrium. These are not just curiosities. Both of these properties characterize modern dynamic equilibrium models of the real economy.

There are still a number of self-professed Keynesian bloggers out there who see the world through the lens of 1950s theory. They have some catching up to do with the literature.

There is No Evidence that the Economy is Self-Correcting (Very Wonkish)

David Andolfatto asks in a twitter exchange for evidence that deviations of GDP from trend are non-stationary. Here is the raw data. Figure 1 is the residual from a regression of the log of real GDP on a constant and a time trend for quarterly US data from 1955q1 through 2014q4. I will refer to this series as "X".

Figure 1: X = Log of Deviation of Real GDP from Trend

Table 1 reveals the regression of X on itself lagged and on a constant. Remember that these data describe deviations from trend so persistence reflects potentially permanent deviations from the trend growth path. Notice that the coefficient on lagged X is 0.996. That of course, does not establish that the data has a unit root. 

Table 1: Regression Results

There are two approaches to testing formally for a unit root. For one group of tests, for example, the augmented Dickey Fuller test, the null hypothesis is that the series is non-stationary. For a second group, for example the KPSS test, the null hypothesis is that the series is stationary.

Table 2 presents the results of a Dickey Fuller test where the null hypothesis is that X has a unit root. Here we are looking for a test statistic that is small in absolute value if the series has a unit root, reflecting the fact that there is nothing pulling the series back towards trend. 

The null hypothesis that X has a unit root cannot be rejected at the 1%, the 5% or the10% level. 

Table 2: Augmented Dickey Fuller Test

The Dickey Fuller test is known to have very little power over the alternative of a root close to unity and sometimes it helps to look at additional evidence. Table 3 presents the KPSS test for which the null hypothesis is stationarity. Here we are looking for a large test statistic if the series has a unit root.

Table 3: KPSS Test

Notice that here, the null hypothesis of stationarity is overwhelmingly rejected. 

What do we learn from this? Much the same as we learn from the fact that unemployment has a unit root. Just as unemployment can remain persistently high, so GDP can remain persistently below trend. There is no evidence that the economy is self-correcting.