Ergodicity

Last Thursday, Jean-Philippe Bouchaud and I held the first meeting of the Rebuilding Macroeconomics project’s Instability Hub. There were roughly twenty people, some in attendance in person and some attending through Zoom. As expected, what emerged was an eclectic mix of ideas, some better presented or better formed than others. The overarching theme that emerged from this meeting, is that macroeconomics needs to deal with the issue of non-ergodicity.

Image from Jean-Philippe's Talk on Equilibrium

Ergodicity is a technical term used by statisticians to reflect the idea that we can learn something about the future by looking at the past. It is an idea that is essential to our use of probability models to forecast the future and it is the failure of economic systems to display this property that makes our forecasts so fragile.

This idea emerged in several different ways at the meeting. First, the post-Keynesians point to the fact that the mainstream has not satisfactorily incorporated Keynes’ ideas on probability theory. Second, psychologists point to the fact that the Von-Neumann Morgenstern model of expected utility is a very bad characterization of human action in uncertain situations. Third, the agent-based modellers and the econo-physicists are perplexed that anyone would imagine that ergodicity would be a good characterization of the social world when it was abandoned in the physical sciences decades ago. So how do we make progress?

One possible avenue is to change our model of human behaviour. We must stop assuming that people are expected utility maximizers and assume instead that they act in ways that we will learn about from the behavioural psychologists. While it is certainly possible that an approach of that kind might be productive; I am skeptical. Even if one takes a reductionist approach to science, it is not true that our knowledge of the world can be reconstructed from the bottom up. At each level of aggregation, natural scientists have learned that they must use new theories to understand emergent properties that arise from the interactions of constituent parts. Just as chemistry is more than aggregate physics so we should expect macroeconomics to be more than aggregate microeconomics.

Agent-based modellers have gone some way in this direction; but they have not gone far enough and ABMs  are similar to the macro models we were constructing in the 1950s in the sense that the behaviours of the agents in these models are reflexive and crude.  They are more sophisticated than 1950s aggregate macroeconomics in the sense that at least there are multiple agents each with possibly different behaviours. But they are, at present, incapable of capturing the kinds of announcement effects that we know are characteristic of real world data. In the real world, an announced future tax increase will bite immediately. In the current generation of ABMs it will not.

Is it possible to construct a macroeconomic theory that allows for more sophisticated individual behaviours but does not preserve the constraints of the representative agent approach? I believe so and the mainstream is already moving in that direction by incorporating heterogeneous agents into simple DSGE models. What the mainstream is missing, is that the future behaviour of prices and quantities may not be governed by stationary probability laws, even if the fundamentals of the economy are governed by such laws.

Some have argued that the social world, like the weather, is obviously governed by chaotic processes; the so-called butterfly effect. What I have learned in my discussions with the applied mathematicians and physicists who attended our meeting, is that the natural world is far less predictable than that. It is not just the variables themselves that evolve in non-linear chaotic ways; it is the probabilities that govern this evolution.

So where do we go from here? First, there is a convergence already happening between DSGE models with heterogeneous agents and ABM modellers. These people need to talk more to each other. Second, a theme that emerges in my own work, is that heterogeneous agent models are replete with multiple equilibria. In multiple equilibrium environments, there is not much to be gained from a more sophisticated view of what we mean by ‘rational’ beliefs about the future. Subjective beliefs are themselves fundamentals.

Finally, what I have learned from talking with smart people from many fields is that words mean different things to different groups. We all must take some time to learn each other’s language and to be a little more humble in our perceptions that our own tribe is the unique repository of all useful knowledge.

Confidence and Crashes

The Dow dropped 4.6% on Monday February 5th.  This was the biggest recorded point drop, 1,175, in history. The markets regained some ground on Tuesday and, as of writing this post, we have simply wiped out the gains that have accumulated since the beginning of January. But we are not yet out of the woods. If the markets continue on their precipitous decline there is real cause for concern.

The vagaries of the market are caused by the animal spirits of market participants. They have little or nothing to do with the ability of the economy to efficiently produce value. Most market participants buy and sell stocks not because they see value in the underlying companies: They buy and sell stocks because they believe that future market participants will be willing to pay more or less for the same shares. There is, after all, a sucker born every day.

But although the market does not reflect social value, it does reflect economic value. My research has shown that the ups and downs of the stock market are followed by ups and downs in employment and I have provided a theory to explain why. When we feel wealthy we are wealthy.  When we feel rich, we buy more goods and services, employment increases, and unemployment falls. There is a causal mechanism from market psychology to tangible economic outcomes.

Normally, the Fed and other central banks around the world would react to a market crash by lowering the interest rate. The cause for concern arises from the fact that they have no room to react to a market drop in the traditional manner as interest rates in the US, the UK, Europe and Japan are at historically low levels. We may be approaching a crisis of the kind I warned of in my book, Prosperity for All.  The solution, as I argue there, is for the Fed to put a floor (and a ceiling) on movements in the S&P by actively buying and selling the market.

What We Know for Sure that Just Ain't So

“What gets us into trouble is not what we don't know. It's what we know for sure that just ain't so.” Mark Twain

David Smith has a piece in the Times yesterday that, as always, is worth reading. But David is a little too certain for my taste. I prefer to follow the dictum that prediction is difficult; especially about the future.

David discusses the Buzzfeed leak of the assessment of Brexit prospects by 'experts' at the behest of the Conservative government. Here is David with a defense against the Brexiteers:

"It was a great scoop for BuzzFeed, though no surprise to economists. Overwhelmingly, credible analysis shows a similar picture. It also produced the usual nonsense, of the kind that says that if you cannot forecast next year how can you forecast for 15 years? This, of course, is not standard economic forecasting but conditional analysis, which looks at the relative difference compared with the baseline when you introduce frictions into trade with your largest trading partner, reduce your attractiveness for foreign direct investment and cut the supply of EU migrant workers. It sets that against modest gains, only over a very long period, from non-EU trade deals."

Brexit may indeed be bad for the economy. But it doesn’t help to overstate the case. However you look at it, the statement that remaining in the EU would lead to an 8% larger economy, 15 years from now,  than leaving the EU with a 'Hard Brexit', is a forecast. And that forecast has standard errors attached. Those standard errors are very large indeed. 

It is also worth remembering that all forecasts assume that we can plan for the future using known statistical probabilities: Like rolling a die that comes up heads with a known probability. That is not the real world. The Bank of England famously produces fan charts that show not only the median forecast but the probability distribution of likely outcomes. For several forecasts in a row following the 2008 crisis, all the realized values of projected inflation were outside of the range of statistical projections. They were Black-Swan events.

Some of us will probably be worse off under Brexit in the near future. Perhaps all of us will be. I have no idea what the consequences will be relative to staying in the EU in 15 years time and nor does anyone else. "What gets us into trouble is not what we don't know. It's what we know for sure that just ain't so." Fifteen years from now, every outcome is a Black-Swan event.

The Brexit arguments are political. They are not Economic. The Economics is clear. Trade between countries increases the ability to produce goods and services. But when the relative prices faced by a country change, some people will gain and others will lose.

The gainers from globalization were those who have skills that are valued internationally and those who own capital that can be combined with cheaper labor abroad. The losers were those who are now competing with cheaper labor in distant lands. 

It is not enough to repeat the trite phrase that the gainers can compensate the losers unless we come up with a credible plan of how that compensation will be achieved. That is not a trivial matter.   David Autor and co-authors have made a credible case that trade with China caused a loss of US manufacturing jobs and recent research at NIESR by Francesca Foliano and Rebecca Riley finds similar results in the UK. 

When the job of the car worker in Northumberland moves to Eastern Europe because his factory was physically dismantled and shipped overseas, that person can be forgiven for blaming EU membership. And that person understands uncertainty better than 90% of experts who, we are told, agree that Brexit was the wrong decision. When you have been let down by politicians on both sides of the aisle, the unknown seems a lot less scary.

Freedom of the Press and Internet Filters

Here are a few thoughts that were inspired by Richard Baldwin's tweet, Random Sunday Findings...

“Freedom of the Press is guaranteed only to those who own one”. A.J. Liebling. It was naïve to think that the internet would change the balance in favor of a more balanced flow of ideas when social media filters the content of our feed

Internet filters feed us ideas that reinforce our own existing biases. If you are on the left, try creating a new internet persona on the right and follow only right leaning feed. If you are on the right, try the opposite.

Justin Lahart points me to this page on the WSJ that lets you run your own experiment on facebook.

The problem of self-confirming biases existed before the advent of social media. In the UK some people read the Daily Mail, some read the Guardian. And it did not only apply to print media. Our perception of social reality was heavily influenced by a small number of TV stations.  In the UK in the 1960s there were two stations; the BBC and the ITV. In the US there were three Network News stations. 

For better or worse, before the internet, most of us shared our window on the external world. Internet filters are polarizing our views in a way that is destructive to social cohesion by feeding us very different self-reinforcing views of the external world.

How much debt do we need? My answer: 70% of GDP

In a post in 2015 I pointed out that government debt is not a bad thing. Here, I elaborate on that idea and I ask, and answer, a simple question: how much debt do we need? My answer: 70% of GDP is a good guess.

In a recent post, Simon Wren-Lewis asks and answers some of the same questions I discuss here. My focus is narrower than Simon’s. I will focus in on the question: what is the right amount of debt?  I will also abstract from one reason why debt should not be zero. That reason, discussed here by Martin Wolf, and here by Isabella Kaminska, is that the public sector does not only accrue debt; it also owns public assets. I will claim that, even if we did not need to build roads and bridges, it would still be a good idea for the public sector to accumulate debt. My argument is based on a remarkable implication of basic economic theory that was first discussed by Paul Samuelson. If we borrow from our children and our grandchildren, everybody, including all future generations, will be better off.

If a household borrows money to pay for a new car, that debt might be paid back over a period of five years or more. Debt that is accrued to help pay for an investment good, like a car, is widely understood to be a good thing. By borrowing to pay for a car, we arrange for the series of benefits we receive by driving to work or to school every day to be matched with the series of payments we make as we pay back the loan used to purchase the car. Debt accrued by a household to facilitate an investment is widely perceived to be privately beneficial.

Suppose instead, a person borrows to pay for an extravagant lifestyle. Instead of taking out a loan and buying a car, that person maxes out their credit cards to throw expensive parties. To pay back that debt, he or she will need to plan for a period of austere living in future years.  Debt accrued by a household to finance an extravagant lifestyle is widely perceived to be deviant behaviour that is discouraged by social norms. But should we apply those same norms to government behaviour?

If government borrows money to pay for a new road or rail network, the new transportation infrastructure will generate benefits to future generations. It is only fair that those generations should help pay for the investments they enjoy and, for that reason, debt accrued to pay for social investment is widely recognized to be socially beneficial. The principle that all government debt should be used to finance infrastructure investments is sometimes called the golden rule of public finance. It is a commonly held belief that government debt should only finance government investment; but it is a belief that does not survive more careful scrutiny.

Governments are not like households. If a household borrows from a bank it will eventually need to repay the money it borrowed. If a government borrows money from the public, it may never repay that money. It is a myth that government debt is repaid by running public surpluses. In reality, the ratio of outstanding debt to GDP shrinks as the economy grows faster than the interest rate at which the government is borrowing.

In the title to this post I raised the question: How much debt do we need? Economic theory provides an answer to that question and it is never zero. In a series of papers that I am writing with Pawel Zabczyk of the Bank of England, soon to be circulated, we show that a fairly standard model of trade between generations can lead to some very non-standard conclusions. We use Samuelson’s  overlapping generations model, which has been widely used to analyse questions of trade between people of different generations. For a calibrated version that we use as an example, the right answer to my opening question; How much debt do we need? is 70% of GDP.

The main theme of my work with Pawel is that governments are not like households. That point has been made many times by many people. Paul Krugman, for example, makes the case here in a NY Times piece. Although the reason often given is that government expenditure can raise employment through a fiscal multiplier, there is a more fundamental reason why we should not eliminate government debt. And this reason applies even if the economy is always operating at full employment. Debt facilitates trade between current and future generations.  

The figure of 70% that I give in this blog is based on some back of the envelope calculations that Pawel and I use to calibrate our theoretical paper and my subjective confidence bands around that figure are large. The optimal size of public sector debt in the UK might be 5% and it might be 140%. But of one thing I am certain. The right answer to my question; how much debt do we need? is never zero!