How I Lost My Macro Religion
By Arnold Kling
At lunch, Nick Schulz asked me what Robert Hall is known for. I said that Hall changed my view of macroeconomics. Even today, Hall’s work influences how I think about global warming. So pull up a chair, grab a cup of your favorite beverage, and let me reminisce.Greg Mankiw has an essay called The Scientist and the Engineer, which is about the gulf between academic macro and the macro used by forecasters and policymakers. I experienced this conflict intensely early in my career.
From January through August of 1976, I was a research assistant in the National Income section at the Federal Reserve Board. I worked for Dave Wyss, a model jockey. A model jockey might ask, “What will be the effect of the stimulus proposal on GDP?” You have an equation, estimated using past data, that predicts how much consumption will go up for a given increase in disposable income. You interact that with a bunch of other equations, and out comes your answer. That is how the engineers look at macro.
In the fall of 1976, I started grad school at MIT. I was surprised to find that young scientists were not impressed by engineers. Ray Fair, an engineer-type from Yale, came to teach a course in macro-econometric modeling, and he became a laughing-stock. The course consisted of Fair walking through his own model of about 100 equations, and I can remember classmate John Huizinga (now at U. of Chicago) sarcastically commenting, “Let me guess. The lagged dependent variable, right?” In layman’s terms, what Huizinga was complaining about was that regardless of the type of variable that Fair was trying to predict (inflation, unemployment, consumer spending, what have you), he always found a theoretical rationale for including the previous quarter’s value of that variable in the prediction equation. The statistical performance of his forecasts rested on this crutch.
Nonetheless, I was still feeling loyalty to the engineers. In fact, a lot of what the scientists were doing struck me as equivalent to asking how many angels can dance on the head of a pin. I remember lashing out at Stan Fischer at the beginning of one his third lecture on “monetary growth models,” which felt to me like angel-counting. I remember that incident primarily because I feel very sorry about it. Fischer, now head of Israel’s central bank, is one of the real gentlemen of the profession.
But at one point, Bob Hall gave a seminar, with the awkward title of “The Life Cycle/Permanent Income Hypothesis of Consumption.” The gist of it was that the quarterly change of income had no statistically significant relationship to the quarterly change of consumption. You might see data on income and consumption that look like this:
Year Q inc con
1968 1 100 80
1968 2 105 83
1968 3 109 88
1968 4 115 92
and think that consumption depends positively on income. The bigger the income number, the bigger the consumption number.
But if you look at the quarterly changes, you get
Year Q inc con
1968 2 $5 $3
1968 3 $4 $5
1968 4 $6 $4
Looked at this way, one does not find that the bigger the income number, the bigger the consumption number.
Lots of people, myself included, suspected Hall of pulling some sort of Swindle. It took him a few years to get his paper published. Soon, I got my degree and went back to work at the Fed.
When I rejoined the engineers at the Fed, Hall had planted seeds of doubt in my mind about the reliability of looking at data over time in terms of absolute levels, because looking at quarterly changes can produce different results. Clive Granger (who recently won a Nobel) and Christopher Sims were raising all sorts of alarms about the problem of what is called nonstationary data. After a few years of agonizing about this issue off and on, I came to the conclusion that the engineers’ models are an exercise in self-deception. Macroeconomics is steeped in data but issues in macro cannot be resolved by data. One’s views on macro are more like religion.
I have not kept up with what the scientists of academia are doing in macro. It still strikes me as angel-counting. But I don’t believe that the engineers know very much, either. I don’t think of the economy in terms of a system of equations. I think that what Ben Bernanke is doing now–floundering, trying to prop up the financial system without creating too much inflation or moral hazard–is more typical of how one has to operate as a central banker (unless things are going smoothly, in which case you sit back and try to do as little as possible).
Hall’s methods also affect my outlook on global warming. The fact that global temperatures are high at the same time that atmospheric carbon dioxide is high does not convince me. Changes in the two over shorter time horizons appear to be unrelated. I understand that there are scientific arguments that would justify a strong long-term relationship and a weak short-term relationship, but those arguments only serve to convince me that the observed data cannot rule out man-made global warming. The case that the data prove man-made global warming is very weak, the way that I see it.
I don’t know what Bob Hall himself thinks about global warming. Whatever his views are, I would take his opinions seriously. He has an excellent mind.