Macroeconomist Says Macroeconomics Really Successful

Narayana Kocherlakota writes a concise defense of modern macroeconomics, and basically says 'it's all good'.

I'm not so sure. I got my PhD in econ because I wanted to be a macroeconomist, but after a year of introductory macro, and having one quarter with models from a Keynesian, another quarter with models from a supply-sider (eg, Kydland & Prescott), it was clear to me they were overfitting the data, and reconciliation was not in the cards. They simply did not have enough business cycles to distinguish between very different theories, and it was too easy to fix models after every new decade's surprise.

For example, the main data is post World War 2 US data, and there have been about 10 recessions. There are hundreds of time series (consumption, consumption per capita, non-durable consumption per capita) where one can derive a model that explains things. Given the failure of economists to forsee the stagflation of the 1970s, the disinflation of the 1980s, the fall in velocity in the 1980s, the growth of the Asian Tigers, the relative productive power of capitalist economies (most thought the Soviet Union's savings rate would necessarily generate higher productivity in a generation circa 1960), it is difficult to see what what else is needed to be discouraged. I've made several strategic errors in my career; leaving macroeconomics was not one of them.

But, if you're a 50 year old macroeconomist, the cognitive dissonance in admitting this is too great. Thus, Kocherlakota notes:

The work of the people on this list is pretty technical. Most are very gifted intuitive economists. But intuition necessarily plays a limited role in macroeconomics. There are just too many things going on in a macroeconomic model of any interest to rely on intuition alone. ... The good news is that, thanks in part to the people on this list [top macroeconomists mentioned earlier], we’ve made enormous progress in the kind of realistic complications that we can usefully model.

An example would really help, because I'm at a loss. It reminds me of John Campbell's Asset Pricing at the Millenium, where he noted:

the period 1979 to 1999 has also been a highly productive one. Precisely because the conditions for the existence of a stochastic discount factor are so general, they place almost no restrictions on financial data

Yup. Progress is generalization, a la String Theory, because explaining things with complicated yet elegant mathematics is progress, right?

The main issues in economics are explaining

• what determines economic growth over long time horizons
• what determines business cycles
• what are the essential characteristics of an optimal fiscal policy
• that are the essential characteristics of an optimal monetary policy

I think to the degree we know anything about these key questions, we have learned via experience. In a productive scientific area, like solid state physics, experts are much better than non-experts at knowing essential truths, but macroeconomists are as divergent on the big issues as anyone. That is, they cannot explain, let alone predict, recessions, just like journalists. Look at the divergent explanations for 2008: the Fed, too much regulation, too little regulation. Which is it? Who knows. They are still arguing about the causes of the Great Depression, and why we got out of it. I have my beliefs, but I realize I can't prove them true.

The most successful macroeconomic policy is perhaps the the Taylor Rule (see here, page 202), which basically was derived by explaining how the actually Fed Funds rate related to inflation and GDP growth in the decade prior to its proposal in 1992. There are lots of dense books on theory that should have been helpful here, and one can retrospectively look in the macro literature to derive this rule, but lets be honest, high-brow theory was pretty irrelevant in the discovery of this useful rule.

Macroeconomics is the triumph of hope over experience, and has been no more successful than sociology. I think it's great that some people are working on this, but let's not kid ourselves that there has been any progress. It is easy to think that merely because a lot of intelligent people have published peer reviewed articles, knowledge must be increasing. The bottom line is the data, and real time experience with macroeconomic models has been horrible as always. It is nice that some of the bad models of the past are now known to be wrong, but the set of wrong models is infinite, so that does not imply we are getting closer to the correct model merely by excluding more bad ones.

Around 1840, Macaulay wrote a grand history of England, and noted that doctors had historically recounted their field’s successes with an obvious lack of detachment:

The history of our country during the last hundred and sixty years is eminently the history of physical, moral, and intellectual improvement. And this is the way the history of medicine used to be written, principally by doctors in their retirement, as a form of ancestor-worship (no doubt in the hope that they, too, would become ancestors worthy of worship). In this version, the history of medicine was that of the smooth and triumphant ascent of knowledge and technique, to our current state of unprecedented enlightenment. . . . [but] it is clear that for centuries it possessed no knowledge or skill that could have helped its patients, rather the reverse.

This was before anesthesia and the theory of germs, a time when visiting a medical doctor was about as useful as visiting a witch doctor.

Macro was created by John Maynard Keynes, before then it was just 'economics'. The simultaneous creation of a model that applied to aggregate variables (eg, aggregate demand) and national income accounting, created what Keynes thought would be the new era of the 'joy of statistics'. It hasn't turned out that way.

Paul Samuelson’s first paper in 1939 was to apply mathematics to the new theory of macroeconomic dynamics, in this case a second-order difference equation. Hyman Minsky's most prominent refereed journal article was a second order difference equation applied to the macroeconomy because that was top line macroeconomics in the 1960s. No one thinks those models work now, they were doomed. Do we really think today's tools are any less futile?

The key indicator of scientific progress is not the opinion of a seasoned practitioner (with their clear bias), but rather, do large financial institutions, who would really benefit from being able to forecast the economy, have thriving economics departments, with the best macroeconomists moving in and out as Chief Economist of Citigroup, to Harvard, and back? No.

In the 1980s, I worked with economists who worked for the Bank of America in the mid-1970s, and they talked of a whole floor of economists, forecasting at various industry and regional growth rates, the things one expects macroeconmists to know. When I got back into banking after graduate school around 1994, the large regional bank I worked for had over 10,000 employees and 1 economist, whose main job was public relations, not advising internal decision making, and this was a typical use for an economist. A few years later, they got rid of him. Macroeconomists are demonstrably not helpful to those institutions that could use economic expertise. Macroeconomists know a lot of stuff, just not anything useful.