Gauti Eggertsson makes the following claim:
As a discipline, macroeconomics was born in response to the Great Depression, giving rise to Keynesianism; the rational-expectations revolution in macroeconomics was born in response to the great inflation on the 1970s.
I don’t wish to contest this claim, at least not directly. I agree that the Depression led to Keynesian economics and that the Great Inflation led to the rise of monetarist/Lucasian ideas. And there is a sense in which macro was born in the Depression. It became a separate field with highly specialized practitioners. But there’s also a sense in which that claim is misleading, and misleading in an interesting way.
Interwar (pre-General Theory) economists had all sorts of recognizable models of the macroeconomy. Today many look ad hoc, but I’d argue they were appropriately ad hoc. Here’s a couple models that form my vision of macro:
MB*V(i) = NGDP, where V is positively related to the 5 year bond yield.
I think it’s a pretty good model, even though other variables like marginal tax rates also impact V. And I think most of the better interwar economists had a model something like this in the back of their minds. Or take this model:
(Hours worked)/ (natural rate of hours worked) = f(W/NGDP), where high relative (not real!) wages reduce hours worked.
Again, many interwar economists assumed a similar sort of sticky-wage model. Fisher was the most advanced; he created a Phillips Curve model in the early 192os.
In my view lots of modern macroeconomists overlook these models, as their vision of a macro model uses a general equilibrium approach, where monetary policy works through the liquidity effect and sticky prices are more important than sticky wages. Something like IS-LM.
Because my preferred approach is similar to that of the interwar economists, I am naturally more likely to treat these early models with respect.
Evan Soltas makes the following claim about improvements in data:
In the beginning, there was no economics data. Greats like Adam Smith wrote treatises on political economy in the equivalent of near-total darkness. Later economists such as Vilfredo Pareto and Alfred Marshall introduced mathematical foundations, changing the direction of what had been a very qualitative philosophical endeavor. After the Great Depression, Paul Samuelson and John Hicks consolidated Keynes’ work into the modern field of macroeconomics — and they received critical (and I might argue significantly under-appreciated) support from econometricians and statisticians like Simon Kuznets.
Kuznets developed the United States’ program of national income accounting — from which the ubiquitous measure of GDP comes — and more broadly, he put heavy emphasis upon data collection. That enabled empirical analysis and complemented economics’ ever more quantitative bent.
Call Kuznets’ revolution the First Generation of economics data. Much of it was low-frequency, with figures released on yearly and quarterly bases. Only some data, largely from labor markets and prices, came out with greater frequency. In large part, data was supplied from government bureaus of statistics and industry groups — a highly centralized model of collection and distribution. And the supply of data was scarce, with each figure an expensive undertaking.
I think we are approaching a Second Generation of economics data. The model is changing, a trend driven by information technology.
I spent several decades immersed in interwar macroeconomic data. And what surprised me most was the high frequency nature of the data, and the fact that it was much more available in “real time” than modern data. I recall during the first quarter of 2011 and the first quarter of 2012 that there was a lot of uncertainty about the macroeconomy. Some data such as ISM numbers and employment numbers showed strong growth. But the actual real GDP numbers (released in late April) were quite disappointing (and later revised.) That wouldn’t have happened in the interwar period.
Christopher Hanes has shown that the interwar economy was very heavily dominated by commodities, and by manufactured goods that are not highly finished (things like steel.) It’s not at all difficult to ascertain the contemporaneous prices of these goods, as they are often traded in auction-style markets, or at the very least (in the case of steel) are relatively homogeneous, and hence the law of one price is approximately true. The WPI (forerunner of the PPI) was actually reported weekly, with very little lag. Admittedly it didn’t include all prices, but it did include the most volatile prices. Hence it did a good job of picking up surges of inflation or deflation.
The data for real output was dominated by agriculture and manufacturing. That’s a weakness in that it ignores services, however:
1. Agricultural and manufacturing comprised a far larger share of GDP during the interwar years.
2. Manufacturing (including mining and utilities) was by far the most volatile part of GDP.
Put those two together and the monthly industrial production numbers gave a pretty good read on the business cycle, far better than the modern IP numbers. And of course they were available much more frequently than our modern GDP figures. And there was even more data available at weekly frequencies, which were highly correlated with the macroeconomy. Steel production, and even more importantly rail shipments (at a time when most goods were shipped by rail.)
Today we are dominated by sectors like finance, consulting, health care, education, software, online journalism, law, accounting, etc, where I don’t even have a clue as to how we should measure “real output” and I don’t think anyone else does either. Under those circumstances the monthly employment data is probability our best cyclical indicator. Unfortunately we have two employment series, and they often diverge sharply.
When I was young I also had a sort of “Whig view of history.” Now that I am a grumpy old reactionary, I no longer think we are evolving toward the right model of the macroeconomy, or the perfect data set. Indeed in both areas I see us regressing, moving ever further away from the golden age of Calvin Coolidge.
The only thing that gives me hope is people like Evan Soltas and Yichuan Wang.