Brief Thoughts on Barry Eichengreen on New Economic Thinking
Barry Eichengreen sees four important sources of new economic thinking:
- “Big data”–the use of computers to handle more than just a few aggregate indicators.
- “New data”–the use of communications technologies to free economists from reliance on a near-exclusive government’s-eye view of the economy.
- “Policy history”–precisely because this time is not (very) different, what policies were used last time and how they worked is valuable information.
- “Institutional history”–it is no longer John Maynard Keynes’s 1925 but our 2015. We have 90 years to add to the 50 he had to try to assess the performance of global post-agricultural market economies. The longer baseline and more institutional variation allows us to move from theory to empirics in studying institutions and the emergent patterns to which they give rise.
Barry:
: An Economics to Fit the Facts: “The economics profession was arguably the first casualty of the 2008-2009 global financial crisis…
…Its practitioners failed to anticipate the calamity, and many appeared unable to say anything useful when the time came to formulate a response. But… there is reason to hope that the discipline is on the mend. Mainstream economic models were discredited by the crisis because they simply did not admit of its possibility…. Training that prioritized technique… and theoretical elegance… did not prepare economists to provide… practical policy advice…. Some argue that the solution is to return to the simpler economic models of the past, which yielded policy prescriptions that evidently sufficed to prevent comparable crises….
Simple models have their place… [and] are useful for making the straightforward but counterintuitive points that distinguish macroeconomics from other fields…. [But, first,] while older members of the economics establishment continue to debate the merits of competing analytical frameworks, younger economists are bringing to bear important new evidence… ‘big data’… [such as] the Billion Prices Project….
A second approach relies not on big data but on new data… ‘bots’ to scrape bits of novel information about economic decisions….
A third approach… global financial crisis was good for economic history… replete with similar events and with evidence concerning which policy responses work….
The fourth and final focus of the new empirical research: institutions…. Renewed attention to history is thus allowing economists to consider more systematically the role of institutions in macroeconomic outcomes.
These developments amount to a sea change…. Analytical frameworks are still needed…. But now there is reason to hope that… economists… will be shaped not by those frameworks’ elegance, but by their ability to fit the facts.
I wish that I were as optimistic as Barry is, but I cannot be. I do not think he has spent enough time sitting in on first year graduate economics courses around the United States and the world. It imposes intellectual blinders that are, I think, positively harmful if one is then going to conduct useful work in big data, new data, comparative policy history, or institutions and their consequences. Yes, even here at Berkeley. It is true that here at Berkeley the first-year sequence is intended one-third as a tool-building course, one-third as a course allowing our students to communicate in the future with students who have been to other universities, and one-third pointing out things wrong with economics as it is currently practiced that we are going to try to fix.
The problem is that the education we are providing the future economics professors is not the preparation that the economics of the future will require its practitioners to have had. The work will be done, but for the most part it is likely to be done by data scientists, computer modelers, and historians of various stripes. And because they will not be in economics departments, the economies of scope to be potentially gained from talking across these areas are unlikely to be fully realized.