I recently engaged in a discussion (a twittercussion) with Leah Boustan of Princeton over the “popularity” of economic history within economics (depicted below). As one can see from the purple section, it is as popular as those hard candies that grandparents give out on Halloween (to be fair, I like those candies just like I do economic history). More importantly, the share seems to be smaller than at the peak of 1980s. It also seems like the Nobel prize going to Fogel and North had literally no effects on the subfield’s popularity. Yet, I keep hearing that “economic history is back”. After all, the Bates Clark medal went to Donaldson of Stanford this year which should confirm that economic history is a big deal. How can this be reconciled with the figure depicted below?
As I explained in my twittercussion with Leah, I think that there is a popularity for using historical data. Economists have realized that if some time is spent in archives to collect historical data, great datasets can be assembled. However, they do not necessarily consider themselves “economic historians” and as such they do not use the JEL code associated with history. This is an improvement over a field where Arthur Burns (former Fed Chair) supposedly said during the 1970s that we needed to look at history to better shape monetary policy. And by history, he meant the 1950s. However, while there are advantages, there is an important danger which is left aside.
The creation of a good dataset has several advantages. The main one is that it increases time coverage. By increasing the time coverage, you can “tackle” the big questions and go for the “big answers” through the generation of stylized facts. Another advantage (and this is the one that summarizes my whole approach) is that historical episodes can provide neat testing grounds that give us a window to important economic issues. My favorite example of that is the work of Petra Moser at NYU-Stern. Without going into too much details (because her work was my big discovery of 2017), she used a few historical examples which she painstakingly detailed in order to analyze the effect of copyright laws. Her results have important ramifications to debates regarding “science as a public good” and “science as a contribution good” (see the debates between Paul David and Terence Kealey on this in Research Policy for this point).
But these two advantages must be weighted against an important disadvantage which Robert Margo has warned against in a recent piece in Cliometrica. When one studies economic history, one must keep in mind that two things must be accomplished simultaneously: to explain history through theory and bring theory to life through history (this is not my phrase, but rather that of Douglass North). To do so, one must study a painstaking amount of details to ascertain the quality of the sources used and their reliability. In considering so many details, one can easily get lost or even fall prey to his own prior (i.e. I expect to see one thing and upon seeing it I ask no question). To avoid this trap, there must be a “northern star” to act as a guide. That star, as I explained in an earlier piece, is a strong and general understanding of theory (or a strong intuition for economics). To create that star and give attention to details is an incredibly hard task and which is why I argued in the past that “great” economic historians (Douglass North, Deirdre McCloskey, Robert Fogel, Nathan Rosenberg, Joel Mokyr, Ronald Coase (because of the lighthouse piece), Stephen Broadberry, Gregory Clark etc.) take a longer time to mature. In other words, good economic historians are projects that have have a long “time to build problem” (sorry, bad economics joke). However, the downside is that when this is not the case, there are risks of ending up with invalid results that are costly and hard to contest.
Just think about the debate between Daron Acemoglu and David Albouy on the colonial origins of development. It took more than five years to Albouy to get his results that threw doubts on Acemoglu’s 1999 paper. Albouy clearly expended valuable resources to get the “details” behind the variables. There was miscoding of Niger and Nigeria, and misunderstandings of what type of mortalities were used. This was hard work and it was probably only deemed a valuable undertaking because Acemoglu’s paper was such a big deal (i.e. the net gains were pretty big if they paid off). Yet, to this day, many people are entirely unaware of the Albouy rebuttal. This can be very well seen in the image below regarding the number of cites of the Acemoglu-Johnson-Robinson paper on an annual basis. There seems to be no effect from the massive rebuttal (disclaimer: Albouy convinced me that he was right) from the Albouy piece.
And it really does come down to small details like those underlined by Albouy. Let me give you another example taken from my work. Within Canada, the French minority is significantly poorer than the rest of Canada. From my cliometric work, we now know that there were poorer than the rest of Canada and North America as far as the colonial era. This is a stylized fact underlying a crucial question today (i.e. Why are French-Canadians relatively poor). That stylized fact requires an explanation. Obviously, institutions are a great place to look. One of the institution that is most interesting is seigneurial tenure which was basically a “lite” version of feudalism in North America that was present only in the French settled colonies. Some historians and economic historians argued that there were no effects of the institutions on variables like farm efficiency. However, some historians noticed that in censuses the French reported different units that the English settlers within the colony of Quebec. To correct for this metrological problem, historians made county-level corrections. With those corrections, the aforementioned has no statistically significant effect on yields or output per farm. However, as I note in this piece that got a revise and resubmit from Social Science Quarterly (revised version not yet online), county-level corrections mask the fact that the French were more willing to move to predominantly English areas than the English were willing to predominantly French areas. In short, there was a skewed distribution. However, once you correct the data on an ethnic composition basis rather than on the county-level (i.e. the same correction for the whole county), you end with a statistically significant negative effect on both output per farm and yields per acre. In short, we were “measuring away” the effect of institutions. All from a very small detail about distributions. Yet, that small detail has supported a stylized fact that the institution did not matter.
This is the risk that Margo speaks about illustrated in two examples. Economists who use history merely as a tool may end up making dramatic mistakes that will lead to incorrect conclusions. I take this “juicy” quote from Margo (which Pseudoerasmus) highlighted for me:
[EH] could become subsumed entirely into other fields… the demand for specialists in economic history might dry up, to the point where obscure but critical knowledge becomes difficult to access or is even lost. In this case, it becomes harder to ‘get the history right’