- Canada’s Jews: Maple Leaves and Mezuzahs Bruce Clark, Erasmus
- We’re still no closer to the end of Pi Oliver Roeder, FiveThirtyEight
- Why is Trump turning his back on Iran’s Christians? Doug Bandow, the Skeptics
- What’s divine about divine law? Jacob P. Ellens, Law and Liberty
A few weeks ago, I mentioned that I am generally skeptical of “accepted wisdom” on many topics. “Accepted wisdom” is a construction of a stylized fact by a party with intense preferences that is gradually able to remove nuances over time to solidify its preferred narrative. The example I gave a few weeks ago concerned antitrust laws. There are many more. One of those concerns a research agenda that I laid claim to in a recent article in Atlantic Economic Journal (co-authored with my dear friend Germain Belzile): the nationalization of electricity in Quebec.
My home province of Quebec is basically one giant network of rivers well-suited for the production of hydro-electricity – a potential that was noticed in the late 19th century and led to a rapid expansion of the network. Historians (and some economists) have depicted the early electrical industry in Quebec as a “trust” (a cartel) that gouged consumers and could only be resolved, as witnessed by the neighboring province of Ontario, by nationalization (which occurred in two waves – one in 1944 and one in 1962).
In the article I published with Belzile, I argue that this narration is largely incorrect. First, before nationalization prices in Quebec were falling and were low by North American standards (see figures below). Second, production was expanding rapidly. This is in spite of the fact that taxes imposed on the electrical industry grew rapidly over time from less than 10% of total expenditures to close to 30%. Moreover, we point out that looking at residential prices is bound to yield bad comparisons (if we can call those made above as “bad”) if there is price discrimination. The industry price discriminated and offered incredibly low prices for industrial customers (large power) than in Ontario or anywhere else in Canada (in spite of the taxes it was operating under and the fact that Ontario subsidized its own).
We also point out that there was a dynamics of interventionism problem. The neighboring province of Ontario (more populous and richer than Quebec) nationalized its industry and set prices well below the market level which is an implicit subsidy. However, at the subsidized rate, Ontario could not supply its own demand and had to buy at the market price in Quebec. Its over-equilibrium quantity of energy demanded was transferred on the freer Quebec market, thus increasing prices on that market.
We also argue that there was wide heterogeneity of rates in Quebec that relate to the structure of municipal regulation (the level at which electricity was regulated pre-1935). The price differences depended on the political games involving rent-seeking firms and politicians (best exemplified by the case of Quebec City). Cities with high prices were places where the electrical market was heavily politicized and franchises (i.e. the contracts fixing rate schedules over long periods of time to recoup capital investment) were short and subject to holdups.
This latter point is meant for us (me and Germain) to stake a claim on future research to document the nationalization and regulation process at the municipal level and see what the effects on prices and outputs were. In a certain way, I am trying to establish a research agenda extending the skepticism of “accepted wisdom” that has emerged with the economic history of antitrust in the United States to the case of electricity trusts in Quebec. This first article is, I believe, a promising start for such an inclusion.
This is a topic that has been bugging me. Very often, historians will (accurately) point out mortality statistics in the United States, Canada (Quebec) and the Latin America during the colonial era were better than in the comparable Old World (comparing French with French, British with British, Spanish with Spanish). However, they will argue that this is evidence that living standards were higher. This is where I wish to make an important nuance.
Settlement colonies (so, here there is a bigger focus on North America, but it applies to smaller extent to Latin America which I am more tempt to label as extractive – see here) are generally frontier economies. This means that they are small economies because of small populations. This means that labor and capital are scarce relative to land. All outputs that come from the relatively abundant factor will thus tend to be cheaper if there is little international trade for the goods that they are best at producing. The colonial period pretty much fits that bill. The American and Canadian colonies were basically agricultural colonies, but very few of those agricultural outputs actually crossed the Atlantic. As such, agricultural produces were cheap. This is akin to saying that nutrition was cheap.
This, by definition, will give settlement colonies an advantage in terms of biological living standards. As they are not international price takers, wheat is cheaper than in the old world. This is why James Lemon spoke of the New World as the “Best poor man’s country” (I love that expression) : it was easy to earn subsistence. However, beyond that it is very hard to go beyond. For example, in my dissertation (articles still in consideration at Cliometrica and Canadian Journal of Economics) I found that when wages were deflated by a subsistence basket containing very few services and manufactured goods and which relied heavily on untransformed foods, Canada was richer than the richest city of France. Once you shifted to a basket that marginally increased transformed goods and manufactured goods, the advantage was wiped away.
Yet, everything indicates that mortality rates were greater in Paris and France and than in Quebec City and Quebec as a whole (but not by a lot) (see images below). Similar gaps seem to exist for the United States relative to Britain, but the data is not as rich as for Quebec. However, the data that exists for New England suggests that death rates were lower than in England but the “bare bones” real incomes measured by Lindert and Williamson show that New England may have been poorer than Great Britain (not by much though).
I am not saying that demographic and biological data is worthless. Quite the contrary (even I wanted to, I could not since I have a paper on the heights of French-Canadians from 1780 to 1830)! The point is that data matters in context. The world is full of small non-linearities between variables. While “good” demographic outcomes are generally tracking “good” economic outcomes, there are contexts where this may be a weaker relation (curvilinear relations between variables). I think that this is a good example of that point.
A few days ago, I received goods news that the Canadian Journal of Economics had accepted my paper that constructed a consumer price index for Canada between 1688 and 1850 from homogeneous sources (the account books of religious congregations). I have to format the article to the guidelines of the journal and attach all my data and it will be good to go (I am planning on doing this over the weekend). In the meanwhile, I thought I would share the finalized price index so that others can see it.
First, we have the price index that focuses on the period from 1688 to 1850. Most indexes that exist for pre-1850 Canada (or Quebec since I assume that Quebec is representative of pre-1850 Canadian price trends) are short-term, include mostly agricultural goods and have no expenditures weights to create a basket. Now, my index is the first that uses the same type of sources continuously over such a long period and it is also the first to use a large array of non-agricultural goods. It also has a weights scheme to create a basket.
The issue of adding non-agricultural goods was especially important because there were important differences in the evolution of different types of goods. Agricultural goods, see next image, saw their nominal prices continually increase between the 17th and 19th centuries. However, most other prices – imported goods, domestically produced manufactured goods etc. – either fall or remain stable. These are very pronounced changes in relative prices. It shows that reliance on agricultural goods price index will overstate the amount of “deflating” needed to arrive at real wages or incomes. The image below shows the nominal price evolution of groupings of goods as described above.
And finally, the pièce de résistance! I link my own index to other existing post-1850 index so as to generate the evolution of prices in Canada since 1688. The figure below shows the evolution of the price index over … 328 years (I ended the series at 2015, but extra years forward can be added). In the years to come, I will probably try to extend this backwards as much as possible at least to 1665 (the first census in Canada) and will probably try to approach Statistics Canada to see if they would like to incorporate this contribution into their wide database of macroeconomic history of Canada.
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’
In debates over health care reform in the US, it is frequent for Canada’s name to pop up in order to signal that Canada is spending much less of its GDP to health care and seems to generate relatively comparable outcomes. I disagree.
Its not that the system presently in place in the US is so great, its that the measure of resources expended on each system is really bad. In fact, its a matter of simple economics. Imagine two areas (1 and 2), the first has single-payer health care, the other has fully-private health care.
In area 2, prices ration access to health care so that people eschew visits to the emergency room as a result of a scraped elbow. In area 1, free access means no rationing through price and more services are consumed. However, to avoid overspending, the government of area 1 has waiting lists or other rationing schemes. In area 2, which I have presented as an ideal free market for the sake of conversation, whatever people expend can be divided over GDP and we get an accurate portrait of “costs”. However, in area 1, costs are borne differently – through taxes and through waiting times. As such, comparing what is spent in area 1 to what is spent in area 2 is a flawed comparison.
So when we say that Canada spends 10.7% of GDP on health care (2013 numbers) versus 17.1% of GDP in the US, is it a viable comparison? Not really. In 2008, the Canadian Medical Association produced a study evaluating the cost of waiting times for four key procedures : total joint replacement surgery, cataract surgery, coronary artery bypass
graft (CABG) and MRI scans. These procedures are by no means exhaustive and they concern only “excessive” waiting times (rather than the whole waiting times or at least the difference with the United States). However, the CMA found that, for the 2007 (the year they studied), the cost of waiting was equal to 14.8$ billion (CAD). Given the size of the economy back in 2007, this represented 1.3% of GDP. Again, I must emphasize that this is not an exhaustive measure of the cost of waiting times. However, it does bring Canada closer to the United States in terms of the “true cost” of health care. Any estimate that would include other wait times would increase that proportion.
I know that policy experts are aware of that, but it is so frequent to see comparisons based on spending to GDP in order to argue for X and Y policy as being relatively cheap. I just thought it was necessary to remind some people (those who decide to read me) that prudence is mandatory here.
I have been trying, for some time now, to circle an issue that we can consider to be a cousin of the emerging “state capacity” literature (see Mark Koyama’s amazing summary here). This cousin is the literature on “empire effects” (here and here for examples).
The core of the “empire effect” claim is that empires provide global order which we can consider as a public good. A colorful image would be the British Navy roaming the seas in the 19th century which meant increased protection for trade. This is why it is a parent of the state capacity argument in the sense that the latter concept refers (broadly) to the ability of a state to administer the realm within its boundaries. The empire effect is merely the extension of these boundaries.
I still have reservations about the nuances/limitations of state capacity as an argument to explain economic growth. After all, the true question is not how states consolidate, but how they create constraints on rulers to not abuse the consolidated powers (which in turn generates room for growth). But, it is easy to heavily question its parent: the empire effect.
Shipping is one of the industry that is most likely to be affected by large empires – positively or negatively. Indeed, the argument for empire effects is that they protect trade. As such, the British navy in the 19th century protected trade and probably helped the shipping industry become more productive. But, achieving empire comes at a cost. For example, the British navy needed to grow very large in size and it had to employ inputs from the private sector thus crowding-it out. In a way, if a security effect from empire emerged as a benefit, there must have been a cost. The cost we wish to highlight is the crowding-out one.
In the paper (written with Jari Eloranta of Appalachian State University and Vadim Kufenko of University of Hohenheim), I argue that, using the productivity of the Canadian shipping industry which was protected by the British Navy, the security effect from a large navy was smaller than the crowding-out from high-levels of expenditures on the navy.
While it is still a working paper which we are trying to expand and improve, our point is that what allowed the productivity of the Canadian shipping industry (which was protected by Britain) to soar was that the British Navy grew smaller in absolute terms. While the growth of the relative strength of the British Navy did bolster productivity in some of our tests, the fact that the navy was much smaller was the “thing in the mix that did the trick”. In other words, the empire effect is just the effect of a ramping-down in military being presented as something else than it truly is (at least partly).
That’s our core point. We are still trying to improve it and (as such) comments are welcomed.