On doing economic history

I admit to being a happy man. While I am in general a smiling sort of fellow, I was delightfully giggling with joy upon hearing that another economic historian (and a fellow  Canadian from the LSE to boot), Dave Donaldson, won the John Bates Clark medal. I dare say that it was about time. Nonetheless I think it is time to talk to economists about how to do economic history (and why more should do it). Basically, I argue that the necessities of the trade require a longer period of maturation and a considerable amount of hard work. Yet, once the economic historian arrives at maturity, he produces long-lasting research which (in the words of Douglass North) uses history to bring theory to life.

Economic History is the Application of all Fields of Economics

Economics is a deductive science through which axiomatic statements about human behavior are derived. For example, stating that the demand curve is downward-sloping is an axiomatic statement. No economist ever needed to measure quantities and prices to say that if the price increases, all else being equal, the quantity will drop. As such, economic theory needs to be internally consistent (i.e. not argue that higher prices mean both smaller and greater quantities of goods consumed all else being equal).

However, the application of these axiomatic statements depends largely on the question asked. For example, I am currently doing work on the 19th century Canadian institution of seigneurial tenure. In that work, I  question the role that seigneurial tenure played in hindering economic development.  In the existing literature, the general argument is that the seigneurs (i.e. the landlords) hindered development by taxing (as per their legal rights) a large share of net agricultural output. This prevented the accumulation of savings which – in times of imperfect capital markets – were needed to finance investments in capital-intensive agriculture. That literature invoked one corpus of axiomatic statements that relate to capital theory. For my part, I argue that the system – because of a series of monopoly rights – was actually a monopsony system through the landlords restrained their demand for labor on the non-farm labor market and depressed wages. My argument invokes the corpus of axioms related to industrial organization and monopsony theory. Both explanations are internally consistent (there are no self-contradictions). Yet, one must be more relevant to the question of whether or not the institution hindered growth and one must square better with the observed facts.

And there is economic history properly done. It tries to answer which theory is relevant to the question asked. The purpose of economic history is thus to find which theories matter the most.

Take the case, again, of asymetric information. The seminal work of Akerlof on the market for lemons made a consistent theory, but subsequent waves of research (notably my favorite here by Eric Bond) have showed that the stylized predictions of this theory rarely materialize. Why? Because the theory of signaling suggests that individuals will find ways to invest in a “signal” to solve the problem. These are two competing theories (signaling versus asymetric information) and one seems to win over the other.  An economic historian tries to sort out what mattered to a particular event.

Now, take these last few paragraphs and drop the words “economic historians” and replace them by “economists”.  I believe that no economist would disagree with the definition of the tasks of the economist that I offered. So why would an economic historian be different? Everything that has happened is history and everything question with regards to it must be answered through sifting for the theories that is relevant to the event studied (under the constraint that the theory be consistent). Every economist is an economic historian.

As such, the economic historian/economist must use advanced tools related to econometrics: synthetic controls, instrumental variables, proper identification strategies, vector auto-regressions, cointegration, variance analysis and everything you can think of. He needs to do so in order to answer the question he tries to answer. The only difference with the economic historian is that he looks further back in the past.

The problem with this systematic approach is the efforts needed by practitioners.  There is a need to understand – intuitively – a wide body of literature on price theory, statistical theories and tools, accounting (for understanding national accounts) and political economy. This takes many years of training and I can take my case as an example. I force myself to read one scientific article that is outside my main fields of interest every week in order to create a mental repository of theoretical insights I can exploit. Since I entered university in 2006, I have been forcing myself to read theoretical books that were on the margin of my comfort zone. For example, University Economics by Allen and Alchian was one of my favorite discoveries as it introduced me to the UCLA approach to price theory. It changed my way of understanding firms and the decisions they made. Then reading some works on Keynesian theory (I will confess that I have never been able to finish the General Theory) which made me more respectful of some core insights of that body of literature. In the process of reading those, I created lists of theoretical key points like one would accumulate kitchen equipment.

This takes a lot of time, patience and modesty towards one’s accumulated stock of knowledge. But these theories never meant anything to me without any application to deeper questions. After all, debating about the theory of price stickiness without actually asking if it mattered is akin to debating with theologians about the gender of angels (I vote that they are angels and since these are fictitious, I don’t give a flying hoot’nanny). This is because I really buy in the claim made by Douglass North that theory is brought to life by history (and that history is explained by theory).

On the Practice of Economic History

So, how do we practice economic history? The first thing is to find questions that matter.  The second is to invest time in collecting inputs for production.

While accumulating theoretical insights, I also made lists of historical questions that were still debated.  Basically, I made lists of research questions since I was an undergraduate student (not kidding here) and I keep everything on the list until I have been satisfied by my answer and/or the subject has been convincingly resolved.

One of my criteria for selecting a question is that it must relate to an issue that is relevant to understanding why certain societies are where there are now. For example, I have been delving into the issue of the agricultural crisis in Canada during the early decades of the 19th century. Why? Because most historians attribute (wrongly in my opinion)  a key role to this crisis in the creation of the Canadian confederation, the migration of the French-Canadians to the United States and the politics of Canada until today. Another debate that I have been involved in relates to the Quiet Revolution in Québec (see my book here) which is argued to be a watershed moment in the history of the province. According to many, it marked a breaking point when Quebec caught up dramatically with the rest of  Canada (I disagreed and proposed that it actually slowed down a rapid convergence in the decade and a half that preceded it). I picked the question because the moment is central to all political narratives presently existing in Quebec and every politician ushers the words “Quiet Revolution” when given the chance.

In both cases, they mattered to understanding what Canada was and what it has become. I used theory to sort out what mattered and what did not matter. As such, I used theory to explain history and in the process I brought theory to life in a way that was relevant to readers (I hope).  The key point is to use theory and history together to bring both to life! That is the craft of the economic historian.

The other difficulty (on top of selecting questions and understanding theories that may be relevant) for the economic historian is the time-consuming nature of data collection. Economic historians are basically monks (and in my case, I have both the shape and the haircut of friar Tuck) who patiently collect and assemble new data for research. This is a high fixed cost of entering in the trade. In my case, I spent two years in a religious congregation (literally with religious officials) collecting prices, wages, piece rates, farm data to create a wide empirical portrait of the Canadian economy.  This was a long and arduous process.

However, thanks to the lists of questions I had assembled by reading theory and history, I saw the many steps of research I could generate by assembling data. Armed with some knowledge of what I could do, the data I collected told me of other questions that I could assemble. Once I had finish my data collection (18 months), I had assembled a roadmap of twenty-something papers in order to answer a wide array of questions on Canadian economic history: was there an agricultural crisis; were French-Canadians the inefficient farmers they were portrayed to be; why did the British tolerate catholic and French institutions when they conquered French Canada; did seigneurial tenure explain the poverty of French Canada; did the conquest of Canada matter to future growth; what was the role of free banking in stimulating growth in Canada etc.

It is necessary for the economic historian to collect a ton of data and assemble a large base of theoretical knowledge to guide the data towards relevant questions. For those reasons, the economic historian takes a longer time to mature. It simply takes more time. Yet, once the maturation is over (I feel that mine is far from being over to be honest), you get scholars like Joel Mokyr, Deirdre McCloskey, Robert Fogel, Douglass North, Barry Weingast, Sheilagh Ogilvie and Ronald Coase (yes, I consider Coase to be an economic historian but that is for another post) who are able to produce on a wide-ranging set of topics with great depth and understanding.

Conclusion

The craft of the economic historian is one that requires a long period of apprenticeship (there is an inside joke here, sorry about that). It requires heavy investment in theoretical understanding beyond the main field of interest that must be complemented with a diligent accumulation of potential research questions to guide the efforts at data collection. Yet, in the end, it generates research that is likely to resonate with the wider public and impact our understanding of theory. History brings theory to life indeed!

On the reversal of fortune, urbanization and Canada

One of the more famous articles of economist Daron Acemoglu is his 2002 article on the reversal of fortunes where he points out that countries colonized by Europeans in 1500 that were relatively rich then are relatively poor now. In the paper, they use urban density as a proxy for economic development at that point in time.

I was not particularly convinced by this because of the issue of ruralization in colonial economies. I am still not convinced in fact. As many scholars interested in American colonial history point out, the country de-urbanized (ruralized) during the colonial era as cities grew at a slower pace than the general population. As such, the share of the US population in rural areas increased. But Jeffrey Williamson and Peter Lindert documented that in 1774, the United States were the richest place in the world (beating England on top of being more egalitarian). 

This is normal. Economies on the frontier had land to labor ratios that were the exact opposite of those in Europe. The opportunity cost of congregating in one area was high given the abundance of land that could be brought under cultivation. This is why the Americas (North America at least) was the Best Poor Man’s Country. As such, areas with low population density are not necessarily poor (even if urbanization is a pretty strong predictor of wealth).

This is where Canada comes in. Today, the country easily fits in the “relatively rich” group. According to the figures 1 and 2 in the work of Acemoglu, Johnson and Robinson, it would have been in the “relatively poor” group well behind countries in Latin America. However, I recently finished compiling the Canadian GDP figures between 1688 and 1790 which I can now compare with those of Arroyo Abad and Van Zanden for Peru and Mexico. With my Canadian data (see the figure below), we can see that Canada was as poor as Latin America around 1680 (the start date of my data).

GelosoGDP.png

So, Canada was a relatively poor country back which was equally poor (or moderately richer) than Latin American countries. Why does that matter to the reversal of fortune story? Well, with the urbanization data, one shows that the non-urbanized of 1500 are the rich of the today. With the GDP data for the 1680s, we see that the more urbanized countries were also poorer than the less urbanized countries.

Now, my argument is limited by the fact that I am using 1680s GDP rather than 1500 GDP. But, one should simply extend the urbanization series to circa 1700 and the issue is resolved.  In any case, this should fuel the skepticism towards the strength of the reversal of fortune argument.

Aggregate measures of well-being, England 1781-1850

I went in the field of economic history after I discovered how much it was to properly measure living standards. The issue that always interested me was how to “capture” the multidimensional nature of living standards. After all, what weight should we give to an extra year of life relative to the quality of that extra year (see all my stuff on Cuba)?

However, I never tried to create “a composite” measure of living standards. I thought that it was necessary, first, to get the measurements right. However, I had been aware of the work of Leandro Prados de la Escosura who has been doing considerable work on this in order to create composite measures (Leandro also influenced me on my Cuba reasoning – see this article).

A year ago, I discovered the work of Daniel Gallardo Albarrán from the University of Groningen at the meeting of the Economic History Society (EHS). Daniel’s work is particularly interesting because he is trying to generate a composite measure of well-being at one of the most important moment in history: the start of the British industrial revolution.

Because of its importance and some pieces of contradicting evidence (inequality, stature, amplitude of real wage increases, amplitude of income increases, urban pollution leading to increased mortality risks etc), the period has been begging for some form of composite measure to come along (at least a serious attempt at generating it). Drawing on some pretty straightforward microeconomic theory (the Beckerian in me likes this), Daniel generates this rich graph (see the paper here).

Daniel

The idea is very neat and I hope it will inspire some economic historians to attempt an expansion upon Daniel’s work. I have already drawn outlines for my own stuff on Canada since I study an era when (from the early 1800s to the mid-1850s) real wages and incomes seem to be going up but stature and mortality are either deteriorating or remaining stable while inequality is clearly increasing.

Household size and growth since 1870 (albeit in Canada)

Two days ago, I posted something on how much we were estimating growth since the 1950s. While organizing another research paper that I am trying to finish, I realized that I could make a follow-up to this based on previous research of mine.

A few months ago, I published (alongside Vadim Kufenko and Klaus Prettner) a short note in Economics Bulletin where we showed that the large differences in household size in Canada that existed up to 1975 led many to overestimate the level of differences between provinces. Moreover, we pointed out that because household size were converging at the same time as incomes, we argued that the rate of convergence from 1945 onwards was slightly overestimated. That paper convinced us to do the same between all the OECD countries (we are assembling the data right now).  But this was an argument about variance, what if we simply plot the “per capita” income of Canada with the “per adult equivalent” income of Canada since 1870.

By using the Maddison dataset combined with the data from my article, it took me a few seconds to get the graph below. What is important to notice in this graph is that, incomes per adult equivalent (measured in 1990 Geary-Kheamis dollars) have increased 40% less than incomes per person. Since adult equivalents are a better measure of living standards (because you capture the economies of scale associated with household size), we can easily say that we have been underestimating the level of improvement in Canada (it is still substantial however).

growthfactors

“Watch” the (industrial) revolution!

I don’t know how I missed such a valuable article, but O’Grada and Kelly have this fascinating piece on the price of watches in England from the early 18th century to the early 19th century in the Quarterly Journal of EconomicsStarting from Adam Smith’s quote that the price of watches had fallen 95% over roughly one hundred years, they collected prices of stolen watches reported in court records.  They find that Smith was wrong. The drop was only 75% (see the sarcasm here).

watch-prices

Why is this interesting? Because it shows something crucial about the industrial revolution. This was a complex good to build which required incredible technical advances – many of which could be considered general purpose technologies which could then be used by other industries for their own advances (on the assumption that other entrepreneurs noticed these technologies). But, more importantly, it provides further evidence against the pessimistic view of living standards in Britain at the beginning of the Industrial Revolution. These “new” goods became incredibly cheaper. Along with nails, glass, pottery and shipping , watches did not weigh heavily in the cost of living of the British. However, they did weigh heavily as industrial prices which meant that costs of production were falling progressively which augured well for the beginning of the industrial revolution*.

Literally, you can watch the industrial revolution in that paper! (sorry, bad pun)

* By the way, I use the term because it is conventional but a revolution is a clean break. The British industrial revolution was not saltation as much as it was a steady process of innovation from the early 18th century up to the mid 19th century. The real “revolution” in my eyes is that of the late 19th century. The technological changes from 1870 to 1890 are the most momentous in history and if there was any technological revolution in the past, this was it.

Did the Thirty Glorious Years Actually Exist?

Okay, I am going for a flashy title here. I should have asked whether the Thirty Glorious were as glorious as they are meant to be. This is a question that matters in debates about both inequality and the often-bemoaned growth slowdown.

In the past (say before 1950), labor force participation was quite low (relative to today) by virtue of large family sizes and most married women not working. However, when they were at-home, these married women produced something. That something was simply not included in our national accounts. When they entered the labor force, they produced less of that something. However, since it had never been measured, we never subtracted that something from the actual output generated from their increased participation.

Even before the 1950s, this mattered considerably as growth tended to be heavily underestimated (by 0.3 percentage points from 1870 to 1890, overestimated by 0.38 points from 1890 to 1910 and by 0.06 percentage points from 1910 to 1930).This was at a time when variations between the household economy and the market economy were small. Imagine the importance of overestimates since the 1950s! In a short comment reply to Emily Skarbek last year, I pointed out that adjusting for the size of the household economy meant that 1/7th of Canada’s economic growth from 1960 to 1997 (see image below and this was before one additional surge of labor participation resulting from daycare and unemployment policy reforms).

SEcularStagnation2

Recently, I found an old book in my library. It is Kenneth Boulding’s Structure of a Modern EconomyIn it, he makes this exact same argument. Basically, actual output today is overestimated relative to output in the past. And there are many, many, many other articles on this. In all cases, the rate of growth is heavily reduced. In a way, that means that the Thirty Glorious are less glorious (which makes the growth stagnation argument seem more defensible).

And you know what? This is consistent with attempts to correct inequality measures. Most of the attempts made to correct inequality for age, number of workers per household, the size of household and prices, they generally increase very modestly the income growth of the bottom centiles and decrease appreciably the actual level of growth of incomes at the top. While these corrections reduce the level of inequality (and the growth thereof), they also reduce the growth rate of incomes.

Is it possible that the correction to make inequality measures more comparable over time are allow us to see the point about overestimating growth since the 1950s? It means that the Thirty Glorious aren’t that glorious (at the very least, they’re overestimated). It also means that someone who could follow some of the proposed corrections to national income accounts (generally, the best source for this is the Review of Income and Wealth) for every year since 1929 (starting date of the US national accounts which could be extended by using Kuznets’s national income measures from 1913 to 1929) could propose the “actual output” of the country and see how glorious the 1945-1975 period was. That is the work of economic historians to do!

How much has Cuban productivity increased since 1960?

Is it possible for two equally rich countries (on a per capita basis) to have different level of output per worker? The answer is obviously yes, and it matters in the case of measuring growth in Cuba since the revolution.

A country with a very young population will tend to have fewer workers than one with an older (but not too old) population. Let’s say that countries A and B have a median age of 22.5 in year one.  However, in year ten, country A has a median age of 35 but country B has seen a more modest increase to a median age of 25. This will bias any estimates of growth comparison between both country. The increase in the median age suggests that there are more and more workers in country A (people of prime age) than in country B. As a result of that, output per capita will increase faster in country A than in country B even if both countries have equal rates of growth in output per worker.

Well, countries A and B are basically Cuba and most of the rest of Latin America. Since the 1950s, Cuba’s population has aged rapidly but birth rates have plummeted so fast that families shrunk. With fewer kids in the population, it means that the share of the Cuban population that are of prime working age increased rapidly. This is what biases the comparison of Cuban living standards with other Latin American countries.

In the figure below, I took the GDP (the Maddison data) of Cuba since 1950 (indexed at 1960 to see the arrival of Castro) and divided it by the total population, the population above 15 years of age and the population between 15 and 64.

cubagdp

As one can see, with the GDP per capita series, Cubans saw a 50% increase in their incomes between 1960 and 2005 (the Maddison data stops at 2008). However, when you look at GDP per working age adult in order to capture the growth in productive capacity, you get moderately different results whereby the cumulative increase is three-fifths to half as small.

In light of this, it seems like Cuba’s living standards are less and less impressive.