Ten best papers/books in economic history of the last decades (part 2)

01/10/201703/27/2017 Vincent Geloso Economics, History Ann Carlos, economic history, Industrial Revolution, Jan de Vries, living standards, Lowell Gallaway, Native American property rights, property rights, Richard Vedder, Robert Fogel, Roderick Floud, Terry Anderson, unemployment

Yesterday, I published part 1 of what I deemed were the best papers and books in the field of economic history of the last few decades. I posted only the first five and I am now posting the next five.

Carlos, Ann M., and Frank D. Lewis. Commerce by a frozen sea: Native Americans and the European fur trade. University of Pennsylvania Press, 2011.

This book is not frequently cited (only 30 cites according to Google Scholar), but it has numerous gems for scholars to include in their future work. The reason for this is that Carlos and Lewis have pushed the frontier of economic history into the history of Natives in the New World. This issue of Natives in North America is one of those topics that irritates me to no end as an economic historian. A large share of the debates on economic growth in the New World have been centered on the idea that there was either some modest growth (less than 0.5% per year in per capita income) or no growth at all (which is still a strong testimonial given that the population exploded). But all that attention centres on comparing “whites” (and slaves) in the New World with everyone in the Old World. In the first decades of the colonies of Canada and the United States, aboriginals clearly outnumbered the new settlers (in Canada, the native population around 1736 was estimated at roughly 20,000 which was slightly less than the population of Quebec – the largest colony). Excluding aboriginals, who comprised such a large share of the population, at the starting point will indubitably affect the path of growth measured thereafter. My “gut feeling” is that anyone who includes natives in GDP accounting will lower the starting point dramatically. That will increase the rate of long-term growth. Additionally, the output that aboriginals provided was non-negligible and probably grew more rapidly than their population (the rising volume of furs exported was much greater than their population growth). This is why Carlos and Lewis’s work is so interesting: because it is essentially the first to assemble economic continuous time series regarding trade between trappers and traders, the beaver population, property rights and living standards of natives. From their work, all that is needed is a few key defensible assumptions in order to include natives inside estimates of living standards. From there, I would not be surprised that most estimates of growth in the North American colonies would be significantly altered and the income levels relative to Europe would also be altered.

Floud, Roderick, Robert W. Fogel, Bernard Harris, and Sok Chul Hong. The changing body: Health, nutrition, and human development in the western world since 1700. Cambridge University Press, 2011.

This book is in the list because it is a broad overview of the anthropometric history that has arisen since the 1980s as a result of the work of Robert Fogel. I put this book in the list because the use of anthropometric data allows us to study the multiple facets of living standards. For long, I have been annoyed at the idea of this unidimensional concept of “living standards” often portrayed in the general public (which I am willing to forgive) and the economics profession (which is unforgivable). In life, everything is a trade-off. A peasant who left the countryside in the 19th century to get higher wages in a city manufacture estimated that the disamenities of the cities were not sufficient to offset wage gains (see notably Jeffrey Williamson’s Coping with City Growth during the British Industrial Revolution on this). For example, cities tended to have higher food prices than rural areas (the advantage of cities was that there were services no one in the countryside could obtain). Cities were also more prone to epidemics and pollution implied health costs. Taken together, these factors could show up in the biological standard of living, notably on heights. This is known as the “Antebellum puzzle” where the mean heights of individuals in America (and other countries like Canada) fell while there was real income and wage growth. The “Antebellum puzzle” that was unveiled by the work of Fogel and those who followed in his wake represents the image that living standards are not unidimensional. Human development is about more than incomes. Human development is about agency and the ability to choose a path for a better and more satisfying life. However, with agency comes opportunity costs. A choice implies that another path was renounced. In the measurement of living standards, we should never forget the path that was abandoned. Peasants abandoned lower rates of infant mortality, lower overall rates of mortality, the lower levels of crowding and pollution, the lower food prices and the lower crime rates of the countryside in favor of the greater diversity of goods and services, the higher wages, the thicker job market, the less physically demanding jobs and the more secure source of income (although precarious, this was better than the volatile outcomes in farming). This was their trade-off and this is what the anthropometric literature has allowed us to glean. For this alone, this is probably the greatest contribution in the field of economic history of the last decades.

De Vries, Jan. The industrious revolution: consumer behavior and the household economy, 1650 to the present. Cambridge University Press, 2008.

Was there an industrious revolution before the industrial revolution? More precisely, did people increase their labour supply during the 17th and 18th centuries which lead to output growth? In proposing this question, de Vries provided a theoretical bridge of major significance between the observations of wage behavior and incomes in Europe during the modern era. For example, while wages seemed to be stagnating, incomes seemed to be increasing (in the case of England as Broadberry et al. indicated). The only explanation is that workers increased their labor supply? Why would they do that? What happened that caused them to increase the amount of labor they were willing to supply? The arrival of new goods (sugar, tobacco etc.) caused them to change their willingness to work. This is a strong illustration of how preferences can change more or less rapidly (when new opportunities are unveiled). In fact, Mark Koyama (who blogs here) managed to insert this narrative inside a very simple restatement of Gary Becker’s model of time use. Either you have leisure that is cheap but time-consuming (think of leisure in the late middle ages) or leisure that is more expensive but does not consume too much time (think the consumption of tea, sugar and tobacco). Imagine you only have the time-expensive leisure which you value at level X. Now, imagine that the sugar and tea arrive and, although you pay a higher price, it provides more utility than the X level and it takes less time. In such a context, you will likely change your preferences between leisure and work. I am grossly oversimplifying Mark’s point here, but the idea is that the industrious revolution argument advanced by de Vries can easily fit inside a simple neoclassical outlook. On top of solving many puzzles, it also shows that one does not need to engage in some fanciful flight of Marxian theory (I prefer Marxian to Marxist because it is one typo away from being Martian which would adequately summarize my view of Marxism as a social theory). If it fits inside the simpler model, then you don’t need the rest. De Vries does just that.

Anderson, Terry Lee, and Peter Jensen Hill. The not so wild, wild west: Property rights on the frontier. Stanford University Press, 2004.

Governance is not the same as government (in fact, they can be mutually exclusive). In recent years, I have been heavily influenced by Elinor Ostrom’s work on how communities govern the commons in very subtle (but elaborate) ways without the use of coercion. These institutional arrangements are hard to simplify into one variable for a regression, but they are theoretically simple to explain: people respond to incentives. Ostrom’s entire work shows that people on the front line of problems generally have the best incentives to get the right solution because they have skin in the game. What her work shows is that individuals govern themselves (see also Mike Munger’s Choosing in Groups) by generating micro-institutions that allow exchanges to continue. Terry Anderson and Peter Hill provide the best illustration in economic history in that regard by studying the frontier of the American west. Settlers moved to the American West faster than the reach of government and the frontier was thus an area more or less void of government action. So, how did people police themselves? Was it the wild west? No, it was not. Private security firms provided most of the policing, mining clubs established property rights without the need for government, farmers established constitutions in voluntary associations that they formed and many “public goods” were provided privately. The point of Anderson and Hill is that governance did exist on the frontier in a way that demonstrates the ability of voluntary actions (as opposed to coercive government actions) to generate sustainable and efficient solutions. The book has a rich theoretical framework on top of a substantial body of evidence regarding the emergence of institutions. Any good economic historian should own and read this book.

Vedder, Richard K., and Lowell E. Gallaway. Out of work: unemployment and government in twentieth-century America. NYU Press and Independent Institute, 1997.

The last book on the list is an underground classic for me. Richard Vedder and Lowell Gallaway are very good economic historians. It was produced like many other underappreciated classics (like Higgs’s Crisis and Leviathan) by the Independent Institute (see their great book list here). Most of their output was produced from the 1960s to the 1980s. However, as the 1990s came, they moved towards the Austrian school of Economics. With them, they brought a strong econometric knowledge – a rarity among Austrian scholars. They attempted one of the first (well-regarded) econometric studies that relied on Austrian theory of the labor-market (a mixture of New Classical Theory with Austrian Theory). Their goal was to explain variations in unemployment in the United States by variations in “adjusted real wages” (i.e. unit labor costs) all else being equal. At the time of the publication, they used very advanced econometric techniques. The book was well received and even caught the attention of Brad DeLong who disagreed with it and debated Vedder and Gallaway in the pages of Critical Review. Although there are pieces that I disagree with, the book has mostly withstood the test of time. The core insights of Out of Work regarding the Great Depression (and many of its horrible policies like the National Industrial Recovery Act) have been conserved by many like Scott Sumner in his Midas Paradox and they feature prominently in the works of scholars like Lee Ohanian, Harold Cole, Jason Taylor, Price Fishback, Albrecht Ristchl and others. In the foreword to the book, they mention that D.N. McCloskey (then the editor of the Journal of Economic History) had pushed hard for them to publish their work regarding the 1920s and 1930s. McCloskey was right to do so as many of their contentions are now accepted as a legitimate (if still debated) viewpoint. The insights regarding the “Great Depression of 1946” (a pun to ridicule the idea that the postwar reduction in government expenditures led to a massive reduction in incomes) have been generally conserved by Robert Higgs in his Journal of Economic History article I mentioned yesterday (and in this article as well) and even by Alexander Field in his Great Leap Forward. However, Out of Work remains an underground classic that is filled with substantial pieces of information and data that remains unused. There are numerous unexploited insights (some of which Vedder and Gallaway have followed on) as well. The book should be mandatory reading for any economic historian.

Ten best papers/books in economic history of the last decades (part 1)

01/09/201701/09/2017 Vincent Geloso Economics, History abundance, Alan Olmstead, demographics, economic history, Integration, Paul Rhode, productivity, Robert Allen, Robert Higgs, Roman Studer, Stephen Broadberry, wartime economy

In my post on French economic history last week, I claimed that Robert Allen’s 2001 paper in Explorations in Economic History was one of the ten most important papers of the last twenty-five years. In reaction, economic historian Benjamin Guilbert asked me “what are the other nine”?

As I started thinking about the best articles, I realized that such a list is highly subjective to my field of research (historical demography, industrial revolution, great divergence debate, colonial institutions, pre-industrial Canada, living standards measurement) or some of my personal interests (slavery and the great depression). So, I will propose a list of ten papers/works that need to be read (in my opinion) by anyone interested in economic history. I will divide this post in two parts, one will be published today, the other will come out tomorrow.

Higgs, Robert. “Wartime Prosperity? A Reassessment of the US Economy in the 1940s.” Journal of Economic History 52, no. 01 (1992): 41-60.

Higgs’s article (since republished and expanded in a book and in follow-ups like this Independent Review article) is not only an important reconsideration of the issue of World War II as a causal factor in ending the Great Depression, it is also an efficient primer into national accounting. In essence, Higgs argues that the war never boosted the economy. Like Vedder and Gallaway, he argues that deflators are unreliable as a result of price controls. However, he extends that argument to the issue of measuring GDP. In wartime, ressources are directed, not allocated by exchange. Since GDP is a measure of value added in exchanges, the wartime direction of resources does not tell us anything about real production. It tells us only something about the government values. As a result, Higgs follows the propositions of Simon Kuznets to measure the “peacetime concept” of GDP and finds that the prosperity is overblown. There have been a few scholars who expanded on Higgs (notably here), but the issues underlined by Higgs could very well apply to many other topics. Every year, I read this paper at least once. Each time, I discover a pearl that allows me to expand my research on other topics.

Allen, Robert C. The British industrial revolution in global perspective. Cambridge: Cambridge University Press, 2009.

I know I said that Allen’s article in Explorations was one of the best, but Allen produces a lot of fascinating stuff. All of it is generally a different component of a “macro” history. That’s why I recommend going to the book (and then go to the article depending on what you need). The three things that influenced me considerably in my own work were a) the use of welfare ratios, b) the measurement of agricultural productivity and c) the HWE argument. I have spent some time on items A and C (here and here). However, B) is an important topic. Allen measured agricultural productivity in England using population levels, prices and wages to proxy consumption in a demand model and extract output from there (see his 2000 EREH paper here). As a result, Allen managed to compare agricultural productivity over time and space. This was a great innovation and it is a tool that I am looking to important for other countries – notably Canada and the US. His model gives us the long-term evolution of productivity with some frequency. In combination with a conjonctural estimate of growth and incomes or an output-based model, this would allow the reconstruction (if the series match) of a more-or-less high frequency dataset of GDP (from the perspective of an economic historian, annual GDP going back into the 17th century is high-frequency). Anyone interested in doing the “dirty work” of collecting data, this is the way to go.

Broadberry, Stephen, Bruce MS Campbell, Alexander Klein, Mark Overton, and Bas Van Leeuwen. British economic growth, 1270–1870. Cambridge University Press, 2015.

On this one, I am pretty biased. This is because Broadberry (one of the authors) was my dissertation supervisor (and a pretty great one to boot). Nonetheless, Broadberry et al. work greatly influenced my Cornucopian outlook on the world. Early in my intellectual development, I was introduced to Julian Simon’s work (see the best of his work here and here and Ester Boserup whose argument is similar but more complex) on environmental trends. While Simon has generally been depicted as arguing against declining environmental indicators, his viewpoint was much broader. In essence, his argument was the counter-argument to the Malthusian worldview. Basically, Malthusian pressures caused by large populations which push us further down the curve of marginally declining returns have their countereffects. Indeed, more people means more ideas and ideas are non-rival inputs (i.e. teaching you to fish won’t make me unlearn how to fish). In essence, rising populations are no problems (under given conditions) since they can generate a Schumpeterian countereffect (more ideas) and a Smithian countereffect (size of market offsets). In their work, Broadberry et al. basically confirm a view cemented over the last few decades that England had escaped the Malthusian trap before the Industrial Revolution (see Crafts and Mills here and Nicolinni here). They did that by recreating the GDP of Britain from 1270 to 1870. They found that GDP per capita increased while population increased steadily which is a strong piece of evidence. In their book, Broadberry et al. actually discuss this implication and they formulate the Smithian countereffect as a strong force that did offset the Malthusian pressures. Broadberry and al. should stand in everyone’s library as the best guidebook in recreating long-term historical series in order to answer the “big questions” (they also contribute to the Industrious Revolution argument among many other things).

Chilosi, David, Tommy E. Murphy, Roman Studer, and A. Coşkun Tunçer. “Europe’s many integrations: Geography and grain markets, 1620–1913.” Explorations in Economic History 50, no. 1 (2013): 46-68.

Although it isn’t tremendously cited yet, this is one of the best article I have read (and which is also recounted in Roman Studer’s Great Divergence Reconsidered). This is because the paper is one of the first to care about market integration on a “local” scale. Most studies of market integration consider long-distance trade for grains and they generally start with the late 19th century which is known as the first wave of globalisation. However, from an economic historian perspective, this is basically studying things once the ball had already started rolling. Market integration is particularly interesting because it is related to demographic outcomes. Isolated markets are vulnerable to supply shocks. However, with trade it is possible to minimize shocks by “pooling” resources. If village A has a crop failure, prices will rise inciting village B where there was an abundant crop to sell wheat to village A. In the end, prices in village A will drop (causing fewer deaths from starvation) and increase in village B. This means that prices move in a smoother fashion because there are no localized shocks (see the work of my friend Pierre Desrochers who argues that small local markets were associated for most of history with high mortality risks). In their work, Chilosi et al. decide to consider the integration of markets between villages A and B rather than between country A and B. Basically, what they wonder is when geographically close areas became more integrated (i.e. when did Paris and Bordeaux become part of the same national market?). They found that most of Europe tended to be a series of small regions that were more or less disconnected from one another. However, over time, these regions started to expand and integrate so that prices started moving more harmoniously. This is an important development that took place well before the late 19th century. In a way, the ball of market integration started rolling in the 17th century. Put differently, before globalization, there was regionalization. The next step to expand on that paper would be to find demographic data for one of the areas documented by Chilosi et al. and see if increased integration caused declines in mortality as markets started operating more harmoniously.

Olmstead, Alan L., and Paul W. Rhode. Creating Abundance. Cambridge Books (2008).

This book has influenced me tremendously. Olmstead and Rhode contribute to many literatures simultaneously. First of all, they show that most of the increased in cotton productivity in the United States during the antebellum era came from crop improvements. Secondly, they show that these improvements occured with very lax patents systems. Thirdly, they show how crucial biological innovations were in determining agricultural productivity in the United States (see their paper on wheat here and their paper on induced innovation). On top of being simply a fascinating way of doing agricultural history (by the way, most economic history before 1900 will generally tend to be closely related to agricultural history), it forces many other scholars to reflect on their own work. For example, the rising cotton productivity explains the rising output of slavery in the antebellum south. Thus, there is no need to rely on some on the fanciful claims that slaveowners became more efficient at whipping cotton out of slaves (*cough* Ed Baptist *cough*). They also show that Boldrine and Levine are broadly correct in stating that most types of technological innovations do not require extreme patents like those we know today (and which are designed to restrict competition rather than promote competition). In fact, their work on biological innovations have pretty much started a small revolution in that regard (see one interesting example here in French). Finally, they also invalidated (convincingly in my opinion) the induced innovation model that generally argued that technologies are developped merely to ease scarcities of factors. While theoretically plausible, this simplified model did not fit many features of American economic history. Their story of biological innovations is an efficient remplacement.

On How Poor France Was in the 18th Century?

01/06/2017 Vincent Geloso Liberty economic history, France, French Economic History, Strasbourg

I have recently completed a working paper which has now been submitted (thank you a great many scholars who provided comments notably Judy Stephenson and Mark Koyama). That paper basically went back modestly on one datapoint in the work of Robert Allen which was published in 2001 in Explorations in Economic History.

Probably one of the greatest ten papers in the field of economic history for the last twenty-five years, Allen’s article has had a tremendous influence. It introduced a new method of comparing real wages at a time when very few goods were traded internationally and most prices were determined at the local level. In using what we now call “welfare ratios” (which are akin to poverty lines), Allen managed to compare many countries before the industrial revolution.

My entire research agenda has been to improve on this stupendous work and to increase the constellation of observations as part of an “uncoordinated” (many scholars are working on this separately) effort to map living standards prior to the mid 19th century. The main part of my agenda is to add Canada and devote more attention to the important issue of relative prices in comparing old world (high labor to land ratios) and new world (high land to labor ratios) economies. In the process of comparing parts of the world, I had to re-examine some data for some established countries. One of my reconsiderations was for Strasbourg in France where I found that Allen might have misclassified wages of skilled workers which included in-kind payments as unskilled workers receiving full compensation in money wages.

When I enacted corrections to the money wage rate, I found that the Alsace region where Strasbourg is located had living standards more or less in line with those observed in Paris (rather than living standards at less than half the level of Paris). If you’re interested, the note is available here.

Note: For those who are interested, I really recommend reading this short article in Cliometrica by Sharp and Weisdorf who also discuss comparisons between France and England (and how it may relate to topics like the French Revolution).

Minimum wage and length of poverty spells

01/03/201701/03/2017 Vincent Geloso Economics employment, Mark Koyama, minimum wage, poverty, poverty alleviation, unemployment

I had a pre-programmed blog post on the issue of the minimum wage and poverty which was preempted by Mark Koyama (a blogger here at Notes on Liberty). The tweet is below and it has forced me to adjust the post.

An important & often neglected point. Minimum wage is s bad anti-poverty tool even if employment effects are zero https://t.co/lVEqwEhglz

— Mark Koyama (@MarkKoyama) 3 janvier 2017

Mark is absolutely right! Let me explain why with my own spin on it.

First of all, the demand curve slopes downwards – always. However, the method of adjusting to price changes (wages are a price and the minimum wage is a price control) is not an empirical constant. I am unlikely to fire workers for a 1% in the inflation-adjusted minimum wage. Firing workers implies transaction costs that are dependent of context (for example, if I am friend with my employee, this is a transaction cost in the form of a lost friendship), firm size (I won’t fire my only employee which represents 50% of my output for a 1% hike in MW) laws (firing and hiring regulations), institutions (social institutions, reputation, norms), my clientele (how elastic is their demand) and technological alternatives. For a 1% increase, I am likely to reduce work hours or cut marginal benefits (no free soup for you). For a 10% increase, I am more likely to consider the option of firing a worker or I may shift to a new technological set that reduces my demand for labor. It may happen rapidly or take some time, but there will eventually be an adjustment.

In any case, the minimum wage will imply some losses with a deadweight loss. Only the method by which it materializes is debatable. By definition, some people will be hurt and generally and even if supply is super-elastic (doubtful), some suppliers (workers) will be ejected from the market (or the quantity of labor they can supply will be ulitmately reduced). Since the minimum wage generally tends to fall on unskilled workers, this must be correlated with workers close to the poverty line.

Ideally, we’d need a measure of the minimum wage to be compared with the “at-risk” population over a long period of time in order to encapsulate all the effects of the minimum wage. The perfect measure is the “length of poverty spell” variable which has been emerging progressively from the BLS. The problem is that it is not broken down by state. Fortunately, Canada has that variable (well, a low-income variable which is a relatie poverty measure) for provinces. Inside the Survey of Labor and Income Dynamics (affectionally known as the SLID), this longitudinal variable has a span of eight years. Basically, we can know if a person has been below the low-income threshold for up to eight years. Let’s take that extreme measure and plot it against the minimum wage divided by the average wage.

As one can see from the scatter plot below, there is a more or less clear relationship between the minimum wage as a share of the average wage and the length of poverty spells. What is more impressive is that this graph is not a regression. More precisely, the provinces with the highest minimum wages (like my own province of Quebec and the province of Nova Scotia) also have the most extensive social welfare nets. Alberta, a province with the lowest minimum wage ratio and one of the least “generous” social welfare net in Canada, is at the very bottom of the pack in terms of the persistence of poverty.

minimumwagepoverty

I think this graph acts in very modest (but clear) support to Mark’s point (which is also the point of Burkhauser, Sabia, MaCurdy and many others)

Stock markets and economic growth: from Smoot-Hawley to Donald Trump

12/30/201612/30/2016 Vincent Geloso Economics, History Bernard Beaudreau, economic history, free trade, Great Depression, international trade, protectionism, Smoot-Hawley, Steve Horwitz, stock market

In a recent article for the Freeman, Steve Horwitz (who has the great misfortune of being my co-author) argued that stock markets tell us very little about trends in economic growth. Stock markets tell us a lot about profits, but profits of firms on the stock market may be higher because of cronyism. Basically, that is Steve’s argument. He applies this argument in order to respond to those who say that a soaring stock market is the proof that Donald Trump is “good” for the economy.

I know Steve’s article was published roughly a month ago, so I am a little late. But I tend to believe it is never too late to talk about economic history. And basically, its worth pointing out that there are economic history examples to show Steve’s point. In fact, its the best example: Smoot-Hawley.

Bernard Beaudreau from Laval University has advanced, for some years, an underconsumptionist view of the Great Depression (I consider it a “dead theory”). While I am highly unconvinced by this theory (in both its original and current “post-keynesian” reformulation), Beaudreau tries hard to resurrect the theory (see here and here) and merits to be discussed. In the process, Beaudreau attempted to reestimated the effects of of Smoot-Hawley on the stock market with an events study. Unconvinced about the rest of his research, this is a clear instance of sorting the wheat from the chaff. In this case, the wheat is his work (see here for his article in Essays in Economic and Business History) on Smoot-Hawley.

Basically, Beaudreau found that good news regarding the probability of the adoption of the tariff bill actually pushed the stock market to appreciate. Thus, Smoot-Hawley -which had so many negative macroeconomic ramifications* – actually boosted the stock market. Firms that gained from the rising tariffs actually saw greater profits for themselves and thus the firms on the stock market would have been excited at the prospect of restricting their competitors. If that is true, could it be that Donald Trump is the modern equivalent (for the stock market) of Smoot-Hawley.

*NDLR: I believe that Allan Meltzer was right in saying that the Smoot-Hawley might have had monetary ramifications that contributed to the money supply collapse. It was a real shock that precipitated the collapse of weak banks which then caused a nominal shock and then the sh*t hit the proverbial fan.

On 19th Century Tariffs & Growth

12/26/201612/26/2016 Vincent Geloso Economics, History Canada, economic development, economic growth, economic history, Frank Lewis, growth, Ian Keay, James Buchanan, Kris Inwood, Marvin McInnis, MC Urquhart, Pseudoerasmus, tariffs

A few days ago, Pseudoerasmus published a blog piece on Bairoch’s argument that in the 19th century, the countries that had high tariffs also had fast growth. It is a good piece that summarizes the litterature very well. However, there are some points that Pseudoerasmus eschews that are crucial to assessing the proper role of tariffs on growth. Most of these issues are related to data quality, but one may be the result of poor specification bias. For most of my comments, I will concentrate on Canada. This is because I know Canada best and that it features prominently in the literature for the 19th century as a case where protection did lead to growth. I am unconvinced for many reasons which will be seen below.

Data Quality

Here I will refrain my comments to the Canadian data which I know best. Of all the countries with available income data for the late 19th century, Canada is one of those with the richest data (alongside the UK, US and Australia). This is largely thanks to the work of M.C. Urquhart who recreated the Canadian GNP series fom 1870 to 1926 in collaborative effort with scholars like Marvin McInnis, Frank Lewis, Marion Steele and others.

However, even that data has flaws. For example, me and Michael Hinton have recomputed the GDP deflator to account for the fact that its consumption prices component did not include clothing. Since clothing prices behaved differently than the other prices from 1870 to 1885, this changes the level and trend of Canadian incomes per capita (this paper will be completed this winter, Michael is putting the finishing touch and its his baby). However, like Morris Altman, our corrections indicate a faster rate of growth for Canada from 1870 to 1913, but in a different manner. For example, there is more growth than believed in the 1870-1879 period (before the introduction of the National Policy which increased protection) and more growth in the 1890-1913 period (the period of the wheat boom and of easing of trade restrictions).

Moreover, the work of Marrilyn Gerriets, Alex Chernoff, Kris Inwood and Jim Irwin (here , here, here, here) that we have a poor image of output in the Atlantic region – the region that would have been adversely affected by protectionism. Basically, the belief is a proper accounting of incomes in the Atlantic provinces would show lower levels and trends that would – at the national aggregated level – alter the pattern of growth.

I also believe that, for Quebec, there are metrological issues in the reporting of agricultural output. The French-Canadians tended to report volume units in manners poorly understood by enumerators but that these units were larger than the Non-French units. However, as time passed, census enumerators caught on and got the measures and corrections right. However, that means that agricultural output from French-Canadians was higher than reported in the earlier census but that it was more accurate in the later censuses. This error will lead to estimating more growth than what actually took place. (I have a paper on this issue that was given a revise and resubmit from Agricultural History).

Take all of these measurements issue and you have enough doubt in the data underlying the methods that one should feel the need to be careful. In fact, if the sum of these (overall) minor flaws is sufficient to warrant caution, what does it say about Italian, Spanish, Portugese, French, Belgian, Irish or German GDP ( I am not saying they are bad, I am saying that I find Canada’s series to be better in relative terms).

How to measure protection?

The second issue is how to measure protection. Clemens and Williamson offered a measure of import duties revenue over imports volume. That is a shortcut that can be used when it is hard to measure effective protection. But, it may be a dangerous shortcut depending on the structure of protection.

Imagine that I set an import duty so high as to eliminate all entry of the good taxed (like Canada’s 300% import tax on butter today). At that level, there is zero revenue from butter import and zero imports of butter. Thus, the ratio of protection is … zero. But in reality, its a very restrictive regime that is not being measured.

More recent estimates for Canada produced by Ian Keay and Eugene Beaulieu (in separate papers, but Keay’s paper was a conference paper) attempted to measure more accurate indicators of protection and the burden imposed on Canadians. Beaulieu and his co-author found that using a better measure, Canada’s trade policy was 11% more restrictive than believed. Moreover, they found that the welfare loss kept increasing from 1870 to 1890 – reaching a figure equal to roughly 1.5% of GDP (a non-negligible social cost).

It ought to be noted though that alongside Lewis and Harris, Keay has found that the infant industry argument seems to apply to Canada (I am not convinced, notably for the reasons above regarding GDP measurements). However, that was in the case of Canada only and it could have been a simple outlier. Would the argument hold if better trade restriction measures were gathered for all other countries, thus making Canada into a weird exception?

James Buchanan to the rescue

My last argument is about political economy. Was the institutional arrangement of protection a way to curtail government growth? Protection is both a method for helping national industries and for raising revenues. However, the government cannot overprotect at the risk of loosing revenues. It must protect just enough to allow goods to continue entering to earn revenues from imports. This tension is crucial especially since most 19th century countries did not have uniform general tariffs (like a flat 5% import duty) which would have very wide bases. The duties tended to concern a few goods very heavily relative to other goods. This means very narrow tax bases.

Standard public finance theory mandates wide tax bases with a focus on inelastic sources. However, someone with a public choice perspective (like James Buchanan) will argue that this offers the possibility for the government to grow. Basically, a public choice theorist will argue that the standard public finance viewpoint is that the sheep is tame. Self-interested politicians will exploit this tameness to be elected and this might imply growing government. However, with a narrow and elastic tax base, politicians are heavily constrained. In such a case, governments cannot grow as much.

The protection of the 19th century – identified by many as a source of growth – may thus simply be the symptom of an institutionnal arrangement that was meant to keep governments small. This may have stimulated growth by keeping other sectors of the economy more or less free of government meddling. So, maybe protection was the offspring of the least flawed institutional arrangement that could be adopted given the political economy of the time.

This last argument is the one that I find the most convincing in rebuttal to the Bairoch argument. It means that we are suffering from a poor specification bias: we have identified a symptom of something else as the cause of growth.

Spanish GDP since 1850

12/23/201612/23/2016 Vincent Geloso Economics Angus Maddison, economic development, economic growth, GDP per capita, Leandro Prados de la Escosura, Spain, statistics

Among the great economic historians is Leandro Prados de la Escosura. Why? Because, before venturing in massively complex explanations to explain academic puzzles, he tries to make sure the data is actually geared towards actually testing the theory. That attracts my respect (probably because it’s what I do as well which implies a confirmation bias on my part). Its also why I feel that I must share his most recent work which is basically a recalculation of the GDP of Spain.

The most important I see from his work is that the recomputation portrays Spain as a less poor place than we have been led to believe – throughout the era. To show how much, I recomputed the Maddison data for Spain and compared it with incomes for the United Kingdom and compared it Leandro’s estimates for Spain relative to those for Britain (the two methods are very similar thus they seem like mirrors at different levels). The figure below emerges (on a log scale for the ratio in percentage points). As one can see, Spain is much closer to Britain than we are led to believe throughout the 19th century and the early 20th century. Moreover, with Leandro’s corrections, Spain convergence towards Britain from the end of the Civil War to today is very impressive.

spanishgdp

The only depressing thing I see from Leandro’s work is that Spain’s productivity (GDP / hours worked) seems to have stagnated since the mid-1980s.

spanishproductivity

On getting the data right : price disparities before 1914

12/22/201612/23/2016 Vincent Geloso Economics Angus Maddison, economic growth, economic history, GDP (PPP) per capita, Joshua Hendrickson, Peter Lindert

I am a weird bird. I get excited at weird things. I get excited at reading economics and history papers (and books). I get particularly excited when I read papers and books that “get the data right”. This is because I believe that most theoretical debates in economics stem from poor data forcing us to develop grandiose theories or very advanced models to explain simple things. One example of that is the work of Joshua Hendrickson who argued that monetary aggregates (M1, M2 etc.) are not necessarily perfect indicators of money. However, these aggregates were used in statistical tests and generated strange results inconsistent with theory. This issue has been the cause of many debates. Josh stepped in and said that we just had a variable that was not created to measure what the theory said. Using broader measures of money, he found the results consistent with theory. The debates were driven by poor data (as I think is the case in issues over fiscal multipliers, crowding-out and business cycles).

Thus, I am always excited to see data work that “get things right”. One recent example that adds to cases like that of Hendrickson is Peter Lindert’s working paper at the National Bureau of Economic Researcher. Now, before I proceed, I must state that I am very partial to Lindert as he has been a big supporter of my own research and has volunteered important quantities of his time to helping me move forward. Thus, I have a favorable bias towards Lindert (and his partner in crime, Jeffrey Williamson). Nonetheless, his working paper requires a discussion because it “gets prices right”.

The essence of his new working paper is that our GDP per capita estimates prior to 1914 may overestimate divergence between countries over time.

Generally, when we measure GDP, we try to derive “volume indexes” that measure quantities produced at a fixed vector of prices. For example, when I measured Canadian economic growth from 1688 to 1790 (I am submitting it in a few weeks), I took the quantities of grain reported in censuses and weighed them by prices for a fixed year. This is a good approach for measuring productivity (changes in quantities). Nonetheless, there are issues when you try to move this method over a very long period in time. The prices may become unrepresentative. So you get time-related distortions. Add to this that all the time-related distortions may be different over space. After all, should we believe the relative price of wheat to oats in 1910 was the same in Canada as it was in Russia? Variations in relative prices over space will affect this issue. Basically, you juxtapose these two types of distortions when trying to measure GDP per capita over centuries and you may end up so far in the left field that you’re in fact in the right field.

In his working paper, Lindert tried to adjust for those problems by moving to prices that were more representative. The approach he used is basically the one used by Robert Allen in his work on the Great Divergence. You create a bundle of goods that capture the cost of living in different regions – a basic bundle of goods. This generates purchasing power parities. From there, he recomputed incomes per capita with these measures prior to 1914. The results are striking: there is much more divergence between Europe and Asia that commonly proposed and the United States are much richer than otherwise believed (and were more richer very early on – as far back as the colonial era).

Now, why does this matter?

Well, consider the debate on convergence. Many scholars have been unimpressed by the level of income convergence across countries (at least until the 1980s). However, Lindert’s estimates suggest that the starting point was well below what we think it was. In a way, what this is telling us is that many puzzles regarding the “catching-up” of poor countries may be simply related to poor data. Imagine, for a second, that we could redo what Lindert did with many more countries at a higher time frequency. What would this tell us? Imagine also that this new data would confirm Lindert’s point, what would that entail for those entangled in debates over development?

Basically, what I am saying is this: most of our debates often stem from poor data. If a simple (and theoretically sound) correction can eliminate the puzzles, maybe our task as economists should be to stop bickering over advanced theory and make sure the data is actually geared towards testing our theories!

How Well Has Cuba Managed To Improve Health Outcomes? (part 2)

12/20/201612/21/2016 Vincent Geloso Economics, History Brazil, Car ownership, Castro, Chile, communism, Cuba, Cuba in Transition, Economic Freedom, economic history, Fidel, health, health care

In a recent post, I pointed out that life expectancy in Cuba was high largely as a result of really low rates of car ownerships. Fewer cars, fewer road accidents, higher life expectancy. As I pointed out using a paper published in Demography, road fatalities reduced life expectancy by somewhere between 0.2 and 0.8 years in Brazil (a country with a car ownership rate of roughly 400 per 1,000 persons). Obviously, road fatalities have very little to do with health care. Praising high life expectancy in Cuba as the outcome Castrist healthcare is incorrect, since the culprit seems to be the fact that Cubans just don’t own cars (only 55 per 1,000). But that was a level argument – i.e. the level is off.

It was not a trend argument. The rapid increase in life expectancy is undeniable, so my argument about level won’t affect the claim that Cubans saw their life expectancy increase under Castro.

I say “wait just a second”.

Cuba is quite unique with regards to car ownership. In 1958, it had the second highest rate of car ownership of all Latin America. However, while the rate went up in all of Latin America between 1958 and 1988, it went down in Cuba. During that period, life expectancy went up in all countries while there were substantial increases in car ownership (which would, all things being equal, slow down life expectancy growth). Take Chile and Brazil as example. In these countries, the rate went up by 6.9% and 8.1% every year – these are fantastic rates of growth. During the same period, life expectancy increased 25% in Chile and 19% in Brazil compared with Cuba where the increase stood at 17%. In Cuba, the moderate decline in car ownership (-0.1% per annum) would have (very) modestly contributed to the increase of life expectancy. In the other countries, car ownership hindered the increase. (The data is also from the WHO section on Road Safety while the life expectancy data is from the World Bank Database)

This does not alter the trend of life expectancy in Cuba dramatically, but it does alter it in a manner that forces us, once more, to substract from Castro’s accomplishments. This increase would not have been the offspring of the master plan of the dictator, but rather an accidental side-effect springing from policies that depressed living standards so much that Cubans drove less and were less subjected to the risk of dying while driving. However, I am unsure as to whether or not Cubans would regard this as an “improvement”.

Below are the comparisons between Cuba, Chile and Brazil.

cars

The other parts of How Well Has Cuba Managed To Improve Health Outcomes?

Life Expectancy Changes, 1960 to 2014
Car ownership trends playing in favor of Cuba, but not a praiseworthy outcome
Of Refugeees and Life Expectancy
Changes in infant mortality
Life expectancy at age 60-64
Effect of recomputations of life expectancy
Changes in net nutrition
The evolution of stature
Qualitative evidence on water access, sanitation, electricity and underground healthcare
Human development as positive liberty (or why HDI is not a basic needs measure)

On quasi-rents and the minimum wage

12/19/201612/19/2016 Vincent Geloso Economics economic development, Economics Bulletin, minimum wage, public policy, Ryan Murphy

Ryan Murphy of Southern Methodist University has a new article published in Economics Bulletin regarding the minimum wage and “quasi-rents”. The argument made by Ryan has the advantage of theoretically fleshing out a point made by many skeptics of the new literature. Generally, the argument has been that in the short-term, the minimum wage may have minimal effects, but in the long-term, firms will adjust.

I tended, until Ryan’s article, to be more or less skeptic of the value of this counter-argument. My point has always been that the new literature (like the Dube-Lester-Reich paper) tends to act as a partial equilibrium story (focusing only on one sector only or one indicator). My view has always been very “Coasian” in the sense that there are transaction costs to adapting to any new minimum wage rate.

The height of the hike and what industries are primarily affected will determine the method of adjustments. Firms can cut on benefits, substitute between forms of labor (the minimum wage increases the supply of older workers which remplace younger inexperienced workers), hours or training. They can also, depending on the elasticity of demand for their products, increase prices or cut quality. They can also cut employment. All of these are channels of adjustment and they will be used differently depending on the context. They are all different expressions of the fact that the demand curve slopes downward. But each expression has costs to be used that are to be weighted against their benefits – which are highly circumstantial. For example, if I have a firm of two employees, I will not sacrifice half my workforce by firing a worker (thus sacrificing 50% of my output) for a 5% hike in the minimum wage. Not only would this be an over-reaction, but there are transaction costs for me to fire that worker : separation fees, emotional pain, learning what the employee was doing etc. Reducing his hours would be a safer adjustment.

Until there is a study that measures all of these adjustments channels at once, I am skeptical.

So where does Ryan’s story come in? Well, none of my arguments had a long-term component. They were largely void of any time dimension. While I am aware of research like those of Meer and West, Clemens and Wither and Clemens regarding job growth patterns following minimum wage hikes, I always discounted that argument. I was always reluctant to engage in long-term reasoning because I felt it was conceding a point that ought not to be conceded even if that counter-point is valid. I only used it to top up the rest of my argument. But Ryan introduced to me the concept of quasi-rents, of which I had vaguely heard during my undergraduate microeconomics class.

Basically, here is the argument about quasi-rents: in the short-term, there are rents to be extracted from fixed factors of productions. Firms need these quasi-rents to remain in business, but only in the long-run. However, if labor can find a way to capture the rents in the short-run, they will get higher earnings and employers will not fire people as much. As a result, there is basically a reshuffling of the consumer surplus. However, in the long-run, nothing is fixed and firm owners can adjust by shifting to different production methods. Thus, they will reduce their future hirings. In Ryan’s words:

But the on-impact negative effects of minimum wages may be hidden. In the longer run, after the quasi-rent is dissipated, the owner would have the incentive to eventually switch from more labor-intensive methods to ones that are less globally efficient (this being the conventional “demand slopes down” result). More perniciously, the threat of future increases in the minimum wage may create regime uncertainty undermining a willingness to invest in the types of technology and capital complementary to low skilled labor, thereby reducing employment for low skilled workers. That is to say, the risk of the appropriation of quasi-rents can shift investment towards capital unlikely to be appropriated via the minimum wage. Repeated and arbitrary increases in the minimum wage worsen this risk. This is consistent with the recent shift towards long run effects of increases in the minimum wage, for instance Meer and West (2016).

This is exactly what Andrew Seltzer found for the introduction of the minimum wage during the Great Depression in certain American industries. In the short-term, the capital was more or less fixed and production methods could not be abandonned easily. In the long run, firms adapted and shifted production methods. This is why Ryan’s argument is convincing. It offers a theoretical explanation for the empirical results observed by Dube, Lester and Reich or Card and Krueger. It fits well with theories of imperfect markets (damn I hate that word that is basically saying that all markets have frictions) like those of Alan Manning (see his Monopsony in Motion here).

This is the kind of work on the minimum wage that, if measured, should force considerable requestionning on the part of minimum wage hike advocates.

Canadian Megatrends: Top 1% income share and median age

12/19/201612/19/2016 Vincent Geloso Economics, Liberty Canada, demographics, income inequality, inequality, Norway, statistics

Statistics Canada just came up with a study on the top income share of the top 1% in Canada. As I have explained elsewhere, my view of inequality is that: a) it has increased; b) not as much as we think; c) a lot of the increase is from desirable factors (personal utility maximization differing from income maximization or international immigration) or neutral factors (demography, marriage); d) that the inequality that is worrisome stems either from birth or government manipulations of the market and; e) that those stemming from government manipulations, direct (like subsidizing firms) or indirect (like the war on drugs which means that a large number of individuals are jailed and then released with a “prison earnings penalty” which stymies their income levels and growth), are the easiest to fight.

The recent Statistics Canada study allows me to make my point again with regards to element C of my answer. As I looked at their series, all I could think was “median age”. A lot of the variations seem to be related to the median age of the population. I went back to the census data I had collected for my book and plotted it against the data. This is what it looks like.

medianage

Why would there be a relation? Well, each year you measure the income distribution, the demographic structure of that population changes. As it grows older, you have more people at the top of their earnings curve relative to those at the bottom. Not only that, but earnings curve seem elongated in recent times – we live longer and so some people work older as witnessed by increased labor force participation rates above a certain age closer to retirement. And the heights of the earnings curve are now higher than ever before while we also enter later into the labor market.

Now, I am not sure how much aging would “explain away” rising inequality in Canada, but there is no point denying that it does explain some of it away. But, I would not be surprised that a large part is explained away. Why am I saying that? Because of this paper on Norway’s age structure.

In Norway, the median age in 1950 was much higher than it was in Canada back then and today, it is roughly the same as Canada (although Canada has had a steeper increase in inequality). And according to the paper on Norway, adjusting for composition bias in inequality measures caused by aging, eliminates entirely the upward trend in that country. In fact, it may even reverse the trend whereby inequality adjusted for age has actually declined over time. This is a powerful observation. Given that Canada has had a steeper increase in median age, this suggests that the increase in inequality might be simply the cause of a statistical artifice.

Has Canada been Poorer than the US for so long?

12/16/201612/21/2016 Vincent Geloso Economics, History, Liberty Canada, Canadian economy, economic growth, economic history, History, Native American property rights, Native Americans, Natives

A standard stylized fact in Canada is that we are poorer, on average, than the average American. This has been presented as a fact that is as steady as the northern star. But our evidence on Canadian incomes is pretty shoddy prior to 1870 (here I praise M.C. Urquhart for having designed a GNP series that covers from 1870 to 1926 and links up with the official national accounts even if I think there are some improvements that can be brought to measuring output from some key industries and get the deflator right). But what about anything before 1870? There are some estimates for Ontario from 1826 to 1851 by Lewis and Urquhart (great stuff), but Ontario was pretty much the high-income of Canada.

So, can we go further back? This is what my work is about (partially), and I just made available my results on Canadian living standards (proxied by Quebec where the vast majority of the population was) from 1688 to 1775 as captured by welfare ratios. So that’s pretty much the closest we can get to the “founding”. Below are my results derived from this paper. They show that the colonists in Canada were not very much richer than their counterparts in France with the basket meant to capture the meanest of subsistence and roughly equal to their counterparts in France with a basket that includes more manufactured goods like clothing and more alcohol. This explains why most migrants from France to Canada were “volunteered” (in the sense that they were pretty much reluctant migrants) for migration. But the key interesting result is that relative to New England – the poorest of the American colonies – it is poorer regardless of the basket used. Thus, there seems to be truth to the common logic about Canadians being always poorer than the Americans.

comparingcanadane

However, I am not fully convinced of my own results. This may surprise some. The reason is not that I do not trust my data (in fact, I think it is superior to most of what exists for the time given that I will be able to proceed to tons of other data). The reason is simple (and rarely discussed): natives.

Natives are always omitted from the stories of living standards. But they existed nonetheless. In terms of national accounts, if the British and French settlers dispossessed and killed natives, their welfare losses are just not computed. But the welfare losses of a musket shot to the head are real. I have always been convinced that if we could correct estimates of living standards to account for the living standards of natives, the picture would change terribly. The reason is two-fold. The first reason is that the historiography is pretty clear that while they were obviously not nice, the French were nicer than the British towards the Natives (at least until 1763 when the British shifted strategy). In fact, trade between French and Natives was very frequent and so it might be that for the whole population (natives + settlers), the French-area peoples enjoyed more growth and higher average levels. In the British colony, if the settlers killed and dispossessed natives, this is basically the British turning native capital stocks into their own capital stock or into consumption (which would enter settlers GDP but not change total GDP). In essence, this is basically a variation on the arguments of Robert Higgs with regards to measuring the American GDP in World War Two and Albrecht Ritschl on the German interwar growth. I am pretty sure that adjusting for the lives of natives would show a greater level for Canada leading to rough equality between the two colonies. However, I am not sure if the argument would cut that way (my guts say yes) since in their conjectural growth estimates, Mancall and Weiss show that with the natives included, their zero rate of income per capita growth turns into a positive rate.

Nonetheless, I still think that knowing that the settlers were better off in the US as an improvement over the current state of knowledge. Until ways to impute the value of native output and production are found, my current estimates are only a step forward, not the whole nine yards.

Minimum wage, measurements and incarceration rates

12/15/201612/18/2016 Vincent Geloso Current Events, Economics Barry Ritzholtz, Donald Boudreaux, Dube Lester Reich, economic growth, incarceration rates, labor supply, measurement, minimum wage, prison population

A few weeks ago, I published a blog post about how incarceration rates affect our measurement of the relative economic conditions of Blacks in America. My claim was that the statistics are hiding a reversal of the painfully achieved advances secured between 1870 and 1960. Basically, my claim was that those who (in greater numbers) found their ways to a prison cell tended to be at the bottom of the income distribution, were more susceptible to be unemployed and had lower wages. This creates a composition effect whereby the official surveys cream-skim the top of black wage, income and employment distributions.

But, could this problem also affect our measurement of the effects of minimum wage? Let me be clear before you continue ahead, I am just asking this question because I could find no satisfactory answer to (or even mention of) this issue.

In recent times, minimum wage surveys have tended to find some gains in earnings for some workers following increases in minimum wage rates. Regardless of how you look at the prison population, it increases – albeit at a decelerating rate since the early 2000s – since the 1980s. Coincidentally, that starting point is also the point at which the famous Minimum Wage Study Commission was published (1981). That report basically cemented the point made by George Stigler (i.e. minimum wages are not desirable). That report surveyed the entire literature to summarize the amplitude of the effects. That literature encompassed articles written between the end of the Second World War and … well… 1981. If you look below at the graph, incarceration rates were more or less constant during that regime. Thus, if there were composition effects associated with surveys of wages, incomes and employment, they were more moderate than after 1981 when incarceration rates surged.

But, its also after 1981 that some papers began to find some positive effects of minimum wage increases. These studies took place under a growing composition problem in surveys of wages, incomes and employment. Take the famous Dube, Lester and Reich paper in the Review of Economics and Statistics who used data from 1990 to 2006. During that period, the male incarceration rate surged from 297 per 100,000 to 501 per 100,000. I understand that DLR used a time fixed effect method, but would that be sufficient to at least deal with the issue of shifting labour supplied (it won’t for the data bias issues described notably by Bruce Western)

If we assume that those who are plausibly affected by minimum wages (i.e. lower income individuals) are also those more likely to end up in jail in the United States, then there is clearly a bias. As they are dropped from the labor market (or as they join the prison population), they leave only the workers least affected by the minimum wage inside the samples. That is one possibility.

The other possibility – which is that surveys do not suffer from a large composition, but which is not mutually exclusive to that composition problem – is that the growing prison population represents a year-over-year reduction in the labor supply which offsets the effects of hikes in the minimum wage (or maybe even eliminates them entirely if the shift is big enough).

I have tried many variations of this google scholar research and went back to my copy of the Handbook of Labor Economics and my Economics of Inequality, Poverty and Discrimination (a book worth reading by the way) and I found very little on this point. Very few scholars have considered the possibility of this problem (which implies a shift of the labor supply curve concurrent with minimum wage hikes and a composition problem where those affected are simply not measured anymore). Yet, I feel like this is a defensible claim. In England, where some studies also show minimal effects or positive effects of the minimum wage, there has also been an increase in the prison population. In contrast, Canada – whose prison population is declining moderately (meaning that the labor supply is increasing as the minimum wage is being increased – the studies do tend to find the “conventional” result.

Am I crazy or is this a case of poor measurement? Personally, I feel that there must an answer, but please tell me I did not just stumble on this!

Sensitive and Crucial: on Measuring Living Standards in the 18th Century

12/15/201612/15/2016 Vincent Geloso Economics, History economic development, economic growth, economic history, household size, if it matters, Industrial Revolution, Judy Stephenson, living standards, measure it, measurement

In the course of the twitterminar on the High-Wage Economy argument (HWE) which generated responses from John Styles on his blog (who has convinced me that the key solution to HWE rests in Normandy, not the Alsace) and many other on Twitter. In the course of that discussion, I skirted a point I have been meaning to make for a long time. However, I decided to avoid it because it is tangentially related to the HWE story. Its about how we measure living standards over space in the past.

Basically, the HWE story is a productivity story and all that matters in such a story is wage rates relative to other input prices. Because we’re talking about relatives, the importance of proper deflators is not that crucial. However, when you move beyond HWE and try to ask the question regarding absolute differences over space in living standards, the wage rates are not sufficient and proper deflators are needed.

They are many key issues to estimating living standards across space. The largest is that given that very few goods crossed borders in the past, converting American incomes into British sterling units using reported exchange rates would be rife with errors and calculating purchasing power parities would be complicated. The solution, very simple and elegant by its simplicity, is to rely on the logic of the poverty measures. Regardless of where you are, there is a poverty threshold. Then, all that is needed is to express incomes as the ratio of income to the poverty line. If the figure is three, then the average income buys three times the poverty line. Expressed as such, comparisons are easy to do. This is what Robert Allen did and it was basically a deeper and more complete approach than Fernand Braudel’s “Grain-Wages” (wage rates divided by grain prices).

Where should the line be?

While this represents a substantial improvement for economic historians like me who are deeply interested in “getting the data right”, there are flaws. In the course of my dissertation on living standards in Canada (see also my working papers here and here), I saw one such flaw in the form of how long the length of the work year was. In fact, a lot of my comments in this post were learned on the basis of Canada as an extreme outlier in terms of sensitivity. In Canada, winter is basically a huge preindustrial limitation on the ability to work year-round (thus, the expression mon pays ce n’est pas un pays, c’est l’hiver). But this flaw is only the tip of the iceberg. First of all, the winter means that the daily energy intake must substantially greater than 2,500 calories in order to maintain body mass. The mechanism through which the temperature increases the energy requirements of the human metabolism is in part the greater weight carried by the heavier clothing in addition to the energy needed by the body to maintain body temperature. At higher altitudes, these are compounded by the difference in air pressure.In their attempt to construct estimates of the living standards of Natives in the Canadian north during the fur trade era, Ann Carlos and Frank Lewis assert that it is necessary to adjust the basket of comparison to include more calories for the natives given the climate – they assert that 3500 calories were needed rather 2500 calories for English workers.In Russia, Boris Mironov estimated that the average calories ingested stood at 2952 per day between 1865 and 1915 while the adult male had to consume 3204 calories per day. In Canada in the 18^th century, it was estimated that patients at the Augustines hospital in Quebec City required somewhere 2628 calories and 3504 calories per day while soldiers consumed on average 2958 calories per day and the average population consumed 2845 calories per day (see my papers linked up above). The range of calorie requirements for soldiers (which I took from a reference inside my little sister’s military stuff) is quite large: from 3,100 in the desert at 33 degrees Celsius to 4,900 in artic conditions (minus 34 degrees Celsius) – a 58% difference. So basically, when we create welfare ratios for someone in, say, Mexico, the calories needed in the basket should be lower than in the Canadian basket.

Another issue, of greater importance, is the role of fuel. In the welfare ratios commonly used, fuel is alloted at 2MBTU for the basic level of sustenance which. This is woefully insufficient even in moderately warm countries, let alone Canada. My estimates of fuel consumption in Canada is that the worst case hovers around 20MBTU (ten times above the assumption) if the most inefficient form of combustion (important losses) and the worst kind of wood possible (red pine). Similar levels are observed for the American colonies.

Combined together, these corrections suggest that the Canadian poverty threshold should be higher than the one observed in France, England, South Carolina or Argentina. These adjustments can more or less be easily made by using military manuals. The army measures the basic calories requirements for all types of military theaters.

How to factor in family size and use equivalence scales.

Equivalence scales refer to the role of family size. Given the same income, families of different size will have different levels of welfare. Thanks to economies of scale in housing, cooking, lighting and heating, larger households can get more utility out of one dollar of income. That adjustments are required to render different households comparable is well accepted amongst economists. However, given the sensitivity of any analysis to the assumptions underlying any adjustments, there is an important debate to be had.

The convention among economic historians has been to assume that households have three adult equivalents. This assumption has gone largely undiscussed. The problem is “which scale to use”. The conversion into adult equivalents is subject to debates. Broadly speaking, three approaches exist. The first uses the square root of the number of individuals. The second attributes the full weight of the first adult, half the weight of the second adult and 30% for each child. This approach is commonly used by the OECD, Statistics Canada and numerous government agencies in Canada The third approach is the one used by the National Academy of Sciences in the United States which proposed to use an exponent ranging between 0.65 and 0.75 to household size but only after having multiplied the number of children by 0.7. As a result, a family of four (two parents, two infants) can have either 2 adult equivalents (square root), 2.1 adult equivalents (OECD and Statistics Canada approach) or 2.36 adult equivalent (NAS approach). The differences relative to the square roots approach are 5% and 18%. If we move to a family of 6 persons, the differences increase to 10.22% and 34.72%. If we are comparing regions with identical family structures, this would not be a problem. If not, then it is an issue. The selection of one method over another would have important effect on the cost of the living basket, with the NAS approach showing the costliest basket. Using a method relatively close to that of the OECD (although not exactly that measure), Eric Schneider found that the relatively small size of families in England led Allen to underestimate living standards. In a more recent paper, Allen alongside Schneider and Murphy pointed out that extending Schneider’s analysis to Latin America where “family sizes were likely larger (…) than in England and British North America” would amplify the wage gap between the two regions.

familysize

The table above shows how much family size varied around the late 17th century across region. Clearly, this is a non-negligible issue.

Sensitivity of estimates

Just to see how much these points matter, let’s modify for two easily modifiable factors: household size (given the numbers above) and fuel requirements (calories from food are harder to adjust for and I am still in the process of doing that). Let’s recompute the welfare ratios (those classified as bare bones) of Canada (the outlier) relative to the other according to different changes circa the end of the 17th century. How much does it matter?

Comparing New World places like Canada and Boston does not change much – they are more or less similar (family size and relative price-wise). However, just adjusting for family size eliminates a quarter of the gap between Canada and Paris (from 61% to somewhere 43.9% and 49.5%). Then, the adjustment for the fact that it is freezing cold in Canada eliminates a little more than half the advantage Canada enjoyed. So roughly two third of the Canadian advantage over Paris (the richest place in France) is eliminated by adjusting for family size and fuel consumption without adjusting for food requirements. However, family size does not affect dramatically the comparison between Paris and London (regardless of whether we use the Allen figures or the Stephenson-Adjusted figures). Thus, most of the sensitivity issues are related to comparing the New World with the Old World. effectofcorrections

Still, there are some appreciable differences from family structures within Europe (i.e. the Old World) that may alter the relative positions. For example, Ireland had much larger families than England in the 18th century (see here – the authors shared their dataset with me and a co-author): in 1700, England & Wales had an average household size of 4.7 compared with 5.32 in Ireland. That would moderately disrupt the comparison. Not as much as comparison between the New World and Old World, but enough to make cautious about European differences.

Conclusion

I have seen many discussions regarding the sensitivity of welfare ratios in numerous papers. I am not attempting to make my present point into some form of revolutionary issue. However, all the sensitivity estimates were concentrated on a case or another and they all concern a specific problem. No one has gathered all the problems in one place and provided a “range of estimates”. Maybe its time to go in that direction so that we know which place was poor and which was not (relative to one another, since anything preindustrial was basically dirt-poor by our modern standards).

On Capitalism and Slavery : Pêle-Mêle Comments

12/14/201612/14/2016 Vincent Geloso Current Events, Economics, History Canada, economic development, economic growth, Edward Baptist, Ludwig von Mises, methodology, public choice theory, Quebec, slavery, theory

Last week, a debate was initiated via an article in the Chronicle of Higher Education that relates to the clash between historians and economists over the topic of slavery. The debate seems acrimonious given the article and at the reading of a special issue of the Journal of Economic History regarding the Half has never been told by Edward Baptist, its hard to conclude otherwise. Pseudoerasmus published comments on the issue in a series of posts and a Trumpian twitterstorm (although the quality is far from being Trumpian). I find myself largely in agreement with him in response to the historians, but there are some pêle-mêle points that I felt I needed to add.

On Historians Versus Economists

To be honest, when I took my first classes in economic history, it seemed clear that there were important points that were agreed upon in the literature on slavery. The first was that the accounting profitability of slavery was not the same as the economic profitability (think opportunity cost here) of slavery. Thus, it was possible that (concentrating on the US here) the peculiar institution could more or less thrive regardless of the social costs it imposed (i.e. slavery is a tax on leisure which also increases the expropriation rate from slaves, and non-slaveowners often had to shoulder the cost of enforcing the institution). This argument is not at all new; in fact it is basically a public choice argument that Gordon Tullock and Anne Krueger could have signed on to without skipping a heartbeat (see Sheilagh Ogilvie – one of my favorite economist who does history in equality with Jane Humphries). The second point of agreement is that no one agreed on how to measure the productivity of slavery in the United States and the distribution of its costs and gains. The second point has been a very deep methodological debate which related to the method of measuring productivity (CES vs Translog TFP – stuff that would make your head blow and which also lead to the self-invitation of the Cambridge Capital Controversy to the debate). The quality of the data has been at the centre-stage as well, and datasets on slave prices, attributes, tasks and many other variables are still being collected (see notably the breathtaking work of Rhode and Olmsted here and here).

Thus, I will admit to being unimpressed by the use of oral histories to contest that literature. In addition, the absence of theory in Baptist’s work yields an underwhelming argument. Oral histories are super-duper important. The work of Jane Humphries on child labor is a case in point of the need to use oral histories. She very carefully used the tales told by children who worked during the industrial revolution to document how labor markets for children worked. The story she told was nuanced, carefully argued and supported by other primary evidence. This is economic history at its best – a merger of cliometrician and historian. In fact, while this is an evaluation that is subjective, the best economists are also historians and vice-versa. The reason for that is the mix of theory with multiple forms of evidence. But they key is to have a theory to guide the analysis.

Unexpectedly for some, the best exposition of this argument comes from Ludwig von Mises in his unknown book Theory and History. I was made aware of that book in a discussion with Chris Coyne of George Mason University and I proceeded to reading it. I was surprised how many similarities there were between the Mises who wrote that book and the Douglass Norths and the Robert Fogels of this world. The core argument of Theory and History is that axiomatic statements can be applied to historical events. The goal of historians and economic historians is to sort which theory applies. For example, the theory of signaling and the theory of asymmetric information are both axiomatically true. Without the need for evidence, we know that they must exist. The question of an economic historian becomes to ask “did it matter”? Both theories can compete to offset each other: if signaling is cheap, then asymmetric information can be solved; if it is not, asymmetric information is a problem. Or both may be irrelevant to a given historical development. To explain which two axiomatic statements apply to the event (and in what dosage), you need data (quantitative and qualitative). Thus, Theory and History actually proposes the use of econometrics and statistical methods because it does not try to predict as much as it tries to a) sort which axiomatic statements applied; b) the relative strengths of competing forces; c) the counterfactual scenario.

Without theory, all you have is Baptist’s descriptions which tell us very little and can, incidentally, be distorted by he who recounts the tales he read.

On the Culture of Peasants/Slaves/Slaveowners

When I started my PhD dissertation Canadian economic history, the most annoying thing I saw was the claim that the French-Canadians had “different mentalities” or “more conservative outlooks”. This was basically the way of calling them stupid. This has recently evolved to say that they “maximized goals other than wealth”. Regardless, this was basically: the French-Canadian was not culturally suited for economic development.

But culture is not a fixed variable, it is not an exogenous variable. Culture is basically the coherent framework built by individuals who share certain features to “cut out” the noise. Everyday, we are bombarded with tons of pieces of information and there is no way that the human brain can process them all. Thus, we have a framework – culture (ideology does the same thing) – which tells us what is relevant and what is irrelevant and what interpretation to give to relevant information.

People can cling to old beliefs for a long time, but only if there is no cost to them. I can persist in terrible farming practices if I am not made aware of the proper valuation of the opportunity I am foregoing. For example, British farmers who arrived in Quebec in the 19th century tended to use oxen as they did in England for tilling the soil. They had probably been taught to do that by their parents who learnt it from their grandparents because it was part of the farming culture of England. The behavior was culturally inherited. However, when they saw that the French-Canadians were using horses and that horses – in the Canadian hinterland – got the job done better, they shifted. The culture changed at the sight of how important was the foregone opportunity by continuing to use oxen. Where the British and the French co-existed, both were equally good farmers. Where they could not observe each other, they were all sub-optimal farmers. Seeing the other methods forced changes in culture.

The same applies to slaveowners and slaves! Slaveowners were a more or less tightly knit group that frequented similar circles and were constantly on the lookout to increase productivity. If some master had noticed that he could increase production by whipping more slaves, why would he not adopt this method? Why would he leave 100$ bill on the street? Why did the masters growing cotton in South Carolina not adopt the method of whipping adopted by growers in Louisiana? Without a theory of how culture changes (and what purposes it serves beyond the simplistic Marxist power structure argument), there is no answer to this question. With the work of Rhode and Olmstead, there is an answer: the type of cotton that had higher yields was not suited for growing everywhere! In this case, we are applying my comment from the section above on Historians versus Economists. There are competing theories of explaining increasing output: either some slave masters were unable to observe the other slave masters and adopt the torture methods they had (which would need to be the case for Baptist to be right) or there were biological limitations to growing the better crops in some areas (Rhode and Olmstead).

Two competing theories (they are not mutually exclusive though) that can be tested with data and they set a counterfactual. That is why you need theory to make good history.

One last thing: slave owners were not capitalists

This is probably the most childish thing to come out of works like those of Baptist: to assert that because slaves were capital assets, that the owners were capitalists. That is true if you want to adhere to the inconsistent (and self-contradicting) Marxist approach to capital. In fact, as Phil Magness pointed out to me, slave owners were not free market types. They were very much anti-capitalists. Slavery apologists like Fitzhugh and Carlyle were even more anti-capitalists than that. It’s not because you own capital that you are a capitalist unless you adhere to Marxist theory.

But, capital is just a production input. Its value depends on what it can produce. As Jeffrey Hummel pointed out, there is a deadweight loss from slavery: enforcement costs, the overproduction of cotton because slavery is basically a tax on leisure and the implicit taxation of the output produced by slaves. All three of these factors would have slowed down economic growth in the south. Thus, as capital assets, slaves were relatively inefficient.

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On Capitalism and Slavery : Pêle-Mêle Comments

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