Nightcap

  1. African-American incomes in mid-century Tom Westland, Decompressing History
  2. Black American Culture and the Racial Wealth Gap Coleman Hughes, Quillette
  3. When Black Unemployment Rates Were Equal to White Unemployment Rates… Vincent Geloso, NOL
  4. My Great-Grandfather, the Nigerian Slave Trader Adaobi Tricia Nwaubani, New Yorker

How poor was 18th century France? Steps towards testing the High-Wage Hypothesis (HWE)

A few days ago, one of my articles came online at the Journal of Interdisciplinary HistoryIt is a research note, but as far as notes go this one is (I think) an important step forwards with regards to the High-Wage Hypothesis (henceforth HWE for high-wage economy) of industrialization.

In the past, I explained my outlook on this theory which proposes that high wages relative to energy was a key driver of industrialization. As wages were high while energy was cheap, firms had incentives to innovate and develop labor-saving technologies.  I argued that I was not convinced by the proposition because there were missing elements to properly test its validity. In that post I argued that to answer why the industrial revolution was British we had to ask why it was not French (a likely competitor). For the HWE to be a valid proposition, wages had to be higher in England than in France by a substantial margin. This is why I have been interested in living standards in France.

In his work, Robert Allen showed that Paris was the richest city in France (something confirmed by Phil Hoffman in his own work). It was also poorer than London (and other British cities). The other cities of France were far behind. In fact, by the 18th century, Allen’s work suggests that Strasbourg (the other city for which he had data) was one of the poorest in Europe.

In the process of assembling comparisons between Canada and France during the colonial era (from the late 17th to the mid-18th centuries), I went to the original sources that Allen used and found that the level of living standards is understated. First, I found out that the wages were not for Strasbourg per se. They applied to a semi-rural community roughly 70km away from Strasbourg.  Urban wages and rural wages tend to differ massively and so they were bound to show lower living standards. Moreover, the prices Allen used for his basket applied to urban settings. This means that the wages used were not comparable to the other cities used. I also found out that the type of work that was reported in the sources may not have belonged to unskilled workers but rather to semi-skilled or even skilled workers and that the wages probably included substantial in-kind payments.

Unfortunately, I could not find a direct solution to correct the series proposed by Allen. However, there were two ways to circumvent the issue. The most convincing of those two methods relies on using the reported wages for agricultural workers. While this breaks with the convention established by Allen (a justifiable convention in my opinion) of using urban wages and prices, it is not a problem if we compare with similar types of wage work. We do have similar data to compare with in the form of Gregory Clark’s farm wages in England. The wage rates computed by Allen placed Strasbourg at 64% of the level of wages for agricultural workers in England between 1702 and 1775. In comparison, the lowest of the agricultural wage rates for the Alsatian region places the ratio at 74%. The other wage rates are much closer to wages in England.  The less convincing methods relies on semi-skilled construction workers – which is not ideal. However, when these are compared to English wages, they are also substantially higher.

Overall, my research note attempts a modest contribution: properly measure the extent to which wages were lower in France than in Britain. I am not trying to solve the HWE debate with this. However, it does come one step closer to providing the information to do so. Now that we know that the rest of France was not as poor as believed (something which is confirmed by the recent works of Leonardo Ridolfi and Judy Stephenson), we can more readily assess if the gap was “big enough” to matter.  If it was not big enough to matter, then we have to move to one of the other five channels that could confirm the HWE (at least that means I have more papers to write).

Do risk preferences account for 1.4 percentage points of the gender pay gap?

A few days ago, this study of gender pay differences for Uber drivers came out. The key finding, that women earned 7% less than men, was stunning because Uber uses a gender-blind algorithm. The figure below was the most interesting one from the study as it summarized the differences in pay quite well.

DataUber

To explain this, the authors highlight a few explanations borne out by the data: men drive faster allowing them to have more clients; men have spent more time working for Uber and have more experience that may be unobserved; choices of where and when to drive matters. It is this latter point that I find fascinating because it speaks to an issue that I keep underlining regarding pay gaps when I teach.

For reasons that may be sociological or biological (I am agnostic on that), men tend to occupy jobs that have high rates of occupational mortality (see notably this British study on the topic) in the forms of accidents (think construction, firemen) or diseases (think miners and trashmen). They also tend to take the jobs in further removed areas in order to gain access to a distance premium (which is a form of risk in the sense that it affects  family life etc.). The premiums to taking risky jobs are well documented (see notably the work of Kip Viscusi who measured the wage premium accruing to workers who were employed in bars where smoking was permitted). If these premiums are non-negligible but tend to be preferred by men (who are willing to incur the risk to be injured or fall sick), then risk preferences matter to the gender wage gap.

However, there are hard to properly measure in order to assess the share of the wage gap truly explained by discrimination. Here with the case of Uber, we can get an idea of the amplitude of the differences. Male Uber drivers prefer riskier hours (more risks of having an inebriated and potentially aggressive client), riskier places (high traffic with more risks of accidents) and riskier behavior (driving faster to get more clients per hour).  The return to taking these risks is greater earnings. According to the study, 20% of the gap stems from this series of choices or roughly 1.4 percentage points.

I think that this is significantly large to warrant further consideration in the future in the debate. More often than not, the emphasis is on education, experience, marital status, and industry codes (NAICS code) to explain wage differences. The use of industry codes has never convinced me. There is wide variance within industries regarding work accidents and diseases. The NAICS codes industries by wide sectors and then by sub-sectors of activities (see for example the six-digits codes to agriculture, forestry, fishing and hunting here). This does not allow to take account of the risks associated with a job. There are a few study that try to account for this problem, but there are … well … few in numbers. And rarely are they considered in public discussions.

Here, the Uber case shows the necessity to bring back this subtopic in order to properly explain the wage gap.

On Monopsony and Legal Surroundings

A few days ago, in reply to this December NBER study, David Henderson at EconLog questioned the idea that labor market monopsonies matter to explain sluggish wage growth and rising wage inequality. Like David, I am skeptical of this argument. However, I am skeptical for different reasons.

First, let’s point out that the reasoning behind this story is well established (see notably the work of Alan Manning). Firms with market power over a more or less homogeneous labor force which must assume a disproportionate amount of search costs have every incentive to depress wages. This can lead to reductions in growth as, notably, it discourages human capital formation (see these two papers here and here as examples). As such, I am not as skeptical of “monopsony” as an argument.

However, I am skeptical of “monopsony” as an argument. Well, what I mean is that I am skeptical of considering monopsony without any qualifications regarding institutions. The key condition to an effective monopsony is the existence of barriers (natural and/or legal to mobility). As soon as it is relatively easy to leave a small city for another city, then even a city with a single-employer will have little ability to exert his “market power” (Note: I really hate that word). If you think about it simply through these lenses, then all that matters is the ability to move. All you need to care about are the barriers (legal and/or natural) to mobility (i.e. the chance to defect).

And here’s the thing. I don’t think that natural barriers are a big deal. For example, Price Fishback found that the “company towns” im the 19th century were hardly monopsonies (see here, here, here and here). If natural barriers were not a big deal, they are certainly not a big deal today. As such, I think the action is largely legal. My favorite example is the set of laws adopted following the Emancipation of slaves in the United States which limited the mobility (by limiting the chances of Northerners hiring agents to come who would act as headhunters in the South). That is a legal barrier (see here and here). I am also making that argument regarding the institution of seigneurial tenure in Canada in a working paper that I am reorganizing (see here).

What about today? The best example are housing restrictions? Well, housing construction and zoning regulations basically make the supply of housing quite inelastic. The areas where these regulations are the most severe are also, incidentally, high productivity areas. This has two effects on mobility. The first is that low-productivity workers in low-productivity areas cannot easily afford to move to the high-productivity area. As such, you are reducing their options of defection and increasing the likelihood that they will not look. You are also reducing the pool of places to apply which means that, in order to find a more remunerative job, they must search longer and harder (i.e. you are increasing their search costs). The second effect is that you are also tying workers to the areas they are in. True, they gain because the productivity becomes capitalized in the potential rent from selling any property they own. However, they are in essence tied to the place. As such, they can be more easily mistreated by employers.

These are only examples. I am sure I could extend the list to reach the size of the fiscal code (well, maybe not that much). The point is that “monopsony” (to the extent that it exists) is merely a symptom of other policies that either increase search costs for workers or reduce the number of options for defections. And I do not care much for analyzing symptoms.

Testing the High-Wage Economy (HWE) Hypothesis

Over the last week or so, I have been heavily involved in a twitterminar (yes, I am coining that portemanteau term to designate academic discussions on twitter – proof that some good can come out of social media) between myself, Judy Stephenson , Ben Schneider , Benjamin Guilbert, Mark Koyama, Pseudoerasmus,  Anton Howes (whose main flaw is that he is from King’s College London while I am from the LSE – nothing rational here), Alan Fernihough and  Lyman Stone. The topic? How suitable is the “high-wage economy” (HWE) explanation of the British industrial revolution (BIR).

Twitter debates are hard to follow and there is a need for summaries given the format of twitter. As a result, I am attempting such a summary here which is laced with my own comments regarding my skepticism and possible resolution venues.

An honest account of HWE

First of all, it is necessary to offer a proper enunciation of HWE’s role in explaining the industrial revolution as advanced by its main proponent, Robert Allen.  This is a necessary step because there is a literature attempting to use high-wages as an efficiency wage argument. A good example is Morris Altman’s Economic Growth and the High-Wage Economy  (see here too) Altman summarizes his “key message” as the idea that “improving the material well-being of workers, even prior to immediate increases in productivity can be expected to have positive effects on productivity through its impact on economic efficiency and technological change”. He also made the same argument with my native home province of Quebec relative to Ontario during the late 19th century. This is basically a multiple equilibria story. And its not exactly what Allen advances. Allen’s argument is that wages were high in England relative to energy. This factors price ratio stimulated the development of technologies and industries that spearheaded the BIR. This is basically a context-specific argument and not a “conventional” efficiency wage approach as that of Allen. There are similarities, but they are also considerable differences. Secondly, the HWE hypothesis is basically a meta-argument about the Industrial Revolution. It would be unfair to caricature it as an “overarching” explanation. Rather, the version of HWE advanced by Robert Allen (see his book here) is one where there are many factors at play but there is one – HWE – which had the strongest effects. Moreover, while it does not explain all, it was dependent on other factors that contributed independently.  The most common view is that this is mixed with Joel Mokyr’s supply of inventions story (which is what Nick Crafts has done). In the graph below, the “realistically multi-causal” explanation is how I see HWE. In Allen’s explanation, it holds the place that cause #1 does. According to other economists, HWE holds spot #2 or spot #3 and Mokyr’s explanations holds spot #1.

hwe

In pure theoretical terms (as an axiomatic statement), the Allen model is defensible. It is a logically consistent construct. It has some questionnable assumptions, but it has no self-contradictions. Basically, any criticism of HWE must question the validity of the theory based on empirical evidence (see my argument with Graham Brownlow here) regarding the necessary conditions. This is the hallmark of Allen’s work: logical consistency. His work cannot be simply brushed aside – it is well argued and there is supportive evidence. The logical construction of his argument requires a deep discussion and any criticism that will convince must encompass many factors.

Why not France? Or How to Test HWE

As a doubter of Allen’s theory (I am willing to be convinced, hence my categorization as doubter), the best way to phrase my criticism is to ask the mirror of his question. Rather than asking “Why was the Industrial Revolution British”, I ask “Why Wasn’t it French”. This is what Allen does in his work when he asks explicitly “Why not France?” (p.203 of his book). The answer proposed is that English wages were high enough to justify the adoption of labor-saving technologies. In France, they were not. This led to differing rates of technological adoptions, an example of which is the spinning jenny.

This argument hinges on some key conditions :

  1. Wages were higher in England than in France
  2. Unit labor costs were higher in England than in France (productivity-adjusted wages) (a point made by Kelly, Mokyr and Ó Gráda)
  3. Market size factors are not sufficiently important to overshadow the effects of lower wages in France (R&D costs over market size mean a low fixed cost relative to potential market size)
  4. The work year is equal in France as in England
  5. The cost of energy in France relative to labor is higher than in England
  6. Output remained constant while hours fell – a contention at odds with the Industrious Revolution which the same as saying that marginal productivity moves inversely with working hours

If most of these empirical statements hold, then the argument of Allen holds. I am pretty convinced by the evidence advanced by Allen (and E.A. Wrigley also) regarding the low relative of energy in England. Thus, I am pretty convinced that condition #5 holds. Moreover, given the increases in transport productivity within England (here and here), the limited barriers to internal trade (here), I would not be surprised that it was relatively easy to supply energy on the British market prior to 1800 (at least relative to France).

Condition #3 is harder to assess in terms of important. Market size, in a Smithian world, is not only about population (see scale effects literature). Market size is a function of transaction costs between individuals, a large share of which are determined by institutional arrangements. France has a much larger population than England so there could have been scale effects, but France also had more barriers to internal trade that could have limited market size. I will return to this below.

Condition #1,2,4 are basically empirical statements. They are also the main points of tactical assault on Allen’s theory.  I think condition #1 is the easiest to tackle. I am currently writing a piece derived from my dissertation showing that – at least with regards to Strasbourg – wages in France presented in Allen (his 2001 article) are heavily underestimated (by somewhere between 12% and 40% using winter workers in agriculture and as much as 70% using the average for laborers in agriculture). The work of Judy Stephenson, Jane Humphries and Jacob Weisdorf has also thrown the level and trend of British wages into doubts. Bringing French wages upwards and British wages downwards could damage the Allen story. However, this would not be a sufficient theory. Industrialization was generally concentrated geographically. If labor markets in one country are not sufficiently integrated and the industrializing area (lets say the “textile” area of Lancashire or the French Manchester of Mulhouse or the Caën region in Normandy) has uniquely different wages, then Allen’s theory can hold since what matters is the local wage rate relative to energy. Pseudoerasmus has made this point but I can’t find any mention of that very plausible defense in Allen’s work.

Condition #2 is the weakest point and given Robert Fogel’s work on net nutrition in France and England, I have no problem in assuming that French workers were less productive. However, the best evidence would be to extract piece rates in textile-producing regions of France and England. This would eliminate any issue with wages and measuring national productivity differences. Piece rates would perfectly capture productivity and thus the argument could be measured in a very straightforward manner.

Condition #4 is harder to assess and more research would be needed. However, it is the most crucial piece of evidence required to settle the issue once and for all. Pre-industrial labor markets are not exactly like those of modern days. Search costs were high which works in a manner described (with reservations) by Alan Manning in his work on monopsony but with much more frictions. In such a market, workers may be willing to trade in lower wage rates for longer work years. In fact, its like a job security argument. Would you prefer 313 days of work guaranteed at 1 shilling per day or a 10% chance of working 313 days for 1.5 shillings a day (I’ve skewed the hypothetical numbers to make my point)? Now, if there are differences in the structure of labor markets in France and England during the 18th and 19th centuries, there might be differences in the extent of that trade-off in both countries. Different average discount on wages would affect production methods. If French workers were prone to sacrifice more on wages for steady employment, it may render one production method more profitable than in England. Assessing the extent of the discount of annual to daily wages on both markets would identify this issue.

The remaining condition (condition #6) is, in my opinion, dead on arrival. Allen’s model, in the case of the spinning jenny, assumed that labor hours moved in an opposite direction as marginal productivity. This is in direct opposition to the well-established industrious revolution. This point has been made convincingly by Gragnolati, Moschella and Pugliese in the Journal of Economic History. 

In terms of research strategy, getting piece rates, proper wage estimates and proper labor supplied estimates for England and France would resolve most of the issue. Condition #3 could then be assessed as a plausibility residual.  Once we know about working hours, actual productivity and real wages differences, we can test how big the difference in market size has to be to deter adoption in France. If the difference seems implausible (given the empirical limitations of measuring effective market size in the 18th century in both markets), then we can assess the presence of this condition.

My counter-argument : social networks and diffusion

For the sake of argument, let’s imagine that all of the evidence favors the skeptics, then what? It is all well and good to tear down the edifice but we are left with a gaping hole and everything starts again. It would be great to propose a new edifice as the old one is being questioned. This is where I am very much enclined towards the rarely discussed work of Leonard Dudley (Mothers of Innovation). Simply put, Dudley’s argument is that social networks allowed the diffusion of technologies within England that fostered economic growth. He has an analogy from physics which gets the point across nicely. Matter has three states : solid, gas, liquid. Solids are stable but resist to change. Gas, matter are much more random and change frequently by interacting with other gas, but any relation is ephemeral. Liquids permit change through interaction, but they are stable enough to allow interactions to persist for some time. Technological innovation is like a liquid. It can “mix” things together in a somewhat stable form.

This is where one of my argument takes life. In a small article for Economic Affairs, I argued (expanding on Dudley) that social networks allowed this mixing (I am also expanding that argument in a working paper with Adam Martin of Texas Tech University). However, I added a twist to that argument which I imported from the work of Israel Kirzner (one of the most cited books in economics, but not by cliometricians – more than 7000 citations on google scholar). Economic growth, in Kirzner’s mind,  is the result of entrepreneurs discovering errors and arbitrage possibilities. In a way, growth is a process of discovering correcting errors. An analogy to make this point is that entrepreneurs look for profits where the light is while also trying to move the light to see where it is dark. What Kirzner dubs as “alertness” is in fact nothing else than repeated and frequent interactions. The more your interact with others, the easier it becomes for ideas to have sex. Thus, what matters is how easy it is for social networks to appear and generate cheap information and interactions for members without the problem of free riders. This is where the work of Anton Howes becomes very valuable. Howes, in his PhD thesis supervised by Adam Martin who is my co-author on the aforementioned project (summary here), showed that most innovators went in frequent with one another and they inspired themselves from each other. This is alertness ignited!

If properly harnessed, the combination of the works of Howes and Dudley (and also James Dowey who was a PhD student at the LSE with me and whose work is *Trump voice* Amazing) can stand as a substitute to Allen’s HWE if invalidated.

Conclusion

If I came across as bashing on Allen in this post, then you have misread me. I admire Allen for the clarity of his reasoning and his expositions (given that I am working on a funded project to recalculate tax-based measures in the US used by Piketty to account for tax avoidance, I can appreciate the clarity in which Allen expresses himself). I also admire him for wanting to “Go big or go home” (which you can see in all his other work, especially on enclosures). My point is that I am willing to be convinced of HWE, but I find that the evidence leans towards rejecting it. But that is very limited and flawed evidence and asserting this clearly is hard (as some of the flaws can go his way). Nitpicking Allen’s HWE is a necessary step for clearly determining the cause of BIR. It is not sufficient as a logically consistent substitute must be presented to the research community. In any case, there is my long summary of the twitteminar (officially trademarked now!)

P.S. Inspired by Peter Bent’s INET research webinar on institutional responses to financial crises, I am trying to organize a similar (low-cost) venue for presenting research papers on HWE assessment. More news on this later.

England circa 1700: low-wage or high-wage

A few months ago, I discussed the work of my friend (and fellow LSE graduate) Judy Stephenson on the “high-wage economy” of England during the 18th century. The high-wage argument basically states that high wages relative to capital incite management to find new techniques of production and that, as a result, the industrial revolution could be initiated. Its a crude summary (I am not doing it justice here), but its roughly accurate.

In her work, Judy basically indicated that the “high-wage economy” observed in the data was a statistical artifact. The wage rates historians have been using are not wage rates, they’re contract rates that include an overhead for contractors who hired the works. The wage rates were below the contract rates in an amplitude sufficient to damage the high-wage narrative.

A few days ago, Jane Humphries (who has been a great inspiration for Judy and whose work I have been discretely following for years) and Jacob Weisdorf came out with a new working paper on the issue that have reinforced my skepticism of the wages regarding England. A crude summary of Humphries and Weisdorf’s paper goes as such: preindustrial labor markets had search costs, workers were willing to sacrifice on the daily wage rate (lower w) in order to obtain steady employment (greater L) and thus the proper variable of interest is the wage paid on annual contracts.

While their results do not affect England’s relative position (it only affects the trend of living standards in England), it shows that there are flaws in the data. These flaws should give us pause before proposing a strong theory like the “high-wage economy” argument. Taken together, the work of Stephenson (whom I am told is officially forthcoming), Humphries and Weisdorf show the importance of doing data work as the new data may overturn some key pieces of research (maybe, I am not sure, there is some stuff worth testing).