Author: Vincent Geloso

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

Vincent Geloso History , , , , , , , , ,

A few days ago, one of my articles came online at the Journal of Interdisciplinary History. It 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).

Is Free-Riding for Union Negotiations a Myth?

Vincent Geloso Liberty , , , , , , ,

As the US Supreme Court is considering the case of Janus v. AFSCME on mandatory deductions for the purposes of union negotiations, I think it is time to truly question the argument underlying mandatory deductions: free-riding. Normally, the argument is that union members fight hard to get advantageous conditions. After taking the risks associated with striking and expending resources to this end, non-members could simply get the job and the benefits associated with prior negotiations and not contribute to the “public good” of negotiation. This is an often-used argument.  I come from Quebec in Canada where closed shop unionism (i.e. you are forced to join the union to get the job) still exists and mandatory dues are more stringently enforced than in the United States. There, one of the most repeated defense of the closed shop system and of the mandatory dues is the free-riding argument. As such, the free-riding argument is an often-used communication line.

That is, in essence, the free-riding argument. While it appears axiomatically true, I do not believe that it is actually a relevant problem. However, before I proceed, let me state that I have a prior in favor of consent and I only sign off on “forcing” people when the case is clear and clean-cut (I am what you could call a radical “contractarian”).

So, is free-riding a problem? The answer is in the negative (in my opinion) as the free-riding argument entails that unionism provides a public good. One of the main feature of a public good is an inability to exclude non-payers.  Think about the often-used example of lighthouses in public economics: the lighthouse provides a light that everyone can see and yet the owner of the lighthouse would have a very hard time to collect dues (although Ronald Coase in 1974 and Rosolino Candela and myself more recently have emitted doubts about the example).  However, why would a union be unable to exclude? After all, it is very easy to contractually “pre-exclude” non-payers. A non-member could obtain only 50% or 75% or 80% of the benefits negotiated of the union. Only upon joining would he be able to acquire the full benefits of the union.

As such, “excludability” is feasible. In fact, there are precedents that could serve as a framework for using this exclusion mechanism. Consider the example of “orphan clauses” which were very popular in my neck of the wood in the 1990s and early 2000s. Basically, these clauses “create differences in treatment, based solely on the hiring date, in some of the employment conditions of workers who perform the same tasks“. These existed for police forces, firefighters and other public sector workers.  Now, this was a political tool for placating older union members while controlling public spending. As such, it is not an example of exclusion for negotiation purposes. Nevertheless, such contracts could switch the “date of employment” for the “union status” in determining differences in treatment.

Another mechanism for exclusion is social ostracism. This may seem callous, but social ostracism is actually well rooted in evolutionary psychology. It also works really well in contexts of continuous dealings (see also this example by Avner Greif which has been the object of debates with Sheilagh Ogilvie and Jessica Goldberg)  Workplace relations between workers are continuous relations and shirkers can be ostracized easily.  The best example is the “water dispenser gossip” where co-workers will spread rumors about other workers and their behavior. All that is needed is an individual marginally inclined towards the union (who could even get special treatment from the union for being the ostracism-producer) who will generate the ostracism. As such, the free-riding argument has a solution in that second channel.

In fact, ostracism and contractual exclusion can be combined as they are in no way mutually exclusive. These two channels are the reason why I do not adhere to the “free-riding” argument as valid justification of compulsory payment for financing unions.

On Antitrust, the Sherman Act and Accepted Wisdom

Vincent Geloso Economics, History, Law , , , ,

I am generally skeptical of “accepted wisdom” on many policy debates. People involved in policy-making are generally politicians who carefully craft justifications (i.e. cover stories) where self-interest and common good cannot be disentangled easily.  These justifications can easily become “accepted wisdom” even if incorrect. I am not saying that “accepted wisdom” is without value or that it is always wrong, but more often than not it is accepted at face value without question.

My favorite example is “antitrust”.  In the United States, the Sherman Act (the antitrust bill) was first introduced in 1889 (passed in 1890). The justification often given is that it was meant to promote competition as proposed by economists. However, as often pointed out, the bill was passed well before the topic of competition in economics had been unified into a theoretical body.  It was also rooted in protectionist motives. Moreover, the bill was passed after the industries most affected saw prices fall faster than the overall price level and output increase faster than the overall output level (see here here here here and here). Combined, these elements should give pause to anyone willing to cite the “accepted wisdom”.

More recently, economist Patrick Newman provided further reason for caution in an article in Public Choice. Interweaving political history and the biographical details about senator John Sherman (he of the Sherman Act), Newman tells a fascinating story about the self-interested reasons behind the introduction of the act.

In 1888, John Sherman failed to obtain the Republican presidential nomination – a failure which he blamed on the governor of Michigan, Russell Alger. Out of malice and a desire of vengeance, Sherman defended his proposal by citing Alger as the ringmaster of one of the “trusts”. Alger, himself a presidential hopeful for the 1892 cycle, was politically crippled by the attack (even if it appears that it was untrue). Obviously, this was not the sole reason for the Act (Newman highlights the nature of the Republican coalition which would have demanded such an act). However, once Alger was fatally wounded, Sherman appears to have lost interest in the Act and left others to push it through.

As such, the passage of the bill was partly motivated by political self-interest (thus illustrating the key point of behavioral symmetry that underlies public choice theory). Entangled in the “accepted wisdom” is a wicked tale of revenge between politicians. At such sight, it is hard not to be cautions with regards to “accepted wisdom”.

If causality matters, should the media talk about mass shootings?

Vincent Geloso Current Events, Economics , , , , , ,

My answer to that question is “maybe not” or at the very least “not as much”. Given the sheer amount of fear that can be generated by a shooting, it is understandable to be shocked and the need to talk about it is equally understandable. However, I think this might be an unfortunate opportunity to consider the incentives at play.

I assume that criminals, even crazy ones, are relatively rational. They weigh the pros and cons of potential targets, they assess the most efficient tool or weapon to accomplish the objectives they set etc. That entails that, in their warped view of the world, there are benefits to committing atrocities. In some instances, the benefit is pure revenge as was the case in one of the famous shooting in my hometown of Montreal (i.e. a university professor decided to avenge himself of the slights caused by other professors). In other instances, the benefit is defined in part by the attention that the violent perpetrator attracts for himself. This was the case of another infamous shooting in Montreal where the killer showed up at an engineering school to kill 14 other students and staff. He committed suicide and also left a suicide statement that read like a garbled political manifesto. In other words, killers can be trying to “maximize” media hits.

This “rational approach” to mass shootings opens the door to a question about causality: is the incidence of mass shootings determining the number of media hits or is the number of media hits determining the incidence of mass shootings. In a recent article in the Journal of Public Economics, the possibility of the latter causal link has been explored with regards to terrorism.  Using the New York Times‘ coverage of some 60,000 terrorist attacks in 201 countries over 43 years, Michael Jetter used the exogenous shock caused by natural disasters to study they reduced the reporting of terrorist attacks and how this, in turn, reduced attention to terrorism. That way, he could arrive at some idea (by the negative) of causality. He found that one New York Times article increased attacks by 1.4 in the following three weeks. Now, this applies to terrorism, but why would it not apply to mass shooters? After all, there are very similar in their objectives and methods – at the very least with regards to the shooters who seek attention.

If the causality runs in the direction suggested by Jetter, then the full-day coverage offered by CNN or NBC or FOX is making things worse by increasing the likelihood of an additional shooting. For some years now, I have been suggesting this possibility to journalist friends of mine and arguing that maybe the best way to talk about terrorism or mass shooters is to move them from the front page of a newspaper to a one-inch box on page 20 or to move the mention from the interview to the crawler at the bottom. In each discussion, my claim about causality is brushed aside with either incredulity at the logic and its empirical support or I get something like “yes, but we can’t really not talk about it”. And so, the thinking ends there. However, I am quite willing to state that its time for media outlets to deeply reflect upon their role and how to best accomplish the role they want. And that requires thinking about causality and accepting that “splashy” stories may be better left ignored.

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

Vincent Geloso Economics , , , , ,

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.

Prices in Canada since 1688

Vincent Geloso Economics, History , , , , , ,

A few days ago, I received goods news that the Canadian Journal of Economics had accepted my paper that constructed a consumer price index for Canada between 1688 and 1850 from homogeneous sources (the account books of religious congregations). I have to format the article to the guidelines of the journal and attach all my data and it will be good to go (I am planning on doing this over the weekend). In the meanwhile, I thought I would share the finalized price index so that others can see it.

First, we have the price index that focuses on the period from 1688 to 1850.  Most indexes that exist for pre-1850 Canada (or Quebec since I assume that Quebec is representative of pre-1850 Canadian price trends) are short-term, include mostly agricultural goods and have no expenditures weights to create a basket. Now, my index is the first that uses the same type of sources continuously over such a long period and it is also the first to use a large array of non-agricultural goods. It also has a weights scheme to create a basket.

PriceIndexCanada

The issue of adding non-agricultural goods was especially important because there were important differences in the evolution of different types of goods. Agricultural goods, see next image, saw their nominal prices continually increase between the 17th and 19th centuries. However, most other prices – imported goods, domestically produced manufactured goods etc. – either fall or remain stable. These are very pronounced changes in relative prices. It shows that reliance on agricultural goods price index will overstate the amount of “deflating” needed to arrive at real wages or incomes.  The image below shows the nominal price evolution of groupings of goods as described above.

PriceIndexCanada2

And finally, the pièce de résistance! I link my own index to other existing post-1850 index so as to generate the evolution of prices in Canada since 1688. The figure below shows the evolution of the price index over … 328 years (I ended the series at 2015, but extra years forward can be added). In the years to come, I will probably try to extend this backwards as much as possible at least to 1665 (the first census in Canada) and will probably try to approach Statistics Canada to see if they would like to incorporate this contribution into their wide database of macroeconomic history of Canada.

PriceIndexCanada3

The best economic history papers of 2017

Vincent Geloso Economics, History , , , , , , , , , , , , ,

As we are now solidly into 2018, I thought that it would be a good idea to underline the best articles in economic history that I read in 2017. Obviously, the “best” is subjective to my preferences. Nevertheless, it is a worthy exercise in order to expose some important pieces of research to a wider audience.  I limited myself to five articles (I will do my top three books in a few weeks). However, if there is an interest in the present post I will publish a follow-up with another five articles.

O’Grady, Trevor, and Claudio Tagliapietra. “Biological welfare and the commons: A natural experiment in the Alps, 1765–1845.” Economics & Human Biology 27 (2017): 137-153.

This one is by far my favorite article of 2017. I stumbled upon it quite by accident. Had this article been published six or eight months earlier, I would never have been able to fully appreciate its contribution. Basically, the authors use the shocks induced by the wars of the late 18th century and early 19th century to study a shift from “self-governance” to “centralized governance” of common pool resources. When they speak of “commons” problems, they really mean “commons” as the communities they study were largely pastoral communities with area in commons.  Using a difference-in-difference where the treatment is when a region became “centrally governed” (i.e. when organic local institutions were swept aside), they test the impact of these top-down changes to institutions on biological welfare (as proxied by infant mortality rates). They find that these replacements worsened outcomes.

Now, this paper is fascinating for two reasons. First, the authors offer a clear exposition of its methodology and approach. They give just the perfect amount of institutional details to assuage doubts.  Second, this is a strong illustration of the points made by Elinor Ostrom and Vernon Smith. These two economists emphasize different aspects of the same thing. Smith highlights that “rationality” is “ecological” in the sense that it is an iterative process of information discovery to improve outcomes.  This includes the generation of “rules of the game” which are meant to sustain exchanges. These rules need not be formal edifices. They can be norms, customs, mores and habits (generally supported by the discipline of continuous dealings and/or investments in social-distance mechanisms). On her part, Ostrom emphasized that the tragedy of the commons can be resolved through multiple mechanisms (what she calls polycentric governance) in ways that do not necessarily require a centralized approach (or even market-based approaches).

In the logic of these two authors, attempts at “imposing” a more “rational” order (from the perspective of the planner of this order) may backfire. This is why Smith often emphasizes the organic nature of things like property rights. It also shows that behind seemingly “dumb” peasants, there is often the weight of long periods of experimentation in order to adapt rules and norms in order to fit the constraints faced by the community.  In this article, we can see those two things – the backfiring and, by logical implication, the strengths of the organic institutions that were swept away.

Fielding, David, and Shef Rogers. “Monopoly power in the eighteenth-century British book trade.” European Review of Economic History 21, no. 4 (2017): 393-413.

In this article, the authors use a legal change caused by the end of the legal privileges of the Stationers’ Company (which amounted to an easing of copyright laws).  The market for books may appear to be “non-interesting” for mainstream economics. However, this would be a dramatic error. The “abundance” of books is really a recent development. Bear in mind that the most erudite monk of the late middle ages had less than fifty books from which to draw knowledge (this fact is a vague recollection of mine from Kenneth Clark’s art history documentary from the late 1960s which was aired by the BBC). Thus, the emergence of a wide market for books – which is dated within the period studied by the authors of this article – should not be ignored. It should be considered as one of the most important development in western history. This is best put by the authors when they say that “the reform of copyright law has been regarded as one of the driving forces behind the rise in book production during the Enlightenment, and therefore a key factor in the dissemination of the innovations that underpinned Britain’s Industrial Revolution”.

However, while they agree that the rising popularity of books in the 18th century is an important historical event, they contest the idea that liberalization had any effect. They find that the opening up of the market to competition had little effects on prices and book production. They also find that mark-ups fell but that this could not be attributed to liberalization. At first,  I found these results surprising.

However, when I took the time to think about it I realized that there was no reason to be surprised. First, many changes have been heralded as crucial moments in history. More often than not, the importance of these changes has been overstated. A good example of an overstated change has been the abolition of the Corn Laws in England in the 1840s. The reduction in tariffs, it is argued, ushered Britain into an age of free trade and falling food prices.

In reality, as John Nye discusses, protectionist barriers did not fall as fast as many argued and there were reductions prior to the 1846 reform as Deirdre McCloskey pointed out. It also seems that the Corn Laws did not have substantial effects on consumption or the economy as a whole (see here and here).  While their abolition probably helped increase living standards, it seems that the significance of the moment is overstated. The same thing is probably at play with the book market.

The changes discussed by Fielding and Rogers did not address the underlying roots of the level of market power enjoyed by industry players. In other words, it could be that the reform was too modest to have an effect. This is suggested by the work of Petra Moser. The reform studied by Fielding and and Rogers appears to have been short-lived as evidenced by changes to copyright laws in the early 19th century (see here and here). Moser’s results point to effects much larger (and positive for consumers) than those of Fielding and Rogers.  Given the importance of the book market to stories of innovation in the industrial revolution, I really hope that this sparks a debate between Moser and Fielding and Rogers.

Johnson, Noel D., and Mark Koyama. “States and economic growth: Capacity and constraints.” Explorations in Economic History 64 (2017): 1-20.

I am biased as I am fond of most of the work of these two authors. Nevertheless, I think that their contribution to the state capacity debate is a much needed one. I am very skeptical of the theoretical value of the concept of state capacity.  The question always lurking in my mind is the “capacity to do what?”.

A ruler who can develop and use a bureaucracy to provide the services of a “productive state” (as James Buchanan would put it) is also capable of acting like a predator.  I actually emphasize this point in my work (revise and resubmit at Health Policy & Planning) on Cuban healthcare: the Cuban government has the capacity to allocate large quantities of resources to healthcare in amounts well above what is observed for other countries in the same income range. Why? Largely because they use health care for a) international reputation and b) actually supervising the local population. As such, members of the regime are able to sustain their role even if the high level of “capacity” comes at the expense of living standards in dimensions other than health (e.g. low incomes). Capacity is not the issue, its capacity interacting with constraints that is interesting.

And that is exactly what Koyama and Johnson say (not in the same words). They summarize a wide body of literature in a cogent manner that clarifies the concept of state capacity and its limitations. In doing so, they ended up proposing that the “deep roots” question that should interest economic historians is how “constraints” came to be efficient at generating “strong but limited” states.

In that regard, the one thing that surprised me from their article was the absence of Elinor Ostrom’s work. When I read about “polycentric governance” (Ostrom’s core concept), I imagine the overlap of different institutional structures that reinforce each other (note: these structures need not be formal ones). They are governance providers. If these “governance providers” have residual claimants (i.e. people with skin in the game), they have incentives to provide governance in ways that increased the returns to the realms they governed. Attempts to supersede these institutions (e.g. like the erection of a modern nation state) requires dealing with these providers. They are the main demanders of constraints which are necessary to protect their assets (what my friend Alex Salter calls “rights to the realm“). As Europe pre-1500 was a mosaic of such governance providers, there would have been great forces pushing for constraints (i.e. bargaining over constraints).

I think that this is where the literature on state capacity should orient itself. It is in that direction that it is the most likely to bear fruits. In fact, there have been some steps taken in that direction For example, my colleagues Andrew Young and Alex Salter have applied this “polycentric” narrative to explain the emergence of “strong but limited states” by focusing on late medieval institutions (see here and here).  Their approach seems promising. Yet, the work of Koyama and Johnson have actually created the room for such contributions by efficiently summarizing a complex (and sometimes contradictory) literature.

Bodenhorn, Howard, Timothy W. Guinnane, and Thomas A. Mroz. “Sample-selection biases and the industrialization puzzle.” The Journal of Economic History 77, no. 1 (2017): 171-207.

Elsewhere, I have peripherally engaged discussants in the “antebellum puzzle” (see my article here in Economics & Human Biology on the heights of French-Canadians born between 1780 and 1830). The antebellum puzzle refers to the possibility that the biological standard of living (e.g. falling heights, worsening nutrition, increased mortality risks) fell while the material standard of living increased (e.g. higher wages, higher incomes, access to more services, access to a wider array of goods) during the decades leading to the American Civil War.

I am inclined to accept the idea of short-term paradoxes in living standards. The early 19th century witnessed a reversal in rural-urban concentration in the United States. The country had been “deurbanizing” since the colonial era (i.e. cities represented an increasingly smaller share of the population). As such, the reversal implied a shock in cities whose institutions were geared to deal with slowly increasing populations.

The influx of people in cities created problems of public health while the higher level of population density favored the propagation of infectious diseases at a time where our understanding of germ theory was nill. One good example of the problems posed by this rapid change has been provided by Gergely Baics in his work on the public markets of New York and their regulation (see his book here – a must read).  In that situation, I am not surprised that there was a deterioration in the biological standard of living. What I see is that people chose to trade-off shorter wealthier lives against longer poorer lives. A pretty legitimate (albeit depressing) choice if you ask me.

However, Bodenhorn et al. (2017) will have none of it. In a convincing article that has shaken my priors, they argue that there is a selection bias in the heights data – the main measurement used in the antebellum puzzle debate.  Most of the data on heights comes either from prisoners or enrolled volunteer soldiers (note: conscripts would not generate the problem they describe). The argument they make is that as incomes grow, the opportunity cost of committing a crime or of joining the army grows.  This creates the selection bias whereby the sample is going to be increasingly composed of those with the lowest opportunity costs. In other words, we are speaking of the poorest in society who also tended to be shorter. Simultaneously, fewer tall individuals (i.e. rich individuals) committed crimes or joined the army because incomes grew. This logic is simple and elegant. In fact, this is the kind of data problem that every economist should care about when they design their tests.

Once they control for this problem (through a meta-analysis), the puzzle disappears. I am not convinced by the latter part of the claim. Nevertheless, it is very likely that the puzzle is much smaller than initially gleaned. In yet to be published work, Ariell Zimran (see here and here) argues that the antebellum puzzle is robust to the problem of selection bias but that it is indeed diminished. This concedes a large share of the argument to Bodenhorn et al. While there is much to resolve, this article should be read as it constitutes one of the most serious contributions to the field of economic history published in 2017.

Ridolfi, Leonardo. “The French economy in the longue durée: a study on real wages, working days and economic performance from Louis IX to the Revolution (1250–1789).” European Review of Economic History 21, no. 4 (2017): 437-438.

I discussed Leonardo’s work elsewhere on this blog before. However, I must do it again. The article mentioned here is the dissertation summary that resulted from Leonardo being a finalist to the best dissertation award granted by the EHES (full dissertation here). As such, it is not exactly the “best article” published in 2017. Nevertheless,  it makes the list because of the possibilities that Leonardo’s work have unlocked.

When we discuss the origins of the British Industrial Revolution, the implicit question lurking not far away is “Why Did It Not Happen in France?”. The problem with that question is that the data available for France (see notably my forthcoming work in the Journal of Interdisciplinary History) is in no way comparable with what exists for Britain (which does not mean that the British data is of great quality as Judy Stephenson and Jane Humphries would point out).  Most estimates of the French economy pre-1790 were either conjectural or required a wide array of theoretical considerations to arrive at a deductive portrait of the situation (see notably the excellent work of Phil Hoffman).  As such, comparisons in order to tease out improvements to our understanding of the industrial revolution are hard to accomplish.

For me, the absence of rich data for France was particularly infuriating. One of my main argument is that the key to explaining divergence within the Americas (from the colonial period onwards) resides not in the British or Spanish Empires but in the variation that the French Empire and its colonies provide. After all, the French colony of Quebec had a lot in common geographically with New England but the institutional differences were nearly as wide as those between New England and the Spanish colonies in Latin America. As such, as I spent years assembling data for Canada to document living standards in order to eventually lay down the grounds to test the role of institutions, I was infuriated that I could do so little to compare with France. Little did I know that while I was doing my own work, Leonardo was plugging this massive hole in our knowledge.

Leonardo shows that while living standards in France increased from 1550 onward, the level was far below the ones found in other European countries. He also showed that real wages stagnated in France which means that the only reason behind increased incomes was a longer work year. This work has also unlocked numerous other possibilities. For example, it will be possible to extend to France the work of Nicolini and Crafts and Mills regarding the existence of Malthusian pressures. This is probably one of the greatest contribution of the decade to the field of economic history because it simply went through the dirty work of assembling data to plug what I think is the biggest hole in the field of economic history.

On the “tea saucer” of income inequality since 1917

Vincent Geloso Economics, History , , , , , , ,

I disagree often with the many details that underlie the arguments of Thomas Piketty and Emmanuel Saez. That being said, I am also a great fan of their work and of them in general. In fact, I think that both have made contributions to economics that I am envious to equal. To be fair, their U-curve of inequality is pretty much a well-confirmed fact by now: everyone agrees that the period from 1890-1929 was a high-point of inequality which leveled off until the 1970s and then picked up again.

Nevertheless, while I am convinced of the curvilinear aspect of the evolution of income inequality in the United State as depicted by Piketty and Saez, I am not convinced by the amplitudes. In their 2003 article, the U-curve of inequality really looks like a “U” (see image below).  Since that article, many scholars have investigated the extent of the increase in inequality post-1980 (circa). Many have attenuated the increase, but they still find an increase (see here here here here here here here here here). The problem is that everyone has been considering the increase – i.e. the right side of the U-curve. Little attention has been devoted to the left side of the U-curve even though that is where data problems should be considered more carefully for the generation of a stylized fact. This is the contribution I have been coordinating and working on for the last few months alongside John Moore, Phil Magness and Phil Schlosser. 

Blog Figure

To arrive at their proposed series of inequality, Piketty and Saez used the IRS Statistics of Income (SOI) to derive top income fractiles. However, the IRS SOI have many problems. The first is that between 1917 and 1943, there are many years where there are less than 10% of the potential tax population that files a tax return. This prohibits the use of a top 10% income share in many years unless an adjustment is made. The second is that prior to 1943, the IRS reports net income and reports adjusted gross income after 1943. As such, to link post-1943 with pre-1943, there needs to be an additional adjustment. Piketty and Saez made some seemingly reasonable assumptions, but they have never been put to the test regarding sensitivity and robustness. This is leaving aside issues of data quality (I am not convinced IRS data is very good as most of it was self-reported pre-1943 which is a period with wildly varying tax rates). The question here is “how good” are the assumptions?

What we did is verify each assumption to see their validity. The first one we tackle is the adjustment for the low number of returns. To make their adjustments, Piketty and Saez used the fact that single households and married households filed in different quantities relative to their total population. Their idea is that a year in which there was a large number of return was used, the ratio of single to married could be used to adjust the series. The year they used is 1942. This is problematic as 1942 is a war year with self-reporting when large quantities of young American males are abroad fighting. Using 1941, the last US peace year, instead shows dramatically different ratios. Using these ratios knocks off a few points from the top 10% income share. Why did they use 1942? Their argument was there was simply not enough data to make the correction in 1941.  They point to a special tabulation in the 1941 IRS-SOI of 112,472 1040A forms from six states which was not deemed sufficient to make to make the corrections. However, later in the same document, there is a larger and sufficient sample of 516,000 returns from all 64 IRS collection districts (roughly 5% of all forms). By comparison, the 1942 sample Piketty and Saez used to correct only had 455,000 returns.  Given the war year and the sample size, we believe that 1941 is a better year to make the adjustment.

Second, we also questioned the smoothing method to link net income-based series with adjusted-gross income based series (i.e. pre-1943 and post-1943 series). The reason for this is that the implied adjustment for deductions made by Piketty and Saez is actually larger than all the deductions claimed that were eligible under the definition of Adjusted Gross Income – which is a sign of overshot on their parts. Using the limited data available for deductions by income groups and making some assumptions (very conservative ones) to move further back in time, we found that adjusting for “actual deductions” yields a lower level of inequality. This is contrasted with the fixed multipliers which Piketty and Saez used pre-1943.

Third, we question their justification for not using the Kuznets income denominator. They argued that Kuznets’ series yielded an implausible figure because, in 1948, its use yielded a greater income for non-fillers than for fillers.  However, this is not true of all years. In fact, it is only true after 1943. Before 1943, the income of non-fillers is equal in proportion to the one they use post-1944 to impute the income of non-fillers. This is largely the result of an accounting error definition. Incomes before 1943 were reported as net income and as gross incomes after that point. This is important because the stylized fact of a pronounced U-curve is heavily sensitive to the assumption made regarding the denominator.

These three adjustments are pretty important in terms of overall results (see image below).  The pale blue line is that of Piketty of Saez as depicted in their 2003 paper in the Quarterly Journal of Economics. The other blue line just below it is the effect of deductions only (the adjustment for missing returns affects only the top 10% income share). All the other lines that mirror these two just below (with the exception of the darkest blue line which is the original Kuznets inequality estimates) compound our corrections with three potential corrections for the denominators. The U-curve still exists, but it is not as pronounced. When you look with the adjustments made by Mechling et al. (2017) and Auten and Splinter (2017) for the post-1960 period (green and red lines) and link them with ours, you can still see the curvilinear shape but it looks more like a “tea saucer” than a pronounced U-curve.

In a way, I see this as a simultaneous complement to the work of Richard Sutch and to the work of Piketty and Saez: the U-curve still exists, but the timing and pattern is slightly more representative of history. This was a long paper to write (and it is a dry read given the amount of methodological discussions), but it was worth it in order to improve upon the state of our knowledge.

FigureInequality

On Ronald Coase as an Economic Historian?

Vincent Geloso Economics, History ,

Can we consider Ronald Coase as an economic historian? Most economists or social scientists that read this blog must appreciate Coase largely for his Nature of the Firm and the Problem of Social Cost. Personally, while I appreciate these works for their theoretical insights (well, isn’t that an understatement!), I appreciate Coase much more for articles that very few know about.

Generally, after these two articles, most economists do not know what Coase wrote about.  Some might know about Coase’s proviso regarding durability and monopoly (a single firm producing a durable good cannot be a monopoly because it competes with its future self) or about his work on the Federal Communications Commission (which is an application of his two main papers).

Fewer people know about his piece about the lighthouse in economics. While it is not an unknown piece, it is mostly known within the subfield of public economics as it concerns the scope for the private provision of public goods. Generally, I found that those who know about the piece know the “takeaway” which was that lighthouses (which because of their low marginal costs and non-excludability have been deemed public goods ever since J.S. Mill) could be produced privately. While this was indeed Coase’s point, this summary (like that Stigler made of the Coase Theorem) misses the peripheral insights that matter. Coase did the economic history job of documenting the institutional details behind the provision of lighthouses which sparked debates in journals such as Journal of Legal Studies, Cambridge Journal of Economics, European Review of Economic History, Public Choice and Public Finance Review (they still go to this day and I am trying to contribute to that with this piece that me and Rosolino Candela have recently submitted). It seems unclear whether or not the lighthouse can even be considered a public good or if it was merely an instance of government failure rather than market failure (or the reverse). Regardless of the outcome, if you read the lighthouse paper by Coase, you will read an application of theory to history bringing a “boring” topic (i.e. that of maritime safety pre-1900) to life through theory.  The lighthouse paper is an application of industrial organization through the Coasean lenses of transaction costs and joint provision. And it is a fine application if I might say!

But that is not his only piece! Has anyone ever read his article in the Journal of Law & Economics on Fisher Body and vertical integration? Or his piece on the British Post Office and private messengers in the same journal?  In those articles, Coase brings theory to life by asking simple questions to history in ways that force us to question some common day conceptions like “vertical integration was the results of holdup problems” or “postal services need to be publicly provided”.  In both of these articles and the lighthouse article, Coase basically applies simple theoretical tools to cut through a maze of details in order to answer questions of great relevance to economic theory and even policy (i.e. the post office example). And this is why, earlier in 2017, I mentioned that Coase should be considered in the league of the top economic historians.

On the popularity of economic history

Vincent Geloso Books, Culture, Economics , , , , , , , , , , ,

I recently engaged in a discussion (a twittercussion) with Leah Boustan of Princeton over the “popularity” of economic history within economics (depicted below).  As one can see from the purple section, it is as popular as those hard candies that grandparents give out on Halloween (to be fair, I like those candies just like I do economic history). More importantly, the share seems to be smaller than at the peak of 1980s. It also seems like the Nobel prize going to Fogel and North had literally no effects on the subfield’s popularity. Yet, I keep hearing that “economic history is back”. After all, the Bates Clark medal went to Donaldson of Stanford this year which should confirm that economic history is a big deal.  How can this be reconciled with the figure depicted below?

EconomicHIstoryData

As I explained in my twittercussion with Leah, I think that there is a popularity for using historical data. Economists have realized that if some time is spent in archives to collect historical data, great datasets can be assembled. However, they do not necessarily consider themselves “economic historians” and as such they do not use the JEL code associated with history.  This is an improvement over a field where Arthur Burns (former Fed Chair) supposedly said during the 1970s that we needed to look at history to better shape monetary policy. And by history, he meant the 1950s. However, while there are advantages, there is an important danger which is left aside.

The creation of a good dataset has several advantages. The main one is that it increases time coverage. By increasing the time coverage, you can “tackle” the big questions and go for the “big answers” through the generation of stylized facts. Another advantage (and this is the one that summarizes my whole approach) is that historical episodes can provide neat testing grounds that give us a window to important economic issues. My favorite example of that is the work of Petra Moser at NYU-Stern. Without going into too much details (because her work was my big discovery of 2017), she used a few historical examples which she painstakingly detailed in order to analyze the effect of copyright laws. Her results have important ramifications to debates regarding “science as a public good” and “science as a contribution good” (see the debates between Paul David and Terence Kealey on this in Research Policy for this point).

But these two advantages must be weighted against an important disadvantage which Robert Margo has warned against in a recent piece in Cliometrica.  When one studies economic history, one must keep in mind that two things must be accomplished simultaneously: to explain history through theory and bring theory to life through history (this is not my phrase, but rather that of Douglass North). To do so, one must study a painstaking amount of details to ascertain the quality of the sources used and their reliability.  In considering so many details, one can easily get lost or even fall prey to his own prior (i.e. I expect to see one thing and upon seeing it I ask no question). To avoid this trap, there must be a “northern star” to act as a guide. That star, as I explained in an earlier piece, is a strong and general understanding of theory (or a strong intuition for economics). To create that star and give attention to details is an incredibly hard task and which is why I argued in the past that “great” economic historians (Douglass North, Deirdre McCloskey, Robert Fogel, Nathan Rosenberg, Joel Mokyr, Ronald Coase (because of the lighthouse piece), Stephen Broadberry, Gregory Clark etc.) take a longer time to mature. In other words, good economic historians are projects that have have a long “time to build problem” (sorry, bad economics joke).  However, the downside is that when this is not the case, there are risks of ending up with invalid results that are costly and hard to contest.

Just think about the debate between Daron Acemoglu and David Albouy on the colonial origins of development. It took more than five years to Albouy to get his results that threw doubts on Acemoglu’s 1999 paper. Albouy clearly expended valuable resources to get the “details” behind the variables. There was miscoding of Niger and Nigeria, and misunderstandings of what type of mortalities were used.  This was hard work and it was probably only deemed a valuable undertaking because Acemoglu’s paper was such a big deal (i.e. the net gains were pretty big if they paid off). Yet, to this day, many people are entirely unaware of the Albouy rebuttal.  This can be very well seen in the image below regarding the number of cites of the Acemoglu-Johnson-Robinson paper on an annual basis. There seems to be no effect from the massive rebuttal (disclaimer: Albouy convinced me that he was right) from the Albouy piece.

AcemogluPaperCites

And it really does come down to small details like those underlined by Albouy. Let me give you another example taken from my work. Within Canada, the French minority is significantly poorer than the rest of Canada. From my cliometric work, we now know that there were poorer than the rest of Canada and North America as far as the colonial era. This is a stylized fact underlying a crucial question today (i.e. Why are French-Canadians relatively poor).  That stylized fact requires an explanation. Obviously, institutions are a great place to look. One of the institution that is most interesting is seigneurial tenure which was basically a “lite” version of feudalism in North America that was present only in the French settled colonies. Some historians and economic historians argued that there were no effects of the institutions on variables like farm efficiency.  However, some historians noticed that in censuses the French reported different units that the English settlers within the colony of Quebec. To correct for this metrological problem, historians made county-level corrections. With those corrections, the aforementioned has no statistically significant effect on yields or output per farm. However, as I note in this piece that got a revise and resubmit from Social Science Quarterly (revised version not yet online), county-level corrections mask the fact that the French were more willing to move to predominantly English areas than the English were willing to predominantly French areas. In short, there was a skewed distribution. However, once you correct the data on an ethnic composition basis rather than on the county-level (i.e. the same correction for the whole county), you end with a statistically significant negative effect on both output per farm and yields per acre. In short, we were “measuring away” the effect of institutions. All from a very small detail about distributions. Yet, that small detail has supported a stylized fact that the institution did not matter.

This is the risk that Margo speaks about illustrated in two examples. Economists who use history merely as a tool may end up making dramatic mistakes that will lead to incorrect conclusions. I take this “juicy” quote from Margo (which Pseudoerasmus) highlighted for me:

[EH] could become subsumed entirely into other fields… the demand for specialists in economic history might dry up, to the point where obscure but critical knowledge becomes difficult to access or is even lost. In this case, it becomes harder to ‘get the history right’

Indeed, unfortunately.

On the point of quantifying in general and quantifying for policy purposes

Vincent Geloso Economics , , , , , , , , , , , , ,

Recently, I stumbled on this piece in Chronicle by Jerry Muller. It made my blood boil. In the piece, the author basically argues that, in the world of education, we are fixated with quantitative indicators of performance. This fixation has led to miss (or forget) some important truths about education and the transmission of knowledge. I wholeheartedly disagree because the author of the piece is confounding two things.

We need to measure things! Measurements are crucial to our understandings of causal relations and outcomes.  Like Diane Coyle, I am a big fan of the “dashboard” of indicators to get an idea of what is broadly happening.  However, I agree with the authors that very often the statistics lose their entire meaning. And that’s when we start targeting them!

Once we know that this variable becomes the object of target, we act in ways that increase this variable. As soon as it is selected, we modify our behavior to achieve fixed targets and the variable loses some of its meaning. This is also known as Goodhart’s law whereby “when a measure becomes a target, it ceases to be a good measure” (note: it also looks a lot like the Lucas critique).

Although Goodhart made this point in the context of monetary policy, it applies to any sphere of policy – including education. When an education department decides that this is the metric they care about (e.g. completion rates, minority admission, average grade point, completion times, balanced curriculum, ratio of professors to pupils, etc.), they are inducing a change in behavior which alters the significance carried by this variable.  This is not an original point. Just go to google scholar and type “Goodhart’s law and education” and you end up with papers such as these two (here and here) that make exactly the point I am making here.

In his Chronicle piece, Muller actually makes note of this without realizing how important it is. He notes that “what the advocates of greater accountability metrics overlook is how the increasing cost of college is due in part to the expanding cadres of administrators, many of whom are required to comply with government mandates“(emphasis mine).

The problem he is complaining about is not metrics per se, but rather the effects of having policy-makers decide a metric of relevance. This is a problem about selection bias, not measurement. If statistics are collected without an intent to be a benchmark for the attribution of funds or special privileges (i.e. that there are no incentives to change behavior that affects the reporting of a particular statistics), then there is no problem.

I understand that complaining about a “tyranny of metrics” is fashionable, but in that case the fashion looks like crocs (and I really hate crocs) with white socks.

In health care, expenditures to GDP may be misleading!

Vincent Geloso Economics , , , ,

In debates over health care reform in the US, it is frequent for Canada’s name to pop up in order to signal that Canada is spending much less of its GDP to health care and seems to generate relatively comparable outcomes. I disagree.

Its not that the system presently in place in the US is so great, its that the measure of resources expended on each system is really bad. In fact, its a matter of simple economics.  Imagine two areas (1 and 2), the first has single-payer health care, the other has fully-private health care.

In area 2, prices ration access to health care so that people eschew visits to the emergency room as a result of a scraped elbow. In area 1, free access means no rationing through price and more services are consumed. However, to avoid overspending, the government of area 1 has waiting lists or other rationing schemes. In area 2, which I have presented as an ideal free market for the sake of conversation,  whatever people expend can be divided over GDP and we get an accurate portrait of “costs”. However, in area 1, costs are borne differently – through taxes and through waiting times. As such, comparing what is spent in area 1 to what is spent in area 2 is a flawed comparison.

So when we say that Canada spends 10.7% of GDP on health care (2013 numbers) versus 17.1% of GDP in the US, is it a viable comparison? Not really.  In 2008, the Canadian Medical Association produced a study evaluating the cost of waiting times for four key procedures : total joint replacement surgery, cataract surgery, coronary artery bypass
graft (CABG) and MRI scans. These procedures are by no means exhaustive and they concern only “excessive” waiting times (rather than the whole waiting times or at least the difference with the United States). However, the CMA found that, for the 2007 (the year they studied), the cost of waiting was equal to 14.8$ billion (CAD).  Given the size of the economy back in 2007, this represented 1.3% of GDP. Again, I must emphasize that this is not an exhaustive measure of the cost of waiting times. However, it does bring Canada closer to the United States in terms of the “true cost” of health care.  Any estimate that would include other wait times would increase that proportion.

I know that policy experts are aware of that, but it is so frequent to see comparisons based on spending to GDP in order to argue for X and Y policy as being relatively cheap.  I just thought it was necessary to remind some people (those who decide to read me) that prudence is mandatory here.

On Monopsony and Legal Surroundings

Vincent Geloso Economics, History , , , , ,

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.

On Financial Repression and ♀ Labor Supply after 1945

Vincent Geloso Economics, History , , , , , , , , ,

I just came back from the Economic History Association meeting in San Jose. There are so many papers that are worth mentioning (and many have got my brains going, see notably the work of Nuno Palma on monetary neutrality after the “discovery” of the New World). However, the thing that really had me thinking was the panel on which one could find Barry Eichengreen and Carmen Reinhart (who was an early echo of the keynote speech by Michael Bordo).

Here’s why : Barry Eichengreen seemed uncomfortable with the current state of affairs regarding financial regulation and pointed out that the after-war period was marked by rapid growth and strong financial regulation. Then, Reinhart and Bordo emphasized the role of financial repression in depressing growth – notably in the period praised by Eichengreen. I have priors that make more favorable to the Reinhart-Bordo position, but I can’t really deny the point made by Eichengreen.

This had me thinking for some time during and after the talks. Both positions are hard to contest but they are mutually exclusive. True, it is possible that growth was strong in spite of financial repression, but some can argue that by creating some stability, regulations actually improved growth in a way that surpassed the negative effects caused by repression. But, could there be another explanation?

Elsewhere on this blog, I have pointed out that I am not convinced that the Thirty Glorious were that “Glorious”.  In line with my Unified Growth Theory inclinations (don’t put me in that camp, but don’t exclude me either I am still cautious on this), I believe that we need to account for demographic factors that foil long-term comparisons. For example, in a paper on Canadian economic growth, I pointed out that growth from 1870 to today is much more modest once we divide output by household-size population rather than overall population (see blog post here that highlights my paper). Later, I pointed out the ideas behind another paper (which I am still writing and for which I need more data, notably to replicate something like this paper) regarding the role of the unmeasured household economy. There, I argued that the shift of women from the household to the market over-measures the actual increase in output. After all, to arrive at the net value of increased labor force participation, one must deduce the value of foregone outputs in the household – something we know little about in spite of the work of people like Valerie Ramey.

Both these factors suggest the need for corrections based on demographic changes to better reflect actual living standards. These demographic changes were most pronounced in the 1945-1975 era – that of the era of rapid growth highlighted by Eichengreen and of financial repression highlighted by Reinhart and Bordo. If these changes were most momentous in that period, it is fair to say that the measurement errors they induce are also largest in that era.

So, simply put, could it be that these were not years of rapid growth but of modest growth that were overestimated?  If so, that would put the clash of ideas between Bordo-Reinhart and Eichengreen in a different light – albeit one more favorable to the former than the latter.

But heh, this is me speculating about where research could be oriented to guide some deeply relevant policy questions.

Minimum Wages: Where to Look for Evidence (A Reply)

Vincent Geloso Liberty , , , , ,

Yesterday, here at Notes on Liberty, Nicolas Cachanosky blogged about the minimum wage. His point was fairly simple: criticisms against certain research designs that use limited sample can be economically irrelevant.

To put you in context, he was blogging about one of the criticisms made of the Seattle minimum wage study produced by researchers at the University of Washington, namely that the sample was limited to “small” employers. This criticism, Nicolas argues, is irrelevant since the researchers were looking for those who were likely to be the most heavily affected by the minimum wage increase since it will be among the least efficient firms that the effects will be heavily concentrated. In other words, what is the point of looking at Costco or Walmart who are more likely to survive than Uncle Joe’s store? As such, this is Nicolas’ point in defense of the study.

I disagree with Nicolas here and this is because I agree with him (I know, it sounds confused but bear with me).

The reason is simple: firms react differently to the same shock. Costs are costs, productivity is productivity, but the constraints are never exactly the same. For example, if I am a small employer and the minimum wage is increased 15%, why would I fire one of my two employees to adjust? If that was my reaction to the minimum wage, I would sacrifice 33% of my output for a 15% increase in wages which compose the majority but not the totality of my costs. Using that margin of adjustment would be insensible for me given the constraint of my firm’s size. I might be more tempted to cut hours, cut benefits, cut quality, substitute between workers, raise prices (depending on the elasticity of the demand for my services). However, if I am a large firm of 10,000 employees, sacking one worker is an easy margin to adjust on since I am not constrained as much as the small firm. In that situation, a large firm might be tempted to adjust on that margin rather than cut quality or raise prices. Basically, firms respond to higher labor costs (not accompanied by greater productivity) in different ways.

By concentrating on small firms, the authors of the Seattle study were concentrating on a group that had, probably, a more homogeneous set of constraints and responses. In their case, they were looking at hours worked. Had they blended in the larger firms, they would have looked for an adjustment on the part of firms less to adjust by compressing hours but rather by compressing the workforce.

This is why the UW study is so interesting in terms of research design: it focused like a laser on one adjustment channel in the group most likely to respond in that manner. If one reads attentively that paper, it is clear that this is the aim of the authors – to better document this element of the minimum wage literature. If one seeks to exhaustively measure what were the costs of the policy, one would need a much wider research design to reflect the wide array of adjustments available to employers (and workers).

In short, Nicolas is right that research designs matter, but he is wrong in that the criticism of the UW study is really an instance of pro-minimum wage hike pundits bringing the hockey puck in their own net!