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

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!

Rent-Seeking Rebels of 1776

Since yesterday was Independence Day, I thought I should share a recent piece of research I made available. A few months ago, I completed a working paper which has now been accepted as a book chapter regarding public choice theory insights for American economic history (of which I talked about before).  That paper simply argued that the American Revolutionary War that led to independence partly resulted from strings of rent-seeking actions (disclaimer: the title of the blog post was chosen to attract attention).

The first element of that string is that the Americans were given a relatively high level of autonomy over their own affairs. However, that autonomy did not come with full financial responsibility.  In fact, the American colonists were still net beneficiaries of imperial finance. As the long period of peace that lasted from 1713 to 1740 ended, the British started to spend increasingly larger sums for the defense of the colonies. This meant that the British were technically inciting (by subsidizing the defense) the colonists to take aggressive measures that may benefit them (i.e. raid instead of trade). Indeed, the benefits of any land seizure by conflict would large fall in their lap while the British ended up with the bill.

The second element is the French colony of Acadia (in modern day Nova Scotia and New Brunswick). I say “French”, but it wasn’t really under French rule. Until 1713, it was nominally under French rule but the colony of a few thousands was in effect a “stateless” society since the reach of the French state was non-existent (most of the colonial administration that took place in French North America was in the colony of Quebec). In any case, the French government cared very little for that colony.   After 1713, it became a British colony but again the rule was nominal and the British tolerated a conditional oath of loyalty (which was basically an oath of neutrality speaking to the limited ability of the crown to enforce its desires in the colony). However, it was probably one of the most prosperous colonies of the French crown and one where – and this is admitted by historians – the colonists were on the friendliest of terms with the Native Indians. Complex trading networks emerged which allowed the Acadians to acquire land rights from the native tribes in exchange for agricultural goods which would be harvested thanks to sophisticated irrigation systems.  These lands were incredibly rich and they caught the attention of American colonists who wanted to expel the French colonists who, to top it off, were friendly with the natives. This led to a drive to actually deport them. When deportation occurred in 1755 (half the French population was deported), the lands were largely seized by American settlers and British settlers in Nova Scotia. They got all the benefits. However, the crown paid for the military expenses (they were considerable) and it was done against the wishes of the imperial government as an initiative of the local governments of Massachusetts and Nova Scotia. This was clearly a rent-seeking action.

The third link is that in England, the governing coalitions included government creditors who had a strong incentives to control government spending especially given the constraints imposed by debt-financing the intermittent war with the French.  These creditors saw the combination of local autonomy and the lack of financial responsibility for that autonomy as a call to centralize management of the empire and avoid such problems in the future. This drive towards centralization was a key factor, according to historians like J.P. Greene,  in the initiation of the revolution. It was also a result of rent-seeking on the part of actors in England to protect their own interest.

As such, the history of the American revolution must rely in part on a public choice contribution in the form of rent-seeking which paints the revolution in a different (and less glorious) light.

James Buchanan on racism


Ever since Nancy MacLean’s new book came out, there have been waves of discussions of the intellectual legacy of James Buchanan – the economist who pioneered public choice theory and won the Nobel in economics in 1986. Most prominent in the book are the inuendos of Buchanan’s racism.  Basically, public choice had a “racist” agenda.  Even Brad DeLong indulged in this criticism of Buchanan by pointing that he talked about race by never talking race, a move which reminds him of Lee Atwater.

The thing is that it is true that Buchanan never talked about race as DeLong himself noted.  Yet, that is not a sign (in any way imaginable) of racism. The fact is that Buchanan actually inspired waves of research regarding the origins of racial discrimination and was intellectually in line with scholars who contributed to this topic.

Protecting Majorities and Minorities from Predation

To see my point in defense of Buchanan here, let me point out that I am French-Canadian. In the history of Canada, strike that, in the history of the province of Quebec where the French-Canadians were the majority group, there was widespread discrimination against the French-Canadians. For all intents and purposes, the French-Canadian society was parallel to the English-Canadian society and certain occupations were de facto barred to the French.  It was not segregation to be sure, but it was largely the result of the fact that the Catholic Church had, by virtue of the 1867 Constitution, monopoly over education. The Church lobbied very hard  in order to protect itself from religious competition and it incited logrolling between politicians in order to win Quebec in the first elections of the Canadian federation. Logrolling and rent-seeking! What can be more public choice? Nonetheless, these tools are used to explain the decades-long regression of French-Canadians and the de facto discrimination against them (disclaimer: I actually researched and wrote a book on this).

Not only that, but when the French-Canadians started to catch-up which in turn fueled a rise in nationalism, the few public choice economists in Quebec (notably the prominent Jean-Luc Migué and the public choice fellow-traveler Albert Breton) were amongst the first to denounce the rise of nationalism and reversed linguistic discrimination (supported by the state) as nothing else than a public narrative aimed at justifying rent-seeking attempts by the nationalists (see here and here for Breton and here and here for Migué). One of these economists, Migué, was actually one of my key formative influence and someone I consider a friend (disclaimer: he wrote a blurb in support of the French edition of my book).

Think about this for a second : the economists of the public choice tradition in Quebec defended both the majority and the minority against politically-motivated abuses. Let me repeat this : public choice tools have been used to explain/criticize attempts by certain groups to rent-seek at the expense of the majority and the minority.

How can you square that with the simplistic approach of MacLean?

Buchanan Inspired Great Research on Discrimination and Racism

If Buchanan didn’t write about race, he did set up the tools to explain and analyze it. As I pointed out above, I consider myself in this tradition as most of my research is geared towards explaining institutions that cause certain groups of individuals to fall behind or pull ahead.  A large share of my conception of institutions and how state action can lead to predatory actions against both minorities and majorities comes from Buchanan himself!  Nevermind that, check out who he inspired who has published in top journals.

For example, take the case of the beautifully written articles of Jennifer Roback who presents racism as rent-seeking. She sets out the theory in an article in Economic Inquiry , after she used a case study of segregated streetcars in the Journal of Economic HistoryA little later, she consolidated her points in a neat article in the Harvard Journal of Law and Public PolicyShe built an intellectual apparatus using public choice tools to explain the establishment of discrimination against blacks and how it persisted for long.

Consider also one of my personal idols, Robert Higgs who is a public-choice fellow traveler who wrote Competition and Coerciowhich considers the topic of how blacks converged (very slowly) with whites in hostile institutional environment. Higgs’ treatment of institutions is well in line with public choice tools and elements advanced by Buchanan and Tullock.

The best case though is The Origins and Demise of South African Apartheid by Anton David Lowenberg and William H. Kaempfer. This book explicitly uses a public choice to explain the rise and fall of Apartheid in South Africa.

Contemporaries that Buchanan admired were vehemently anti-racist

Few economists, except maybe economic historians, know of William Harold Hutt. This is unfortunate since Hutt produced one of the deepest and most thoughtful economic criticism of Apartheid in South Africa, The Economics of the Colour Bar This book stands tall and while it is not the last word, it generally is the first word on anything related to Apartheid – a segregation policy against the majority that lasted nearly as long as segregation in the South.  This writing, while it earned Hutt respect amongst economists, made him more or less personae non grata in his native South Africa.

Oh, did I mention that Hutt was a public choice economist? In 1971, Hutt published Politically Impossible which has been an underground classic in the public choice tradition. Unfortunately, Hutt did not have the clarity of written expression that Buchanan had and that book has been hard to penetrate.  Nonetheless, the book is well within the broad public choice tradition.  He also wrote an article in the South African Journal of Economics which expanded on a point made by Buchanan and Tullock in the Calculus of Consent. 

Oh, wait, I forgot to mention the best part. Buchanan and Hutt were mutual admirers of one another. Buchanan cited Hutt’s work very often (see here and here) and spoke with admiration of Hutt (see notably this article here by Buchanan and this review of Hutt’s career where Buchanan is discussed briefly).

If MacLean wants to try guilt by (inexistent) association, I should be excused from providing redemption by (existent) association.  Not noting these facts that are easily available shows poor grasp of the historiography and the core intellectual history.

Simply Put

Buchanan inspired a research agenda regarding how states can be used for predatory purposes against minorities and majorities which has produced strong interpretations of racism and discrimination. He also associated with vehement and admirable anti-racists like William H. Hutt and inspired students who took similar positions. I am sure that if I were to assemble a list of all the PhD students of Buchanan, I would find quite a few who delved into the deep topic of racism using public choice tools. I know better and I did not spend three years researching Buchanan’s life. Nancy MacLean has no excuse for these oversights.

Is the U-curve of US income inequality that pronounced?

For some time now, I have been skeptical of the narrative that has emerged regarding income inequality in the West in general and in the US in particular. That narrative, which I label UCN for U-Curve Narrative, simply asserts that inequality fell from a high level in the 1910s down to a trough in the 1970s and then back up to levels comparable to those in the 1910s.

To be sure, I do believe that inequality fell and rose over the 20th century.  Very few people will disagree with this contention. Like many others I question how “big” is the increase since the 1970s (the low point of the U-Curve). However, unlike many others, I also question how big the fall actually was. Basically, I do think that there is a sound case for saying that inequality rose modestly since the 1970s for reasons that are a mixed bag of good and bad (see here and here), but I also think that the case that inequality did not fall as much as believed up to the 1970s is a strong one.

The reasons for this position of mine relates to my passion for cliometrics. The quantitative illustration of the past is a crucial task. However, data is only as good as the questions it seek to answer. If I wonder whether or not feudal institutions (like seigneurial tenure in Canada) hindered economic development and I only look at farm incomes, then I might be capturing a good part of the story but since farm income is not total income, I am missing a part of it. Had I asked whether or not feudal institutions hindered farm productivity, then the data would have been more relevant.

Same thing for income inequality I argue in this new working paper (with Phil Magness, John Moore and Phil Schlosser) which is a basically a list of criticisms of the the Piketty-Saez income inequality series.

For the United States, income inequality measures pre-1960s generally rely on tax-reporting data. From the get-go, one has to recognize that this sort of system (since it is taxes) does not promote “honest” reporting. What is less well known is that tax compliance enforcement was very lax pre-1943 and highly sensitive to the wide variations in tax rates and personal exemption during the period. Basically, the chances that you will report honestly your income at a top marginal rate of 79% is lower than had that rate been at 25%. Since the rates did vary from the high-70s at the end of the Great War to the mid-20s in the 1920s and back up during the Depression, that implies a lot of volatility in the quality of reporting. As such, the evolution measured by tax data will capture tax-rate-induced variations in reported income (especially in the pre-withholding era when there existed numerous large loopholes and tax-sheltered income vehicles).  The shift from high to low taxes in the 1910s and 1920s would have implied a larger than actual change in inequality while the the shift from low to high taxes in the 1930s would have implied the reverse. Correcting for the artificial changes caused by tax rate changes would, by definition, flatten the evolution of inequality – which is what we find in our paper.

However, we go farther than that. Using the state of Wisconsin which had a tax system with more stringent compliance rules for the state income tax while also having lower and much more stable tax rates, we find different levels and trends of income inequality than with the IRS data (a point which me and Phil Magness expanded on here). This alone should fuel skepticism.

Nonetheless, this is not the sum of our criticisms. We also find that the denominator frequently used to arrive at the share of income going to top earners is too low and that the justification used for that denominator is the result of a mathematical error (see pages 10-12 in our paper).

Finally, we point out that there is a large accounting problem. Before 1943, the IRS provided the Statistics of Income based on net income. After 1943, there shift between definitions of adjusted gross income. As such, the two series are not comparable and need to be adjusted to be linked. Piketty and Saez, when they calculated their own adjustment methods, made seemingly reasonable assumptions (mostly that the rich took the lion’s share of deductions). However, when we searched and found evidence of how deductions were distributed, they did not match the assumptions of Piketty and Saez. The actual evidence regarding deductions suggest that lower income brackets had large deductions and this diminishes the adjustment needed to harmonize the two series.

Taken together, our corrections yield systematically lower and flatter estimates of inequality which do not contradict the idea that inequality fell during the first half of the 20th century (see image below). However, our corrections suggest that the UCN is incorrect and that there might be more of small bowl (I call it the Paella-bowl curve of inequality, but my co-authors prefer the J-curve idea).


On Borjas, Data and More Data

I see my craft as an economic historian as a dual mission. The first is to answer historical question by using economic theory (and in the process enliven economic theory through the use of history). The second relates to my obsessive-compulsive nature which can be observed by how much attention and care I give to getting the data right. My co-authors have often observed me “freaking out” over a possible improvement in data quality or be plagued by doubts over whether or not I had gone “one assumption too far” (pun on a bridge too far). Sometimes, I wish more economists would follow my historian-like freakouts over data quality. Why?

Because of this!

In that paper, Michael Clemens (whom I secretly admire – not so secretly now that I have written it on a blog) criticizes the recent paper produced by George Borjas showing the negative effect of immigration on wages for workers without a high school degree. Using the famous Mariel boatlift of 1980, Clemens basically shows that there were pressures on the US Census Bureau at the same time as the boatlift to add more black workers without high school degrees. This previously underrepresented group surged in importance within the survey data. However since that underrepresented group had lower wages than the average of the wider group of workers without high school degrees, there was an composition effect at play that caused wages to fall (in appearance). However, a composition effect is also a bias causing an artificial drop in wages and this drove the results produced by Borjas (and underestimated the conclusion made by David Card in his original paper to which Borjas was replying).

This is cautionary tale about the limits of econometrics. After all, a regression is only as good as the data it uses and suited to the question it seeks to answer. Sometimes, simple Ordinary Least Squares are excellent tools. When the question is broad and/or the data is excellent, an OLS can be a sufficient and necessary condition to a viable answer. However, the narrower the question (i.e. is there an effect of immigration only on unskilled and low-education workers), the better the method has to be. The problem is that the better methods often require better data as well. To obtain the latter, one must know the details of a data source. This is why I am nuts over data accuracy. Even small things matter – like a shift in the representation of blacks in survey data – in these cases. Otherwise, you end up with your results being reversed by very minor changes (see this paper in Journal of Economic Methodology for examples).

This is why I freak out over data. Maybe I can make two suggestions about sharing my freak-outs.

The first is to prefer a skewed ratio of data quality to advanced methods (i.e. simple methods with crazy-data). This reduces the chances of being criticized for relying on weak assumptions. The second is to take a leaf out of the book of the historians. While historians are often averse to advantaged data techniques (I remember a case when I had to explain panel data regressions to historians which ended terribly for me), they are very respectful of data sources. I have seen historians nurture datasets for years before being willing to present them. When published, they generally stand up to scrutiny because of the extensive wealth of details compiled.

That’s it folks.


Can we trust US interwar inequality figures?

This question is the one that me and Phil Magness have been asking for some time and we have now assembled our thoughts and measures in the first of a series of papers. In this paper, we take issue with the quality of the measurements that will be extracted from tax records during the interwar years (1918 to 1941).

More precisely, we point out that tax rates at the federal level fluctuated wildly and were at relatively high levels. Since most of our inequality measures are drawn from the federal tax data contained in the Statistics of Income, this is problematic. Indeed, high tax rates might deter honest reporting while rapidly changing rates will affect reporting behavior (causing artificial variations in the measure of market income). As such, both the level and the trend of inequality might be off.  That is our concern in very simple words.

To assess whether or not we are worrying for nothing, we went around to find different sources to assess the robustness of the inequality estimates based on the federal tax data. We found what we were looking for in Wisconsin whose tax rates were much lower (never above 7%) and less variable than those at the federal levels. As such, we found the perfect dataset to see if there are measurement problems in the data itself (through a varying selection bias).

From the Wisconsin data, we find that there are good reasons to be skeptical of the existing inequality measured based on federal tax data. The comparison of the IRS data for Wisconsin with the data from the state income tax shows a different pattern of evolution and a different level (especially when deductions are accounted for). First of all, the level is always inferior with the WTC data (Wisconsin Tax Commission). Secondly, the trend differs for the 1930s.

Table1 for Blog

I am not sure what it means in terms of the true level of inequality for the period. However, it suggests that we ought to be careful towards the estimations advanced if two data sources of a similar nature (tax data) with arguably minor conceptual differences (low and stable tax rates) tell dramatically different stories.  Maybe its time to try to further improve the pre-1945 series on inequality.

Empire effects : the case of shipping

I have been trying, for some time now, to circle an issue that we can consider to be a cousin of the emerging “state capacity” literature (see Mark Koyama’s amazing summary here). This cousin is the literature on “empire effects” (here and here for examples).

The core of the “empire effect” claim is that empires provide global order which we can consider as a public good. A colorful image would be the British Navy roaming the seas in the 19th century which meant increased protection for trade. This is why it is a parent of the state capacity argument in the sense that the latter concept refers (broadly) to the ability of a state to administer the realm within its boundaries. The empire effect is merely the extension of these boundaries.

I still have reservations about the nuances/limitations of state capacity as an argument to explain economic growth. After all, the true question is not how states consolidate, but how they create constraints on rulers to not abuse the consolidated powers (which in turn generates room for growth). But, it is easy to heavily question its parent: the empire effect.

This is what I am trying to do in a recent paper on the effects of empire on shipping productivity between 1760 and 1860.

Shipping is one of the industry that is most likely to be affected by large empires – positively or negatively. Indeed, the argument for empire effects is that they protect trade. As such, the British navy in the 19th century protected trade and probably helped the shipping industry become more productive. But, achieving empire comes at a cost. For example, the British navy needed to grow very large in size and it had to employ inputs from the private sector thus crowding-it out. In a way, if a security effect from empire emerged as a benefit, there must have been a cost. The cost we wish to highlight is the crowding-out one.

In the paper (written with Jari Eloranta of Appalachian State University and Vadim Kufenko of University of Hohenheim), I argue that, using the productivity of the Canadian shipping industry which was protected by the British Navy, the security effect from a large navy was smaller than the crowding-out from high-levels of expenditures on the navy.

While it is still a working paper which we are trying to expand and improve, our point is that what allowed the productivity of the Canadian shipping industry (which was protected by Britain) to soar was that the British Navy grew smaller in absolute terms. While the growth of the relative strength of the British Navy did bolster productivity in some of our tests, the fact that the navy was much smaller was the “thing in the mix that did the trick”.  In other words, the empire effect is just the effect of a ramping-down in military being presented as something else than it truly is (at least partly).

That’s our core point. We are still trying to improve it and (as such) comments are welcomed.