From the Comments: Weber, Geloso on inequality

How did I not see these before? Rick chimed in on Zak’s post about inequality and libertarianism awhile back. As usual, he tries to give the opposition the benefit of the doubt:

Taking public choice logic seriously means considering the political distortions/impediments to proposed policy. Taking inequality seriously is the flip side of that. Perceptions of (and attitudes towards) inequality matter and libertarians (and conservatives) would do well to acknowledge it.

I suspect that the problem is that 1) (like any ideology) we’ve got a blind spot, and inequality is in that spot. 2) Our liberal friends can see into that blind spot. 3) They’ve got a blind spot that leads them to make silly policy prescriptions (e.g. ignoring public choice roots of inequality and instead calling for policies that would reduce growth). And as a result, 4) we’re turned off by discussion of inequality before considering it.

Vincent, in the usual French manner, has a different take:

Okay massive disagreement here:

A: Inequality is not something “measurable” in the sense of utility. I chose to be an economist. My income is X% below that of my wife who went to school fewer years than I did and her income grows faster than mine and she will live longer than me (in probabilistic terms given life expectancy differences M/F). According to that definition, my couple is an unequal one and growing more unequal. Yet, I would not trade her job for mine even if her job was twice as remunerative (she is an attorney). I chose a path of lesser income because it made me happy. Income maximization was, in that case, not synonymous with utility maximization. By definition, rich societies will have more cases like that since gains in marginal utility may not be associated with marginal gains in monetary income. See the issue of the backward-bending labor supply curve.

B: The literature on linking growth to inequality is VERY weak. Look at the empirical papers, the results often depend on the choice of variables and the time window. It NEVER accounts for what I mentioned in point A. More importantly, there is NO THEORETICAL LINK with neoclassical theory on this (with the notable exception of Herb Gintis and Sam Bowles and I am working on a paper tackling their logic) that is axiomatically consistent. An empirical observation without a theory that is logically sound (the most repeated is the general Keynesian argument about consumption, but that is very weak and that rebuttal is powerful in the theoretical papers) is basically rubbish.

C: The Great Gatsby Curve is also rubbish since most of the past observations are based on the weird assumptions that mobility based on father-sons is a proper estimate to compare with modern estimates. You can consult the very convincing rebuttals made by Scott Winship. Moreover, the Great Gatsby curve is again a case of empirical observations without theory. I don’t need any of this story to see that mobility is down (modestly) at the same time that labor market restrictions are up.

There is more discussion, too.

A Common Conservative Fallacy

I believe folly serves liberals better than it serves conservatives. Our way is the rational way while liberals tend to rely on their gut-feelings and on their sensitive hearts which make them comparatively indifferent to hard facts. That’s why they voted for  Pres. Obama. That’s why they voted for Mrs Bill Clinton against all strong evidence (known evidence, verifiable, not just suppositions) of her moral and intellectual unsuitability. That’s why many of them still can’t face emotionally the possibility of buyer’s remorse with respect to Mr Obama. That’s why they can’t collectively face the results of the 2016 election. So, conservatives have a special duty to wash out their brains of fallacy often.

It’s the task of every conservative to correct important errors that have found their way into fellow conservatives’ mind. Here is one I hear several times a week, especially from Rush Limbaugh (whom I otherwise like and admire). What’s below is a paraphrase, a distillation of many different but similar statements, from Limbaugh and from others I listen to and read, and from Internet comments, including many on my own Facebook:

“Government does not create jobs,”


“Government does not create wealth (it just seizes the wealth created by business and transfers it to others).”

Both statements are important and both statements are just false. It’s not difficult to show why.

First, some government actions make jobs possible that would not exist, absent those actions. Bear with me.

Suppose I have a large field of good bottom land. From this land I can easily grow a crop of corn sufficient to feed my family, and our poultry, and our pig, Gaspard. I grow a little more to make pretty good whiskey. I have no reason to grow more corn than this. I forgot to tell you: This is 1820 in eastern Ohio. Now, the government uses taxes (money taken from me and from others under threat of violence, to be sure) to dig and build  a canal that links me and others to the growing urban centers of New York and Pennsylvania. I decide to plant more corn, for sale back East. This growth in my total production works so well that I expand again. Soon, I have to hire a field hand to help me out. After a while, I have two employees.

In the  historically realistic situation I describe, would it not be absurd to declare that the government gets no credit, zero credit for the two new jobs? Sure, absent government tax-supported initiative, canals may have been built as private endeavors and with private funds. In the meantime, denying that the government contributed to the creation of two new jobs in the story above is not true to fact.

Second, it should be obvious that government provides many services, beginning with mail delivery. Also, some of the services private companies supply in this country are provided elsewhere by a branch of government. They are comparable. This fact allows for an estimation of the economic value of the relevant government services. Emergency services, ambulance service, is a case in point. Most ambulances are privately owned and operated in the US while most ambulances are government-owned and operated in France. If you have a serious car accident in the US, you or someone calls a certain number and an ambulance arrives to administer first aid and to carry you to a hospital if needed. Exactly the same thing happens in France under similar circumstances. (The only difference is that, in France, the EM guy immediately hands you a shot of good cognac. OK, it’s not true; I am kidding.)

In both countries, the value of the service so rendered is entered into the national accounting and it does in fact appear in the American Gross Domestic Product for the year (GDP) and in the French GDP, respectively. The GDP of each country thus increases by something like $500 each time an ambulance is used. Incidentally, the much decried GDP is important because it’s the most common measure of the value of our collective production. One version of GDP (“PPP”) is roughly comparable between countries. When the GDP is up by 3,5 % for a year, it makes every American who knows it, happy; also some who don’t know it. When the GDP shrinks by 1%, we all worry and we all feel poorer. If the GDP change shrinks below zero for two consecutive quarters, you have the conventional definition of a recession and all hell breaks lose, including usually a rise in unemployment.

Exactly the same is true in France. The government-provided French ambulance service has exactly the same effect on the French GDP.

Now think of this: Is there anyone who believes that the equivalent service supplied in France by a government agency does not have more or less the same value as the American service provided by a private company? Would anyone argue that the ambulance service supplied in France, in most ways identical to the service in America, should not be counted in the French GDP? Clearly, both propositions are absurd.

Same thing for job creation. When the French government agency in charge of ambulances hires an additional ambulance driver, it creates a new job, same as when an American company hires an ambulance driver.

By the way, don’t think my story trivial. “Services” is a poorly defined category. It’s even sometimes too heterogeneous to be useful (not “erogenous,” please pay attention). It includes such disparate things as waitressing, fortune-telling, university teaching, and doing whatever Social Security employees do. Yet it’s good enough for gross purposes. Depending on what you include, last year “services” accounted for something between 45% and 70% of US GDP. So, if you think services, such as ambulance service, should not be counted, you should know that it means that we are earning collectively about half to three quarters less than we think we do. If memory serves, that means that our standard of living today is about the same as it was in 1950 or even in 1930.

Does this all imply that we should rejoice every time the government expands? The answer is “No,” for three reasons. These three reasons however should only show up after we have resolved the issue described above, after we have convinced ourselves that government does provide service and that it and does create real jobs, directly and indirectly. Below are the three questions that correspond to the three reasons why conservatives should still not rejoice when government enlarges its scope. Conservatives should ask these three questions over and over again:

1 Is this service a real service to regular people or is it created only, or largely, to serve the needs of those who provide it, or for frivolous reasons? Some government services fall into this area, not many, I think. Look in the direction of government control, inspection, verification functions. Don’t forget your local government.

Often, the answer to this question is not clear or it is changing. Public primary and secondary education looks more and more like a service provided largely or even primarily to give careers to teachers and administrators protected by powerful unions. It does not mean that the real, or the expected service, “education,” is not delivered, just that it’s often done badly by people who are not the best they could be to provide that particular service; also people who are difficult or impossible to replace.

2   Is this particular service better provided by government or by the private sector? Is it better provided by government although the provision of the service requires collecting taxes and then paying out the proceeds to the actual civil servants through a government bureaucracy? That’s a very indirect way to go about anything, it would seem. That’s enough reason to be skeptical. The indirectness of the route between collecting the necessary funds and their being paid out to providers should often be enough to make government service more expensive than private, market-driven equivalent services. Note that the statement is credible even if every government employee involved is a model of efficiency.

The US Post Office remains the best example of a  situation where one would say  the private sector can do it better.

Only conservatives dare pose this question with respect to services one level of government or other has been supplying for a long time or forever. The Post Office is inefficient; if it were abolished, the paper mail would be delivered, faster or cheaper, or both. Some paper mail would not be delivered anymore. Many more of us would count it a blessing than the reverse. While there is a broad consensus across the political spectrum that children should be educated at collective expense, there is growing certitude that governments should not be in the business of education. In many parts of the country, the public schools are both expensive and bad. Last time I looked, Washington DC was spending over $20,000 per pupil per year. Give me half that amount and half the students or better will come out knowing how to read, I say. (It’s not the case now.)

3   This is the most serious question and the most difficult to answer concretely: Does the fact that this service is provided by government (any level) have any negative effect on our liberties? This is a separate question altogether. It may be that the government’s supply of a particular service is both inefficient and dangerous to freedom. It may be however that government supply is the most efficient solution possible and yet, I don’t want it because it threatens my freedom. As a conservative, I believe that my money is my money. I am free to use it to buy inefficiently, in order to preserve liberty, for example. I am not intellectually obligated to be “pragmatic” and short sighted.

To take an example at random, if someone showed me, demonstrated beyond a reasonable doubt, that Obamacare would reduce the cost of health care without impairing its quality, if that happened, I would still be against it because of the answer I would give to the third and last question above.

I don’t want a any government bureaucracy to make decisions that are ultimately decisions of life and death on my behalf. The possibility of blackmail is too real. Even thinking about it is likely to make some citizens more docile than they otherwise would be. So much power about such real issues must have a chilling effect on the many.

The rule of thumb is this: Every expansion of government reduces individual freedom. That’s true even if this expansion creates and efficient and effective government agency, say, a real good Post Office we don’t even know how to dream of. And this is not an abstract view. The well-intentioned and in other ways laudable recognition of homosexual marriage was followed in short order by threats and fines against a hapless baker who declined to bake a cake for a gay wedding. We must keep in mind at all times that, of course, the power to fine, like the power to tax, is the power to destroy.

An efficient but ethically objectionable government service is not something I worry much about, in the case of Obamacare specifically, by the way. It is inefficient, ineffective and dangerous to individual liberty all at once.

Conservatives don’t do enough to proclaim that their opposition to big government has an ethical basis, that it’s a moral position independent of the quality of big government. This silence makes if easy for liberals to caricature conservatives as just selfish grouches who don’t want to pay taxes.

Most of the time, I don’t want to pay taxes because I don’t want to be forced. I would gladly give away twice the amount of my taxes if there were a way to do it voluntarily instead of paying taxes.

I am so opposed to this kind of force that I think even the undeserving and obscenely rich should not be despoiled by the government. It’s an ethical position, not a pragmatic one. And, it sure cannot be called “selfish.” (WTF!)

Minimum wage, measurements and incarceration rates

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

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

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


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

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

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


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

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

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

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

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

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

Where should the line be?

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

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

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

How to factor in family size and use equivalence scales. 

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

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


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

Sensitivity of estimates

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

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

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


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