The Cost of ‘Free’ – or why I don’t like freeware

This is a partial response to Fabio Rojas recent post on the fate of Stata, a statistics package, given the rise of a free alternative, R. Rojas and others have many reasons for why R is a good package, but for now I wish to deal with the argument that it being ‘free’ is a virtue.

R is free, but I see it as a fault because it reveals that it doesn’t have a devoted support system and because it isn’t free at all. It’s actually very costly!

If you’ve spent any time with an economist you should know that there is no such thing as a free lunch. If R is free we should not simply assume it is better. To the contrary we should ask why it is free. As I have tried to argue elsewhere, it is because when you purchase software you aren’t just purchasing a few lines of code. You’re purchasing the support system that comes with it. When a company purchases Stata, or any commercial software, they do so with the expectation that they can call a dedicated hotline for troubleshooting. As software has evolved you’ve seen companies experiment with pricing to acknowledge the fact that we don’t purchase a one time software but a continuous support system.

Consider Xbox or Playstation’s online services. Their use is charged on a per time basis because it costs money to run servers and provide customer support. Even ‘freemium’ games, which nominally don’t require any money to play, survive off micro transactions which enable companies to earn steady revenues in exchange for continuing support and new content. I would not be surprised if freemium statistical software is tried in the future – access to basic regressions is free but more advanced models cost money to run. I half joke.

But let’s assume you’re good at coding and don’t need much support outside of a few days reading an R book. Should you praise R for being ‘free’? No, because you still paid the time value of your time. Every hour spent learning how to code in R is an hour you could have spent doing any number of things.

Now to be clear, you may still want to learn R if it frees up your time in the future by automating X process. This post isn’t to argue against adopting R. My point is only to say that it isn’t free in a meaningful sense. Adopting R costs in the sense that you’re giving up a devoted support system and value of time equal to how long it takes you to become proficient in it.

It’s possible that once you account for those things R is still ‘cheaper’ than commercial software like Stata or SPSS. That is an empirical question beyond the scope of this post.


How dairy farmers unions in Canada are distorting the facts about supply management

Under heat recently as President Trump has criticized supply management in Canada and retaliated against it, the different provincial associations representing dairy farmers have moved on the offensive. To promote the virtues of this system meant to reduce production in order to prop up prices through the use of trade tariffs, production quotas and price controls (how can we call those virtues), these unions have produced numerous infographics to make their case. It is even part of what they dub their These-infographics-show-that-diary-prices-are-lower-in-Canada-than-elsewhere, that milk is still a cheap drink relative to other type of drinks and those prices, supposedly, increase more slowly than elsewhere. All of these graphics are dishonest and must be dismantled.

The most egregious of these infographics – present in the “lobby day kit” – shows the price of milk in Australia (1.55 CAD), Canada (1.45 CAD) and New Zealand (1.65 CAD). They are seemingly using 2014 prices. First of all, they use data that conflicts massively with the reports of Statistics Canada that suggest that milk prices hover between 2.33$ to 2.48$ per liter.  Their data is provided by AC Nielsen but no justification is presented as to why they are better than Statistics Canada. The truth is that it is not better. Participants in Nielsen surveys come from a self-selected pool of storeowners who wish to participate and are then selected by Nielsen to be part of the data collection. Then, they can record prices. It should be mentioned that not all regions of Canada are covered in the data. Although the Nielsen data does have some uses (especially with regards to market studies), it hardly measures up Statistics Canada when comes the time to evaluate price levels. This is because the government agency collects information from all regions and tries a broader sweep of retailers in order to create the consumer price index.

But an even larger problem is that, in their comparison of prices, they don’t mention that New Zealand taxes milk. In New Zealand, all food items are subjected to sales tax, which is not the case in Canada and Australia. Hence, when they compare retail prices, they are comparing prices that exclude taxes and prices that include taxes. One would like to find if they acknowledge this fact in the methodological mentions, but there are none!

Using prices available at and and the exchange rates made available by the Bank of Canada, we can correct for this problem of theirs. Simply changing prices source leads to a massively different result with regards to Australia whose milk prices are lower than in Canada. Secondly, once we adjust for the sales tax in New Zealand, we find that prices in New Zealand are lower than in Canada. In fact they are lower than in one of Canada’s cheapest market, Montreal (let alone Toronto or Vancouver).  So the infographic they show in order to lobby governments is a fabrication.

Table 1: The real price of milk

Using (regular milk)
Unadjusted Adjusted for taxes
 Australia  $           1.59  $                 1.59
 New Zealand  $           2.26  $                 1.97
 Canada  $           1.99  $                 1.99
 Using (whole milk)
 Unadjusted  Adjusted for taxes
 Sydney  $           1.82  $                 1.47
 Wellington  $           2.42  $                 2.10
 Montreal  $           2.87  $                 2.87

Source: and, consulted May 16th 2014 and the Bank of Canada’s currency converter. Note: using the Statistics Canada price would make Canada’s situation even worse by comparison.

This is part of a pattern of deceit since they also massage data for numerous other graphs that are presented to Canadians in efforts to convince them of the virtues of supply management. One other example is an infographic that presents a figure of nominal milk prices in Australia before and after the abolition of supply management. Given that prices seem more volatile after 2000 and that they increase more steeply, they try to make us believe that liberalization was a failure. This is not the case. Any sensible policy analyst would deflate nominal prices by the general price index to control for inflation. When one does just that using the data from the Australian Bureau of Statistics, one sees that real prices stabilized in the first ten years of deregulation after increasing roughly 15% in the decade prior. And since 2010, real prices have been falling constantly.

Other examples abound. In one instance, the Quebec union of dairy farmers circulated an infographic meant to show that nominal prices for dairy products increased faster in the United States than in Canada. Again, they omit inflation. Since 1990 (their own starting date), prices of dairy products have risen more slowly than inflation – indicating a decline in real prices. In Canada, the opposite occurred – inflation increased more slowly than dairy prices indicating an increase of the real price.

The debate around supply management is complicated. The policy course to adopt in order to improve agricultural productivity and lower prices for Canadians is hard to pinpoint. But whatever position one may hold, no one is well-served by statistical manipulations offered by the unions representing dairy farmers.

On 7 million deaths from air pollution

ATTN published a video of An-huld (the really cool guy who made my childhood by being in all my favorite action movies like Predator* and who ended up being the governor of California). In that short clip, Schwarznegger starts by saying that 7 million individuals die from pollution-related illnesses.

That number is correct. But it is misleading.

People see pollution as “all and the same”. But some forms of pollution increase with development (sulfur emissions and some would argue that too much CO2 emissions is pollution as it causes climate change). However, others drop dramatically – especially heavy particules (Pm10) which are a great cause of smog. Julian Simon (the late cornucopian economist who is one my greatest intellectual influence) pointed out this issue and noted that the deadliest forms of pollution are those that relate to underdevelopment.

Back in 2003, Jack Hollander published the Real Environmental Crisis: Why Poverty, Not Affluence is the Environment’s Number One Enemy. Hollander pointed out that simply from the combustion of organic matter (read: firewood and animal manure – literally burning fecal matter) indoors for the purposes of heating, cooking and lighting was responsible for close to 2 millions deaths.

Since then, the WHO came out with a study pointing out that around 3 billion people cook and heat their homes with open fires and stoves that rely on biomass or anthracite-coal. They put the number of premature deaths directly resulting from this at over 4 million people. This is close to 60% of the figure cited by the former President of California (yes, I know he was governor – see here). In other words, 60% of the people who die prematurely as a result of strokes, ischaemic heart diseases, chronic obstructive pulmonary diseases and lung cancers can be attributed to indoor air pollution. That means pollution resulting from the fact that you are so poor that you have to burn anything at hand at the cost of your health.

True, richer countries pollute and there are policy solutions (I have often argued that governments are better at polluting than at reducing pollution, but that is another debate) that should be adopted. But, these forms of pollution do not harm human life as much as those that come with poverty.

* By the way, when you watch Predator, do you realize that there are two future American governors in that movie? I mean, imagine that when Predator came out, some dude from the future told you that two of the main actors would end governing American states. Pretty freaky!

Spanish GDP since 1850

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

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


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


Canadian Megatrends: Top 1% income share and median age

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

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


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

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

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

Castro: Coercing Cubans into Health

On Black Friday, one of the few remaining tyrants in the world passed away (see the great spread of democracy in the world since 1988). Fidel Castro is a man that I will not mourn nor will I celebrate his passing. What I mourn are the lives he destroyed, the men and women he impoverished, the dreams he crushed and the suffering he inflicted on the innocents. When I state this feeling to others, I am told that he improved life expectancy in Cuba and reduced infant mortality.

To which I reply: why are you proving my point?

The reality that few people understand is that even poor countries can easily reduce mortality with the use of coercive measures available to a centralized dictatorship. There are many diseases (like smallpox) that spread because individuals have a hard time coordinating their actions and cannot prevent free riders (if 90% of people get vaccinated, the 10% remaining gets the protection without having to endure the cost). This type of disease is very easy to fight for a state: force people to get vaccinated.

However, there is a tradeoff to this. The type of institutions that can use violence so cheaply and so efficiently is also the type of institutions that has a hard time creating economic growth and development. Countries with “unfree” institutions are generally poor and grow slowly. Thus, these countries can fight some diseases efficiently (like smallpox and yellow fever), but not other diseases that are related to individual well-being (i.e. poverty diseases). This implies that you get unfree institutions and low rates of epidemics but high levels of poverty and high rates of mortality from tuberculosis, diarrhea, typhoid fever, heart diseases, nephritis.

This argument is basically the argument of Werner Troesken in his great book, The Pox of LibertyHow does it apply to Cuba?

First of all, by 1959, Cuba was already in the top of development indexes for the Americas – a very rich and healthy place by Latin American standards. A large part of the high levels of health indicators were actually the result of coercion. Cuba actually got its very low levels of mortality as a result of the Spanish-American war when the island was occupied by American invaders. They fought yellow fever and other diseases with impressive levels of violence. As Troesken mentions, the rate of mortality fell dramatically in Cuba as a result of this coercion.

Upon taking power in 1959, Castro did exactly the same thing as the Americans. From a public choice perspective, he needed something to shore up support.  His policies were not geared towards wealth creation, but they were geared towards the efficient use of violence. As Linda Whiteford and Laurence Branch point out, personal choices are heavily controlled in Cuba in order to achieve these outcomes. Heavy restrictions exist on what Cubans can eat, drink and do. When pregnancies are deemed risky, doctors have to coerce women to undergo abortion in spite of their wishes. Some women are incarcerated in the Casas de Maternidad in spite of their wishes. On top of this, forced sterilization in some cases are an actually documented policy tool.   These restrictions do reduce mortality, but they feel like a heavy price for the people. On the other hand, the Castrist regime did get something to brag about and it got international support.

However, when you look at the other side of the tradeoff, you see that death rates from “poverty diseases” don’t seem to have dropped (while they did elsewhere in Latin America).  In fact, there are signs that the aggregate infant mortality rates of many other Latin Americans countries collapsed toward the low-levels seen in Cuba when Castro took over in 1959  (here too). Moreover, the crude mortality rate is increasing while infant mortality is decreasing (which is a strong indictment about how much shorter adult lives are in Cuba).

So, yes, Cuba has been very good at reducing mortality from communicable diseases and choice-based outcomes (like how to give birth) that can be reduced by the extreme use of violence. The cost of that use of violence is a low level of development that allows preventable diseases and poverty diseases to remain rampant. Hardly something to celebrate!

Finally, it is also worth pointing two other facts. First of all, economic growth in Cuba has taken place since the 1990s (after decades of stagnation in absolute terms and decline in relative terms). This is the result of the very modest forms of liberalization that were adopted by the Cuban dictatorship as a result of the end of Soviet subsidies. Thus, what little improvements we can see can be largely attributed to those. Secondly, the level of living standards prior to 1990 was largely boosted by the Soviet subsidies but we can doubt how much of it actually went into the hands of the population given that Fidel Castro is worth 900$ million according to Forbes. Thus, yes, Cubans did remain dirt poor during Castro’s reign up to 1990. Thirdly, doctors are penalized for “not meeting quotas” and thus they do lie about the statistics. One thing that is done by the regime is to categorize “infant deaths” as “late fetal deaths” – its basically extending the definition in order to conceal a poorer performance.

Overall, there is nothing to celebrate about Castro’s dictatorship. What some do celebrate is something that was a deliberate political action on the part of Castro to gain support and it came at the cost of personal freedom and higher deaths from preventable diseases and poverty diseases.

H/T : The great (and French-speaking – which is a plus in my eyes because there is so much unexploited content in French) Pseudoerasmus gave me many ideas – see his great discussion here.

The News: Fair and Unbiased

Reminder: Favorite Democratic presidential candidate Clinton (H.) must be considered innocent until she is found guilty by a court of law. Be patient!

The Obama Air Force bombed a Doctors Without Borders clinic in Afghanistan, killing about twenty people including doctors and underage patients. White House spokesperson: “We are still the best!” (Learning how to write headlines liberal style.)

I looked at a picture of the Oregon mass killer. He looked African-American to me. I am not an expert on race but I am pretty sure he would not have been seated at a Sears lunch counter in Mississippi in 1956. I wonder if he too was a white supremacist.

The police found thirteen of his firearms, all perfectly gun controlled (legal, in other words).

It seems to me that the statistics that matters the most with respect to homicides is type of homicide for 100,000 people. For the period 2000-2014 the US stands high in the ranking of deaths per hundred thousand within the context of a mass killings. It ranks number four, behind Norway, Finland, and….Switzerland. N. S.! (From the Wall Street Journal of 10.3 4 2015 reporting on an academic study.) I think a fourteen year period is significant. It does not look like cherry picking to me but I am open minded.

This all makes me muse about how raw figures are presented to the public. We all know the US homicide rate is high. (I don’t have the numbers at hand but there is no disagreement about the general statement.) I wonder what the US ranking would be if we deducted from the US homicide total count all homicides committed by African-Americans in areas administered by Democrats for a long time, say, more than ten years. I am thinking Chicago and Baltimore, for example. Just imagining.