On demography and living standards in the colonial era

This is a topic that has been bugging me. Very often, historians will (accurately) point out mortality statistics in the United States, Canada (Quebec) and the Latin America during the colonial era were better than in the comparable Old World (comparing French with French, British with British, Spanish with Spanish). However, they will argue that this is evidence that living standards were higher. This is where I wish to make an important nuance.

Settlement colonies (so, here there is a bigger focus on North America, but it applies to smaller extent to Latin America which I am more tempt to label as extractive – see here) are generally frontier economies. This means that they are small economies because of small populations.  This means that labor and capital are scarce relative to land. All outputs that come from the relatively abundant factor will thus tend to be cheaper if there is little international trade for the goods that they are best at producing. The colonial period pretty much fits that bill. The American and Canadian colonies were basically agricultural colonies, but very few of those agricultural outputs actually crossed the Atlantic. As such, agricultural produces were cheap. This is akin to saying that nutrition was cheap.

This, by definition, will give settlement colonies an advantage in terms of biological living standards. As they are not international price takers, wheat is cheaper than in the old world. This is why James Lemon spoke of the New World as the “Best poor man’s country” (I love that expression) : it was easy to earn subsistence. However, beyond that it is very hard to go beyond. For example, in my dissertation (articles still in consideration at Cliometrica and Canadian Journal of Economics) I found that when wages were deflated by a subsistence basket containing very few services and manufactured goods and which relied heavily on untransformed foods, Canada was richer than the richest city of France. Once you shifted to a basket that marginally increased transformed goods and manufactured goods, the advantage was wiped away.

Yet, everything indicates that mortality rates were greater in Paris and France and than in Quebec City and Quebec as a whole (but not by a lot) (see images below).  Similar gaps seem to exist for the United States relative to Britain, but the data is not as rich as for Quebec. However, the data that exists for New England suggests that death rates were lower than in England but the “bare bones” real incomes measured by Lindert and Williamson show that New England may have been poorer than Great Britain (not by much though).

Crude Death Rates


I am not saying that demographic and biological data is worthless. Quite the contrary (even I wanted to, I could not since I have a paper on the heights of French-Canadians from 1780 to 1830)! The point is that data matters in context.  The world is full of small non-linearities between variables. While “good” demographic outcomes are generally tracking “good” economic outcomes, there are contexts where this may be a weaker relation (curvilinear relations between variables). I think that this is a good example of that point.


Trump’s Inauguration: Ageing Pains


Vincent has discussed the relative age of US presidents. There is something to be said about the age of electorates.

I was living in the United Kingdom when we voted for Brexit (I was a soft remainer). I was living in the United States when Trump won the election. So I can’t help but feel that Trump’s inauguration is part of a generalised nationalist turn that, ironically, transcends national borders. Why is this nationalist turn happening? And why has it wrong-footed pollsters and political scientists more than once now?

We are repeatedly, and correctly, warned not to over-interpret individual events as somehow determined by given factors. Both the Brexit vote and the presidential election were close, with Trump taking the electoral college without the popular vote. One domino that didn’t fall last year was the Austrian presidency that, after a close call, went to a Green rather than a Nationalist. So whatever explanation we are looking for has to be a tendency that’s slightly shifted the odds in favour of nationalist politicians without the experts being able to anticipate it in advance.

Some suggest that this resurgent economic nationalism is an inevitable outcome of the overreach of trade liberalisation that has undermined national self-determination and humiliated local cultures. Others argue that the real cause is growing income and wealth inequality. I think a potentially more straightforward factor is demography. The electorate is simply older than it used to be.

There are a few reasons why this explanation may work better than the more popular ones. The ageing electorate is almost unprecedented in history. This could make it harder for political scientists to predict its impact on elections. Surveys might be able to tell us how older people vote as individuals without being able to work out how older people surrounded, in addition, by lots of older peers will behave.

Countries like Italy and Japan were somewhat ahead of us on this demographic transition. And perhaps not entirely coincidentally, Italy repeatedly elected a mini-Trump, Silvio Berlusconi as Prime Minister, while continuing to support the elderly at the expense of opportunities for the young. Meanwhile, Japan has always been more ethno-nationalist than other developed economies and in some ways has grown more politically reactionary in recent decades.

This explanation chimes with the fact that Trump voters were not typically economically disadvantaged. They were older and less educated but typically economically secure. Age was also a big factor explaining support for Brexit. At the same time, an ageing population presents real economic challenges that translate into politically salient problems. Demography is probably responsible for a great deal of the sustained drop in real interest rates, precisely the sort of thing that worries ageing savers with slowly growing pension pots.

Trump wants to boost infrastructure, construction and manufacturing. But these sectors do best with young and growing populations, where families want new and bigger houses and offices, roads to connect them and cars to drive to and from them. What happens when everyone already has a great deal of material goods and a country hasn’t got as many young adults to demand new stuff? Inevitably, an economy’s trend growth declines and may even contract, leaving investors with fewer places to get a good return.

What could this mean about the future? On the one hand, this could be quite a pessimistic explanation. There is very little that can be done in the short or medium term about the demographics of an electorate. So we might just be in for a more reactionary period. The vote is not about strength of belief, just the sheer numbers nudged in that direction, and that is what age can do.

On the other, this could be an optimistic hypothesis. The situation we find ourselves in is a side-effect of two generally attractive outcomes: people living much longer, and lower fertility thanks to women becoming more educated. The balance between the young and the elderly might eventually improve once the demographic bulge of the baby boomers has passed into history (this depends critically on whether institutions permit new family formation). In addition, tomorrow’s elderly are not the same as today’s elderly. They will probably be more educated, less nationalist and possibly less subject to cognitive decline than the current generation. They are less likely to be impressed by a bad sales pitch.

How Well Has Cuba Managed To Improve Health Outcomes? (part 3)

As part of my series of blog post reconsidering health outcomes in Cuba, I argued that other countries were able to generate substantial improvements in life expectancy even if Cuba is at the top. Then I pointed out that non-health related measures made Cubans so poor as to create a paradoxical outcome of depressing mortality (Cubans don’t have cars, they don’t get in car accidents, life expectancy is higher which is not an indicator of health care performance). Today, I move to the hardest topic to obtain information on: refugees.

I have spent the last few weeks trying to understand how the Cuban refugees are counted in the life tables. After scouring the website of the World Health Organization and the archives of Statistics Canada during my winter break, I could not find the answer.  And it matters. A lot.

To be clear, a life table shows the probability that an individual of age will die by age X+1 (known as Qx). With a life table, you will obtain age-specific death rates(known as Mx), life expectancy at different points and life expectancy at birth (Lx)(Where x is age). Basically, this is the most important tool a demographer can possess. Without something like that, its hard to say anything meaningful in terms of demographic comparison (although not impossible).The most common method of building such a table is known as a “static” method where we either compare the population structure by age at a single point in time or where we evaluate the age of deaths (which we can compare with the number of persons of each group alive – Ax). The problem with such methods is that static life tables need to be frequently updated because we are assuming stable age structure.

When there is important migration, Qx becomes is not “mortality” but merely the chance of exiting the population either by death of migration. When there are important waves of migration (in or out), one must account for age of the entering/departing population to arrive at a proper estimates of “exits” from the population at each age point that separate exits by deaths or exits (entries) by migration.

As a result, migration – especially if large – creates two problems in life tables. It changes the age structure of the population and so, the table must be frequently updated in order to get Ax right. It also changes the structure of mortality (exits). (However, this is only a problem if the age structure of migrants is different from the age structure of the overall population).

Since 2005, the annual number of migrants from Cuba to the United States has fluctuated between 10,000 and 60,000. This means that, on an annual basis, 0.1% to 0.5% of Cuba’s population is leaving the country. This is not a negligible flow (in the past, the flow was much larger – sometimes reaching north of 1% of the population). Thus, the issue would matter to the estimation of life tables. The problem is we do not know how Cuba has accounted for migration on both mortality and the reference populations! More importantly, we do not know how those who die during migration are measured.

Eventually, Ax will be adjusted through census-based updates (so there will only be a drift between censuses). However, if the Cuban government counts all the migrants as alive as they arrive in a foreign country as if none died along the way, it is underestimating the number of deaths. Basically, when the deaths of refugees and emigrants are not adequately factored into survival schedules, mortality schedules are be biased downward (especially between censuses as a result of poor denominator) and life expectancy would be accordingly biased upward.

Now, I am willing to reconsider my opinion on this particular point if someone indicates some study that has escaped my gaze (my Spanish is very, to put it euphemistically, poor). However, when I am able to find such information for other Latin American countries like Chile or Costa Rica and not for Cuba, I am skeptical of the value of the health statistics that people cite.

The other parts of How Well Has Cuba Managed To Improve Health Outcomes?

  1. Life Expectancy Changes, 1960 to 2014
  2. Car ownership trends playing in favor of Cuba, but not a praiseworthy outcome

A short note on minorities and the Left

Lately I have been thinking about how minorities affect the Democratic Party here in the US. Basically, all minorities vote for the Democrats in national elections, but minorities tend to be conservative culturally. This has the effect of pulling the Leftist party waaaaay to the center (a fact that makes it hard for me to complain about Democrats’ pandering tactics).

Sure, the GOP will always be the party of old white people, but if the Democrats’ left-wing is essentially neutered due to minority voting blocs within the Party, who cares?

The fact that the Democrats pine for minorities explains why the US has never had a very powerful socialist movement. Socialists will often blame “neoliberals,” “capitalists,” “reactionaries,” and other assorted boogeymen, but doesn’t the minority insight make much more sense?

This minority insight has also got me thinking about demographic changes in Europe over the past 30 years. Basically, Europe has had a huge influx of immigrants since the fall of socialism. In the old days, Sweden was for Swedes, France was for the French, Germany was for Germans, etc. etc. This  mindset helps to explain why European states had such overbearing welfare states and why economic growth was so limited up until the late 1980s.

As immigrants moved into these welfare states, the Left-wing parties began to pander to them. This had the same effect as it did in the United States: culturally conservative voting blocs diluted the Leftism of traditionally Left-wing parties. As a result, these welfare states became less robust and economic growth became attainable again.

A big underlying point about my musings on this subject is that socialism relies on nationalism in the area of popular politics and policymaking. Without Sweden for the Swedes-type sloganeering, socialism becomes ridiculous to the masses. This underlying point, along with the straightforward fact that immigrants dilute socialist power (economic, political, and cultural), suggests to me that libertarians who pay close attention to popular politics should relax when it comes to the fact that minorities don’t find libertarian ideals all that appealing.