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.

spanishgdp

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.

spanishproductivity

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.

medianage

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.

From the Comments: Asylum Seekers and the Canadian Experience

Dr Amburgey takes some precious time out of his schedule to rebut Dr J:

@Brandon

I can understand your reluctance to yet again engage with Professor Pinocchio’s fact-resistant Islamophobia. However you must give him credit for actually using some real data. Granted the choice of country and time period are idiosyncratic [id est cherrypicked] but anything not pulled straight from his anus is a dramatic change. Should you feel like responding in kind, use this: Canada for the period 2004 – 2013. Top 8 countries of origin for refugees landing in Canada

Columbia – 17381
China – 15344
Sri Lanka – 12326
Pakistan – 10641
Haiti – 7872
Mexico – 6512
India – 4988
USA – 4451

Based on this data Catholicism and Hinduism far outstrip Islam as religions producing sick societies.There is currently no other view that is even modestly supported by anything but ideological intransigence.

Indeed. Only the most ideological of ideologues continue to pretend that Islam is responsible for the problem in the Middle East.

When the Austro-Hungarian empire collapsed, the Holocaust happened. One could argue that, because the state is less efficient on the post-Ottoman world, what we’re witnessing is a process similar to the one we witnessed in the Occident, only in a much more haphazard way.

How does emigration impact institutions?

Hello everyone. As usual I’ve come to ask for feedback on my latest research. I can’t emphasize enough how much it helps to blog it out, if only because it forces me to sit down and try to summarize things in a few hundred words.

My current research is looking at the effect emigration has, if any, on institutions. Institutions come in various forms. The state is an institution, but family, religion, and even organized crime are too. Broadly speaking institutions are those rules that govern society, both formal and informal. Institutions have increasingly been acknowledged as being one of the key (if not the key) determinants of a nation’s wealth.

Despite the importance of institutions, we know relatively little about them. By no means is this due to a lack of trying, and in there have been some earnest attempts to tackle the issue. Acemoglu’s Why Nations Fail is one such attempt.* For the time being the goal in institutional studies is to properly explain how and why institutions form.

My goal is to neither explain the origin of institutions or to measure their impact on economic well being. I take it for granted that good (and bad) institutions populate the world. Instead I am interested in how different institutions interact with one another.

My former boss at Cato has looked at how immigration has influenced a destination country’s (the USA) institutions. He finds little effect. In my project I try to look at the problem from the opposite end – how does emigration influence an origin country’s institutions. To measure the impact of emigration I use remittance data.

Remittances come in two form. There are monetary remittances, which are cash transfers from emigrants to their family members and friends back home. There is a broad economic literature on the former and its affect on development outcomes. There is however little (if any- I haven’t found any at least) economic work on social remittances. Social remittances is the transfer of ideas from emigrants to their family members and friends. In general the economic remittance literature has not yet attempted to connect itself with the institution literature despite both being part of the larger development literature.

Most work on social remittances has been done by sociologists. Thus far though most of the work has been qualitative and/or focused on how social remittances tie migrant communities with their origin countries. There has been little work on how this communication translates to changes in institutions.

Political scientists are currently taking the lead on the question. Earlier this year Abel et al. published a paper looking at how remittances affect democratic transition. They find that increased monetary remittances decreases voter turn out and thus weakens the political base of populist-based autocracies. Another recent paper by Miller et al. find that emigration increase the possibility of civil war by giving opposition parties an external funding source.

I think Abel and Miller’s work the best thus far in seeing how emigration affects institutions. My biggest concern with Abel’s paper is that he looks at democratic transition events, but there is no reason why democracy must lead to better institutions. Hong Kong and Singapore alternate as the most economically free states in the world, but neither is a bastion of democracy. India is the world’s largest democracy and by most metrics has awful institutions.

Miller’s work on the other hand looks at how the probability of civil war increases, but civil war in itself is not always bad. On occasion war is necessary for the improvement of institutions**.

To remedy my concerns I look at how remittances marginally influence institutions. I use the Fraser Institute’s Economic Freedom in the World summary index as my measure of a country’s institutions. My regression tables are found below. All observations are for north American (including central America but excluding the Caribbean) countries from 1994-2012.

Column 1 is a simply regression between a country’s EFW score and remittances as a percent of GDP. Initially we find a negative correlation between the two – a 1 percentage point increase in remittances is associated with a 0.01 point decrease in its EFW score. Is this a sign that brain drain, the emigration of high skilled migrants, is reducing the institutional qualify of origin countries? Not quite – it’s simply caused by the lack of control variables. At this point remittances is a proxy for a country being undeveloped.

Columns 2-4 are me playing around with various control variables. The interaction of phone subscriptions with remittances is my attempt to proxy for social remittances. Presumably emigrants are more likely to call back home, and exchange ideas, if their family members and friends have a phone to be contacted at. The 1 year lagged EFW index symbolizes the ‘stickiness’ of institutions: in the short run institutions do not drastically change.

Column 5 is simply column 4 re-run using clustered errors and country fixed effects. Country fixed effects, for those of you who have been spared endless hours of statistical classes, is a technique that allows us to account for unobserved characteristics of a country that do not change across the observed time span. This is usually done to account for such things as culture or geography.

In this final iteration we find that a one percentage point increase in remittances increases a country’s EFW index score by 0.05 points. This is a marginal effect, but its not irrelevant. See the Cato Institute’s interactive map of economic freedom. The difference between the United States and Russia is about one point despite the former presumably being a bastion of freedom.

Thoughts?

*Why Nations Fail has been discussed on NOL several times before, see here and here.
** But let me emphasize that this is rarely the case and war should be the last option. We really do need to make our own NOL foreign policy quiz.

(1) (2) (3) (4) (5)
VARIABLES EFW Index EFW Index EFW Index EFW Index EFW Index
Remittances as a percent of GDP – Fraser EFW -0.01* 0.04*** 0.00 0.01** 0.05***
(0.01) (0.01) (0.00) (0.01) (0.01)
Fixed telephone subscriptions (per 100 people) 0.03*** 0.01* 0.01
(0.00) (0.00) (0.01)
Remittances * Phone -0.00 -0.00 -0.00**
(0.00) (0.00) (0.00)
EFW Index 1-year lag 0.81*** 0.78*** 0.54***
(0.04) (0.05) (0.05)
Income Per Capita in 000s, Constant 2005 dollars. 0.00* -0.00 -0.01
(0.00) (0.00) (0.05)
Constant 7.39*** 6.60*** 1.33*** 1.50*** 3.04***
(0.06) (0.06) (0.28) (0.32) (0.45)
Country Fixed Effects No No No No Yes
Observations 134 134 110 110 110
R-squared 0.03 0.66 0.91 0.91 0.93

Standard errors in parentheses in columns 1-4. Robust errors in column 5.

*** p<0.01, ** p<0.05, * p<0.1