The “debate” about climate change is so poisoned it has brought down at least two Australian prime ministers, and the very term is redacted from US government websites.
So maybe it’s time to retire, or at least rein in, this line of argument. The externalities produced by burning coal and oil, from factory farming etc., have many facets that can be tackled. Notably, health.
Take this recent study on air pollution from researchers at Arizona State:
“We find that a 1 microgram-per-cubic-meter increase in average decadal exposure (9.1% of the mean) increases the probability of receiving a dementia diagnosis by 1.3 percentage points (6.7% of the mean). This finding is consistent with hypotheses from the medical literature.”
“Burgeoning medical literature provides reason to suspect that long-term exposure to elevated pollution levels may permanently impair older adults’ cognition, especially in the case of particulates smaller than 2.5 microns in diameter, commonly known as “fine particulate matter” or “PM2.5”. The small size of PM2.5 allows it to remain airborne for long periods, to penetrate buildings, to be inhaled easily, and to reach and accumulate within brain tissue. The accumulation of particulates in the brain can cause neuroinflammation, which is asso-ciated with symptoms of dementia…”
So, emissions are not just harmful to the environment, but human health as well. The suffering isn’t only in the long term, evident only in a computer model, but in the health of real people living right now.
It’s also worthwhile thinking about who bears the brunt of this. The workers in industries like mining, obviously. But as a recent hurricane in North Carolina showed, polluting industries are also often situated in poorer areas:
“Even after adjusting for socioeconomic factors — and even without a hurricane — life expectancy in southeastern North Carolina communities near industrial meat growers is lower than in places without these hog operations. A recent study published in North Carolina Medical Journal found that residents near the industrial animal operations had higher rates of all-cause mortality, infant mortality, mortality from anemia, kidney disease, tuberculosis, and septicemia, and higher rates of emergency room visits than the residents in the control group.”
As Ketan Joshi has noted, denying climate science is now akin to being an anti-vaxxer both in the scientific illiteracy required as well as the harm being wrought. But we can’t expect to win this fight, especially in the short time we have to take action. Instead, we should change the subject. There are plenty of other arguments to make.
With Australia currently engaged in an abysmal debate over same sex marriage, it‘s refreshing to be reminded that morality often has a utilitarian history.
For example, this recent paper suggests that norms around illegitimate children are based in economics.
Based on data from the Austro-Hungarian Empire and modern Austria,
we show that regions that focused on animal husbandry (as compared to crop farming) had significantly higher illegitimacy ratios in the past, and female descendants of these societies are still more likely to approve illegitimacy and give birth outside of marriage today.
The key point is actually buried a fair bit down in the paper. The reason there is this split in social norms between crop and animal farming communities is apparently due to differing labor structures.
18th and 19th century workers on crop farms were on short term contracts, often working as day labourers.
In crop farming, the work load and the resulting demand for additional
labor, is determined by the rhythm of the seasons… additional manpower is needed in the harvest season.
Workers on animal farms, meanwhile, had long term contracts. This was less precarious, but they also tended to live on the farms and so had little opportunity to create their own households. Their illegitimate children were tolerated by the communities.
In contrast, in animal husbandry the workload is distributed relatively evenly throughout the year… Animal husbandry requires a sound knowledge of the peculiarities of each animal (analogous to firm-specific human capital), while harvesting is less specific.
An interesting paper by Etienne Leppers at the LSE suggests that where central bankers (specifically, those on the Federal Open Market Committee of the the US Federal Reserve) were educated has a "systematic impact" on the way they vote on monetary policy.
This is true even considering the more than four decades that have elapsed since Chairwoman Janet Yellen got her PhD.
"graduate training in economics is the first place for the formation of biased preferences, because of the substantial ideological sorting that exists across universities."
"The literature on the determinants of central bankers’ voting behaviour has already revealed that governors do not simply respond to economic variables and models’ outputs. They are influenced by deliberation, by the chairman, by politics through appointment choices and by pressures in and out of election times; and by their pre-central-bank career and post-central-bank career plans. In this paper, the analysis is extended to include yet one more variable: ideologically influenced academic training."
Economics may be a special case here, as there is significant debate in some areas, with identifable ideological "camps". And, in America at least, certain universities can be clearly identified with schools of thought.
"Robert Hall already drew in 1976 a clear ideological and methodological line between two schools: the freshwater school (Midwest of the US: e.g. Chicago or Minnesota), for which the government is not capable of reviving the economy because fluctuations come from supply shifts as opposed to the saltwater school (in coastal US universities: e.g. Berkeley, Harvard or Princeton) which focuses on stimulating demand through government policies."
But I am still astounded at the sheer length of time over which this effect can be observed. It goes to show how much an impact not only early ideas and influences can have, but social connections too. Your mentors, your friends, your favourite books and first job… Your choice of university is huge.
"…earlier professional life is not the most important period for the formation of inflation preferences. Instead, we try to demonstrate the role of academic training and the socialisation that happens not in the different types of careers, but in the different types of universities."
Can you think of any biases that still hang around from your university days?
Dirk Baur over at the University of Western Australia has constructed a fantastically simple model, using the board game Monopoly to look at the interplay of housing and inequality.
For all its simplicity, the results bear a striking resemblance to empirical data.
"We assume a city with four suburbs each populated with five streets. There is one house in each street. The price of the houses (including the land) varies across streets and increases from 1 to 20 monotonically with the cheapest house being in the first street in the first suburb and the most expensive house being in the last street in the fourth suburb. The rental yield is assumed to be 5% and thus varies between 0.05 currency units for the cheapest house and 1 currency unit for the most expensive house."
"There are N players of the game. Each of them sequentially roll a die and buy the house (including the land it is built on) if the initial or remaining budget suffices. If the house has already been purchased by another player rent must be paid to the owner of the house.The default budget for each player is set equal to the amount that would be needed to buy x houses so that all houses can be sold on average."
Baur runs this simulation multiple ways, fiddling with starting capital, wages (the equivalent of passing Go), and rules around what causes the game to end. One thing is constant – the correlation between inequality and housing.
"Interestingly, the correlation between house ownership and budgets across players remains close to one even for positive regular income parameters. This means that the regular income can decrease the inequality in ownership and capital wealth but not change the ranking of the players based on the house ownership."
"…the simulations show that (i) inequality is a frequent phenomenon in the game, (ii) house prices increase both with higher starting capital and higher wages, (iii) wealth inequality falls if wages are sufficiently high relative to house price growth and (iv) inequality is extreme when players do not own any property. We compare the results with house prices and disposable income of eight industrial countries and find striking similarities with the model outcomes despite the model’s simplicity."
But my biggest takeaway is something this model makes implicit but is quite hidden in the real world – the real inequality is between those who are playing and those that haven’t started yet.
"Whatever the dynamics of the inequality among the players of the game are, the inequality measured with those that are not (yet) part of the game, i.e. future players or future generations, almost always increases and can easily reach extreme values."