What I Read: “SCIENCE!”-Articles mk. IV

1. Farm-Animal Welfare, Legislation, And Trade by G. Matheny & C. Leahy (2007)

Short Summary: The paper offers a detailed look at the farm animal welfare standards in the United States and then contrasts these to the standards in Europe (see overview on pg. 341) – 98% of the animals raised and killed are actually farm animals. Therefore if one wants to improve living standards for animals one should help these animals first.

Animal welfare has only recently become an issue, when breeding, medicine and specialised food made it possible to sever the link between animal welfare and productivity. Now, productivity is only loosely based on welfare, e. g. because it’s cheaper to let an animal die then to provide a proper animal-friendly environment. This is reflected in the fact that there are “only 220 veterinarians responsible for the care of more than nine billion farm animals” (329).

Poultry breeding is especially cruel for the animals. As hens, turkeys and other birds account for a vast majority of the animals living and killed in the United States (fish and poultry account for 99% of the farm animals), so an increase in poultry regulation would greatly benefit the overall animal welfare level. This is not impossible as Europe’s regulation has shown.

But one should be clear that farm animal welfare can not improve without an increase in price. So far only Europe’s population seems willing to pay more for their meat. The cheapest improvement only amounts to about two dollars per year and person, however. Their highest scenario totals to about twenty-seven dollars (see Table 3, 347). A reasonable amount considering the welfare improvement possible with them. Luckily, the willingness to pay more for welfare assurances has increased (see Singer’s article below).

Comment: The simplest and most consistent solution to animal welfare problems is obviously vegetarianism. Punkt. There’s no better solution to animal welfare and everybody is aware of this. Even if being a vegetarian doesn’t mean that you are not responsible for the death of million animals (see the last two articles in German).

The second best solution would be to at least abstain from eating poultry (and fish). This means to get into conflict with climate change, as climate change activists advice to skip red meat (usually) entirely. In case you are willing to reduce your consumption then it obviously doesn’t matter. A diet depending on one’s preferences (pleasure of meat variety and how important each goal is head-to-head) is also an option.

Globally, the situation is more complicated as China will easily make up for any reduced consumption in Europe and North America. Personally, I feel that changing your eating habits for animal welfare has a higher chance of success than to fight global warming. Climate change is a much more complex situation and is much more value-laden than animal welfare, too.

Nonetheless, the future is not as bleak as it sounds. A combination of technological and societal change may just be able to produce a better outcome for animal welfare. Technological, because analogues, artificial or “petri dish” meat will become easier to produce, better in taste and more importantly, cheaper. Societal, because eating habits will change, albeit slowly, and organic meat might capture a bigger market share than now. This should also reduce some global warming effects, but it’s probably negligible.

Further Reading: New Republic, Tyler Cowen’s comment and a new Peter Singer article, 3-D printed meat AMA on reddit, Verursachen Vegetarier mehr Blutvergießen als Fleischesser, Vegetarier sind auch Mörder.

2. The Psychology of Intelligence Analysis: Drivers of Prediction Accuracy in World Politics by P. Tetlock et al. (2014)

Short Summary: Tetlock and his team try to answer what arrangement (individual and group) reach the best results in predicting the outcome of certain (more or less specific) geopolitical and economic events. They formulate five hypothesis based on various behavioral theories: (i) greater skill in inductive and numerical reasoning, as well as cognitive control, (ii) more open-mindendess, (iii) possess more political knowledge, (iv) hypothesis (i) to (iii) will remain significant even if controlled for teamwork, training and other situational variables, and (v) higher engagement/motivation all lead to better forecasting.

Their tests confirm the hypothesis. Their results also show that a more complex model (including all variables) produces a better outcome (a R of 0.64 vs one of 0.31) than the simpler ones. Although their “behavioral variables” have the biggest impact on the accuracy of the forecasting.

In their conclusion they talk about how to improve public forecasting and accuracy by eliminating some of the vagueness that is often presented. On one hand more accountability is necessary but on the other hand more accountability usually leads to even more hedging. They propose to hold many (long-term) prediction tournaments to foster the skill of forecasting, as well as to create a reliable track record for experts.

Further Comment: I find their solution to hold public forecasting tournaments rather interesting, but wouldn’t “betting markets” be better than tournaments? Easier to organize, easier to participate, easier to control.

Further Reading: Silberzahn & Jones about the paper.

3. Institutions Do Not Rule: Reassessing the Driving Forces of Economic Development by J. Luo & Yi Wen

Short Summary: Luo and Wen try to find out how institutions, geography and economic development interact. What is the temporal sequence? Which factor is stronger?

Their addition to the vast literature is that the authors differentiate between agrarian and industrialised societies. They propose different factors have different influences on the country depending on its development stage.

Not surprisingly, their results align with their hypothesis. For agrarian societies geography is very important because “labor productivity in autarkic agrarian economies depends in a fundamental way on geographic conditions, such as the quality of land, climate, water resources, and diseases” (15). Once a country is industrialised its geography does not matter any longer and institutions take over as (human) capital-intensive influence grows.

Their preliminary findings also associate geography with a higher chance for industrialisation; mainly via the malaria risk variable. This still holds true when controlled for “institutions, international trade, colony identities, natural resources, religion and human capital” (22) and therefore provides a strong support for their hypothesis.

Comment: I’m currently reading Why Nations Fail and find Robinson’s and Acemoglu’s approach too simplistic and rather one-dimensional, so far at least. So this article is a breath of fresh air. It’s hardly surprising that the answer to the question would lie somewhere between the competing theories. It makes Luo and Wen’s approach rather appealing.

At the same time long historical data series are far from perfect and their statistical analysis are hard to judge without looking at the data yourself (see “This Time Is Different”). One should refrain from formulating strong conclusions. Luckily, the authors discuss their method and data extensively, and provide some interesting ideas and ways to enhance their analysis. Furthermore, their paper provides good starting points for future research and a finer, more nuanced debate about the forces behind income gaps and economic development in our world.

Personally, I find their reasoning behind geography causing industrialisation a bit unconvincing. The mechanism does not seem very clear. Geography seems to be a simple proxy for distance from “patient zero” (England -> Europe -> World). Obviously, one would still have to explain how and why “patient zero” happened in the first place. I’ll keep a close eye on their publications and hope that they’ll answer some of the questions raised.

Further Reading: Bob Lawson’s comment on the paper and of course there’s an article by Jeffrey Sachs and many many more if you search for “geography vs institutions” or anything, really.


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