> turn towards qualitative methods and epistemologies that are either misaligned with or explicitly reject the scientific method.
At least you can see their questionable method upfront, and can disagree with it.
Economics is worse: it has become completely quantitative, with sophisticated mathematics. I’ve heard the approach referred to as ‘physics envy’
It appears unapproachable to a non-expert and authoritative. But it’s not like physics
It’s conclusions are often catastrophically wrong because all the mathematics relies on shaky qualitative assumptions: people are perfectly rational, etc.
For example we have published economic research that forecasts that severe climate change will only damage global GDP by 1%.
They conclude that farming productivity will be reduced by 25% and farming is 4% of global GDP, so it’s 1%. Then they model some effect on the consumer because food prices go up.
It does not occur to the authors to model impact of physical result of that, which is, famine and political instability that comes with it.
It is not just that they are wrong, they are intentionally wrong. Someone wants that 1% number and economists will happily deliver. If someone wanted to pay for a study saying it would affect gdp by 50% they would get it.
This is the great illustration of the hokey thinking that happens in economics. They don't focus on modeling humans as agentic systems. What happens if GDP is pushed to 1000%, 10,000%? When there is so much agricultural production that food is free? How does that affect geopolitics, human social values and demands? It's clear to me the models completely breakdown and are really only epsilon valid (e.g okay for modeling small, but not catastrophic pertrubations)
Maybe I’m wired differently, but what you’re describing sounds like estimation, so I’d expect that they’ve made some underlying assumptions, foresight being imperfect and all.
I’m unclear what you’re arguing for here, that we should not attempt to estimate because we have to make some assumptions about future events? Or is it that the estimators in this case should have used different assumptions? Or is it that they should also be estimating the potential for famines and political instability (which maybe they don’t feel qualified to do?)
That assertion is due to the incorrect assumption that we can’t feed everyone on the planet if farming becomes less productive than it is today, and ignores that we currently produce very large food surpluses.
> They conclude that farming productivity will be reduced by 25% and farming is 4% of global GDP, so it’s 1%. Then they model some effect on the consumer because food prices go up.
> It does not occur to the authors to model impact of physical result of that, which is, famine and political instability that comes with it.
> incorrect assumption that we can’t feed everyone on the planet
You are the one making incorrect assumptions, specifically that food production is a steady and constant process like producing iPhones.
In the real world, crops fail due to seasonal weather all the time and it affects global food prices.
Research predicts multiple famines due to simultaneous crop failures in global bread baskets. That’s why responsible countries like Norway started stockpiling food.
The point is not even that - economists are simply not qualified to assess accuracy of their base assumptions.
now I have to debate people who claim we should not address climate change because worst case is 1% damage to GDP.
What are the report margins on that? Suppose there is a 10% chance that the drop is higher, like 30%/35% and does cause a famine specifically concentrated in the US, or nuclear armed Pakistan, and Global GDP falls by 40%.
Have you seen them report finds the n a way that accounts for, however small; possibility of total disaster?
That article has no mention of famines. The article is about supply chains and price shocks and using stockpiles of grain as “buffers” to soften sudden price swings. It makes sense: Grain in one place can’t feed people in another unless it can move through the supply chain.
> Research predicts multiple famines due to simultaneous crop failures.
Economics, sociology, psychology, even ecology in relation to humans are all really one subject. Then to make matters worse we are using the tools of reductionist linear science to study the already artificial subsets of this subject as independent, stationary, ergodic chunks, leading to obviously ridiculous conclusions when these chunks are reassembled.
Then somehow complex systems and non-linear dynamics has really failed to gain any traction in the popular discourse. Labeling the subject "Chaos theory" in the 80s was really really dumb.
On the other hand, the popular mind has a delusional view of science. As if there is an efficient market hypothesis for scientific truth. That scientific truth is instantaneously transmitted and discounted.
This is all just one of the many examples from history happening in real time of a decades long Kuhnian paradigm shift while the popular mind continues to argue outdated nonsense like the best way to measure aether and phlogiston.
At least you can see their questionable method upfront, and can disagree with it.
Economics is worse: it has become completely quantitative, with sophisticated mathematics. I’ve heard the approach referred to as ‘physics envy’
It appears unapproachable to a non-expert and authoritative. But it’s not like physics
It’s conclusions are often catastrophically wrong because all the mathematics relies on shaky qualitative assumptions: people are perfectly rational, etc.
For example we have published economic research that forecasts that severe climate change will only damage global GDP by 1%.
They conclude that farming productivity will be reduced by 25% and farming is 4% of global GDP, so it’s 1%. Then they model some effect on the consumer because food prices go up.
It does not occur to the authors to model impact of physical result of that, which is, famine and political instability that comes with it.