I think there may be a bit of a disconnect between what I meant and how it was received, perhaps magnified by the fact that I was only giving my skim-derived impressions. First, I fully agree with jackmalde’s point that GDP isn’t a perfect measure, but partially reflecting a comment from your second paragraph, I presume that a lot of economists recognize that measures like GDP are not perfect (in fact, at least 2 if not all 3 of the econ professors I’ve had have explicitly said something along those lines). Second, based on the first paragraph of the Cambridge article (“Nature is a “blind spot” in economics”) it seemed like the implication was that 1) economists have massively ignored this, and 2) adding consideration of “nature” would be model-shattering. When the claim is simply “nature is a factor” (among multiple others), I think that’s probably reasonable. Third, I should clarify what I mean about my skepticism: I am not the slightest bit skeptical that economic models could be improved in general. However, by default I am skepticaltowards any specific claim of widespread blindness among economists, because I think that most of these claims will be wrong—i.e., I have a low outside view/base rate for each specific claim, especially with regards to the questions I mentioned in my original answer/comment. Building on that, I don’t want to over-articulate my thought process since it was largely just my initial, informal thoughts, but: There may be good evidence to back up Partha’s claim, it just seems like something that falls within a category of “Things that, if true, would be much more widely recognized [by economists] / would not have to be presented as some major ‘blind spot.‘” I don’t claim that this heuristic is good for someone whose work/research relates to this (i.e., those kinds of people should do more research than initial impressions), but as someone who is not in economics I think it’s more effective to have that kind of skepticism as opposed to treating every economic idea of the day/hour as equally legitimate. Lastly, I’ll admit that I may have been judging it a bit too hastily as a result of its similarity to some of the discourse I’ve seen from nature-as-an-inherent-value environmentalists. If he is trying to put forward a way to measure the (extrinsic) impact of ecosystems on human wellbeing in a way not measured by other standards of wellbeing (e.g., pollution’s effects on health indicators, timber’s and fish stocks’ ability to provide consumption value, insect pollination’s effects on agricultural productivity), that might be interesting, it’s just that a lot of the initial examples presented felt like they could have been examples of double counting (see previous parenthetical). This is an important point that helps tie together some of the previous issues.
I view economists are more like physicists working with spherical cows, and often happy to continue to do so. So that means we should expect lots of specific blind spots, and for them to be easy to identify, and for them to be readily acknowledged by many economists. Under this model, economists are also not particularly concerned with the practical implications of the simplifications they make. Hence they would readily acknowledge many specific limitations of their models. Another way of putting it: this is more of a blind spot for economics, not economists.
I’ll also get back to this point about measurement… there’s a huge space between “nature has intrinsic value” and “we can measure the extrinsic value of nature”. I think the most reasonable position is: - Nature has some intrinsic value, because there are conscious beings in it (with a bonus because we don’t understand consciousness well enough to be confident that we aren’t under-counting). - Nature has hard to quantify, long-term extrinsic value (in expectation), and we shouldn’t imagine that we’ll be able to quantify it appropriately any time soon. - We should still try to quantify it sometimes, in order to use quantitative decision-making / decision-support tools. But we should maintain awareness of the limitations of these efforts.
I think there may be a bit of a disconnect between what I meant and how it was received, perhaps magnified by the fact that I was only giving my skim-derived impressions. First, I fully agree with jackmalde’s point that GDP isn’t a perfect measure, but partially reflecting a comment from your second paragraph, I presume that a lot of economists recognize that measures like GDP are not perfect (in fact, at least 2 if not all 3 of the econ professors I’ve had have explicitly said something along those lines).
Second, based on the first paragraph of the Cambridge article (“Nature is a “blind spot” in economics”) it seemed like the implication was that 1) economists have massively ignored this, and 2) adding consideration of “nature” would be model-shattering. When the claim is simply “nature is a factor” (among multiple others), I think that’s probably reasonable.
Third, I should clarify what I mean about my skepticism: I am not the slightest bit skeptical that economic models could be improved in general. However, by default I am skeptical towards any specific claim of widespread blindness among economists, because I think that most of these claims will be wrong—i.e., I have a low outside view/base rate for each specific claim, especially with regards to the questions I mentioned in my original answer/comment.
Building on that, I don’t want to over-articulate my thought process since it was largely just my initial, informal thoughts, but: There may be good evidence to back up Partha’s claim, it just seems like something that falls within a category of “Things that, if true, would be much more widely recognized [by economists] / would not have to be presented as some major ‘blind spot.‘” I don’t claim that this heuristic is good for someone whose work/research relates to this (i.e., those kinds of people should do more research than initial impressions), but as someone who is not in economics I think it’s more effective to have that kind of skepticism as opposed to treating every economic idea of the day/hour as equally legitimate.
Lastly, I’ll admit that I may have been judging it a bit too hastily as a result of its similarity to some of the discourse I’ve seen from nature-as-an-inherent-value environmentalists. If he is trying to put forward a way to measure the (extrinsic) impact of ecosystems on human wellbeing in a way not measured by other standards of wellbeing (e.g., pollution’s effects on health indicators, timber’s and fish stocks’ ability to provide consumption value, insect pollination’s effects on agricultural productivity), that might be interesting, it’s just that a lot of the initial examples presented felt like they could have been examples of double counting (see previous parenthetical). This is an important point that helps tie together some of the previous issues.
I view economists are more like physicists working with spherical cows, and often happy to continue to do so. So that means we should expect lots of specific blind spots, and for them to be easy to identify, and for them to be readily acknowledged by many economists. Under this model, economists are also not particularly concerned with the practical implications of the simplifications they make. Hence they would readily acknowledge many specific limitations of their models. Another way of putting it: this is more of a blind spot for economics, not economists.
I’ll also get back to this point about measurement… there’s a huge space between “nature has intrinsic value” and “we can measure the extrinsic value of nature”. I think the most reasonable position is:
- Nature has some intrinsic value, because there are conscious beings in it (with a bonus because we don’t understand consciousness well enough to be confident that we aren’t under-counting).
- Nature has hard to quantify, long-term extrinsic value (in expectation), and we shouldn’t imagine that we’ll be able to quantify it appropriately any time soon.
- We should still try to quantify it sometimes, in order to use quantitative decision-making / decision-support tools. But we should maintain awareness of the limitations of these efforts.