Thesis: Woke up, got out of bed, dragged a comb across my head... And wrote a thesis chapter in one sitting.
Regulatory burdens are primarily driven by property value. People are mobile, but their investment in property is a non-liquid asset, and they will pay a lot to keep it from being polluted. If it's federal land out west, or a jungle island like Borneo - not so much. Borneo has more species and more "environment" to spoil, but the property values there make it easier to mine than a richer vein of ore on Long Island.
As wealthy neighborhoods have resources to worry about smaller and smaller cognitive risks, compliance with risk (e.g. toxics in air or wipe tests, employee safety standards) become more expensive in wealthy jurisdictions. This provides incentives for markets to outsource, or purchase from, areas with lower property values and less regulatory oversight.
This phenomenon has been examined through a lens of "environmental justice" for two decades. Groups of people who tend to live in less affluent neighborhoods tend to be less critical of local employers who tolerate these risks. Whether the "disproportionate enforcement" of standards is based on race, income, or real estate value, it coincides with the opinions of neighbors.
In environmental risk, the "worst neighbors" are the industries with the highest toxics and workplace hazards. These are know to be metal mining. Virgin ore extraction is strongly correlated with releases of mercury and lead. The number one source of mercury in the USA is gold mining; number two is silver mining. The more valuable an end product, the higher the tolerance for pollution, but the farther the activity occurs from high property values.
During the past 50 years, this dynamic has led to the "most polluted places on earth" being located in the least accessible, lowest property values on earth. Property value is known to be correlated with demand for the property, and remote property has less demand.
Kabwe Zambia has been named the most polluted place on earth (Time Magazine).
La Oroya, Peru is definitely in the running. (NY Times)
Even within the confines of the USA, the most toxic industries are found in the most remote places, usually on federally owned land (a private landowner is less likely to tolerate pollution than the public landowner). Of the top ten most areas with the most toxic releases, the first eight are in remote areas.. and (according to Scorecard.goodguide.com TRI reports), the states with the most land covered by the General Mining Act of 1872 have the most toxic releases.
Calculated as a percent, the Pareto Principle (80/20 Rule) appears to apply. The top twenty sites on the list of 100 are 83.75% of the total toxics: The top 4 sites of the top 20 represent 73% of toxics.
Total Toxics Emitted (Top 10) 1,484,112,451
All Top 100 1,991,863,954
Top 10 of 100 74.51%
Top 4 of Top 20 73.11%
Top 20 of 100 83.75%
Yet spending on "Superfund Enforcement" is not correlated with the toxics... it's correlated to property value and population. One has to wonder how many sites on federal lands haven't even been sampled... if a pound of mercury drops in the forest, and no regulator is there to detect it, it still makes pollution.
This data is USA only, but the trend (in my thesis) is that the more environmentally damaging or toxic a process (e.g. gold or silver mining), the further the extraction will be placed from property values and populations. Property value correlates with population up to a certain point (Manhattan Apartment) and then declines (ghettos and slums) because the more income people have, the more personal space they can afford.
Fast income growth would be associated with increasing property values.
In this thesis, the "good enough market" will be a rapidly emerging city, with electricity and potential wifi (like 1990s Guangzhou and Lima Peru, Cairo and Jakarta in the 2000s). There is a labor force here, but the percentage of that labor force engaged in scrap wouldn't account for the fact that nothing "e-waste" is being shipped to rural areas even lower on the evolutionary scale; for that matter, the presence of e-waste in concentrations at Guiyu or Agbogbloshie (with proximity to Shenzhen or Accra, cities growing at a faster than average pace for their continents), and the absence of a proportionally similar concentration of E-waste in even poorer cities like Mogadishu or Port-au-Prince, would be best explained by the growth and value added and not by the economics of externalization of pollution.
Haiti is closer and poorer than Accra or Kuala Lumpur, but the prices offered for e-scrap are much higher in cities (see Alibaba or Recycle.net) which are growing.
This establishes a reverse normal curve. The demand for "used goods" and "cheap displays" like CRT monitors is very low in Manhattan, rises in middle income markets earning $3000 per year, and then drops precipitously again in very poor cities. Mining, in comparison, grows in direct proportion to poverty, the lower the income level and property values, the greater the potential investments in raw material extraction. You find coltan mining and gold mining investments in jungles. A single mine like the OK Tedi Copper Mine, in a single day, dwarfs the toxics created by all the aqua regia and wire burning in all the cities of the world for a year. If you want to find cataclysmic environmental damage, look in the opposite direction of recycling and repair.
According to my thesis, it is therefore the perception of "waste" formed by rich cities in areas with high environmental enforcement (driven by property value) which has been projected onto middle income cities which are actually buying used goods for "good enough" purposes. It is true that the middle income cities have lower wage and environmental standards than the rich cities, but the correlation is exaggerated if you can't replicate the business in an even poorer city. This is an example of "cognitive risk" which is marketed to by corporate interests in planned obsolescence, anti-gray markets, and competition from contract manufacturers scaling into good enough market economies.
It is the relative inexperience in rich nations with extreme forms of poverty which cause us to conflate "good enough markets" with images of suffering. We create artificial groupings like "non-OECD" which basically mean "not as rich as us". It's like creating a term "not forest" to describe everything that is not a forest, grouping deserts, meadows, swamps, and tundra together into a single term.
There are many types of snow.
End of Part 1.
Regulatory burdens are primarily driven by property value. People are mobile, but their investment in property is a non-liquid asset, and they will pay a lot to keep it from being polluted. If it's federal land out west, or a jungle island like Borneo - not so much. Borneo has more species and more "environment" to spoil, but the property values there make it easier to mine than a richer vein of ore on Long Island.
As wealthy neighborhoods have resources to worry about smaller and smaller cognitive risks, compliance with risk (e.g. toxics in air or wipe tests, employee safety standards) become more expensive in wealthy jurisdictions. This provides incentives for markets to outsource, or purchase from, areas with lower property values and less regulatory oversight.
This phenomenon has been examined through a lens of "environmental justice" for two decades. Groups of people who tend to live in less affluent neighborhoods tend to be less critical of local employers who tolerate these risks. Whether the "disproportionate enforcement" of standards is based on race, income, or real estate value, it coincides with the opinions of neighbors.
In environmental risk, the "worst neighbors" are the industries with the highest toxics and workplace hazards. These are know to be metal mining. Virgin ore extraction is strongly correlated with releases of mercury and lead. The number one source of mercury in the USA is gold mining; number two is silver mining. The more valuable an end product, the higher the tolerance for pollution, but the farther the activity occurs from high property values.
During the past 50 years, this dynamic has led to the "most polluted places on earth" being located in the least accessible, lowest property values on earth. Property value is known to be correlated with demand for the property, and remote property has less demand.
Kabwe Zambia has been named the most polluted place on earth (Time Magazine).
La Oroya, Peru is definitely in the running. (NY Times)
Even within the confines of the USA, the most toxic industries are found in the most remote places, usually on federally owned land (a private landowner is less likely to tolerate pollution than the public landowner). Of the top ten most areas with the most toxic releases, the first eight are in remote areas.. and (according to Scorecard.goodguide.com TRI reports), the states with the most land covered by the General Mining Act of 1872 have the most toxic releases.
Calculated as a percent, the Pareto Principle (80/20 Rule) appears to apply. The top twenty sites on the list of 100 are 83.75% of the total toxics: The top 4 sites of the top 20 represent 73% of toxics.
Total Toxics Emitted (Top 10) 1,484,112,451
All Top 100 1,991,863,954
Top 10 of 100 74.51%
Top 4 of Top 20 73.11%
Top 20 of 100 83.75%
Yet spending on "Superfund Enforcement" is not correlated with the toxics... it's correlated to property value and population. One has to wonder how many sites on federal lands haven't even been sampled... if a pound of mercury drops in the forest, and no regulator is there to detect it, it still makes pollution.
This data is USA only, but the trend (in my thesis) is that the more environmentally damaging or toxic a process (e.g. gold or silver mining), the further the extraction will be placed from property values and populations. Property value correlates with population up to a certain point (Manhattan Apartment) and then declines (ghettos and slums) because the more income people have, the more personal space they can afford.
Fast income growth would be associated with increasing property values.
In this thesis, the "good enough market" will be a rapidly emerging city, with electricity and potential wifi (like 1990s Guangzhou and Lima Peru, Cairo and Jakarta in the 2000s). There is a labor force here, but the percentage of that labor force engaged in scrap wouldn't account for the fact that nothing "e-waste" is being shipped to rural areas even lower on the evolutionary scale; for that matter, the presence of e-waste in concentrations at Guiyu or Agbogbloshie (with proximity to Shenzhen or Accra, cities growing at a faster than average pace for their continents), and the absence of a proportionally similar concentration of E-waste in even poorer cities like Mogadishu or Port-au-Prince, would be best explained by the growth and value added and not by the economics of externalization of pollution.
Haiti is closer and poorer than Accra or Kuala Lumpur, but the prices offered for e-scrap are much higher in cities (see Alibaba or Recycle.net) which are growing.
This establishes a reverse normal curve. The demand for "used goods" and "cheap displays" like CRT monitors is very low in Manhattan, rises in middle income markets earning $3000 per year, and then drops precipitously again in very poor cities. Mining, in comparison, grows in direct proportion to poverty, the lower the income level and property values, the greater the potential investments in raw material extraction. You find coltan mining and gold mining investments in jungles. A single mine like the OK Tedi Copper Mine, in a single day, dwarfs the toxics created by all the aqua regia and wire burning in all the cities of the world for a year. If you want to find cataclysmic environmental damage, look in the opposite direction of recycling and repair.
According to my thesis, it is therefore the perception of "waste" formed by rich cities in areas with high environmental enforcement (driven by property value) which has been projected onto middle income cities which are actually buying used goods for "good enough" purposes. It is true that the middle income cities have lower wage and environmental standards than the rich cities, but the correlation is exaggerated if you can't replicate the business in an even poorer city. This is an example of "cognitive risk" which is marketed to by corporate interests in planned obsolescence, anti-gray markets, and competition from contract manufacturers scaling into good enough market economies.
It is the relative inexperience in rich nations with extreme forms of poverty which cause us to conflate "good enough markets" with images of suffering. We create artificial groupings like "non-OECD" which basically mean "not as rich as us". It's like creating a term "not forest" to describe everything that is not a forest, grouping deserts, meadows, swamps, and tundra together into a single term.
There are many types of snow.
End of Part 1.
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