The Productivity Consequences of Pollution-Induced Migration in China

Abstract

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Air Pollution Quotas and the Dynamics of Internal Skilled Migration in Chinese Cities

“…Meng (2016) defines high-skill labour as workers with at least a high school education. One the other hand, Khanna et al (2019) define high-skill as college education or above). The top two graphs suggest that the density of non-urban agricultural Hukous in urban districts is somewhere between the density plots for high school and diploma degrees.…”

“…In the past few decades, the Eastern provinces have experienced a net inflow of highskilled labour as the flourishing local economic conditions offer prosperous career opportunities and represent target destinations for many graduates. However, an emerging trend is that high-skilled workers have started to factor in air pollution in their utility functions which affect their outmigration decisions (Chen et al, 2017;Khanna et al, 2019). A recent survey focusing on Beijing, a city with many exceptionally talented and skilled workers, finds that since 2011, severe air pollution has decreased the willingness of young college graduates to work in this city (Hao et al, 2020).…”

“…20 Air pollution differences across cities can lead to a spatial sorting on skills. According to Figure 3 of Khanna et al (2019), many Central and few Western provinces (such as Sichuan) can be attractive for highskilled workers to reside in. On the other hand, low-skilled workers are less sensitive to air pollution and are more evenly geographically distributed across China.…”

Pollution in Ugandan Cities: Do Managers Avoid it or Adapt in Place?

“…Heblich et al (2021) document the persistent effects of industrial pollution on neighborhood sorting within English cities. By focusing on location choices within as opposed to across cities, we also relate to a growing literature on how environmental conditions such as pollution or natural resource availability determine the sorting of firms and households across space and migration decisions(Gollin et al 2021;Liu and Sekhri, 2021;Khanna et al 2021; Chen et al 2017).5 Source: World Bank: https://data.worldbank.org/indicator/EN.ATM.PM25.MC.M3?name_desc=true& view=map. PM stands for particulate matter and 2.5 refers to the size of the particles (2.5 micrometers).…”

“…Cross-country research estimates an income elasticity of vehicle ownership of 1.1(Dargay et al 2007, Ingram andLiu 1999).8 The Ministry of Works and Transport reports that petrol and diesel vehicles are 15.4 and 16.4 years old on average, respectively (Source: http://www.airqualityandmobility.org/PCFV/EAC_Workshop/ Ugandasinitiativecleanervehicles.pdf).Kirenga et al (2015) emphasize the role of unpaved roads in driving up PM2.5 concentrations in Kampala and Jinja, two Ugandan cities: residential sites with unpaved roads had very high PM2.5 concentrations of 152.6 micrograms per cubic meter vs 120.5 micrograms per cubic meter on average in residential sites.9Khanna et al (2021) show that high-skilled individuals in China are more likely to migrate in response to pollution.…”