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Does government information transparency contribute to pollution abatement? Evidence from 264 Chinese cities

pmid: 33566288
Government information transparency is taken as a prominent instrument of environmental regulation in Chinese cities, especially in the current digital age. However, polluters' strategic emission and production behaviors across cities, confronted with changing information disclosure level, might make the policy's effect unexpected in practice. While many existing studies have explored the impact of institutions on pollution, government information disclosure only attracted little attention from empirical studies. Using the method framework of the spatial Durbin model, this study empirically investigates the impact of government information transparency on sulfur dioxide emissions with samples of 264 Chinese cities from 2005 to 2012. We find that a city's government information transparency negatively relates to its local emission level of sulfur dioxide. Moreover, a city's sulfur dioxide emissions positively relate to its neighboring cities' government information transparency levels. The further calculations of marginal effects show that the average of such a direct and local impact of government information transparency outweighs the average indirect effect a city receives from its neighboring cities, making government information transparency benefits to pollution abatement in total.
- Xi'an Jiaotong University China (People's Republic of)
- Xiamen University China (People's Republic of)
- Xiamen University China (People's Republic of)
- Xi’an Jiaotong-Liverpool University China (People's Republic of)
- Research Center for Energy Economics Germany
Air Pollutants, China, Air Pollution, Government, Sulfur Dioxide, Cities, Environmental Pollution
Air Pollutants, China, Air Pollution, Government, Sulfur Dioxide, Cities, Environmental Pollution
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
