• Resources Science
  • Vol. 42, Issue 5, 801 (2020)
Heping CAO, Jianming XI*, and Yuezhuo CHEN
Author Affiliations
  • School of Economics, Peking University, Beijing 100871, China
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    DOI: 10.18402/resci.2020.05.01 Cite this Article
    Heping CAO, Jianming XI, Yuezhuo CHEN. Urban residents’ marginal willingness to pay for environmental pollution control[J]. Resources Science, 2020, 42(5): 801 Copy Citation Text show less

    Abstract

    Residents’ marginal willingness to pay for the environment is the most direct measurement of social-environmental preference, and is the basis of environmental system reform and detailed policies. Based on the panel data of 31 provinces in China’s mainland from 1993 to 2015, this study selected the indicators for measuring residents’ environmental preference and analyzed the main factors affecting the environmental preference of urban residents in China. It is found that factors such as residents’ income level, environmental pollution level, regional urbanization level, and residents’ education level are related to the environmental preference of urban residents, which can be used as the indicators of residents’ willingness-to-pay for the high-quality environment. According to the results, if the annual average emission of industrial waste gas is reduced by 1 ton, the marginal willingness-to-pay of Chinese urban residents for the environment improvement is 0.21 yuan. Compared with developed countries, China is still at a low level of willingness-to-pay for the environment. This study innovatively introduces the concept of environmental preference, uses the petition data of Chinese residents to the environment as the proxy variable to measure the degree of consumers’ environmental preference, and measures the marginal willingness-to-pay of urban residents for environmental governance, which provides a quantifiable basis for the government to make decisions on environmental pollution control.
    Heping CAO, Jianming XI, Yuezhuo CHEN. Urban residents’ marginal willingness to pay for environmental pollution control[J]. Resources Science, 2020, 42(5): 801
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