- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Over the last three decades, rapid industrialization in China has generated an unprecedentedly high level of air pollution and associated health problems. Given that China accounts for one-fifth of the world population and suffers from severe air pollution, a comprehensive review of the indicators accounting for the health costs in relation to air pollution will benefit evidence-based and health-related environmental policy-making. This paper reviews the conventional static and the new dynamic approach adopted for air pollution-related health cost accounting in China and analyzes the difference between the two in estimating GDP loss. The advantages of adopting the dynamic approach for health cost accounting in China, with conditions guaranteeing its optimal performance are highlighted. Guidelines on how one can identify an appropriate approach for health cost accounting in China are put forward. Further, we outline and compare the globally-applicable and China-specific indicators adopted by different accounting methodologies, with their pros and cons being discussed. A comprehensive account of the available databases and methodologies for health cost accounting in China are outlined. Future directions to guide health cost accounting in China are provided. Our work provides valuable insights into future health cost accounting research in China. Our study has strengthen the view that the dynamic approach is comparatively more preferred than the static approach for health cost accounting in China, if more data is available to train the dynamic models and improve the robustness of the parameters employed. In addition, future dynamic model should address the socio-economic impacts, including benefits or losses of air pollution polices, to provide a more robust policy picture. Our work has laid the key principles and guidelines for selecting proper econometric approaches and parameters. We have also identified a proper estimation method for the Value of Life in China, and proposed the integration of engineering approaches, such as the use of deep learning and big data analysis for health cost accounting at the fine-grained level (city-district or sub-regional level). Our work has also identified the gap for more accurate health cost accounting at the fine-grained level in China, which will subsequently affect the quality of healthrelated air pollution policy decision-making at such levels, and the health-related quality of life of the citizens in China.
6. Recommendations and conclusions
This study provides recommendations and conclusions on air pollution-related health cost accounting research in China, by studying the differences among different health cost accounting models and their related economic parameters, the China-specific and globally-applicable indicators, data resource, and conducting a bibliometric review on the past 30-year research trend. Finally, we conclude this paper by recommending areas of improvements and highlighting the general research directions for health cost accounting.
6.1. Select the best model for health cost accounting
More attentions should be paid to the choice of appropriate model for health cost accounting. The static model is likely to underestimate the total health costs, mainly by ignoring the long-term effects of crosssectoral interactions (Matus et al., 2012; Nam et al., 2010; Reilly et al., 2013); the dynamic model based on CGE model can take into account of the interaction effects, and create a soft-link between the CGE model and models on air quality and health impacts to better represent the true costs of health due to air pollution in China. However, though the dynamic model has been developed, further effort is needed in future to improve the model structure to address the robustness of the parameters, and to take into account any country specific variables that may contribute to the final health costs of individuals. At the moment, the efficiency of the dynamic model in China may be affected if there is not enough empirical data available to facilitate parameter calibration. However, with increasing attention paid to the health effects of air pollution in China by the government and the public, the scale and quality of available health and air pollution data to be fed into the CGE model should be improved subsequently.