IMF Working Papers

Climate Mitigation in China: Which Policies Are Most Effective?

ByIan W.H. Parry, Baoping Shang, Philippe Wingender, Tarun Narasimhan

July 25, 2016

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Ian W.H. Parry, Baoping Shang, Philippe Wingender, and Tarun Narasimhan. "Climate Mitigation in China: Which Policies Are Most Effective?", IMF Working Papers 2016, 148 (2016), accessed 12/4/2025, https://doi.org/10.5089/9781475574524.001

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Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

For the 2015 Paris Agreement on climate change, China pledged to reduce the carbon dioxide (CO2) intensity of GDP by 60–65 percent below 2005 levels by 2030. This paper develops a practical spreadsheet tool for evaluating a wide range of national level fiscal and regulatory policy options for reducing CO2 emissions in China in terms of their impacts on emissions, revenue, premature deaths from local air pollution, household and industry groups, and overall economic welfare. By far, carbon and coal taxes are the most effective policies for meeting environmental and fiscal objectives as they comprehensively cover emissions and have the largest tax base.

Subject: Carbon tax, Consumption, Environment, Fuel prices, Greenhouse gas emissions, National accounts, Non-renewable resources, Prices, Taxes

Keywords: aggregate welfare costs estimate, air pollution, carbon tax, China, coal tax, Consumption, consumption rate, economic welfare cost, elasticity scenario, emissions price trajectory, emissions trading, energy price, fuel economy, Fuel prices, generation cost, generation cost elasticity, Global, Greenhouse gas emissions, incidence, income elasticity, Non-renewable resources, Paris Agreement, price projection, processing plant, renewables price, welfare effects, WP

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