Exploring the impacts of a carbon tax on the Chinese economy using a CGE model with a detailed disaggregation of energy sectors

Highlights

• Restructuring the industry sectors to get a robust simulation results.

• Simulating the carbon tax's impacts on China economy by using CGE model.

• A moderate rate of carbon tax is an effective policy alternative for China.

• Levying carbon tax has significant impacts on carbon emission reduction.

Abstract

This paper applies a computable general equilibrium model to investigate the impacts of a carbon tax on China's economy and carbon emissions based on China's 2010 Input–Output Table. To obtain robust simulation results, we further disaggregate the energy sectors into eight departments according to energy use characteristics. The empirical results indicate that a moderate carbon tax would significantly reduce carbon emissions and fossil fuel energy consumption and slightly reduce the pace of economic growth. However, a large carbon tax has a significantly negative impact on China's economy and social welfare. Moreover, a large carbon tax would entail marked price changes in China. Of the fossil fuels in use, reducing coal consumption would have the greatest impact on reducing carbon emissions, and the ad valorem duty rate for coal would be the highest after levying a carbon tax because it has the highest carbon emission coefficient. Therefore, China should strive to promote clean coal technology, which may be crucial to reducing carbon emissions. Moreover, levying a carbon tax would improve the use of clean energy, which would be an effective means of reducing carbon emissions. Therefore, the Chinese government should formulate the regulations for and pass a carbon tax as early as possible to achieve its carbon emission abatement target and further contribute to mitigating climate change.

Introduction

Due to its massive population and rapid economic growth, China has become the largest carbon dioxide emitter in the world. At the 2009 United Nations Climate Change Conference, the Chinese government committed to reducing carbon dioxide emissions per unit of GDP by 40%–45% below 2005 levels by 2020, although Chinese per capita carbon emissions are very low. To achieve its ambitious emission reduction target, the National Economic and Social Development Statement in China's Twelfth Five-Year Plan (2011–2015) declared that the percentage of non-fossil energy in total primary energy consumption will increase to 11.4%, and carbon dioxide emissions per unit of GDP will be reduced by 17% during the period of Twelfth Five-Year Plan (2011–2015). However, country-level conditions create enormous difficulties for China to realize this goal. For example, coal will be the dominant form of primary energy in the foreseeable future, as China is rich in coal but lacks gas and oil. In addition, energy-intensive industries play a dominant role in the Chinese economy. Moreover, China's efforts to accelerate the process of industrialization and urbanization are at a crucial stage, and hence, substantial energy input is needed. Therefore, it is important for China to adopt effective measures to reduce fossil fuel consumption and carbon emissions to achieve its emission reduction goal. Theory indicates that a carbon tax is effective at reducing carbon emissions, and it represents one of the most plausible carbon mitigation strategies in China.

As levying a carbon tax may have negative effects on economic growth, extensive studies have applied various alternative approaches to discuss this issue and formulate effective environmentally friendly economic policies. Of these approaches, a computable general equilibrium (CGE) model provides a consistent framework to analyze the economic impacts of policy and a complete description of the economy, including the direct and indirect effects of policy changes. In a pioneering application of the CGE model, Whalley and Wigle, 1991, Whalley and Wigle, 1992used it to model climate change issues and developed a multinational, static CGE model involving global trade and carbon emission to analyze the international effects of carbon taxation. Since then, the CGE has been the popular tool to investigate the impacts of a carbon tax on the social and economic systems. Kamat et al. (1999) simulated the economic effects of global carbon taxes using a CGE model of the US Susquehanna River Basin. Using a dynamic, multi-sector CGE model, Kemfert and Welsch (2000) compared the economic effects of carbon taxes under different estimates of the energy–capital–labor substitution elasticity. Based on a CGE model, Bruvoll and Fæhn (2004) quantified the effects of endogenous carbon tax policy in Norway, where ambitious climate policy has been implemented. The results indicated that the environmental benefits declined and the economic costs increased when a global rather than a national perspective was employed. Wissema and Dellink (2007) developed a CGE model with specific detail in taxation and energy use to quantify the impact of implementing energy taxation to reduce carbon dioxide emissions in Ireland. Given the increasing specialization of sector-specific capital varieties, Bretschger et al. (2011) developed a new type of CGE model in which growth is fully endogenous. This model was applied to simulate the effects of carbon policies on consumption, welfare, and industrial development in the long run. Orlov and Grethe (2012) investigated the economic effects of carbon taxes on the Russian economy under the assumptions of perfect competition and a Cournot oligopoly in output markets. Recently, Meng et al. (2013) employed a CGE model with an environmentally extended social accounting matrix to simulate the effects of a carbon tax of $23 per ton of carbon dioxide, as proposed by the Australian government, on the environment and economy.

As the world's largest carbon dioxide emitter, China has attracted substantial attention, and an increasing number of studies focus on analyzing carbon taxation in China. The question of whether carbon tax is suitable for China has been a source of controversy. Many studies have explored the impact of a carbon tax on the Chinese economy using the CGE model. As no official carbon emission data are available in China, we have to estimate the carbon emissions. The approach employed in sector aggregation and disaggregation has significant impacts on the Input–Output Table, which provides the basic data for the CGE model. (For additional details on sector disaggregation, see Su et al., 2010, Su and Ang, 2012a, Su and Ang, 2012b). Thus, when using the CGE model to analyze carbon or energy taxation issues, it is vital to disaggregate the energy sectors. Past efforts at disaggregating the energy sectors in China for use in energy and environmental CGE models are summarized in Table 1. While extant studies adopt different energy sector classifications, these efforts include three common features. First, most previous studies combine the coal mining and washing sector and the coking sector into a single sector and the petroleum extraction sector and refined oil sector into another, which may bias the policy simulation results because the feedstock input of crude oil or coal in the refining or coking process will be considered as the energy input. In addition, petroleum and natural gas extraction activities are tabulated as a single sector in China's Input–Output Table. However, petroleum and extraction of natural gas extraction activities are heterogeneous, and hence disaggregating this sector is necessary in policy analysis. Second, many researchers disaggregate the petroleum and natural gas extraction sector into a petroleum extraction sector and a natural gas extraction sector solely based on their physical shares in primary energy consumption. This disaggregation technique produces inaccurate results, as the two products' output structures in the production process and distribution structures differ substantially. Finally least, most existing studies failed to disaggregate clean power from electric power. In this paper, clean power includes nuclear power, hydroelectric power, wind power, solar power, tidal power, and geothermal power. Recently, clean power has developed rapidly in China, accounting for approximately 8% of total energy in 2011. It is necessary to distinguish clean power from electric power, as the carbon emission coefficients of clean power and thermal power are significantly different. It is worth noting that Lin and Jiang (2011) and Liu and Li (2011) disaggregated the power sector into five sub-sectors, including clean power from nuclear power, hydroelectric power, and renewable power, but it is unclear how they realize this disaggregation or what types of data they employ to do so.

In this paper, we restructure the energy sectors to overcome the three shortcomings mentioned above and to obtain robust simulation results using a CGE model. In addition, the latest data from the Chinese Input–Output Table, from 2010, are used in this paper.

This paper is organized as follows: Section 2 discusses the disaggregation of the energy sectors. Section 3 introduces the model's structure and functional characteristics. Section 4 analyzes the simulation results and policy implications. Section 5 concludes this paper.