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Energy use and exporting: an analysis of Chinese firms

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Abstract

As global emissions increase with global trade, there is a critical need to understand the importance of energy use in export-oriented manufacturing activities in emerging economies. We investigate this issue by examining whether the extent of firms’ involvement in exporting is associated with the energy-intensiveness of their production activities. We use data from a survey of Chinese firms, officially classified as users of ‘advanced’ technologies. Although in recent years China has been attempting to discourage exports of energy- and pollution-intensive products, our results show a positive association between firms’ energy-use intensity and their exporting. This relationship exists across industries with different levels of technological sophistication, but is particularly salient in industries characterized by high energy-use intensity. We discuss the theoretical and policy implications of these findings.

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Data availability

The dataset used in the current study is not publicly available. It derives from a survey administered by the Ministry of Science and Technology of China. The authors obtained the data and the permission to use it because of the involvement of the fourth author of this paper in the administration of the survey.

Notes

  1. Since the mid-2000s, China has had the world’s largest renewable power capacity (whether including hydro power or not) (REN21, 2010, 2014) and Chinese firms lead the global wind turbine and solar PhotoVoltaic (PV) technology markets (Nahm and Steinfeld 2014). China also hosts the largest number of Kyoto mechanism projects aimed at reducing carbon emissions (Bodas Freitas et al. 2012).

  2. It might be that the association between energy intensity and export competitiveness might be hiding potentially greater innovativeness of energy-intensive, export-oriented firms. However, we found no positive association between energy intensity and export intensity, and firm innovation performance (see Sect. 5).

  3. The six main energy-intensive sectors in China are petroleum, chemicals, ferrous and non-ferrous metals, non-metallic mineral products, electric and heat power. These activities accounted for 50% of China’s total energy consumption in 2016 (International Energy Charter 2018).

  4. “Since June 2004, a differential electricity price has been applied to energy-intensive industries, along with a surcharge for poor energy efficiency performance” (International Energy Charter 2018).

  5. Exporters do not have to pay VAT, but firms can estimate the amount of VAT paid to domestic or foreign suppliers of raw materials, machinery, services. The abolition of these rebates meant that firms were forced to absorb the costs of VAT incurred by the production of goods for export.

  6. In 2011, the average electricity price in each province ranged from 0.36 RMB (about 3.5 GB pence) in Quinghai to 0.63 RMB (6.1 GB pence) in Guangdong, 0.54 RMB in Shanghai and 0.49 RMB (4.8 GB pence) in Hebei (Berkeley Lab 2014).

  7. 6% for revenues below RMB50 million, 4% for revenues between RMB50 million and RMB200 million, and 3% for revenues above RMB200 million.

  8. Their products or services must belong to one of the state-supported sectors (i.e., Electronic information technology; Biological and medical technology; Aviation and space technology; New materials technology; High-tech services; New energy and energy conservation technology; Resources and environmental technology; Transformation of traditional sectors through new technologies).

  9. The bounded nature of the dependent variable means that a linear regression model is not appropriate.

  10. Inclusion of industry dummies caused convergence problems in the comparison between high-tech and low-tech industries. We therefore compared models including average growth of energy intensity in place of the industry dummies. We also compared the high-energy-intensity industry subsamples, including the industry dummies. We obtained the same results for both comparison exercises.

  11. Note that because the focus of this paper is on the association between energy intensity and exporting and the use of cross-section data does not permit examining lagged effect, the tests we describe are aimed at establishing the correlation between energy intensity and export intensity, not the potential causal effect of the former on the latter.

  12. The two-stage model we adopted requires the continuous dependent variables; we therefore logit transformed the export intensity variable (Baum 2008; Beverelli et al. 2015; Saenz and Thompson 2017).

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Authors and Affiliations

  1. Grenoble Ecole de Management, 12 Rue Pierre Sémard, 38000, Grenoble, France

    Isabel-Maria Bodas Freitas & Jojo Jacob

  2. UNU-MERIT, Maastricht University, Maastricht, The Netherlands

    Lili Wang

  3. Hebei University of Technology, Tianjin, People’s Republic of China

    Zibiao Li

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  1. Isabel-Maria Bodas Freitas
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  2. Jojo Jacob
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  4. Zibiao Li
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Correspondence to Jojo Jacob.

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Appendices

Appendix 1

Table 5 Summary of ownership categories in the sample
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Appendix 2

Table 6 Summary of industry categories in the sample
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Appendix 3

Table 7 Sectoral pattern of energy consumption, export and revenue in China, 2005–2013
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Freitas, IM.B., Jacob, J., Wang, L. et al. Energy use and exporting: an analysis of Chinese firms. J Evol Econ 33, 179–207 (2023). https://doi.org/10.1007/s00191-022-00796-1

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