Foreign direct investment and energy intensity in China: Firm-level evidence

By Maoliang Bu, Shuang Li, Lei Jiang. Energy Economics, 2019

184 citations recorded by the source corpus.

Given the significance of energy use, which emits greenhouse gases and generates air pollution, decreasing energy intensity is considerably important for both China and the global environment. We employ a unique dataset of firm-level data on 13 cities in Jiangsu Province of China and investigate the relationship between FDI and energy intensity. Taking into account the heterogeneity characteristics of firms, we confirm a significant and negative coefficient of the FDI variable, which implies that FDI firms have lower energy intensity than their local counterparts. We introduce the interaction term of FDI and regional absorptive capacity, and the empirical results show that regions endowed with more absorptive capacity usually have lower energy intensity. Specifically, more spending on technology tends to narrow the technology gap between foreign and local firms, since local firms absorb international technology transfer more effectively and efficiently. Moreover, examining the cases of the textile and chemical industries, we find that FDI firms in the chemical industry have lower energy intensity than their local counterparts, while we observe no difference between FDI firms and non-FDI ones in the textile industry.

Subfields: Economics and Econometrics, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/5d3e867c60366bd1cfd985d21e0fa461c8e3c86c

How researchers see this paper

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In Economics and Econometrics

1. Avik Sinha
2. X. Vo
3. Muhammad Shahbaz
4. Chandrashekar Raghutla
5. Kun Yang
6. Liang Liu
7. Jun Liu
8. Hidemichi Fujii

In Strategy and Management

1. Avik Sinha
2. X. Vo
3. Chandrashekar Raghutla
4. Hidemichi Fujii
5. Muhammad Shahbaz

Citations in the corpus

• Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel (2021, background): “, 2018), capital intensity (Bu et al., 2019) and R&D level (Huang et al.”
• Decomposing Scale and Technique Effects of Financial Development and Foreign Direct Investment on Renewable Energy Consumption (2022, methodology): “Bu et al. (2019) applied panel-corrected standard errors (PCSE) and OLS regression techniques for examining the relationship between foreign direct investment and energy intensity for a panel of 13 Provinces in China.”