A spatial panel analysis of carbon emissions, economic growth and high-technology industry in China

By Li Li, Xuefei Hong, K. Peng. Structural Change and Economic Dynamics, 2019

137 citations recorded by the source corpus.

Abstract This paper constructed a spatial panel STRIPAT-Durbin model using data for 30 Chinese provinces during the period of 2004–2016. It examined the influence of economic development and the industrial structure on carbon emissions by exploring the spatial agglomeration and spillover effects of high-tech industry, economic growth, FDI, population and carbon emissions based on spatial correlation. The empirical results showed that high-tech industry, FDI, population and carbon emissions have spatial dependence and spatial agglomeration effects. High-tech industries, FDI and population have a spatial spillover effect on carbon emissions. Therefore, the government should develop a low-carbon economy by increasing the proportion of high-tech industry through technological progress and developing vigorous resource-saving and environmentally friendly tertiary industry by promoting cleaner production technology. Furthermore, local governments at all levels should use their location to promote the flow of industry transfer and technology and achieve a high inter-regional carbon industry flow and reasonable spatial distribution.

Subfields: Economics and Econometrics, Environmental Engineering, Health, Toxicology and Mutagenesis

View Paper: https://www.semanticscholar.org/paper/f01ba0f5384d08cd65a1af1244c55fea492079e5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Avik Sinha
2. Tuhin Sengupta
3. Xuejiao Ma
4. Rafael Alvarado
5. Tanaya Saha
6. Muhammad Shahbaz
7. Arshian Sharif
8. Umer Shahzad

In Environmental Engineering

1. Avik Sinha
2. Tuhin Sengupta
3. Rafael Alvarado
4. Xuejiao Ma
5. Olimpia Neagu

In Health, Toxicology and Mutagenesis

1. Avik Sinha
2. Xuejiao Ma

Citations in the corpus

• Interplay between technological innovation and environmental quality: Formulating the SDG policies for next 11 economies (2020, background): “Also, environmental 33 regulation on production processes, technology and pollution management; the population size, and the 34 type of energy source are factors that significantly affect the levels of air pollution (Wang et al., 2019; 1 Zeng et al., 2019; Li et al., 2019).”
• Technology policy and environmental quality at crossroads: Designing SDG policies for select Asia Pacific countries (2020, background): “Li et al. (2018) conducted a study on 30 13 provinces in China and employed a spatial model to understand the effect of economic growth 14 and high-technology toward carbon emissions.”
• How does tourism development affect environmental pollution? (2021, methodology): “Fifth, according to the STIRPAT model discussed above, we use population, GDP per capita and energy intensity as control variables, and they are known to influence CAR (Li et al., 2019; Pao et al., 2011; Sun, 2016; Zafar et al., 2019; Zhang et al., 2019b).”