A Spatial Panel Data Analysis of Economic Growth, Urbanization, and NOx Emissions in China

Abstract

Is nitrogen oxides emissions spatially correlated in a Chinese context? What is the relationship between nitrogen oxides emission levels and fast-growing economy/urbanization? More importantly, what environmental preservation and economic developing policies should China’s central and local governments take to mitigate the overall nitrogen oxides emissions and prevent severe air pollution at the provincial level in specific locations and their neighboring areas? The present study aims to tackle these issues. This is the first research that simultaneously studies the nexus between nitrogen oxides emissions and economic development/urbanization, with the application of a spatial panel data technique. Our empirical findings suggest that spatial dependence of nitrogen oxides emissions distribution exists at the provincial level. Through the investigation of the existence of an environmental Kuznets curve (EKC) embedded within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework, we conclude something interesting: an inverse N-shaped EKC describes both the income-nitrogen oxides nexus and the urbanization-nitrogen oxides nexus. Some well-directed policy advice is provided to reduce nitrogen oxides in the future. Moreover, these results contribute to the literature on development and pollution.

Environmental Accounting of Financial Development and Foreign Investment: Spatial Analyses of East Asia

“…Liu et al [25] agreed with the idea of spatial dependency as well, and in their study on China, they have argued that Chinese provinces are spatially dependent on each other in terms of eco-environment while urbanization has a strong role in that as well. Ge et al [7] agreed to the concept of spatial dependency in terms of emissions in China. Chen et al [2] argued about a strong existence of spatial dependency in the region mentioning that other than environmental degradation, pollution has spatial effects on public health as well.…”

“…A wide variety of studies conducted on the topic so far is mostly limited to testing the existence of EKC in the Asia region [3,19] or to limit the scope to find the monotonic effect of different variables on the pollution emissions in South and Southeast Asia [15][16][17][18] and does not proceed to incorporate spatial effects. Other than studies conducted on China [1,2,[5][6][7][8][21][22][23][24][25][26][27], no extensive research has been done on EKC with the prevalence of spatial effects in the panel of East Asia region which is a vast research gap that this study focuses on filling.…”

“…They analyze China from a spatial perspective and mention that depending on the level of urbanization in the part of the country, emissions grow differently while industrial and environmental policies play their role in the equation as well. Ge et al [7] have conducted a spatial study on NO x emissions of China. Through a stochastic impacts by regression on population, affluence, and technology (STIRPAT) framework, the results of the study have suggested an inverse N-shaped relationship between urbanization and NO x on a provincial level in China.…”

“…Xiaong et al [20] have tested the effect of FMD on CO 2 emissions in a single country case of China, but no study has yet tested the effect of FMD in a panel of East Asia. Additionally, the role of spatial dependency is something that is scant in the empirical environment literature; although, a good number of studies have investigated the spatial effects in the provinces or cities of China [1,2,[5][6][7][8][21][22][23][24][25][26][27]. However, this analysis is totally absent for a panel of East Asia, and there is a need to incorporate this idea into research.…”

Exploring Environmental Kuznets Curves of Kitakyushu: 50-Year Time-Series Data of the OECD SDGs Pilot City

“…Since the first empirical results of the EKC (Grossman and Krueger, 1991;Panaĭotou, 1993;Shafik and Bandyopadhyay, 1992), the debate around the hypothesis has become more controversial with evidence on both sides (Crespo Cuaresma et al, 2017;Ota, 2017;Özokcu and Özdemir, 2017). In the literature of EKC, real GDP and GDP per capita are the most frequently used economic indicators to explore the EKC in all types of data, from panel data (Ge et al, 2018;Narayan and Narayan, 2010;Ozcan, 2013;Sharma, 2011;Sinha and Bhattacharya, 2016), to time-series (Ahmad et al, 2017;Ali et al, 2017;Bölük and Mert, 2015;Rafindadi, 2016) and cross-sectional data (Hill and Magnani, 2002). However, there appears a scarcity of studies done on the EKC of industrial growth, despite the fact that industrial growth contributes substantially to economic growth and exert major effects on environmental degradation.…”