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<p>Based on the double critical value method and the data of the China Household Panel Survey from 2014 to 2023, this paper measures the multidimensional relative household energy poverty in China. After confirming the impact of income poverty on energy poverty, this paper explores the formation mechanism of energy poverty from the perspective of opportunity acquisition. It explores the occurrence path of “opportunity access-income poverty-energy poverty” of residents by combining the structural equation model. Finally, the impact of Internet use on energy poverty was investigated through multiple regression analysis. According to the study, China’s official poverty line is about 2.0 US dollars, and the energy poverty line has increased by 49.6% in 2022 compared with 197.2 yuan in 2018. In the empirical analysis of access level and energy poverty, the coefficient of Internet learning is 0.311. Further, adding the moderating effect model regression results of the interaction term shows that the Internet penetration rate has a significant positive impact on multidimensional energy poverty. When it is increased by 1%, the multidimensional energy poverty is reduced by 9.25%.</p>
</abstract>

Based on the double critical value method and the data of the China Household Panel Survey from 2014 to 2023, this paper measures the multidimensional relative household energy poverty in China. After confirming the impact of income poverty on energy poverty, this paper explores the formation mechanism of energy poverty from the perspective of opportunity acquisition. It explores the occurrence path of “opportunity access-income poverty-energy poverty” of residents by combining the structural equation model. Finally, the impact of Internet use on energy poverty was investigated through multiple regression analysis. According to the study, China’s official poverty line is about 2.0 US dollars, and the energy poverty line has increased by 49.6% in 2022 compared with 197.2 yuan in 2018. In the empirical analysis of access level and energy poverty, the coefficient of Internet learning is 0.311. Further, adding the moderating effect model regression results of the interaction term shows that the Internet penetration rate has a significant positive impact on multidimensional energy poverty. When it is increased by 1%, the multidimensional energy poverty is reduced by 9.25%.

Internet usage and household energy poverty

School of Management, Tianjin University of Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Internet usage and household energy poverty"}

Based on the double critical value method and the data of the China Household Panel Survey from 2014 to 2023, this paper measures the multidimensional relative...

Internet usage and household energy poverty

Data publikacji: 02 lip 2024

Zakres stron: -

Otrzymano: 10 mar 2024

Przyjęty: 02 cze 2024

DOI: https://doi.org/10.2478/amns-2024-1538

Słowa kluczowe
Dual critical value approach, Energy poverty measurement, Structural equation modeling, Multiple regression analysis

© 2024 Yifei Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Internet usage and household energy poverty

Data publikacji: 02 lip 2024

Zakres stron: -

Otrzymano: 10 mar 2024

Przyjęty: 02 cze 2024

DOI: https://doi.org/10.2478/amns-2024-1538

Słowa kluczoweDual critical value approach, Energy poverty measurement, Structural equation modeling, Multiple regression analysis

© 2024 Yifei Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Dual critical value approach, Energy poverty measurement, Structural equation modeling, Multiple regression analysis