TY - JOUR
T1 - The convergence of energy intensity in developing countries
T2 - a spatial econometric analysis with Indonesia’s provincial panel data
AU - Azaliah, Rhisa
AU - Kurniawan, Hengky
AU - Hartono, Djoni
AU - Widyastaman, Putu Angga
N1 - Funding Information:
The authors would like to thank Universitas Indonesia for funding this research through PUTI Grant with contract number NKB-800/UN2.RST/HKP.05.00/2020.
Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature B.V.
PY - 2024/6
Y1 - 2024/6
N2 - Energy intensity convergence can be used to assess the effectiveness of policies in reducing energy intensity. This study analyzes the energy intensity convergence in Indonesia based on panel data of 33 provinces from 2010 to 2018. Spatial econometrics techniques are used in the estimation of beta convergence to measure the spatial dependence of energy intensity. Empirical results show that there is evidence of both absolute and conditional beta convergences with no evidence of sigma convergence. From the results, this study found that other variables, such as provincial income, the role of manufacturing industries, the role of international trade, FDI, and population density, might encourage energy intensity convergence. From the estimation results, several policy recommendations are derived to increase energy efficiency: First, using a more efficient industrial technology. Second, attracting foreign investment to non-industrial sectors. Third, developing exports from sectors that use less energy to increase energy efficiency.
AB - Energy intensity convergence can be used to assess the effectiveness of policies in reducing energy intensity. This study analyzes the energy intensity convergence in Indonesia based on panel data of 33 provinces from 2010 to 2018. Spatial econometrics techniques are used in the estimation of beta convergence to measure the spatial dependence of energy intensity. Empirical results show that there is evidence of both absolute and conditional beta convergences with no evidence of sigma convergence. From the results, this study found that other variables, such as provincial income, the role of manufacturing industries, the role of international trade, FDI, and population density, might encourage energy intensity convergence. From the estimation results, several policy recommendations are derived to increase energy efficiency: First, using a more efficient industrial technology. Second, attracting foreign investment to non-industrial sectors. Third, developing exports from sectors that use less energy to increase energy efficiency.
KW - Absolute and conditional convergence
KW - Convergence
KW - Energy intensity
KW - Indonesia
KW - Spatial regression
UR - http://www.scopus.com/inward/record.url?scp=85152419295&partnerID=8YFLogxK
U2 - 10.1007/s10668-023-03227-8
DO - 10.1007/s10668-023-03227-8
M3 - Article
AN - SCOPUS:85152419295
SN - 1387-585X
VL - 26
SP - 14915
EP - 14939
JO - Environment, Development and Sustainability
JF - Environment, Development and Sustainability
IS - 6
ER -