Economic Agglomeration and District-Level Carbon Emissions in Indonesia
DOI:
https://doi.org/10.15408/sjie.v15i2.50229Keywords:
economic agglomeration, employment density, carbon emissions, spatial concentration, nonlinear relationshipAbstract
Research Originality: This study contributes to the literature by incorporating employment density as a proxy of economic agglomeration into an extended STIRPAT framework to examine its nonlinear relationship with district-level carbon emissions in Indonesia.
Research Objectives: This study aims to investigate whether economic agglomeration promotes emission efficiency or intensifies environmental pressure, and to identify potential nonlinear dynamics across Indonesian districts.
Research Methods: This study employs a balanced panel dataset of 514 districts and municipalities in Indonesia over the period 2017–2024. A two-way fixed-effects model is estimated within an extended STIRPAT framework, with a quadratic specification to capture nonlinear effects.
Empirical Results: The results indicate that economic agglomeration is associated with lower carbon emissions per capita, suggesting efficiency effects. However, the nonlinear estimation reveals a U-shaped relationship: agglomeration reduces emissions at lower levels but increases environmental pressure beyond a threshold. The findings also indicate substantial regional heterogeneity.
Implications: The results suggest that agglomeration does not inherently lead to environmental improvements. Differentiated policies should strengthen regional growth and efficiency in low-density areas while prioritizing low-carbon transitions and congestion mitigation in dense regions.
JEL Classification: Q56, R12, O18
How to Cite:
Nugroho, R.A. & Hartono, D. (2026). Economic Agglomeration and District-Level Carbon Emissions in Indonesia. Signifikan: Jurnal Ilmu Ekonomi, 15(2), 471-486. https://doi.org/10.15408/sjie.v15i2.50229.
References
Ahmad, M., Li, H., Anser, M. K., Rehman, A., Fareed, Z., Yan, Q., & Jabeen, G. (2021). Are the Intensity of Energy Use, Land Agglomeration, CO2 Emissions, and Economic Progress Dynamically Interlinked Across Development Levels? Energy & Environment, 32(4), 690–721. https://doi.org/10.1177/0958305X20949471.
Aziz, S., & Chowdhury, S. A. (2023). Analysis of Agricultural Greenhouse Gas Emissions Using the STIRPAT Model: A Case Study of Bangladesh. Environment, Development and Sustainability, 25(5), 3945–3965. https://doi.org/10.1007/s10668-022-02224-7.
Borsha, F. H., Voumik, L. C., Rashid, M., Das, M. K., Stępnicka, N., & Zimon, G. (2024). An Empirical Investigation of GDP, Industrialization, Population, Renewable Energy and CO2 Emission in Bangladesh: Bridging EKC-STIRPAT Models. International Journal of Energy Economics and Policy, 14(3), 560–571. https://doi.org/10.32479/ijeep.15423.
BPS. (2025). Neraca Arus Energi dan Neraca Emisi Gas Rumah Kaca Indonesia 2019–2023. Jakarta: Badan Pusat Statistik.
Chanda, P., Majhi, P., & Akther, S. (2024). Testing the validity of the Environmental Kuznets Curve for carbon Emissions: A Cross-Sectional Analysis. Nature Environment and Pollution Technology, 23(4), 2251–2258. https://doi.org/10.46488/NEPT.2024.v23i04.029.
Cheng, Z. (2016). The Spatial Correlation and Interaction Between Manufacturing Agglomeration and Environmental Pollution. Ecological Indicators, 61, 1024–1032. https://doi.org/10.1016/j.ecolind.2015.10.060.
Combes, P.-P., & Gobillon, L. (2021). The Empirics of Agglomeration Economies. In. Duranton, G., Henderson, J. V., & Strange, W. C. (Eds). Handbook of Regional and Urban Economics. Amsterdam: Elsevier.
Cooray, A., & Özmen, I. (2024). Institutions and Carbon Emissions: An Investigation Employing STIRPAT and Machine Learning Methods. Empirical Economics, 67(3), 1015–1044. https://doi.org/10.1007/s00181-024-02579-y.
Cottineau, C., Finance, O., Hatna, E., Arcaute, E., & Batty, M. (2019). Defining Urban Clusters to Detect Agglomeration Economies. Environment and Planning B: Urban Analytics and City Science, 46(9), 1611–1626. https://doi.org/10.1177/2399808318755146.
Dong, B., Ma, X., Zhang, Z., Zhang, H., Chen, R., Song, Y., Shen, M., & Xiang, R. (2020). Carbon Emissions, the Industrial Structure and Economic Growth: Evidence from Heterogeneous Industries in China. Environmental Pollution, 262, 114322. https://doi.org/10.1016/j.envpol.2020.114322.
Duranton, G., & Puga, D. (2004). Micro-Foundations of Urban Agglomeration Economies. Handbook of Regional and Urban Economics, 4, 2063-2117. https://doi.org/10.1016/S0169-7218(04)07048-0
Ercole, R., & O’neill, R. (2017). The Influence of Agglomeration Externalities on Manufacturing Growth within Indonesian Locations. Growth and Change, 48(1), 91–126. https://doi.org/10.1111/grow.12145.
Falahuddin, M. I., Zukhrufah, A. Y., Sitanggang, C. J. R., & Pusponegoro, N. H. (2024). Spatial Analysis of the Determinants of Interregional Income Distribution Inequality in 2022. Proceedings at Seminar Nasional Official Statistics 2024. https://doi.org/10.34123/semnasoffstat.v2024i1.2147
Fatorachian, H., & Kazemi, H. (2025). Sustainable optimization strategies for on-demand transportation systems: Enhancing efficiency and reducing energy use. Sustainable Environment, 11(1), 2464388. https://doi.org/10.1080/27658511.2025.2464388.
Gatzioura, A., Sànchez-Marrè, M., & Gibert, K. (2019). A Hybrid Recommender System to Improve Circular Economy in Industrial Symbiotic Networks. Energies, 12(18), 3546. https://doi.org/10.3390/en12183546.
Glaeser, E. L., & Kahn, M. E. (2008). The Greenness of Cities: Carbon Dioxide Emissions and Urban Development. NBER Working Paper No. w14238.
Han, F., Xie, R., & Fang, J. (2018). Urban Agglomeration Economies and Industrial Energy Efficiency. Energy, 162, 45–59. https://doi.org/10.1016/j.energy.2018.07.163.
Hong, J., Gu, J., Liang, X., Liu, G., Shen, G. Q., & Tang, M. (2019). Spatiotemporal Investigation of Energy Network Patterns of Agglomeration Economies in China: Province-Level Evidence. Energy, 187, 115998. https://doi.org/10.1016/j.energy.2019.115998.
Jamal, A. (2017). Geographical Economic Concentration, Growth and Decentralization: Empirical Evidence in Aceh, Indonesia. Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan, 18(2), 142-150. https://doi.org/10.23917/jep.v18i2.2786.
Koirala, B., Pradhan, G., & Mensah, E. C. (2025). The Environmental Kuznets Curve and CO2 emissions under policy uncertainty in G7 countries. Economies, 13(12), 363. https://doi.org/10.3390/economies13120363
Kurniawan, R., & Managi, S. (2018). Economic Growth and Sustainable Development in Indonesia: An Assessment. Bulletin of Indonesian Economic Studies, 54(3), 339–361. https://doi.org/10.1080/00074918.2018.1450962.
Li, F., & Li, G. (2018). Agglomeration and Spatial Spillover Effects of Regional Economic Growth in China. Sustainability, 10(12), 4695. https://doi.org/10.3390/su10124695.
Liu, Y., Yang, M., & Cui, J. (2024). Urbanization, Economic Agglomeration and Economic Growth. Heliyon, 10(1), e23772. https://doi.org/10.1016/j.heliyon.2023.e23772.
McCann, P., & van Oort, F. (2019). Chapter 1: Theories of Agglomeration and Regional Economic Growth: A Historical Review. In. Capello, R., & Nijkamp, P (Eds). Handbook of Regional Growth and Development Theories. New York: Edward Elgar Publishing. https://doi.org/10.4337/9781788970020.00007.
Melo, P. C., Graham, D. J., & Noland, R. B. (2009). A Meta-Analysis of Estimates of Urban Agglomeration Economies. Regional Science and Urban Economics, 39(3), 332–342. https://doi.org/10.1016/j.regsciurbeco.2008.12.002.
Nkengfack, H., Fotio, H. K., & Djoudji, S. T. (2019). The Effect of Economic Growth on Carbon Dioxide Emissions in Sub-Saharan Africa: Decomposition into Scale, Composition and Technique Effects. Modern Economy, 10(05), 1398–1418. https://doi.org/10.4236/me.2019.105094.
Resbeut, M., Gugler, P., & Charoen, D. (2019). Spatial Agglomeration and Specialization in Emerging Markets: The Economic Efficiency of Clusters in Thai Industries. Competitiveness Review, 29(3), 236–252. https://doi.org/10.1108/CR-10-2018-0065.
Shahbaz, M., Ozturk, I., Afza, T., & Ali, A. (2013). Revisiting the Environmental Kuznets Curve in a Global Economy. Renewable and Sustainable Energy Reviews, 25, 494–502. https://doi.org/10.1016/j.rser.2013.05.021.
Stern, D. I. (2004). The Rise and Fall of the Environmental Kuznets Curve. World Development, 32(8), 1419–1439. https://doi.org/10.1016/j.worlddev.2004.03.004.
Stern, D. I. (2017). The Environmental Kuznets Curve After 25 Years. Journal of Bioeconomics, 19(1), 7–28. https://doi.org/10.1007/s10818-017-9243-1.
Tatoğlu, F. Y., & Polat, B. (2021). Occurrence of Turning Points on Environmental Kuznets Curve: Sharp Breaks or Smooth Shifts? Journal of Cleaner Production, 317, 128333. https://doi.org/10.1016/j.jclepro.2021.128333.
Wang, F., Fan, W., Liu, J., Wang, G., & Chai, W. (2020). The Effect of Urbanization and Spatial Agglomeration on Carbon Emissions in Urban Agglomeration. Environmental Science and Pollution Research, 27(19), 24329–24341. https://doi.org/10.1007/s11356-020-08597-4.
Wang, X., Xu, L., Ye, Q., He, S., & Liu, Y. (2022). How Does Services Agglomeration Affect the Energy Efficiency of the Service Sector? Evidence from China. Energy Economics, 112, 106159. https://doi.org/10.1016/j.eneco.2022.106159.
Wilonoyudho, S., Rijanta, R., Keban, Y. T., & Setiawan, B. (2017). Urbanization and Regional Imbalances in Indonesia. Indonesian Journal of Geography, 49(2), 125–132. https://doi.org/10.22146/ijg.13039.
Wu, Z., Woo, S. H., Piboonrungroj, P., & Lai, P. L. (2025). Manufacturing Agglomeration and Carbon Emissions: An Ensemble Learning Approach with Evidence from South Korea. Humanities and Social Sciences Communications, 12, 90. https://doi.org/10.1057/s41599-025-05150-x.
Yi, Y., Wang, Y., Li, Y., & Qi, J. (2021). Impact of Urban Density on Carbon Emissions in China. Applied Economics, 53(53), 6153–6165. https://doi.org/10.1080/00036846.2021.1937491.
Yilmaz, E., & Sensoy, F. (2022). Effects of Fossil Fuel Usage in Electricity Production on CO2 Emissions: A STIRPAT Model Application on 20 Selected Countries. International Journal of Energy Economics and Policy, 12(6), 224–229. https://doi.org/10.32479/ijeep.13707.
York, R., Rosa, E. A., & Dietz, T. (2003). STIRPAT, IPAT and ImPACT: Analytic Tools for Unpacking the Driving Forces of Environmental Impacts. Ecological Economics, 46(3), 351–365. https://doi.org/10.1016/S0921-8009(03)00188–5.
Yu, Q., Li, M., Li, Q., Wang, Y., & Chen, W. (2022). Economic Agglomeration and Emissions Reduction: Does High Agglomeration in China’s Urban Clusters Lead to Higher Carbon Intensity? Urban Climate, 43, 101174. https://doi.org/10.1016/j.uclim.2022.101174.
Yunitasari, D., Fauzan, A., & Prianto, F. W. (2023). Reducing Regional Disparity in Java: A Spatial Econometrics Approach. Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan, 24(1), 129–140. https://doi.org/10.23917/jep.v24i1.18532.
Zhou, M., Shao, W., Jiang, K., & Huang, L. (2024). How Does Economic Agglomeration Affect Carbon Emissions at the County Level in Liaoning, China? Ecological Indicators, 158. 111507. https://doi.org/10.1016/j.ecolind.2023.111507.
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