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City centrality, population density and energy efficiency

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  • He, Xiaoping
  • Yu, Yuxuan
  • Jiang, Shuo

Abstract

We use continuous night light data and LandScan population data to construct a monocentric index to measure whether a city tends to be a monocentric or polycentric spatial structure, and estimate the impact of such structure on energy efficiency by using a two-way fixed effects model. In order to solve the endogeneity of urban structure, the historical census data and topographic relief data at the city level are used to construct the instrumental variables. We find that an increase in the urban monocentricity index would significantly reduce the level of the urban energy intensity. Meanwhile, the relationship between monocentricity and urban energy intensity is U-shaped. When the degree of monocentricity is at relatively low level, its impact on energy efficiency is positive, implying the dominance of agglomeration effect. When economic agglomeration is greater than a certain degree, the impact of monocentricity becomes negative which results from the dominance of congestion effect. Moreover, impact of urban structure on energy intensity varies with urban population density. An increase in population density would weaken the negative impact of monocentricity on energy intensity, that is, in sparsely populated cities, the monocentricity is more conducive to energy saving. In terms of city form, monocentric structure may improve energy efficiency in the cities with poor transportation infrastructure more than in the cities with good transportation infrastructure. Monocentricity facilitates energy efficiency primarily by increasing corporate innovation and saving commuting time and distance. We perform a series of robustness tests and the findings are basically consistent with the baseline result. Our findings suggest that the cities at this stage should continue to strengthen the development of monocentricity, pay attention to compactness of urban spatial structure, and develop the polycentric structure cautiously. Meanwhile, in the development process, the local population density and the carrying capacity of the transportation infrastructure should be taken into consideration to avoid the negative effects caused by the congestion in main center.

Suggested Citation

  • He, Xiaoping & Yu, Yuxuan & Jiang, Shuo, 2023. "City centrality, population density and energy efficiency," Energy Economics, Elsevier, vol. 117(C).
  • Handle: RePEc:eee:eneeco:v:117:y:2023:i:c:s0140988322005655
    DOI: 10.1016/j.eneco.2022.106436
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    as
    1. Glaeser, Edward L. & Kahn, Matthew E., 2010. "The greenness of cities: Carbon dioxide emissions and urban development," Journal of Urban Economics, Elsevier, vol. 67(3), pages 404-418, May.
    2. Schwanen, Tim & Dieleman, Frans M. & Dijst, Martin, 2002. "The impact of metropolitan structure on commute behavior in the Netherlands: a multilevel approach," ERSA conference papers ersa02p069, European Regional Science Association.
    3. Tim Schwanen & Frans M. Dieleman & Martin Dijst, 2004. "The Impact of Metropolitan Structure on Commute Behavior in the Netherlands: A Multilevel Approach," Growth and Change, Wiley Blackwell, vol. 35(3), pages 304-333, September.
    4. Yingcheng Li & Rui Du, 2022. "Polycentric urban structure and innovation: evidence from a panel of Chinese cities," Regional Studies, Taylor & Francis Journals, vol. 56(1), pages 113-127, January.
    5. Doremus, Jacqueline M. & Jacqz, Irene & Johnston, Sarah, 2022. "Sweating the energy bill: Extreme weather, poor households, and the energy spending gap," Journal of Environmental Economics and Management, Elsevier, vol. 112(C).
    6. Crompton, Paul & Wu, Yanrui, 2005. "Energy consumption in China: past trends and future directions," Energy Economics, Elsevier, vol. 27(1), pages 195-208, January.
    7. Huijie Yan, 2015. "Provincial energy intensity in China: The role of urbanization," Post-Print hal-01457329, HAL.
    8. Bu, Maoliang & Li, Shuang & Jiang, Lei, 2019. "Foreign direct investment and energy intensity in China: Firm-level evidence," Energy Economics, Elsevier, vol. 80(C), pages 366-376.
    9. Ciccone, Antonio & Hall, Robert E, 1996. "Productivity and the Density of Economic Activity," American Economic Review, American Economic Association, vol. 86(1), pages 54-70, March.
    10. Garcia-López, Miquel-Àngel & Moreno-Monroy, Ana I., 2018. "Income segregation in monocentric and polycentric cities: Does urban form really matter?," Regional Science and Urban Economics, Elsevier, vol. 71(C), pages 62-79.
    11. Jan K. Brueckner, 2000. "Urban Sprawl: Diagnosis and Remedies," International Regional Science Review, , vol. 23(2), pages 160-171, April.
    12. Paolo Veneri, 2010. "Urban Polycentricity and the Costs of Commuting: Evidence from Italian Metropolitan Areas," Growth and Change, Wiley Blackwell, vol. 41(3), pages 403-429, September.
    13. Song, Feng & Zheng, Xinye, 2012. "What drives the change in China's energy intensity: Combining decomposition analysis and econometric analysis at the provincial level," Energy Policy, Elsevier, vol. 51(C), pages 445-453.
    14. Wang, Zhaohua & Feng, Chao & Zhang, Bin, 2014. "An empirical analysis of China's energy efficiency from both static and dynamic perspectives," Energy, Elsevier, vol. 74(C), pages 322-330.
    15. Zhang, Chuanguo & Lin, Yan, 2012. "Panel estimation for urbanization, energy consumption and CO2 emissions: A regional analysis in China," Energy Policy, Elsevier, vol. 49(C), pages 488-498.
    16. Wang, Yafei & Liao, Meng & Wang, Yafei & Xu, Lixiao & Malik, Arunima, 2021. "The impact of foreign direct investment on China's carbon emissions through energy intensity and emissions trading system," Energy Economics, Elsevier, vol. 97(C).
    17. Sadorsky, Perry, 2013. "Do urbanization and industrialization affect energy intensity in developing countries?," Energy Economics, Elsevier, vol. 37(C), pages 52-59.
    18. Ma, Ben, 2015. "Does urbanization affect energy intensities across provinces in China?Long-run elasticities estimation using dynamic panels with heterogeneous slopes," Energy Economics, Elsevier, vol. 49(C), pages 390-401.
    19. Yan, Huijie, 2015. "Provincial energy intensity in China: The role of urbanization," Energy Policy, Elsevier, vol. 86(C), pages 635-650.
    20. Huang, Junbing & Du, Dan & Tao, Qizhi, 2017. "An analysis of technological factors and energy intensity in China," Energy Policy, Elsevier, vol. 109(C), pages 1-9.
    21. Eom, Jiyong & Schipper, Lee, 2010. "Trends in passenger transport energy use in South Korea," Energy Policy, Elsevier, vol. 38(7), pages 3598-3607, July.
    22. Davide Burgalassi & Tommaso Luzzati, 2015. "Urban spatial structure and environmental emissions: a survey of the literature and some empirical evidence for Italian NUTS-3 regions," Discussion Papers 2015/199, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    23. Liu, Yaobin & Xie, Yichun, 2013. "Asymmetric adjustment of the dynamic relationship between energy intensity and urbanization in China," Energy Economics, Elsevier, vol. 36(C), pages 43-54.
    24. Ana Mar�a Fern�ndez-Maldonado & Arie Romein & Otto Verkoren & Renata Parente Paula Pessoa, 2014. "Polycentric Structures in Latin American Metropolitan Areas: Identifying Employment Sub-centres," Regional Studies, Taylor & Francis Journals, vol. 48(12), pages 1954-1971, December.
    25. Poumanyvong, Phetkeo & Kaneko, Shinji, 2010. "Does urbanization lead to less energy use and lower CO2 emissions? A cross-country analysis," Ecological Economics, Elsevier, vol. 70(2), pages 434-444, December.
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