Abstract
This study examines the effects of floor area ratio (FAR) and building coverage ratio (BCR) on property prices in Jakarta. Using a hdonic price mdel with data from property listings and a geographical information system (GIS) analysis, it explores how these regulations influence values across regions and property types, accounting for access to amenities and infrastructure. Results show FAR lowers prices in dense areas like Central Jakarta but raises them in less developed regions like East Jakarta. BCR effects are mixed, positive where infrastructure is strong but negative where it is weak, underscoring the need for context-specific urban planning.
References
[1] Acolin, A., Colburn, G., & Walter, R. J. (2022). How do single-family home owners value residential and commercial density? It depends. Land Use Policy, 113, 105898. doi: https://doi.org/10.1016/j.landusepol.2021.105898.
[2] Arum, S. P., & Fukuda, D. (2020). The impact of railway networks on residential land values within transit oriented development areas. Asian Transport Studies, 6, 100009. doi: https://doi.org/10.1016/j.eastsj.2020.100009.
[3] Choi, W. B. (2023). The impact of urban development on housing prices of nearby cities (Master’s thesis, Department of Civil & Environmental Engineering- The Graduate School- Seoul National University). Accessed 12 March 2025 from https://s-space.snu.ac.kr/bitstream/ 10371/193031/1/000000177034.pdf.
[4] Dell’Anna, F., Bravi, M., & Bottero, M. (2022). Urban green infrastructures: How much did they affect property prices in Singapore?. Urban Forestry & Urban Greening, 68, 127475. doi: https://doi.org/10.1016/j.ufug.2022.127475.
[5] Hu, L., He, S., Han, Z., Xiao, H., Su, S., Weng, M., & Cai, Z. (2019). Monitoring housing rental prices based on social media: An integrated approach of machine learning algorithms and hedonic modeling to inform equitable housing policies. Land Use Policy, 82, 657-673.
[6] Huang, H., &Li, J. (2021). The spatial variation of moderating effects of density and natural amenities on housing prices in Wuhan, China. Regional Science Policy & Practice, 13(6), 1778-1805. doi: https://doi.org/10.1111/rsp3.12455.
[7] Huang, Z., Chen, R., Xu, D., & Zhou, W. (2017). Spatial and hedonic analysis of housing prices in Shanghai. Habitat International, 67, 69-78. doi: https://doi.org/10.1016/j.habitatint.2017.06.002.
[8] Kang, Y., Zhang, F., Peng, W., Gao, S., Rao, J., Duarte, F., & Ratti, C. (2021). Understanding house price appreciation using multi-source big geo-data and machine learning. Land Use Policy, 111, 104919. doi: https://doi.org/10.1016/j.landusepol.2020.104919.
[9] Lancaster, K. J. (1966). A new approach to consumer theory. Journal of Political Economy, 74(2), 132-157. doi: https://doi.org/10.1086/259131.
[10] Li, H., Wei, Y. D., Wu, Y., & Tian, G. (2019). Analyzing housing prices in Shanghai with open data: Amenity, accessibility and urban structure. Cities, 91, 165-179. doi: https://doi.org/10.1016/j.cities.2018.11.016.
[11] Peng, Y., Tian, C., & Wen, H. (2021). How does school district adjustment affect housing prices: An empirical investigation from Hangzhou, China. China Economic Review, 69, 101683. doi: https://doi.org/10.1016/j.chieco.2021.101683.
[12] Rivas, R., Patil, D., Hristidis, V., Barr, J. R., & Srinivasan, N. (2019). The impact of colleges and hospitals to local real estate markets. Journal of Big Data, 6(1), 7. doi: https://doi.org/10.1186/s40537-019-0174-7.
[13] Rojas, A. (2024). Train stations’ impact on housing prices: Direct and indirect effects. Transportation Research Part A: Policy and Practice, 181, 103979. doi: https://doi.org/10.1016/j.tra.2024.103979.
[14] Rosen, S. (1974). Hedonic prices and implicit markets: Product differentiation in pure competition. Journal of Political Economy, 82(1), 34-55. doi: https://doi.org/10.1086/260169.
[15] Sadayuki, T. (2018). Measuring the spatial effect of multiple sites: An application to housing rent and public transportation in Tokyo, Japan. Regional Science and Urban Economics, 70, 155-173. doi: https://doi.org/10.1016/j.regsciurbeco.2018.03.002.
[16] Seo, J., & Kim, J. (2024). Exploring the moderating effect of private green space on the relationship between density and housing prices. Habitat International, 154, 103231. doi: https://doi.org/10.1016/j.habitatint.2024.103231.
[17] Wen, H., Zhang, Y., & Zhang, L. (2014). Do educational facilities affect housing price? An empirical study in Hangzhou, China. Habitat International, 42, 155-163. doi: https://doi.org/10.1016/j.habitatint.2013.12.004.
[18] Xiao, Y., Hui, E. C., & Wen, H. (2019). Effects of floor level and landscape proximity on housing price: A hedonic analysis in Hangzhou, China. Habitat International, 87, 11-26. doi: https://doi.org/10.1016/j.habitatint.2019.03.008.
[19] Yang, L., Chu, X., Gou, Z., Yang, H., Lu, Y., & Huang, W. (2020). Accessibility and proximity effects of bus rapid transit on housing prices: Heterogeneity across price quantiles and space. Journal of Transport Geography, 88, 102850. doi: https://doi.org/10.1016/j.jtrangeo.2020.102850.
[20] Yue, X., Wang,Y., & Zhang, H.O. (2022). Influences of the plot area and floor area ratio of residential quarters on the housing vacancy rate: A case study of the Guangzhou Metropolitan Area in China. Buildings, 12(8), 1197. doi: https://doi.org/10.3390/buildings12081197.
[21] Zhang, L., Zhou, J., & Hui, E. C. M. (2020). Which types of shopping malls affect housing prices? From the perspective of spatial accessibility. Habitat International, 96, 102118. doi: https://doi.org/10.1016/j.habitatint.2020.102118.
Recommended Citation
Manahampi, Stevanus J. and Yudhistira, M. Halley
(2026)
"Impacts of Spatial Intensity Policies on Jakarta Property Prices,"
Jurnal Ekonomi dan Pembangunan Indonesia: Vol. 26:
No.
1, Article 1.
DOI: 10.7454/jepi.v26i1.1748
pp.1-21
Available at:
https://scholarhub.ui.ac.id/jepi/vol26/iss1/1





