Share:


The effects of transaction hotspots and flipping hotspots on housing prices

    Bor-Ming Hsieh Affiliation
    ; Chih-Yuan Yang Affiliation

Abstract

In contrast to much of the literature that focuses on the issue of spatial dependence in housing price research, this study addresses the spatial aggregation of housing transactions and analyzes the effects of transaction hotspots and short-term flipping hotspots on housing prices by using real housing transaction data in Taipei City, Taiwan. The empirical results show that after controlling for the effects of spatial dependence and individual housing attributes, the impact of transaction hotspot areas on housing prices is significantly negative, while the impact of flipping hotspot areas on housing prices is significantly positive. The results verify that the key to driving up housing prices lies in flipping activities. Furthermore, the results of the spatial quantile regression model show that low-priced residential properties are more sensitive to the spatial concentration of housing transactions and flipping transactions in the housing market. Our results have implications for the government’s policy intending to control hot trade volumes to cool skyrocketing housing prices in a booming housing market. It is suggested that the government should pay attention to restraining short-term flipping activities in the housing market rather than setting constrains on housing transactions.

Keyword : housing prices, flipping, spatial aggregation, housing volume, hotspot analysis

How to Cite
Hsieh, B.-M., & Yang, C.-Y. (2024). The effects of transaction hotspots and flipping hotspots on housing prices. International Journal of Strategic Property Management, 28(1), 1–15. https://doi.org/10.3846/ijspm.2024.20899
Published in Issue
Feb 26, 2024
Abstract Views
357
PDF Downloads
328
Creative Commons License

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

References

Anacker, K. B., & Schintler, L. A. (2015). Flip that house: Visualising and analysing potential real estate property flipping transactions in a cold local housing market in the United States. International Journal of Housing Policy, 15(3), 285–303. https://doi.org/10.1080/14616718.2015.1051401

Anselin, L. (1988). Spatial econometrics: Methods and models. Kluwer Academic. https://doi.org/10.1007/978-94-015-7799-1

Anselin, L. (1992). Spatial data analysis with GIS: An introduction to application in the social sciences. National Center for Geographic Information and Analysis.

Anselin, L., & Bera, A. K. (1998). Spatial dependence of linear regression models with an introduction to spatial econometrics. In A. Ullah & D. E. A. Giles (Eds.), Handbook of applied economic statistics (pp. 237–289). Marcel Dekker.

Basu, S., & Thibodeau, T. (1998). Analysis of spatial autocorrelation in house prices. Journal of Real Estate Finance and Economics, 17(1), 61–85. https://doi.org/10.1023/A:1007703229507

Bayer, P., Geissler, C., Mangum, K., & Roberts, J. W. (2020). Speculators and middlemen: The strategy and performance of investors in the housing market. The Review of Financial Studies, 33(11), 5212–5247. https://doi.org/10.1093/rfs/hhaa042

Bilal, A., & Rossi-Hansberg, E. (2021). Location as an asset. Econometrica, 89(5), 2459–2495. https://doi.org/10.3982/ECTA16699

Bø, E. E. (2018). Housing match quality and demand: What can we learn from comparing buyer characteristics? Journal of Housing Economics, 41, 184–199. https://doi.org/10.1016/j.jhe.2018.06.007

Bourassa, S., Cantoni, E., & Hoesli, M. (2007). Spatial dependence, housing submarkets, and house price prediction. Journal of Real Estate Finance and Economics, 35, 143–160. https://doi.org/10.1007/s11146-007-9036-8

Bourassa, S., Cantoni, E., & Hoesli, M. (2010). Predicting house prices with spatial dependence: A comparison of alternative methods. Journal of Real Estate Research, 32(2), 139–159. https://doi.org/10.1080/10835547.2010.12091276

Carrillo, P., & Pope, J. (2012). Are homes hot or cold potatoes? The distribution of marketing time in the housing market. Regional Science and Urban Economics, 42(1–2), 189–197. https://doi.org/10.1016/j.regsciurbeco.2011.08.010

Case, B., Clapp, J., Dubin, R., & Rodriguez, M. (2004). Modeling spatial and temporal housing price patterns: A comparison of four models. Journal of Real Estate Finance and Economics, 29(2), 167–191. https://doi.org/10.1023/B:REAL.0000035309.60607.53

Chakravorty, S. (1995). Identifying crime clusters: The spatial principles. Middle States Geographer, 28, 53–58.

Chang, C. O., & Chen, S. M. (2018). Dilemma of housing demand in Taiwan. International Real Estate Review, 21(3), 397–418. https://doi.org/10.53383/100267

Chang, C. O., & Hsieh, B. M. (2018). Changes in housing policy, housing wellbeing and housing justice in Taiwan. In R. L. H. Chu & S.-K. Ha (Eds.), Housing policy, wellbeing and social development in Asia (pp. 88–105). Routledge. https://doi.org/10.1201/9781315460055-6

Chen, M. C., Chang, C. O., Yang, C. Y., & Hsieh, B. M. (2012). Investment demand and housing prices in an emerging economy. Journal of Real Estate Research, 34(3), 345–373. https://doi.org/10.1080/10835547.2012.12091339

Deng, K., Chen, J., Lin, Z., & Yang, X. (2022). Differential selling strategies between investors and consumers: Evidence from the Chinese housing market. Journal of Real Estate Research, 44(1), 80–105. https://doi.org/10.1080/08965803.2021.2008609

Depken, C. A., Hollans, H., & Swidler, S. (2009). An empirical analysis of residential property flipping. Journal of Real Estate Finance and Economics, 39(3), 248–263. https://doi.org/10.1007/s11146-009-9181-3

Depken, C. A., Hollans, H., & Swidler, S. (2011). Flips, flops and foreclosures: Anatomy of a real estate bubble. Journal of Financial Economic Policy, 3(1), 49–65. https://doi.org/10.1108/17576381111116759

Dubin, R., Pace, R., & Thibodeau, T. (1999). Spatial autoregression techniques for real estate data. Journal of Real Estate Literature, 7, 79–95. https://doi.org/10.1080/10835547.1999.12090079

Fan, Y., Leung, C. K. Y., & Yang, Z. (2022). Financial conditions, local competition, and local market leaders: The case of real estate developers. Pacific Economic Review, 27(2), 131–193. https://doi.org/10.1111/1468-0106.12360

Gu, Y., & You, X. (2022). A spatial quantile regression model for driving mechanism of urban heat island by considering the spatial dependence and heterogeneity: An example of Beijing, China. Sustainable Cities and Society, 79, Article 103692. https://doi.org/10.1016/j.scs.2022.103692

Hua, C. C., Chang, C. O., & Hsieh, C. H. (2001). The price-volume relationships between the existing and the presales housing market in Taiwan. International Real Estate Review, 4(1), 80–94. https://doi.org/10.53383/100030

Huang, D. J., Leung, C. K. Y., & Tse, C. Y. (2018). What accounts for the differences in rent-price ratio and turnover rate? A search-and-matching approach. The Journal of Real Estate Finance and Economics, 57(3), 431–475. https://doi.org/10.1007/s11146-017-9647-7

Jud, G. D., Seaks, T. G., & Winkler, D. T. (1996). Time on the market: The impact of residential brokerage. Journal of Real Estate Research, 12(3), 447–458. https://doi.org/10.1080/10835547.1996.12090852

Kalra, R., & Chan, K. (1994). Censored sample bias, macroeconomic factors, and time on market of residential housing. Journal of Real Estate Research, 9(2), 253–262. https://doi.org/10.1080/10835547.1994.12090750

Kluger, B. D., & Miller, N. (1990). Measuring residential real estate liquidity. Real Estate Economics, 18(2), 145–159. https://doi.org/10.1111/1540-6229.00514

Krainer, J. (2001). A theory of liquidity in residential real estate markets. Journal of Urban Economics, 49(1), 32–53. https://doi.org/10.1006/juec.2000.2180

Kulldorff, M., & Nagarwalla, N. (1995). Spatial disease clusters: Detection and inference. Statistics in Medicine, 14, 799–810. https://doi.org/10.1002/sim.4780140809

Kulldorff, M., Heffernan, R., Hartman, J., Assunção, R., & Mostashari, F. (2005). A space-time premutation scan statistics for disease outbreak detection. PLoS Medicine, 2(3), Article e59. https://doi.org/10.1371/journal.pmed.0020059

LaCour-Little, M., & Yang, J. (2023). Seeking alpha in the housing market. Journal of Real Estate Finance and Economics, 67, 319–374. https://doi.org/10.1007/s11146-021-09853-1

Lee, M. T., Lee, M. L., & Lin, S. H. (2014). Trend properties, cointegration, and diffusion of presale house prices in Taiwan: Can Taipei’s house prices ripple out? Habitat International, 44, 432–441. https://doi.org/10.1016/j.habitatint.2014.09.003

Leung, C. K. Y., & Ng, C. Y. J. (2019). Macroeconomic aspects of housing. In The Oxford research encyclopedia of economics and finance. Oxford University Press. https://doi.org/10.1093/acrefore/9780190625979.013.294

Leung, C. K. Y., & Tse, C. Y. (2017). Flipping in the housing market. Journal of Economic Dynamics and Control, 76, 232–263. https://doi.org/10.1016/j.jedc.2017.01.003

Leung, C. K. Y., Ma, W. Y., & Zhang, J. (2014). The market valuation of interior design and developer strategies: A simple theory and some evidence. International Real Estate Review, 17(1), 63–107. https://doi.org/10.53383/100180

Li, L., Yavas, A., & Zhu, B. (2023). Externalities of residential property flipping. Real Estate Economics, 51, 233–271. https://doi.org/10.1111/1540-6229.12413

Liao, W. C., & Wang, X. (2012). Hedonic house prices and spatial quantile regression. Journal of Housing Economics, 21(1), 16–27. https://doi.org/10.1016/j.jhe.2011.11.001

Musil, R., Brand, F., Huemer, H., & Wonaschütz, M. (2022). The Zinshaus market and gentrification dynamics: The transformation of the historic housing stock in Vienna, 2007–2019. Urban Studies, 59(5), 974–994. https://doi.org/10.1177/00420980211051906

Ngai, L. R., & Tenreyro, S. (2014). Hot and cold seasons in the housing market. American Economic Review, 104(12), 3991–4026. https://doi.org/10.1257/aer.104.12.3991

Rothenberg, J., Galster, G, Butler, V., & Pitkin, J. (1991). The maze of urban housing markets: Theory, evidence, and policy. The University of Chicago Press.

Schilling, G. (1996). Working capital’s role in maintaining corporate liquidity. TMA Journal, 16(5), 4–7.

Teng, H. J., Chang, C. O., & Chen, M. C. (2016). Housing bubble contagion from city centre to suburbs. Urban Studies, 54(6), 1463–1481. https://doi.org/10.1177/0042098016631297

Wang, X., & Varady, D. (2005). Using hot-spot analysis to study the clustering of Section 8 housing voucher families. Housing Studies, 20(1), 29–48. https://doi.org/10.1080/0267303042000308714

Wen, H., Xiao, Y., & Hui, E. C. (2019). Quantile effect of educational facilities on housing price: Do homebuyers of higher-priced housing pay more for educational resources? Cities, 90, 100–112. https://doi.org/10.1016/j.cities.2019.01.019

Wong, S., Deng, K., & Chau, K. (2022). Do short-term real estate investors outperform the market? Journal of Real Estate Research, 44(2), 287–309. https://doi.org/10.1080/08965803.2021.2008608

Xu, W., Chen, H., Frias-Martinez, E., Cebrian, M., & Li, X. (2019). The inverted u-shaped effect of urban hotspots spatial compactness on urban economic growth. Royal Society Open Science, 6(11), Article 181640. https://doi.org/10.1098/rsos.181640

Yang, S., & Yavas, A. (1995). Bigger is not better: Brokerage and time on the market. Journal of Real Estate Research, 10(1), 23–33. https://doi.org/10.1080/10835547.1995.12090770

Yilmaz, S. (2014). Flippers in the housing market: An application of trade networks. The Journal of Real Estate Portfolio Management, 20(2), 163–174.

Yiu, C. Y., Wong, S. K., & Chau, K. W. (2009). Transaction volume and price dispersion in the presale and spot real estate markets. Journal of Real Estate Finance and Economics, 38(3), 241–253. https://doi.org/10.1007/s11146-008-9161-z

Zietz, J., Zietz, E. N., & Sirmans, G. S. (2008). Determinants of house prices: A quantile regression approach. The Journal of Real Estate Finance and Economics, 37(4), 317–333. https://doi.org/10.1007/s11146-007-9053-7