Analyzing the rent-to-price ratio for the housing market at the micro-spatial scale
Abstract
The rent-to-price ratio is one of the popular indicators for monitoring the property market. This study explores micro-scale spatial dynamics of the ratio for houses at the individual property level in Seoul, South Korea. We match the apartment unit sold and the one leased based on the carefully chosen criteria and apply a Bayesian multi-level modeling approach to this matched dataset. We employ the Integrated Nested Laplace Approximations (INLA) algorithm in order to estimate relevant parameters in the multi-level model. The ratio determinants found in the study include property age, apartment unit area, interest rate, and floor. This study also presents the importance of taking into account the hierarchical structure of apartment units, as well as seasonal and spatial variations when estimating the ratio and predicting future trends in the property market based on the ratio.
Keyword : rent-to-price ratio, Bayesian multi-level model, hierarchical structure, seasonal variation, spatial variation, apartment unit
How to Cite
Lee, C., & Park, K. (2018). Analyzing the rent-to-price ratio for the housing market at the micro-spatial scale. International Journal of Strategic Property Management, 22(3), 223-233. https://doi.org/10.3846/ijspm.2018.1416
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
André, C., Gil-Alana, L. A., & Gupta, R. (2014). Testing for persistence in housing price-to-income and price-to-rent ratios in 16 OECD countries. Applied Economics, 46(18), 2127-2138. https://doi.org/10.1080/00036846.2014.896988
Ayuso, J., & Restoy, F. (2006). House prices and rents: an equilibrium asset pricing approach. Journal of Empirical Finance, 13(3), 371-388. https://doi.org/10.1016/j.jempfin.2005.10.004
Baltagi, B. H., & Li, J. (2014). Further evidence on the spatio‐temporal model of house prices in the United States. Journal of Applied Econometrics, 29(3), 515-522. https://doi.org/10.1002/jae.2372
Banerjee, S., Carlin, B. P., & Gelfand, A. E. (2014). Hierarchical modeling and analysis for spatial data. CRC Press.
Beguin, J., Martino, S., Rue, H., & Cumming, S. G. (2012). Hierarchical analysis of spatially autocorrelated ecological data using integrated nested Laplace approximation. Methods in Ecology and Evolution, 3(5), 921-929. https://doi.org/10.1111/j.2041-210X.2012.00211.x
Blangiardo, M., & Cameletti, M. (2015). Spatial and spatio-temporal Bayesian models with R-INLA. John Wiley & Sons. https://doi.org/10.1002/9781118950203
Campbell, S. D., Davis, M. A., Gallin, J., & Martin, R. F. (2009). What moves housing markets: a variance decomposition of the rent–price ratio. Journal of Urban Economics, 66(2), 90-102. https://doi.org/10.1016/j.jue.2009.06.002
Chen, A. (1996). China’s urban housing reform: price-rent ratio and market equilibrium. Urban Studies, 33(7), 1077-1092. https://doi.org/10.1080/00420989650011519
Commons, W. (2012). Wikimedia commons. Retrieved from https://en.wikivoyage.org/wiki/Talk:Seoul
Davis, M. A., Lehnert, A., & Martin, R. F. (2008). The Rent‐price ratio for the aggregate stock of owner‐occupied housing. Review of Income and Wealth, 54(2), 279-284. https://doi.org/10.1111/j.1475-4991.2008.00274.x
Gallin, J. (2008). The long‐run relationship between house prices and rents. Real Estate Economics, 36(4), 635-658. https://doi.org/10.1111/j.1540-6229.2008.00225.x
Goldstein, H., Pan, H., & Bynner, J. (2004). A flexible procedure for analyzing longitudinal event histories using a multilevel model. Understanding Statistics, 3(2), 85-99. https://doi.org/10.1207/s15328031us0302_2
Hattapoglu, M., & Hoxha, I. (2014). The dependency of rent-to-price ratio on appreciation expectations: an empirical approach. Journal of Real Estate Finance and Economics, 49(2), 185-204. https://doi.org/10.1007/s11146-013-9423-2
Hatzvi, E., & Otto, G. (2008). Prices, rents and rational speculative bubbles in the Sydney housing market. Economic Record, 84(267), 405-420. https://doi.org/10.1111/j.1475-4932.2008.00484.x
Holly, S., Pesaran, M. H., & Yamagata, T. (2010). A spatio-temporal model of house prices in the USA. Journal of Econometrics, 158(1), 160-173. https://doi.org/10.1016/j.jeconom.2010.03.040
Ian, H. (2010). An introduction to geographical information systems. Pearson Education India.
Kang, S. W., Shin, Y. S., Lee, T. J., Kang, E. J., Kim, T. W., Choi, H. S., & Lim, Y. S. (2006). A study on social polarization in Korea. Korea Institute for Health and Social Affairs.
KB Kookmin Bank. (2017). Ratio of Jeonseito purchase price for apartment. Monthly Market Report (Sep. of 2017).
Kiel, K. A., & Zabel, J. E. (2008). Location, location, location: the 3L approach to house price determination. Journal of Housing Economics, 17(2), 175-190. https://doi.org/10.1016/j.jhe.2007.12.002
Kim, J., & Lim, G. (2014). Understanding the Irish price–rent ratio: an unobserved component approach. Applied Economics Letters, 21(12), 836-841. https://doi.org/10.1080/13504851.2014.892191
Kim, J. H., Choi, M. J., & Ko, J. (2009). Mismatch between home-ownership and residence in Korea. Housing Finance International, 24(1), 27-33.
Kishor, N. K., & Morley, J. (2015). What factors drive the price-rent ratio for the housing market? A modified present-value analysis. Journal of Economic Dynamics and Control, 58, 235-249. https://doi.org/10.1016/j.jedc.2015.06.006
Korean Statistical Information Service (KOSIS). (2016). S. Korea. Retrieved from www.kosis.kr
Laurini, M. P. (2017). A continuous spatio-temporal model for house prices in the USA. The Annals of Regional Science, 58(1), 235-269. https://doi.org/10.1007/s00168-016-0801-6
Lee, C. M., Chung, E. C., & Choi, S. E. (2009). An empirical analysis on Chonsei to monthly rent conversion rate in the apartment rental market. Housing Studies Review by the Korean Association for Housing Policy Studies, 17(2), 213-229.
Lindgren, F., Rue, H., & Lindström, J. (2011). An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 73(4), 423-498. https://doi.org/10.1111/j.1467-9868.2011.00777.x
Park, B. (2002). A theoretical review on Chonsei and monthly rent system. Journal of the Korea Real Estate Analysts Association, 8(2), 57-69.
Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4), 967-1012. https://doi.org/10.1111/j.1468-0262.2006.00692.x
Ronald, R., & Jin, M. (2015). Rental market restructuring in South Korea: The decline of the Chonsei Sector and its implications. Housing Studies, 30(3), 413-432. https://doi.org/10.1080/02673037.2014.970142
Rue, H., Martino, S., & Chopin, N. (2009). Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 71(2), 319-392. https://doi.org/10.1111/j.1467-9868.2008.00700.x
Seoul. (2016). Seoul Statistics. Department of housing policy.
Shiller, R. J. (2015). Irrational exuberance. Princeton University Press, Princeton, NJ. https://doi.org/10.1515/9781400865536
Shor, B., Bafumi, J., Keele, L., & Park, D. (2007). A Bayesian multilevel modeling approach to time-series cross-sectional data. Political Analysis, 15(2), 165-181. https://doi.org/10.1093/pan/mpm006
Sommer, K., Sullivan, P., & Verbrugge, R. (2013). The equilibrium effect of fundamentals on house prices and rents. Journal of Monetary Economics, 60(7), 854-870. https://doi.org/10.1016/j.jmoneco.2013.04.017
Stegmueller, D. (2013). How many countries for multilevel modeling? A comparison of frequentist and Bayesian approaches. American Journal of Political Science, 57(3), 748-761. https://doi.org/10.1111/ajps.12001
Ayuso, J., & Restoy, F. (2006). House prices and rents: an equilibrium asset pricing approach. Journal of Empirical Finance, 13(3), 371-388. https://doi.org/10.1016/j.jempfin.2005.10.004
Baltagi, B. H., & Li, J. (2014). Further evidence on the spatio‐temporal model of house prices in the United States. Journal of Applied Econometrics, 29(3), 515-522. https://doi.org/10.1002/jae.2372
Banerjee, S., Carlin, B. P., & Gelfand, A. E. (2014). Hierarchical modeling and analysis for spatial data. CRC Press.
Beguin, J., Martino, S., Rue, H., & Cumming, S. G. (2012). Hierarchical analysis of spatially autocorrelated ecological data using integrated nested Laplace approximation. Methods in Ecology and Evolution, 3(5), 921-929. https://doi.org/10.1111/j.2041-210X.2012.00211.x
Blangiardo, M., & Cameletti, M. (2015). Spatial and spatio-temporal Bayesian models with R-INLA. John Wiley & Sons. https://doi.org/10.1002/9781118950203
Campbell, S. D., Davis, M. A., Gallin, J., & Martin, R. F. (2009). What moves housing markets: a variance decomposition of the rent–price ratio. Journal of Urban Economics, 66(2), 90-102. https://doi.org/10.1016/j.jue.2009.06.002
Chen, A. (1996). China’s urban housing reform: price-rent ratio and market equilibrium. Urban Studies, 33(7), 1077-1092. https://doi.org/10.1080/00420989650011519
Commons, W. (2012). Wikimedia commons. Retrieved from https://en.wikivoyage.org/wiki/Talk:Seoul
Davis, M. A., Lehnert, A., & Martin, R. F. (2008). The Rent‐price ratio for the aggregate stock of owner‐occupied housing. Review of Income and Wealth, 54(2), 279-284. https://doi.org/10.1111/j.1475-4991.2008.00274.x
Gallin, J. (2008). The long‐run relationship between house prices and rents. Real Estate Economics, 36(4), 635-658. https://doi.org/10.1111/j.1540-6229.2008.00225.x
Goldstein, H., Pan, H., & Bynner, J. (2004). A flexible procedure for analyzing longitudinal event histories using a multilevel model. Understanding Statistics, 3(2), 85-99. https://doi.org/10.1207/s15328031us0302_2
Hattapoglu, M., & Hoxha, I. (2014). The dependency of rent-to-price ratio on appreciation expectations: an empirical approach. Journal of Real Estate Finance and Economics, 49(2), 185-204. https://doi.org/10.1007/s11146-013-9423-2
Hatzvi, E., & Otto, G. (2008). Prices, rents and rational speculative bubbles in the Sydney housing market. Economic Record, 84(267), 405-420. https://doi.org/10.1111/j.1475-4932.2008.00484.x
Holly, S., Pesaran, M. H., & Yamagata, T. (2010). A spatio-temporal model of house prices in the USA. Journal of Econometrics, 158(1), 160-173. https://doi.org/10.1016/j.jeconom.2010.03.040
Ian, H. (2010). An introduction to geographical information systems. Pearson Education India.
Kang, S. W., Shin, Y. S., Lee, T. J., Kang, E. J., Kim, T. W., Choi, H. S., & Lim, Y. S. (2006). A study on social polarization in Korea. Korea Institute for Health and Social Affairs.
KB Kookmin Bank. (2017). Ratio of Jeonseito purchase price for apartment. Monthly Market Report (Sep. of 2017).
Kiel, K. A., & Zabel, J. E. (2008). Location, location, location: the 3L approach to house price determination. Journal of Housing Economics, 17(2), 175-190. https://doi.org/10.1016/j.jhe.2007.12.002
Kim, J., & Lim, G. (2014). Understanding the Irish price–rent ratio: an unobserved component approach. Applied Economics Letters, 21(12), 836-841. https://doi.org/10.1080/13504851.2014.892191
Kim, J. H., Choi, M. J., & Ko, J. (2009). Mismatch between home-ownership and residence in Korea. Housing Finance International, 24(1), 27-33.
Kishor, N. K., & Morley, J. (2015). What factors drive the price-rent ratio for the housing market? A modified present-value analysis. Journal of Economic Dynamics and Control, 58, 235-249. https://doi.org/10.1016/j.jedc.2015.06.006
Korean Statistical Information Service (KOSIS). (2016). S. Korea. Retrieved from www.kosis.kr
Laurini, M. P. (2017). A continuous spatio-temporal model for house prices in the USA. The Annals of Regional Science, 58(1), 235-269. https://doi.org/10.1007/s00168-016-0801-6
Lee, C. M., Chung, E. C., & Choi, S. E. (2009). An empirical analysis on Chonsei to monthly rent conversion rate in the apartment rental market. Housing Studies Review by the Korean Association for Housing Policy Studies, 17(2), 213-229.
Lindgren, F., Rue, H., & Lindström, J. (2011). An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 73(4), 423-498. https://doi.org/10.1111/j.1467-9868.2011.00777.x
Park, B. (2002). A theoretical review on Chonsei and monthly rent system. Journal of the Korea Real Estate Analysts Association, 8(2), 57-69.
Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4), 967-1012. https://doi.org/10.1111/j.1468-0262.2006.00692.x
Ronald, R., & Jin, M. (2015). Rental market restructuring in South Korea: The decline of the Chonsei Sector and its implications. Housing Studies, 30(3), 413-432. https://doi.org/10.1080/02673037.2014.970142
Rue, H., Martino, S., & Chopin, N. (2009). Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 71(2), 319-392. https://doi.org/10.1111/j.1467-9868.2008.00700.x
Seoul. (2016). Seoul Statistics. Department of housing policy.
Shiller, R. J. (2015). Irrational exuberance. Princeton University Press, Princeton, NJ. https://doi.org/10.1515/9781400865536
Shor, B., Bafumi, J., Keele, L., & Park, D. (2007). A Bayesian multilevel modeling approach to time-series cross-sectional data. Political Analysis, 15(2), 165-181. https://doi.org/10.1093/pan/mpm006
Sommer, K., Sullivan, P., & Verbrugge, R. (2013). The equilibrium effect of fundamentals on house prices and rents. Journal of Monetary Economics, 60(7), 854-870. https://doi.org/10.1016/j.jmoneco.2013.04.017
Stegmueller, D. (2013). How many countries for multilevel modeling? A comparison of frequentist and Bayesian approaches. American Journal of Political Science, 57(3), 748-761. https://doi.org/10.1111/ajps.12001