Investigation on railway investment-induced neighborhood change and local spatial spillover effects in Nagoya, Japan


  • Lisha Wang Nagoya University
  • Meilan JIANG Institute of Innovation for Future Society, Nagoya University
  • Tomio MIWA Institute of Materials and Systems for Sustainability, Nagoya University
  • Takayuki MORIKAWA Institute of Innovation for Future Society, Nagoya University



Residential gentrification, Spatial autocorrelation, Railway investment, Difference-in-differences model


Previous studies have proven the significant causal relationship between railway investment and gentrification in some cities. However, most of them have focused on the gentry and less on the effect on other social classes. To observe how railway investment affects neighborhood change for different population types, this study investigated the investment effects of two urban railway lines separately on the neighborhood change of the gentry, older population, and students in Nagoya, Japan. These two railway lines consisting of a subway and an elevated railway opened in the same year and were located in different areas of the city. Moreover, the spatial autocorrelation in panel data was considered to investigate possible local spillover effects. Finally, we observed that the railway investments in highly urbanized areas were more likely to induce gentrification. In addition, railway investment has some significant treatment effects on students compared to the older population.


Abadie, A. (2005). Semiparametric difference-in-differences estimators. Review of Economic Studies, 72(1), 1–19.

Atkinson, R. (2000). Measuring gentrification and displacement in Greater London. Urban Studies, 37(1), 149–165.

Baltagi, B. H., Song, S. H., & Koh, W. (2003). Testing panel data regression models with spatial error correlation. Journal of Econometrics, 117(1), 123–150.

Bardaka, E., Delgado, M. S., & Florax, R. J. G. M. (2018). Causal identification of transit-induced gentrification and spatial spillover effects: The case of the Denver light rail. Journal of Transport Geography, 71(July), 15–31.

Barsby, S. L., & Cox, D. R. (1975). Interstate migration of the elderly: An economic analysis. Washington, DC: Lexington books.

Bluestone, B., Huff Stevenson, M., & Williams, R. (2008). The urban experience: Economics, society, and public policy. Oxford, UK: Oxford Univeristy Press.

Cervero, R. (2010). Effects of light and commuter rail transit on land prices: Experiences in San Diego County. Journal of the Transportation Research Forum, 43(1), 120–138.

Chapple, K., Austin, M., Coleman, R., Martin, A., Meigs, N., Munekiyo, T., … Wampler, E. (2009). Mapping susceptibility to gentrification: The early warning toolkit. Retrieved from

Chi, G., & Voss, P. R. (2005). Migration decision-making: A hierarchical regression approach. Journal of Regional Analysis and Policy, 35(2), 11–22.

Delgado, M. S., & Florax, R. J. G. M. (2015). Difference-in-differences techniques for spatial data: Local autocorrelation and spatial interaction. Economics Letters, 137, 123–126.

Dubé, J., Legros, D., Thériault, M., & Des Rosiers, F. (2014). A spatial difference-in-differences estimator to evaluate the effect of change in public mass transit systems on house prices. Transportation Research Part B: Methodological, 64(6), 24–40.

Florida, R. (2010). Who’s your city? How the creative economy is making where to live the most important decision of your life. Toronto: Vintage Canada.

Grossmann, K., & Haase, A. (2016). Neighborhood change beyond clear storylines: What can assemblage and complexity theories contribute to understandings of seemingly paradoxical neighborhood development? Urban Geography, 37(5), 727–747.

Grube-Cavers, A., & Patterson, Z. (2015). Urban rapid rail transit and gentrification in Canadian urban centres: A survival analysis approach. Urban Studies, 52(1), 178–194.

Hammel, D. J., & Wyly, E. K. (1996). A model for identifying gentrified areas with census data. Urban Geography, 17(3), 248–268.

Helms, A. C. (2003). Understanding gentrification: An empirical analysis of the determinants of urban housing renovation. Journal of Urban Economics, 54(3), 474–498.

Kahn, M. E. (2007). Gentrification trends in new transit-oriented communities: Evidence from 14 cities that expanded and built rail transit systems. Real Estate Economics, 35(2), 155–182.

Kapoor, M., Kelejian, H. H., & Prucha, I. R. (2007). Panel data models with spatially correlated error components. Journal of Econometrics, 140(1), 97–130.

Kilpatrick, J. A., Throupe, R. L., Carruthers, J. I., & Krause, A. (2007). The impact of transit corridors on residential property values. Journal of Real Estate Research, 29(3), 303–320.

Lin, J. (2002). Gentrification and transit in Northwest Chicago. Transportation Quarterly, 56, 175–191.

Newman, P., & Kenworthy, J. (1999). Sustainability and cities: overcoming automobile dependence. Washington, DC; Island press.

Park, J., & Kim, K. (2016). The residential location choice of the elderly in Korea: A multilevel logit model. Journal of Rural Studies, 44, 261–271.

Plane, D., & Jurjevich, J. (2009). Ties that no longer bind? The patterns and repercussions of age-articulated migration. Professional Geographer, 61(1), 4–20.

Slater, T. (2011). Gentrification of the city. The new Blackwell companion to the city. Hoboken, NJ: Wiley Blackwell.

Wang, L., Jiang, M., Miwa, T., Bardaka, E., & Morikawa, T. (2020). Preliminary study on transit-induced residential gentrification in Nagoya, Japan. Asian Transport Studies, 6(July), 100022.

Zuk, M., Bierbaum, A. H., Chapple, K., Gorska, K., & Loukaitou-Sideris, A. (2018). Gentrification, displacement, and the role of public investment. Journal of Planning Literature, 33(1), 31–44.




How to Cite

Wang, L., JIANG, M., MIWA, T., & MORIKAWA, T. . (2021). Investigation on railway investment-induced neighborhood change and local spatial spillover effects in Nagoya, Japan. Journal of Transport and Land Use, 14(1), 715-735.