Built environment and travel behavior: Validation and application of a continuous-treatment propensity score stratification method
Keywords:Travel behavior, Built Environment, Residential Self-selection, Land use
AbstractThis article discusses the validation and implementation of a propensity score approach with continuous treatment to test the existence of a causal relationship between the built environment and travel behavior using cross-sectional data. The implemented methodology differs from previous applications in the planning literature in that it relaxes the binary treatment assumption, which polarizes the built environment into two extremes (e.g., urban vs suburban). The effectiveness of the proposed methodology in reducing bias was validated via Monte Carlo simulation. The proposed approach was shown to reduce self-selection bias against Ordinary Least Squares (OLS) regression in all but extreme levels of non-linearity. Empirical results suggest that an increase in urbanization has a negative effect on home-based maintenance car trip frequencies, and conversely, a positive effect on home-based maintenance non-motorized trip frequencies. Result estimates suggest the existence of a causal mode substitution mechanism between car and non-motorized modes given increases in the urbanization level at residential locations, thus providing some empirical support to the arguments put forth by compact city advocates.
Alonso, W. (1964). Location and land use: Towards a general theory of land rent. Cambridge, MA: Harvard University Press.
Axhausen, K. (2008). Social networks, mobility biographies, and travel: Survey challenges. Environment and Planning B: Planning and Design, 35(6), 1–17.
Birch, C. P., Oom, S. P., & Beecham, J. A. (2007). Rectangular and hexagonal grids used for observation, experiment and simulation in ecology. Ecological Modelling, 206, 347–359.
Boarnet, M., & Sarmiento, S. (1998). Can land-use policy really affect travel behavior? A study of the link between non-work travel and land-use characteristics. Urban Studies, 35(7), 1155–1169.
Boer, R., Zheng, Y., Overton, A., Ridgeway, G. K., & Cohen, D. A. (2007). Neighborhood design and walking trips in ten U.S. metropolitan areas. American Journal of Preventive Medicine, 32(4), 298–304.
Bohte, W., Maat, K., & van Wee, B. (2009). Measuring attitudes in research on residential self-selection and travel behavior: A review of theories and empirical research. Transport Reviews: A Transnational Transdisciplinary Journal, 29(3), 325–357.
Brown, T. (2006). Confirmatory factor analysis for applied research. New York: The Guilford Press.
Cao, X. (2010). Exploring causal effects of neighborhood type on walking behavior using stratification of propensity score. Environment and Planning A, 42, 487–504.
Cao, X., Handy, S., & Mokhtarian, P. (2006). The influences of the built environment and residential self-selection on pedestrian behavior: Evidence from Austin TX. Transportation, 33, 1–20.
Cao, X., Mokhtarian, P., & Handy, S. (2009a). Examining the impacts of residential self-selection on travel behavior: A focus on empirical findings. Transport Reviews, 29(3), 359–395.
Cao, X., Mokhtarian, P., & Handy, S. (2009b). The relationship between the built environment and nonwork travel: A case study of Northern Carolina. Transportation Research Part A, 43, 548–559.
Cao, X., Mokhtarian, P. L., & Handy, S. L. (2007). Do changes in neighborhood lead to changes in travel behavior? A structural equations modeling approach. Transportation, 34, 535–556.
Cao, X., Yu, Z., & Fan, Y. (2010). Exploring the connections among residential location, self-selection, and driving: Propensity score matching with multiple treatments. Transportation Research Part A, 44, 797–805.
Chatman, D. G. (2009). Residential choice, the built environment, and nonwork travel: Evidence using new data and methods. Environment and Planning A, 41, 1072–1089.
Couper, M. P. (2000). Web surveys: A review of issues and approaches. The Public Opinion Quarterly, 64(4), 464–494.
Dark, S. J., & Bram, D. (2007). The modifiable areal unit problem (MAUP) in physical geography. Progress in Physical Geography, 31(5), 471–479.
Fotheringham, A. S., & Wong, D. W. S. (1991). The modifiable areal unit problem in multivariate statistical analysis. Environment and Planning A, 23(7), 1025–1044.
Fujita, M. (1989). Urban economic theory: Land use and city size. Cambridge, England: Cambridge University Press.
Fukuoka City Transport Bureau (2014). 福岡市交通局・時刻表 [Fukuoka City Transport Bureau: Timetable]. Retrieved from: http://subway.city.fukuoka.lg.jp/schedule/
Guo, J., & Bhat, C. (2007). Operationalizing the concept of neighborhood: Application to residential location choice analysis. Journal of Transport Geography, 15, 31–45.
Handy, S., Cao, X., & Mokhtarian, P. (2005). Correlation or causality between the built environment and travel behavior? Evidence from Northern Carolina. Transportation Research Part D, 10, 427–444.
Handy, S., Cao, X., & Mokhtarian, P. (2006). Self-selection in the relationship between the built environment and walking. Journal of the American Planning Association, 72(1), 55–74.
Handy, S. L., & Clifton, K. J. (2001). Evaluating neighborhood accessibility: Possibilities and practicalities. Journal of Transportation Statistics, 4(2-3), 67–78.
Handy, S. L., & Niemeier, D. A. (1997). Measuring accessibility: An exploration of issues and alternatives. Environment and Planning A, 29(7), 1175–1194.
Heckman, J., Ichimura, H., Smith, J., & Todd, P. (1998). Characterizing selection bias using experimental data. Cambridge, MA: National Bureau of Economic Research.
Heene, M., Hilbert, S., Draxler, C., Ziegler, M., & Bühner, M. (2011). Masking misfit in confirmatory factor analysis by increasing unique variances: A cautionary note on the usefulness of cutoff values of fit indices. Psychological Methods, 16(3), 349–336.
Horvitz, D., & Thompson, D. (1952). A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association, 47, 663–685.
Hu, L., & Bentler, P. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55.
Imai, K., & van Dyk, D. A. (2004). Causal inference with general treatment regimes: Generalizing the propensity score. Journal of the American Statistical Association, 99(467), 854–866.
Imbens, G. M., & Wooldridge, J. M. (2008). Recent developments in the econometrics of program evaluation, Cambridge, MA: National Bureau of Economic Research.
Jelisnki , D. E., & Wu, J. (1996). The modifiable areal unit problem and implications for landscape ecology. Landscape Ecology, 11(3), 129–140.
JR Kyushu. (2014). JR九州駅時刻表 [JR Kyushu station timetables]. Retrieved from http://www.jrkyushu-timetable.jp/jr-k_time/map_fukuoka.html
JR West. (2014). 鉄道のご案内 JRおでかけネット [Train information JR Odekake Net]. [Online] Retrieved from https://www.jr-odekake.net/railroad/#eki
Khattak, A. J., & Rodriguez, D. (2005). Travel behavior in neo-traditional neighborhood developments: A case study in USA. Transportation Research Part A, 39, 481–500.
Kitamura, R., Mokhtarian, P., & Laidet, L. (1997). A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area. Transportation, 24, 125–158.
Krizek, K. J. (2003). Operationalizing neighborhood accessibility for land use travel behavior research. Journal of Planning Education and Research, 22, 270–287.
Marsh, H. W., Hau, K.-T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler's (1999) findings. Structural Equation Modeling: A Multidisciplinary Journal, 11(3), 320–341.
Mills, E. S. (1967). An aggregative model of resource allocation in a metropolitan area. The American Economic Review, 57(2), 197–210.
MLIT. (2011a). 国土数値情報バスルートデータ [National land numerical information: Bus route data]. Ministry of Land, Infrastructure, Transport and Tourism. Retrived from http://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-N07.html
MLIT. (2011b). 国土数値情報バス停留所データ [National land numerical information: Bus stop data]. Ministry of Land, Infrastructure, Transport and Tourism. Retrieved from http://nlftp.mlit.go.jp/ksj/jpgis/datalist/KsjTmplt-P11.html
MLIT. (2013a). 国土数値情報 地価公示調査 [National land numerical information: Published land price survey]. Ministry of Land, Infrastructure, Transport and Tourism. Retrieved from http://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-L01-v2_3.html
MLIT. (2013b). 国土数値情報 都道府県地価調査 [National land numerical information: National survey on land]. Ministry of Land, Infrastructure, Transport and Tourism. Retrieved from http://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-L02-v2_3.html
Mokhtarian, P., & Cao, X. (2008). Examining the impacts of residential self-selection on travel behavior: A focus on methodologies. Transportation Research B, 42(3), 204–228.
Muthen, L., & Muthen, B. (2010). Mplus user’s guide. 7th ed. Los Angeles: Muthen & Muthen.
Naess, P. (2009). Residential self-selection and appropriate control variables in land use: Travel studies. Transportation Reviews: A Transnational Transdisciplinary Journal, 3, 293–324.
Naess, P. (2014). Tempest in a teapot: The exaggerated problem of transport-related residential self-selection as a source of error in empirical studies. Journal of Transport and Land Use, 7(3), 57–79.
National Tax Agency. (2012). Heisei 23 nenbun Minkan kyuuyo jittai chousa [Private income statistical survey for 2011]. Tokyo, Japan. Retrieved from http://www.nta.go.jp/kohyo/tokei/kokuzeicho/minkan2011/minkan.htm
Nishi-Nippon Railroad Co., Ltd. (2014). にしてつ時刻表 [Nishitetsu Timetable]. Retrieved from http://jik.nishitetsu.jp/
PASCO. (2005). 国勢調査地図データ 統計地図 [National census statistical and map data]. PASCO Corporation.
Putman, S. H., & Chung, S. (1989). Effect of spatial system design on spatial interaction models: The spatial definition problem. Environment and Planning A, 21, 27–46.
Rosenbaum, P., & Rubin, D. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.
Rosenbaum, P., & Rubin, D. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79(387), 516–524.
Rubin, D. B., & Thomas, N. (2000). Combining propensity score matching with additional adjustments for prognostic covariates. Journal of the American Statistical Association, 95(450), 573–585.
Saris, W. E., Satorra, A., & Van der Veld, W. M. (2009). Testing structural equation models or detection of misspecifications? Structural Equation Modeling: A Multidisciplinary Journal, 16(4), 561–582.
Scheiner, J., & Holz-Rau, C. (2013). Changes in travel mode use after residential relocation: A contribution to mobility biographies. Transportation, 40, 431–458.
Scheiner, J. (2014). Residential self-selection in travel behavior: Toward an integration into mobility biographies. Journal of Transport and Land Use, 7(3), 15–28.
Silverman, B. W. (1986). Density estimation for statistics and data analysis. New York: Chapman and Hall.
Troncoso Parady, G., Chikaraishi, M., Takami, K., Ohmori, N., & Harata, N. (2015). On the effect of the built environment and preferences on non-work travel: Evidence from Japan. European Journal of Transportation and Infrastructure Research, 15(1), 55–65.
Troncoso Parady, G., Takami, K., & Harata N. (2014a). Connection between built environment and travel behavior: Propensity score approach under a continuous treatment regime. Transportation Research Record, 2453(1), 137–144.
Troncoso Parady, G., Chikaraishi, M., Takami, K., & Harata, N. (2014b). A panel approach to understanding the effect of the built environment on travel behavior: A case study of the Kashiwanoha Area, Chiba, Japan. Urban and Regional Planning Review, 1, 18–38.
Vance, C., & Hedel, R. (2007). The impact of urban form on automobile travel: Disentangling causation from correlation. Transportation, 34, 575–588.
Verplanken, B., Aarts, H., van Knippenberg, A., & van Knippenberg, C. (1994). Attitude versus general habit: Antecedents of travel mode choice. Journal of Applied Social Psychology, 24(11), 285–300.
ZENRIN Co., Ltd. (2011). テレデータPack! [Telepoint Pack DB]. ZENRIN Co., Ltd: s.n. http://www.zenrin.co.jp/product/gis/teldata/teldt.html
Zhang, M., & Kukadia, N. (2005). Metrics of urban form and the modifiable areal unit problem. Transportation Research Record, 1902, 71–79.
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