Estimating the Gains from New Rail Transit Investment: A Machine Learning Tree Approach

49 Pages Posted: 17 Apr 2017

See all articles by Seungwoo Chin

Seungwoo Chin

Ministry of Economy and Finance, Sejong Government Complex

Matthew E. Kahn

University of Southern California; National Bureau of Economic Research (NBER)

Hyungsik Roger Moon

University of Southern California - Department of Economics; USC Dornsife Institute for New Economic Thinking

Date Written: April 2017

Abstract

Urban rail transit investments are expensive and irreversible. Since people differ with respect to their demand for trips, their value of time, and the types of real estate they live in, such projects are likely to offer heterogeneous benefits to residents of a city. Using the opening of a major new subway in Seoul, we contrast hedonic estimates based on multivariate hedonic methods with a machine learning approach that allows us to estimate these heterogeneous effects. While a majority of the "treated" apartment types appreciate in value, other types decline in value. We explore potential mechanisms. We also cross-validate our estimates by studying what types of new housing units developers build in the treated areas close to the new train lines.

Suggested Citation

Chin, Seungwoo and Kahn, Matthew E. and Moon, Hyungsik Roger, Estimating the Gains from New Rail Transit Investment: A Machine Learning Tree Approach (April 2017). NBER Working Paper No. w23326. Available at SSRN: https://ssrn.com/abstract=2953813

Seungwoo Chin (Contact Author)

Ministry of Economy and Finance, Sejong Government Complex ( email )

Korea, Republic of (South Korea)

Matthew E. Kahn

University of Southern California ( email )

2250 Alcazar Street
Los Angeles, CA 90089
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Hyungsik Roger Moon

University of Southern California - Department of Economics ( email )

KAP 300
Los Angeles, CA 90089-0253
United States
213-740-2108 (Phone)
213-740-8543 (Fax)

USC Dornsife Institute for New Economic Thinking ( email )

3620 S. Vermont Avenue, KAP 364F
Los Angeles, CA 90089-0253
United States

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