A spatial difference-in-differences approach to evaluate the impact of light rail transit on property values
Feng Qiu () and
Economic Modelling, 2021, vol. 99, issue C
How to evaluate the comprehensive costs and benefits of urban light trains is a critical issue. The difference-in-differences technique is widely used in the literature. However, the conventional approach assumes the project does not affect the control group, which might be violated in real life due to social and economic interactions. We refine the DID approach and relax the no-spillover assumption. Through an example of impacts of a new light rail transit on house prices in Edmonton, Canada, we illustrate how the approach can be used to calculate three different treatment effects. The results indicate that the train system has negative impacts on values of single-detached houses nearby the train stations, and the negative effects also spill over to properties outside the treatment zone. Our findings show that the direction and magnitude of project impacts depend on the city size, the design of the train system, and relevant neighborhood characteristics.
Keywords: Difference-in-differences (DID); Spatial econometrics; Light rail transit (LRT); Stable-unit-treatment-value assumption (SUTVA); Spillover effects; Spatial hedonic (search for similar items in EconPapers)
JEL-codes: C21 R21 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:99:y:2021:i:c:s0264999321000857
Access Statistics for this article
Economic Modelling is currently edited by S. Hall and P. Pauly
More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().