1 / 14

Valuing Rail Access Using Transport Innovations

Valuing Rail Access Using Transport Innovations. Table 1: Summary statistics and difference in difference estimates: London Metropolitan sample, 30 KM radius from Holborn. Table 3: Rail Service innovations and property: postcode unite aggregated date, 30KM radius from Holborn.

zeki
Download Presentation

Valuing Rail Access Using Transport Innovations

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Valuing Rail Access Using Transport Innovations

  2. Table 1: Summary statistics and difference in difference estimates: London Metropolitan sample, 30 KM radius from Holborn

  3. Table 3: Rail Service innovations and property: postcode unite aggregated date,30KM radius from Holborn Note: Dependent variable is log property price. Data is aggregated to postcode unit level for tow period: pre-2000, 2000 and after. regressions include controls variables detailed in Appendix A Table, panel (a). Coefficients are x100. t-statistics in parentheses Table 4: Rail Service innovations and property: postcode unite aggregated date, 20KM radius from Bromley

  4. Table 5: Rail access and property price: cross section estimates on full london sample, with service-level differences-years 2000 and 2001 only. Note: Dependent variable is log property price. Regressions include controls variables detailed in Appendix A Table, panels (a), plus distance to central business district and distance-to-CBD-time interactions. Coefficients are x100, t-statistics in parentheses, clustered on postcode unit.

  5. Conclusion 1. Consumers do strongly value better transport access as shown by house price rose by 9.3 percentage points more in places affected by transport infrastructure changes, relative to places that were unaffected. 2. Assumed single worker-commuter Households. 3. Excludes benefits to those who live further and intend to drive/bus to stations.

  6. Back

  7. Back

  8. Back

More Related