輕軌系統在近年來重新受到重視，而輕軌系統對於既有公車營運影響程度為本研究嘗試探討之課題。本研究以新北市淡海新市鎮之淡海輕軌為例，利用計量經濟中的雙重差分法（Difference-in-differences, DID），評估輕軌通車對於公車運量變化之效果。利用公車票證資料，於淡海輕軌通車前後，整理相關公車路線運量資料，並透過公車路線停靠站周邊一定距離內是否有輕軌站，將公車路線分別歸類為處理組及對照組。
模型的分析部分，先採用典型DID模型，並在典型DID的交互作用項分別納入2種強度變數，強度變數分別是公車站點涵蓋之輕軌站點數加權與公車站點涵蓋之輕軌站總運量。結果顯示，在90%的信心水準下，行經紅樹林捷運站的處理組公車路線，於輕軌開通後，上午尖峰時間平均每班次運量下降了14.192人；行經淡水捷運站的公車路線，平均每班次運量則下降了9.579人。若使用公車站點特定距離內之輕軌站點數為強度變數，每多涵蓋一個輕軌站，每班次將降低2.698的乘客量；若使用公車站點特定距離內之輕軌站上下客運量為強度變數，若行經的輕軌站運量多1%，公車每班次平均運量下降1.968人。
另外，為了檢驗運量受影響公車路線，對不同票種的影響是否有差異，針對前述運量受影響之公車路線，將其運量進一步區分為普通票 (處理組) 敬老票 (控制組)，結果顯示，輕軌通車對兩者產生的影響程度並無明顯差異。

Communities in Taiwan have added light rail lines to public transit systems that predominantly use buses. Arguments have been made as to whether light rail lines attract new ridership or merely draw ridership from existing riders. We utilized a quasi-experimental method using difference-in-differences (DID) to quantify the impact of light rail lines on ridership after the opening of the Danhai light rail lines in Tamsui District, New Taipei City. According to the range of the geographic coverage, three treatment scenarios were tested: (1) if the bus route is within the catchment area of the light rail, (2) the total number of light rail stations, and (3) the total number of light rail passengers. We also further explored whether riders in different locations were affected differently by the opening of the light rail.
The results of the research confirmed that construction of the Danhai Light Rail had a substantial impact on reducing bus transportation. The results of the DID model showed that the transportation volume was reduced by 14.192 per trip. The model with the second treatment scenario showed that every time a bus route passed through a light rail station, the ridership dropped by 2.6981 per trip. The model with the third treatment scenario showed that for every 1% person increase in traffic volume on the light rail, ridership was decreased by 1.968 per trip.
These results indicate that it may be a good idea to, regardless of route distance, plan for the routes to coordinate with the light rail route to provide passenger transfer support, as well as encouraging bus operators to adjust their operating routes accordingly. According to the results of this study, the best range of the Danhai light rail lines is 400 meters, which is slightly smaller than the distance recorded in past studies. Traffic line adjustments have been carried out through the area around the MRT station, and the planning of these transit systems is specifically designed to reduce frequent use of private transportation by Danshui residents.

Ahlfeldt, G. M., and Holman, N. (2018). Distinctively different: a new approach to valuing architectural amenities. The Economic Journal, 128(608), 1-33.
Atkinson-Palombo, C. (2010). Comparing the capitalisation benefits of light-rail transit and overlay zoning for single-family houses and condos by neighbourhood type in metropolitan Phoenix, Arizona. Urban studies, 47(11), 2409-2426.
Bardaka, E., Delgado, M. S., and Florax, R. J. (2018). Causal identification of transit-induced gentrification and spatial spillover effects: The case of the Denver light rail. Journal of Transport Geography, 71, 15-31.
Bertrand, M., Duflo, E., and Mullainathan, S. (2004). How much should we trust differences-in-differences estimates? The Quarterly journal of economics, 119(1), 249-275.
Besser, L. M., and Dannenberg, A. L. (2005). Walking to public transit: steps to help meet physical activity recommendations. American journal of preventive medicine, 29(4), 273-280.
Bohannon, R. W., and Andrews, A. W. (2011). Normal walking speed: a descriptive meta-analysis. Physiotherapy, 97(3), 182-189.
Boschmann, E. E., and Kwan, M.-P. (2008). Toward socially sustainable urban transportation: Progress and potentials. International journal of sustainable transportation, 2(3), 138-157.
Campbell, K. B., and Brakewood, C. (2017). Sharing riders: How bikesharing impacts bus ridership in New York City. Transportation Research Part A: Policy and Practice, 100, 264-282.
Cao, X. J., and Schoner, J. (2014). The influence of light rail transit on transit use: An exploration of station area residents along the Hiawatha line in Minneapolis. Transportation Research Part A: Policy and Practice, 59, 134-143.
Cascajo, R., Lopez, E., Herrero, F., and Monzon, A. (2019). User perception of transfers in multimodal urban trips: A qualitative study. International Journal of Sustainable Transportation, 13(6), 393-406.
Cervero, R., and Sullivan, C. (2011). Green TODs: marrying transit-oriented development and green urbanism. International journal of sustainable development & world ecology, 18(3), 210-218.
Chen, H., Rufolo, A., and Dueker, K. J. (1998). Measuring the impact of light rail systems on single-family home values: A hedonic approach with geographic information system application. Transportation Research Record, 1617(1), 38-43.
Clair, T. S., and Cook, T. D. (2015). Difference-in-differences methods in public finance. National Tax Journal, 68(2), 319-338.
Creemers, L., Cools, M., Tormans, H., Lateur, P.-J., Janssens, D., and Wets, G. (2012). Identifying the Determinants of Light Rail Mode Choice for Medium- and Long-Distance Trips:Results from a Stated Preference Study. Transportation Research Record, 2275(1), 30-38.
Currie, G., and Burke, M. (2013). Light rail in Australia-performance and prospects. Paper presented at the Australasian Transport Research Forum 2013(pp. 1-17). Australian National Audit Office.
Durand, C. P., Oluyomi, A. O., Gabriel, K. P., Salvo, D., Sener, I. N., Hoelscher, D. M., . . . Robertson, M. C. (2016). The effect of light rail transit on physical activity: design and methods of the travel-related activity in neighborhoods study. Frontiers in public health, 4, 103.
Ferbrache, F., and Knowles, R. D. (2017). City boosterism and place-making with light rail transit: A critical review of light rail impacts on city image and quality. Geoforum, 80, 103-113.
Freeland, A. L., Banerjee, S. N., Dannenberg, A. L., and Wendel, A. M. (2013). Walking associated with public transit: moving toward increased physical activity in the United States. American journal of public health, 103(3), 536-542.
Furth, P. G., and Rahbee, A. B. (2000). Optimal bus stop spacing through dynamic programming and geographic modeling. Transportation Research Record, 1731(1), 15-22.
Giuliano, G. (2004). Land use impacts of transportation investments. The geography of urban transportation, 3, 237-273.
Gomez-ibanez, J. A. (2007). A Dark Side to Light Rail? The Experience of Three New Transit Systems. Journal of the American Planning Association, 51(3), 337-351.
Hess, D. B., and Almeida, T. M. (2007). Impact of proximity to light rail rapid transit on station-area property values in Buffalo, New York. Urban studies, 44(5-6), 1041-1068.
Knowles, R. D. (1996). Transport impacts of Greater Manchester's Metrolink light rail system. Journal of Transport Geography, 4(1), 1-14.
Kuby, M., Barranda, A., and Upchurch, C. (2004). Factors influencing light-rail station boardings in the United States. Transportation Research Part A: Policy and Practice, 38(3), 223-247.
Lechner, M. (2011). The Estimation of Causal Effects by Difference-in-Difference Methods. Foundations and Trends in Econometrics, 4(3), 165-224.
Lee, J., Boarnet, M., Houston, D., Nixon, H., and Spears, S. (2017). Changes in Service and Associated Ridership Impacts near a New Light Rail Transit Line. Sustainability, 9(10).
Lin, T.-m., and Wilson, N. H. (1992). Dwell time relationships for light rail systems. Transportation Research Record(1361), 287.
Masser, I., Svidén, O., and Wegener, M. (1992). From growth to equity and sustainability: Paradigm shift in transport planning? Futures, 24(6), 539-558.
Mathur, S., and Ferrell, C. (2013). Measuring the impact of sub-urban transit-oriented developments on single-family home values. Transportation Research Part A: Policy and Practice, 47, 42-55.
McDonald, J. F., and Osuji, C. I. (1995). The effect of anticipated transportation improvement on residential land values. Regional science and urban economics, 25(3), 261-278.
Murray, A. T., and Wu, X. (2003). Accessibility tradeoffs in public transit planning. Journal of Geographical Systems, 5(1), 93-107.
Nijkamp, P. (1999). Sustainable transport: new research and policy challenge for the next millennium. European Review, 7(4), 551-563.
Pan, Q. (2013). The impacts of an urban light rail system on residential property values: a case study of the Houston METRORail transit line. Transportation Planning and Technology, 36(2), 145-169.
Ransom, M. R. (2018). The effect of light rail transit service on nearby property values. Journal of Transport and Land Use, 11(1), 387-404.
Rijsman, L., Van Oort, N., Ton, D., Hoogendoorn, S., Molin, E., and Teijl, T. (2019). Walking and bicycle catchment areas of tram stops: factors and insights. Paper presented at the 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), p1-5, IEEE.
Shiftan, Y., Kaplan, S., and Hakkert, S. (2003). Scenario building as a tool for planning a sustainable transportation system. Transportation Research Part D: Transport and Environment, 8(5), 323-342.
Sun, G., Zhao, J., Webster, C., and Lin, H. (2020). New metro system and active travel: A natural experiment. Environ Int, 138, 105605.
Werner, C. M., Brown, B. B., Tribby, C. P., Tharp, D., Flick, K., Miller, H. J., . . . Jensen, W. (2016). Evaluating the attractiveness of a new light rail extension: Testing simple change and displacement change hypotheses. Transp Policy (Oxf), 45, 15-23.
Wooldridge, J. (2007). What’s new in econometrics? Difference-in-differences estimation. Paper presented at the NBER Summer Institute.
內政部. (2007). 淡海計畫.
張有恆. (2017). 現代運輸學: 華泰文化.
新北市政府捷運工程局. (2018). 淡海輕軌運輸系統綜合規劃報告書.