TPass 通勤月票政策對公共運輸旅次之影響：不同乘客類型異質性效應的實證分析

Abstract

本研究利用 2023 年 4 月至 2024 年 12 月間的新北市公車上車紀錄，評估 TPass 通勤月票的政策效果。實證方法採用固定效果模型，將政策虛擬變數與線性時間趨勢相互作用，同時控制天氣、星期幾、假日、補班日及暑假影響。為避免高估後期效應，分析聚焦於政策實施後的前六個月（2023 年 7 月 1 日至 12 月 31 日）。

實證結果顯示，平均每日乘車人次增加約 10,000 人（+2.24\\\\\\\\%），主要來自新購月票的使用者；相較之下，平均每日延人公里數僅增加約 1,900 公里（+0.11\\\\\\\\%）。按乘客類型分析，長途通勤學生與原一般票乘客轉而購買月票，呈現替代效應。按公車路線與行程距離百分位的異質性分析發現，高需求路線於政策後增幅高於平均，而月票對長距離旅客最具吸引力。此外，碳減量估算為政策評估提供另一觀點。最後一章則根據實證結果提出政策建議。

This thesis evaluates the TPass Commuter Monthly Pass by analyzing bus boarding records from New Taipei City between April 2023 and December 2024. The empirical strategy employs a fixed-effects model in which a policy dummy is interacted with a linear time trend, while controlling for weather conditions, days of week, holidays, make-up days, and the summer break. To avoid overstating late-period impacts, the analysis focuses on the policy effect of first six months after implementation (1 July 2023 to 31 December 2023).

The results show that average daily ridership rose by about 10,000 passengers (+2.24\\\\\\\\%), driven mainly by new monthly‑pass users. By contrast, average daily passenger‑kilometers increased by only 1,900 (+0.11\\\\\\\\%). Analysis across passenger types suggests a substitution effect, as long‑travel distance students and former general ticket holders adopt the pass. Heterogeneity analysis across bus routes and traveling distance percentiles reveals that high‑demand routes experience larger gains than average after the policy, and the pass proves most attractive to travelers with longer journeys. In addition, the estimation of carbon reduction provides another perspective for policy assessment. The last chapter then proposes policy recommendations based on these empirical research results.