What moves Hong Kong's train ridership?

被引:5
作者
Woo, C. K. [1 ]
Cao, K. H. [2 ]
Zarnikau, J. [3 ]
Yip, T. L. [4 ]
Chow, A. [5 ]
机构
[1] Educ Univ Hong Kong, Dept Asian & Policy Studies, Hong Kong, Peoples R China
[2] Hong Kong Baptist Univ, Dept Econ, Hong Kong, Peoples R China
[3] Univ Texas Austin, Dept Econ, Austin, TX 78712 USA
[4] Hong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R China
[5] Educ Univ Hong Kong, Dept Social Sci, Hong Kong, Peoples R China
关键词
Covid-19; Social unrest; Train service suspension; Willingness to pay; Passenger welfare; Hong Kong; TRAVEL-TIME RELIABILITY; INCENTIVE REGULATION; PRICE-CAP; METAANALYSIS; TRANSPORT; ELECTRICITY; VALUATION; COST; INTERRUPTIONS; SHORTAGE;
D O I
10.1016/j.retrec.2021.101133
中图分类号
F [经济];
学科分类号
02 ;
摘要
Hong Kong is a densely populated international metropolis with similar to 7.5 million residents living in a small geographic area of similar to 1,100 km(2). Like some major cities around the world, it has a vast public transportation system that moves similar to 12.4 million passengers per day, similar to 42% of which is attributable to the Mass Transit Railway's (MTR's) extensive network interconnecting widely dispersed stations across Hong Kong. MTR's ridership substantially declined in 2019 because of social unrest and related system service suspension (SSS). This decline was further exacerbated by Covid-19's outbreak in 2020. Using a hand-collected sample of monthly data for January 2000-June 2020, we estimate a log-linear demand regression to find that MTR's ridership is price and income inelastic, varies seasonally, and exhibits a trend of gradual growth. Further, Covid-19, social unrest and SSS significantly reduce MTR's ridership. Finally, the estimates for passenger welfare losses due to SSS and social unrest are large, revealing the potential gains from improving MTR's service reliability and resolving the root causes of social unrest.
引用
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页数:12
相关论文
共 60 条
[1]   ECONOMIC ACTIVITY AND THE SPREAD OF VIRAL DISEASES: EVIDENCE FROM HIGH FREQUENCY DATA [J].
Adda, Jerome .
QUARTERLY JOURNAL OF ECONOMICS, 2016, 131 (02) :891-941
[2]   Effect of transport transfer quality on intercity passenger mode choice [J].
Allard, Ryan F. ;
Moura, Filipe .
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2018, 109 :89-107
[3]  
[Anonymous], 2008, J PUBLIC TRANSPORT, DOI DOI 10.5038/2375-0901.11.2.3
[4]  
Baker G., 2015, SHOULD TRANSPORT BE
[5]  
Bateman L.J, 2001, VALUING ENV PREFEREN
[6]   Insights into the impact of COVID-19 on household travel and activities in Australia - The early days of easing restrictions [J].
Beck, Matthew J. ;
Hensher, David A. .
TRANSPORT POLICY, 2020, 99 :95-119
[7]  
Carson R., 2014, The discrete choice experiment approach to environmental contingent valuation
[8]   THE COST OF ELECTRIC-POWER INTERRUPTIONS IN THE INDUSTRIAL SECTOR - ESTIMATES DERIVED FROM INTERRUPTIBLE SERVICE PROGRAMS [J].
CAVES, DW ;
HERRIGES, JA ;
WINDLE, RJ .
LAND ECONOMICS, 1992, 68 (01) :49-61
[9]  
Census and Statistics Department, 2019, HONG KONG STAT
[10]  
Champ PatriciaA., 2003, PRIMER NONMARKET VAL