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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/69467

    Title: 汽機車傷亡事故的影響因素-以桃園市為例;The Determinants of The Traffic Accidents- The Example of Taoyuan City
    Authors: 劉玉娟;Liu,Yu chuan
    Contributors: 產業經濟研究所在職專班
    Keywords: 交通事故;酒駕;駕駛年齡;Ordered Probit模型;Probit模型;traffic accident;drunk driving;fatality rate;Ordered Probit model;Probit model
    Date: 2016-01-27
    Issue Date: 2016-03-17 20:42:24 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 中文摘要
    校所組別:國立中央大學 產業經濟研究所 一般組
    論文摘要: 指導教授:蔡偉德 博士

    依Ordered Probit模型實證結果顯示,以車禍事故受傷程度為衡量指標時,女性、年齡、雨天、酒駕、光線昏暗、其他路況,皆有正向顯著的效果。依Probit模型實證結果顯示,以車禍事故死亡為衡量指標時,年齡、雨天、酒駕、光線昏暗、其他路況,皆有正向顯著的效果;然而晴天、女性、保護裝置為負向顯著效果。
    依本文以Ordered Probit模型及Probit模型實證後,顯示汽機車傷亡的影響因素中以駕駛年齡、雨天、酒駕、光線昏暗、其他路況為顯著影響。

    關鍵字: 交通事故、酒駕、駕駛年齡、Ordered Probit模型、Probit模型
    ;The Determinants of The Traffic Accidents- The Example of Taoyuan City
    In view of the 2013 statistics on the traffic accident deaths and injuries related by the National Police Agency (NPA), Ministry of the Interior, Taoyuan City’s traffic accident rate (including locomotive and car accidents) ranks the third highest among the national wide accident rate statistics. Using the A1, A2, class traffic accident investigation report released by NPA, we use ordered probit regression model and profit model, respectively, to empirically analyze the determinants of the degree of the injury and the fatality rate of traffic accidents in Taoyuan City in 2003-2013.
    Our empirical results show that several factors are significantly related to the degree of injury in vehicle accidents, including rainy days, dim light, other road conditions and drivers who are female, elder and drunk driving. For the factors related to the fatality rate of traffic accidents, rainy days, dim lights and drunk driving will significantly increase the fatality rate in traffic accidents; however, sunny days and drivers who are female, fasten the seat belt or wear the helmets are negatively associated with the death rate in traffic accidents.

    Key words: traffic accident, drunk driving, fatality rate, Ordered Probit model, Probit model.
    Appears in Collections:[產業經濟研究所碩士在職專班 ] 博碩士論文

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