本研究使用民國89年至108年台灣各縣市之長期追蹤資料，以駕駛人駕駛各種交通工具發生肇事時，所造成的交通事故肇事總件數進行實證研究，探討經濟景氣對交通事故的影響因素，如失業率、社會治安、車輛概況等，並實證分析影響台灣各縣市每年的道路交通事故肇事件數的影響。 在控制縣市及年的固定效果實證結果中顯示，失業率、受(處)理刑事案件發生總數與道路交通事故肇事總件數呈現負相關關係，其效果顯著；車輛成長率-機車與道路交通事故肇事總件數呈現正相關關係，其效果有顯著；使用警力（人次）與道路交通事故肇事總件數呈現正相關關係，其效果不顯著。 在經濟不景氣的狀態下失業率高，男、女性皆會減少外出機會，即便要外出也會選擇花費較少的交通工具，並以機車作為代步工具，而道路交通事故肇事總件，會隨著景氣好壞呈現同方向變動；各級警察機關現有正式員額對交通事故件數的影響存在著內生性的關係，考量警力內生性的問題後，二階段最小平方法的估計結果呈現警力的多寡對交通事故件數的變化，並無顯著的影響。;This thesis uses Panel data from counties and cities in Taiwan from 2000 to 2019. The empirical study is based on the number of traffic accidents caused by drivers driving various vehicles. We explore factors with the economic determinants to traffic accidents, such as unemployment rate, social security, vehicle profile, etc., Moreover we empirically analyzes the impact on the number of road traffic accidents in Taiwan’s counties and cities each year. The empirical results of the fixed effects model shown that the unemployment rate and the number of criminal cases has a negative correlation between the number of road traffic accidents and shows the significant. Vehicle growth rate motorcycle has a positive correlation between the number of road traffic accidents and shows the significant. The use of police force has a positive correlation between the number of road traffic accidents and shows the insignificant. The unemployment rate is high in the economic downturn. Both men and women will reduce their chances of going out. Even if they want to go out, they will choose a less expensive transportation. And use motorcycles as a means of transportation. The number of road traffic accidents will change in the same direction as the economy turns good or bad. There is an endogenous relationship between the official employee of police agencies at all levels and the number of traffic accidents. Consider the question of the endogenous nature of the police force. The estimation resulted of the two stage the least square method shows the insignificant change of the amount of police force to the number of traffic accidents.
