论文部分内容阅读
1. Introduction
A steep decline in road fatalities in Australia was found within past few decades. It is worthwhile investigating causes， implications as it provides important insight to reduce road fatalities. The implementation of alcohol limit laws was a statistically proven factor in decreasing road fatalities （Gaudry， 2014）. Unemployed people are incapable of buying cars and thus have less exposure to traffic accidents. Another factor is inflation related with actual costs of using motor vehicles. Transportation habits may change due to high petrol and servicing costs. This report examines the issue of vehicle fatalities from macro-views of alcohol laws， unemployment and inflation， which contributes to policy making under dynamic economy.
2. Data
Annual road deaths data from 1925 to 2016 was gathered from Bureau of Infrastructure， Transport and Regional Economics （2017）. The dependent variable FATALITIES refers to total number of annual road deaths per million people. Independent variables of ALCOHOL is the pure alcohol consumption per capita with data from Australian Bureau of Statistics （2017c）； UNEMPLOYMENT is annual Australian unemployment rate with data from Federal Reserve Bank of St. Louis （2017）； INFLATION is annual Australia inflation rate with data from Australian Bureau of Statistics（2017d）. Unit root test for stationarity will be conducted and returned p-values will suggest whether to reject the null hypothesis of nonstationarity. P-values all larger than 0.05 from test suggests non-stationarity. The same test on differenced variables indicates significant results of stationarity.
3. Methodology and Results
Due to the failure to find the co-integration between original variables， first differenced stationary variables are put into OLS regression. The model to estimate relationship between dependent and independent variables is as follow：
（Standard error） （1.284） （4.930） （1.518） （0.676）
（p-value） （0.004） （0.008） （0.004） （0.046）
1 increase alcohol consumption raises fatalities by 13.731 fatalities. 1% increase in INFLATION and UNEMPLOYMENT result in 4.6 and 1.4 decrease by FATALITIES. Findings confirm our hypotheses that alcohol consumption has a positive relationship but inflation and unemployment rate have inverse relationships with road fatalities. Also the adjusted R2 indicates that the model can explain 25.33% of the variations in . Therefore having found significant correlation between the explanatory variables and road deaths has been a great step forward in understanding the possible causes of road deaths. This can assist legislatures or other policy-makers when creating and deciding on effective strategies to lower the national fatality rate. Therefore this adds credibility that to our hypothesis， in that all variables investigated have proven to be significant in explaining Australia’s road fatalities.
A steep decline in road fatalities in Australia was found within past few decades. It is worthwhile investigating causes， implications as it provides important insight to reduce road fatalities. The implementation of alcohol limit laws was a statistically proven factor in decreasing road fatalities （Gaudry， 2014）. Unemployed people are incapable of buying cars and thus have less exposure to traffic accidents. Another factor is inflation related with actual costs of using motor vehicles. Transportation habits may change due to high petrol and servicing costs. This report examines the issue of vehicle fatalities from macro-views of alcohol laws， unemployment and inflation， which contributes to policy making under dynamic economy.
2. Data
Annual road deaths data from 1925 to 2016 was gathered from Bureau of Infrastructure， Transport and Regional Economics （2017）. The dependent variable FATALITIES refers to total number of annual road deaths per million people. Independent variables of ALCOHOL is the pure alcohol consumption per capita with data from Australian Bureau of Statistics （2017c）； UNEMPLOYMENT is annual Australian unemployment rate with data from Federal Reserve Bank of St. Louis （2017）； INFLATION is annual Australia inflation rate with data from Australian Bureau of Statistics（2017d）. Unit root test for stationarity will be conducted and returned p-values will suggest whether to reject the null hypothesis of nonstationarity. P-values all larger than 0.05 from test suggests non-stationarity. The same test on differenced variables indicates significant results of stationarity.
3. Methodology and Results
Due to the failure to find the co-integration between original variables， first differenced stationary variables are put into OLS regression. The model to estimate relationship between dependent and independent variables is as follow：
（Standard error） （1.284） （4.930） （1.518） （0.676）
（p-value） （0.004） （0.008） （0.004） （0.046）
1 increase alcohol consumption raises fatalities by 13.731 fatalities. 1% increase in INFLATION and UNEMPLOYMENT result in 4.6 and 1.4 decrease by FATALITIES. Findings confirm our hypotheses that alcohol consumption has a positive relationship but inflation and unemployment rate have inverse relationships with road fatalities. Also the adjusted R2 indicates that the model can explain 25.33% of the variations in . Therefore having found significant correlation between the explanatory variables and road deaths has been a great step forward in understanding the possible causes of road deaths. This can assist legislatures or other policy-makers when creating and deciding on effective strategies to lower the national fatality rate. Therefore this adds credibility that to our hypothesis， in that all variables investigated have proven to be significant in explaining Australia’s road fatalities.