计量经济学报告英文版

Neimenggu 36.0474096 1126 9136.79 Liaoning 69.895986 2477 9107.55 Jilin 45.500808 1426 8690.62 47.2070776 2027 8272.51 Heilongjiang Shanghai 183.954672 1584 18645.03 Jiangsu 236.595434 3742 12318.57 Zhejiang 356.17209 2742 16293.77 Anhui 56.19649 2170 8470.68 Fujian 64.214859 1671 12321.31 Jiangxi 30.49563748 1593 8619.66 Shandong 198.216018 4158 10744.79 Henan 50.854504 2872 8667.97 Hubei 59.852665 2465 8785.94 Hunan 69.249222 2338 9523.97 Guangdong 868.05048 5573 14769.94 Guangxi 49.731005 1565 9286.7 Hainan 13.10800504 373 8123.94 Chongqing 41.007952 1264 10243.46 Sichuan 109.086012 2709 8385.96 Guizhou 21.972951 1001 8151.13 Yunnan 51.20725848 1311 9265.9 Xizang 3.851182 74 9431.18 Shanxi 30.118608 1384 8272.02 Gansu 18.93180399 778 8086.82 Qinghai 7.3906106 213 8057.85 Ningxia 7.342524 252 8093.64 Xinjiang 28.03356931 746 7990.15 Source: national bureau of statistics yearbook of the People's Republic of China

4.Establish model and test

-3.4056986 0.0209979 0.1014664 -263.58232 4.3337264 0.005906 0.0232113 60.35636 0.7233166 90.002794 #N/A #N/A 23.528159 27 #N/A #N/A 571769.75 218713.58 #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A Establish model and test Regression of data collected to establish a preliminary model, the regression results as follows

Y=-263.58232+ 0.1014664X1+0.0209979X2-3.4056986X3 60.35636 0.0232113 0.005906 4.3337264 N=31 R2=0.7233166 X1= the urban population

X2= per capita annual disposable income X3= the country used for transportation of fiscal spending

As the R2=0.7233166 ,so the three Independent variables together explain about 72.3 percent of variation in y for this sample.

The T test

1.Null hypothesis H0: β1=0 alternative hypothesie H1: β1>0

tβ1(hat)=0.1014664/0.0232113=4.37142254>c=1.073

because we have 27 degrees of freedom,we can use the standard normal critical values.the 5% critical value is1.703. do reject H0.it is statistically significant

2.Null hypothesis H0: β1=0 alternative hypothesie H1: β1>0

tβ2(hat)= 0.0209979/0.005906≈3.554989334>c

because we have 27 degrees of freedom,we can use the standard normal critical values.the 5% critical value is1.703. do reject H0.it is statistically significant

3、Null hypothesis H0: β1=0 alternative hypothesie H1: β1>0

tβ3(hat)= 3.4056986 / 4.3337264=0.785859

because we have 27 degrees of freedom,we can use the standard normal critical values.the 5% critical value is1.703. do not reject H0. is not statistically significant

So we revised Establish model by T test

Y=-263.58232+ 0.1014664X1+0.0209979X2

The X1= the urban population and X2= per capita annual disposable income are statistically significant so we can abandon the X3= the country used for transportation of fiscal spending

The F test

As the excel calculate F=23.528159.>c

This number is above the 5% critical value in the F

distribution 27 degrees of freedom, and the critical value is 23.528159,then F>C.

We can reject that the hypothesis. the three variables are jointly significant

conclusion

1, population have impact on traffic consumer spending , the reason is various, mainly include: (1) the greater the population, the greater the traffic consumption in total; (2) the more population, people's consumption behavior also more diversified, increases the demand for all kinds of traffic tools.

2, disposable income consumer spending also has significant influence to the traffic. The higher level of economic development, people's income is higher, in order to improve the quality of life, people pay attention to the diversification of consumption, consumption is becoming more and more big, the scope of trans-regional transnational communication, tourism travel become more frequently, thereby increasing the corresponding traffic consumer spending. Raising the level of disposable income, on the other hand, represents the improvement of economic level, also reflects the business activities more frequently, people for the purpose of business activity, consumer spending will increase the traffic.

Of course, because of my knowledge and ability is limited, establishing the model, I can't included all the important factors, I also please the teacher put forward your valuable advice and guidance.