1、计量经济学实验报告英文版Econometrics report Class number: No number: Eglish name:Chinese name:ContentsBackground and Data Analysis 2-5 and model T-test 6-8 F-test 8-10Summary,and,suggestion 11 BACKGROUND The report below is about the food sales , I instance the resident population (10 000 ) , per capita income
2、the first year , meat sales , egg sales , the fish sales . In order to build mathematical models to understand the relationship of each variable and its food sales , and I take statistics of Tianjin from 1994 to 2007 the demand for foodYX1X2X3X4X5198.4500 153.2000 560.2000 6.5300 1.2300 1.8900 2100.
3、7000 190.0000 603.1100 9.1200 1.3000 2.0300 3102.8000 240.3000 668.0500 8.1000 1.8000 2.7100 4133.9500 301.1200 715.4700 10.1000 2.0900 3.0000 5140.1300 361.0000 724.2700 10.9300 2.3900 3.2900 6143.1100 420.0000 736.1300 11.8500 3.9000 5.2400 7146.1500 491.7760 748.9100 12.2800 5.1300 6.8300 8144.60
4、00 501.0000 760.3200 13.5000 5.4700 8.3600 9146.9400 529.2000 774.9200 15.2900 6.0900 10.0700 10158.5500 552.7200 785.3000 18.1000 7.9700 12.5700 11169.6800 771.7600 795.5000 19.6100 10.1800 15.1200 12162.1400 811.8000 804.8000 17.2200 11.7900 18.2500 13170.0900 988.4300 814.9400 18.6000 11.5400 20.
5、5900 14178.6900 1094.6500 828.7300 23.5300 11.6800 23.3700 AmongrepresentYfood sales ( tons / year)X1the resident population (10 000 )X2per capita income the first yearX3meat salesX4egg salesX5the fish salesBased on the above data , the conclusions as followsThey are value, stand error R2 freedom SS
6、T SSR -4.688592773.63645562.667718050.1189610.077743-0.165342.2312262922.4720671.268798980.0596240.0381830.267350.9698048595.7740803#N/A#N/A#N/A#N/A51.388658538#N/A#N/A#N/A#N/A8566.490175266.72002#N/A#N/A#N/A#N/AWhere T statistics is-2.101352421.47101822.102553751.9951782.036186-0.00546The model Y=0
7、+1X1+2X2+3X3+4X4+5X5+uY=-0.1653+0.0777X1+0.1190X2+2.6677X3+3.6365X4-4.6886X5+u （0,03818） （0.0596） （1.2688） （2.4721） （2.2312） N=14 R2=0.9698 Y represents the model of food sales ( tons / year)，X1 said the resident population (10 000 ) , The X2 per capita income the first year , X3：meat sales , X4：sai
8、d egg sales , X5：said the fish sales .0.0777 means when resident population increase 1 point, the other factors remain unchanged, the food sales increase 0.777 point .0.1190 means when resident population increase 1 point, the other factors remain unchanged, the food sales increase 0.1190 point .2.6
9、677 means when resident population increase 1 point, the other factors remain unchanged, the food sales increase 2.6677 point .3.6365 means when resident population increase 1 point, the other factors remain unchanged, the food sales increase 3.6365 point .-4.6886 means when resident population incr
10、ease 1 point, the other factors remain unchanged, the food sales decrease 4.6886 point . t-testFor example, for a 5% level test and with n-k-1=8 degrees of freedom, the critical value is c=1.860 Null hypothesis H0: 1=0 alternative hypothesis H1: 10 We have 8 degrees of freedom, we can use the standa
11、rd normal critical values. The 5% critical value is 1.860. t1(hat)= 2.036186C we reject H0. the t statistic for 1(hat) is statistically significant at the 5% level . Null hypothesis H0: 2=0 alternative hypothesis H2: 20 We have 8 degrees of freedom, we can use the standard normal critical values. Th
12、e 5% critical value is 1.860. t2(hat)= 1.995178C we reject H0. the t statistic for 2(hat) is statistically significant at the 5% level . Null hypothesis H0: 3=0 alternative hypothesis H3: 30 We have 8 degrees of freedom, we can use the standard normal critical values. The 5% critical value is 1.860.
13、 t3(hat)= 2.10255375C we reject H0. the t statistic for 3(hat) is statistically significant at the 5% level . Null hypothesis H0: 4=0 alternative hypothesis H4: 40 We have 8 degrees of freedom, we can use the standard normal critical values. The 5% critical value is 1.860. t4(hat)= 1.4710182C we not
14、 reject H0. the t statistic for 4(hat) is statistically insignificant at the 5% level . Null hypothesis H0: 5=0 alternative hypothesis H5: 50 We have 8 degrees of freedom, we can use the standard normal critical values. The 5% critical value is 1.860. t5(hat)= -2.10135242-C we reject H0. the t stati
15、stic for 5(hat) is statistically significant at the 5% level .F STATISTICBecause only X1 X2 X3 X5 statistically significant. so we imposed 1 exclusion restrictions in this model.YX1X2X3X4198.45153.2560.26.531.892100.7190603.119.122.033102.8240.3668.058.12.714133.95301.12715.4710.135140.13361724.2710
16、.933.296143.11420736.1311.855.247146.15491.776748.9112.286.838144.6501760.3213.58.369146.94529.2774.9215.2910.0710158.55552.72785.318.112.5711169.68771.76795.519.6115.1212162.14811.8804.817.2218.2513170.09988.43814.9418.620.5914178.691094.65828.7323.5323.37-2.17362.3532920.1643310.058715-21.67641.52
17、35171.3290760.0542260.03817528.16190.9616376.136089#N/A#N/A#N/A56.400989#N/A#N/A#N/A8494.346338.8643#N/A#N/A#N/A-1.42671.7706233.0304851.538058-0.76971F = (R2ur-R2)/q ( 1-R2ur)/(n-k-1)In this form ,the model change:0= -21.6764 1= 0.058715 2= 0.164331 3= 2.353292 4=-2.1736y=-21.6764 +0.058715X1 +0.16
18、4331X2 +2.353292X3 -2.1736 X4 (0.038175) (0.054226) (1.329076) (1.523517)Where X1the resident population (10 000 )X2per capita income the first yearX3meat salesX4the fish salesH0: 1=0 2=0 3=0 F = (R2ur-R2)/q ( 1-R2ur)/(n-k-1)F=( 0.961637-6.136089)*8/(1-6.136089)/1=8.059754416Through TABLI G.3 c=2.84
19、Since this is well below the 5% critical value, we to reject H0.the variables are jointly significant. In other words the resident population per capita income the first year meat sales the fish sales are jointly significant in the food sales.SummaryIn above data, the meat sales and the resident pop
20、ulation is much impact in the food sales, the fish sales is less impact in food sales, Even Negative impact on the food slaes.In addition to the above can affect food sales factors , including weather, food production . if the weather is good , the food sales of course will good , in opposite ,the bad weather , the food sales will poor . and if there are much food production , will much impact on the food sales ,in opposite , less impact.
