计量经济学所有作业

计量经济学课后习题一部分解答

计量经济学

三章

3.6题

x<-c(128,204,202,197,96,209,170,240,241,55,75,129,24,165,94,96,148,98,161,118,269,189,126,12,167,135,107,72,128,27,152,224,142,104,287,41,312,77,142,262,215,246,191,182,37,103,67,143,83,223,240,312,12,52,79,61,168,28,121,115,186,47,178,142)

>

y<-c(1870,130,310,570,2050,200,670,300,120,290,1180,900,1730,1150,1160,1270,580,660,420,1080,290,270,560,4240,240,430,3020,1420,420,19830,420,530,8640,350,230,1620,190,2090,900,230,140,330,1010,300,1730,780,1300,930,690,200,450,280,4430,270,1340,670,410,4370,1310,1470,300,3630,220,560)

> lm.sol<-lm(y~x+1)

> summary(lm.sol)

Call:

lm(formula = y ~ x + 1)

Residuals:

Min 1Q Median 3Q Max

-2440.3 -981.0 -442.9 333.4 16754.1

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 3470.84 667.00 5.204 2.34e-06 ***

x -14.63 4.16 -3.516 0.000826 ***

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 2509 on 62 degrees of freedom

Multiple R-squared: 0.1662, Adjusted R-squared: 0.1528

F-statistic: 12.36 on 1 and 62 DF, p-value: 0.0008262

> plot(x,1/y)

3.7题

x1<-c(28707.7,29388.6,30308.4,31816.6,33802.5,36118.1,38546.9,42015.6,45207.7,48996.12,52573.61,55172.1,57929.85,60386.54,64027.91,68397.85,72522.12,76589.56,82190.41) >

y<-c(44624.3,43529.3,44265.8,45648.8,44510.1,46661.8,50453.5,49417.1,51229.53,50838.58,46217.52,45263.67,45705.75,43069.53,46946.95,48402.19,49804.23,50160.28,52870.92) > lm.sol<-lm(y~x1+1)

计量经济学课后习题一部分解答

> summary(lm.sol)

Call:

lm(formula = y ~ x1 + 1)

Residuals:

Min 1Q Median 3Q Max

-5165.9 -1503.4 -534.1 1638.7 4322.0

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 4.295e+04 1.908e+03 22.512 4.29e-14 ***

x1 8.748e-02 3.605e-02 2.427 0.0266 *

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 2614 on 17 degrees of freedom

Multiple R-squared: 0.2573, Adjusted R-squared: 0.2136

F-statistic: 5.889 on 1 and 17 DF, p-value: 0.02664

>

x2<-c(47403.1,47822.1,48590.1,48727.9,48795.1,49281.2,50381.4,51238.5,52295.6,53158.41,53820.33,54249.39,54354.9,54014.23,54478.42,55029.34,55750.5,56518.34,58471.68)

>

y<-c(44624.3,43529.3,44265.8,45648.8,44510.1,46661.8,50453.5,49417.1,51229.53,50838.58,46217.52,45263.67,45705.75,43069.53,46946.95,48402.19,49804.23,50160.28,52870.92)

> lm.sol<-lm(y~x2+1)

> summary(lm.sol)

Call:

lm(formula = y ~ x2 + 1)

Residuals:

Min 1Q Median 3Q Max

-5112.4 -1521.5 -274.4 1652.8 4075.7

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 2.136e+04 9.630e+03 2.218 0.0405 *

x2 4.966e-01 1.837e-01 2.704 0.0151 *

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 2537 on 17 degrees of freedom

计量经济学课后习题一部分解答

Multiple R-squared: 0.3007, Adjusted R-squared: 0.2596

F-statistic: 7.311 on 1 and 17 DF, p-value: 0.01506

>

x3<-c(2590.3,2805.1,2930.2,3151.9,3317.9,3593.7,3827.9,3980.7,4083.7,4124.32,4146.41,4253.76,4339.39,4411.56,4636.58,4766.22,4927.69,5107.83,5239.02)

>

y<-c(44624.3,43529.3,44265.8,45648.8,44510.1,46661.8,50453.5,49417.1,51229.53,50838.58,46217.52,45263.67,45705.75,43069.53,46946.95,48402.19,49804.23,50160.28,52870.92)

> lm.sol<-lm(y~x3+1)

> summary(lm.sol)

Call:

lm(formula = y ~ x3 + 1)

Residuals:

Min 1Q Median 3Q Max

-5202.4 -1336.5 277.7 1353.6 3716.0

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 3.807e+04 2.962e+03 12.854 3.49e-10 ***

x3 2.313e+00 7.253e-01 3.189 0.00537 **

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 2399 on 17 degrees of freedom

Multiple R-squared: 0.3744, Adjusted R-squared: 0.3376

F-statistic: 10.17 on 1 and 17 DF, p-value: 0.005368

> 以上可以看出第三个拟合度最好，由题意知y= 3.807*10^4 + 2.313x3 (***)

下面做出年份对化肥用量的线性回归

>

x<-c(1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008)

>

x3<-c(2590.3,2805.1,2930.2,3151.9,3317.9,3593.7,3827.9,3980.7,4083.7,4124.32,4146.41,4253.76,4339.39,4411.56,4636.58,4766.22,4927.69,5107.83,5239.02)

> lm.sol<-lm(x3~x+1)

> summary(lm.sol)

Call:

lm(formula = x3 ~ x + 1)

计量经济学课后习题一部分解答

Residuals:

Min 1Q Median 3Q Max

-191.44 -74.81 -32.03 56.83 241.84

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) -2.693e+05 1.090e+04 -24.71 9.22e-15 ***

x 1.367e+02 5.453e+00 25.08 7.22e-15 ***

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 130.2 on 17 degrees of freedom

Multiple R-squared: 0.9737, Adjusted R-squared: 0.9721

F-statistic: 628.8 on 1 and 17 DF, p-value: 7.216e-15

可以看出，年份与化肥使用量线性拟合度较好，因此x3=-2.693*10^5+1.367*10^2x （*） 将x=2009,x=2010带入（*）得x3(2009)=5330.3与x3(2010)=5467

将x3(2009)=5330.3与x3 …… 此处隐藏：19698字，全部文档内容请下载后查看。喜欢就下载吧 ……