setwd("/Users/luisaavila/Desktop/Econometri\314\201a")
autos<-read.csv('autosUSA.csv',sep = ',')
reg1<-lm(log(ventas)~log(precio)+log(ingreso), data=autos)
summary(reg1)
##
## Call:
## lm(formula = log(ventas) ~ log(precio) + log(ingreso), data = autos)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.27977 -0.09603 0.01293 0.11487 0.27186
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.1536 1.5240 0.101 0.92103
## log(precio) -2.0327 0.5683 -3.577 0.00275 **
## log(ingreso) 2.2742 0.3031 7.502 1.88e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1624 on 15 degrees of freedom
## Multiple R-squared: 0.9159, Adjusted R-squared: 0.9047
## F-statistic: 81.69 on 2 and 15 DF, p-value: 8.619e-09
#Log(ventas) = 0.1536 - (2.0327)(log(precio)) + (2.2742)(log(ingreso))
#R2 = 0.9159
reg2<-lm(log(ventas)~log(precio)+log(ingreso)+log(Stock), data=autos)
summary(reg2)
##
## Call:
## lm(formula = log(ventas) ~ log(precio) + log(ingreso) + log(Stock),
## data = autos)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.21694 -0.07982 0.01759 0.10602 0.19165
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.7207 1.7324 -1.570 0.1386
## log(precio) -1.4220 0.5440 -2.614 0.0204 *
## log(ingreso) 3.2159 0.4543 7.079 5.51e-06 ***
## log(Stock) -1.4789 0.5850 -2.528 0.0241 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1393 on 14 degrees of freedom
## Multiple R-squared: 0.9423, Adjusted R-squared: 0.9299
## F-statistic: 76.17 on 3 and 14 DF, p-value: 6.545e-09
#Log(ventas) = -2.7202 - (1.4220)(log(precio)) + (3.2159)(log(ingreso)) - (1.4789)(log(Stock))
#R2 = 0.9423
Conclusion: