setwd("C:/Users/marcogeovanni/Desktop/Modern Guide To Econometrics/Chapter 5")
library(readstata13)#Necesitamos estimar los retornos de la escolaridad
Schooling <- read.dta13("schooling.dta") #Utilizamos la base de datos Schooling.dta, disponible en MIU
attach(Schooling)
summary(Schooling)
## smsa66 id nearc2 nearc4
## Min. :0.0000 Min. : 2 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:1276 1st Qu.:0.0000 1st Qu.:0.0000
## Median :1.0000 Median :2541 Median :0.0000 Median :1.0000
## Mean :0.6495 Mean :2582 Mean :0.4409 Mean :0.6821
## 3rd Qu.:1.0000 3rd Qu.:3859 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :5225 Max. :1.0000 Max. :1.0000
##
## nearc4a nearc4b ed76 ed66
## Min. :0.0000 Min. :0.0000 Min. : 1.00 Min. : 0.00
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:12.00 1st Qu.: 9.00
## Median :0.0000 Median :0.0000 Median :13.00 Median :11.00
## Mean :0.4927 Mean :0.1894 Mean :13.26 Mean :10.76
## 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:16.00 3rd Qu.:12.00
## Max. :1.0000 Max. :1.0000 Max. :18.00 Max. :18.00
##
## age76 daded nodaded momed
## Min. :24.00 Min. : 0.000 Min. :0.0000 Min. : 0.00
## 1st Qu.:25.00 1st Qu.: 8.000 1st Qu.:0.0000 1st Qu.: 9.00
## Median :28.00 Median : 9.940 Median :0.0000 Median :11.00
## Mean :28.12 Mean : 9.989 Mean :0.2292 Mean :10.34
## 3rd Qu.:31.00 3rd Qu.:12.000 3rd Qu.:0.0000 3rd Qu.:12.00
## Max. :34.00 Max. :18.000 Max. :1.0000 Max. :18.00
##
## nomomed momdad14 sinmom14 step14
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.0000 1st Qu.:1.0000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.0000 Median :1.0000 Median :0.0000 Median :0.00000
## Mean :0.1173 Mean :0.7894 Mean :0.1007 Mean :0.03887
## 3rd Qu.:0.0000 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.00000
##
## south66 lwage76 famed black
## Min. :0.0000 Min. :4.605 Min. :1.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:5.977 1st Qu.:3.000 1st Qu.:0.0000
## Median :0.0000 Median :6.287 Median :6.000 Median :0.0000
## Mean :0.4143 Mean :6.262 Mean :5.934 Mean :0.2336
## 3rd Qu.:1.0000 3rd Qu.:6.564 3rd Qu.:8.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :7.785 Max. :9.000 Max. :1.0000
##
## smsa76 south76 wage76 enroll76
## Min. :0.000 Min. :0.0000 Min. : 100.0 Min. :0.00000
## 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.: 394.2 1st Qu.:0.00000
## Median :1.000 Median :0.0000 Median : 537.5 Median :0.00000
## Mean :0.713 Mean :0.4037 Mean : 577.3 Mean :0.09236
## 3rd Qu.:1.000 3rd Qu.:1.0000 3rd Qu.: 708.8 3rd Qu.:0.00000
## Max. :1.000 Max. :1.0000 Max. :2404.0 Max. :1.00000
##
## kww iqscore mar76 libcrd14
## Min. : 4.00 Min. : 50.0 Min. :1.000 Min. :0.0000
## 1st Qu.:28.00 1st Qu.: 93.0 1st Qu.:1.000 1st Qu.:0.0000
## Median :34.00 Median :103.0 Median :1.000 Median :1.0000
## Mean :33.54 Mean :102.4 Mean :2.271 Mean :0.6743
## 3rd Qu.:40.00 3rd Qu.:113.0 3rd Qu.:4.000 3rd Qu.:1.0000
## Max. :56.00 Max. :149.0 Max. :6.000 Max. :1.0000
## NA's :47 NA's :949 NA's :7 NA's :13
## region exp76 exp762 _merge
## Min. :1.000 Min. : 0.000 Min. : 0.00 Min. :3
## 1st Qu.:3.000 1st Qu.: 6.000 1st Qu.: 36.00 1st Qu.:3
## Median :5.000 Median : 8.000 Median : 64.00 Median :3
## Mean :4.638 Mean : 8.856 Mean : 95.58 Mean :3
## 3rd Qu.:6.000 3rd Qu.:11.000 3rd Qu.:121.00 3rd Qu.:3
## Max. :9.000 Max. :23.000 Max. :529.00 Max. :3
##
E1 <- lm(lwage76~ed76 + exp76 + exp762 + black + smsa76 + south76)#corremos una regresión explicando el logaritmo del salario
summary(E1)
##
## Call:
## lm(formula = lwage76 ~ ed76 + exp76 + exp762 + black + smsa76 +
## south76)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.59297 -0.22315 0.01893 0.24223 1.33190
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.7336643 0.0676026 70.022 < 2e-16 ***
## ed76 0.0740090 0.0035054 21.113 < 2e-16 ***
## exp76 0.0835958 0.0066478 12.575 < 2e-16 ***
## exp762 -0.0022409 0.0003178 -7.050 2.21e-12 ***
## black -0.1896315 0.0176266 -10.758 < 2e-16 ***
## smsa76 0.1614230 0.0155733 10.365 < 2e-16 ***
## south76 -0.1248615 0.0151182 -8.259 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3742 on 3003 degrees of freedom
## Multiple R-squared: 0.2905, Adjusted R-squared: 0.2891
## F-statistic: 204.9 on 6 and 3003 DF, p-value: < 2.2e-16
age762<-age76^2# definimos una variable de edad al cuadrado
VISchooling <- lm(ed76~age76 + age762 + black + smsa76 + south76 + nearc4) #Etapa 1 de 2SLS, forma reducida de Schooling
VIexper <- lm(exp76~age76 + age762 + black + smsa76 + south76 + nearc4)#Etapa 1 de 2SLS, forma reducida Age
VIexper2 <- lm(exp762~age76 + age762 + black + smsa76 + south76 + nearc4)#Etapa 1 de 2SLS, forma reducida Af2^2
summary(VISchooling)
##
## Call:
## lm(formula = ed76 ~ age76 + age762 + black + smsa76 + south76 +
## nearc4)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12.511 -1.722 -0.296 1.876 7.199
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.869524 4.298357 -0.435 0.663638
## age76 1.061441 0.301398 3.522 0.000435 ***
## age762 -0.018760 0.005231 -3.586 0.000341 ***
## black -1.468367 0.115443 -12.719 < 2e-16 ***
## smsa76 0.835403 0.109252 7.647 2.76e-14 ***
## south76 -0.459700 0.102434 -4.488 7.47e-06 ***
## nearc4 0.347105 0.106997 3.244 0.001191 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.516 on 3003 degrees of freedom
## Multiple R-squared: 0.1185, Adjusted R-squared: 0.1168
## F-statistic: 67.29 on 6 and 3003 DF, p-value: < 2.2e-16
summary(VIexper)
##
## Call:
## lm(formula = exp76 ~ age76 + age762 + black + smsa76 + south76 +
## nearc4)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.199 -1.876 0.296 1.722 12.511
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.130476 4.298357 -0.961 0.336658
## age76 -0.061441 0.301398 -0.204 0.838482
## age762 0.018760 0.005231 3.586 0.000341 ***
## black 1.468367 0.115443 12.719 < 2e-16 ***
## smsa76 -0.835403 0.109252 -7.647 2.76e-14 ***
## south76 0.459700 0.102434 4.488 7.47e-06 ***
## nearc4 -0.347105 0.106997 -3.244 0.001191 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.516 on 3003 degrees of freedom
## Multiple R-squared: 0.6318, Adjusted R-squared: 0.631
## F-statistic: 858.7 on 6 and 3003 DF, p-value: < 2.2e-16
summary(VIexper2)
##
## Call:
## lm(formula = exp762 ~ age76 + age762 + black + smsa76 + south76 +
## nearc4)
##
## Residuals:
## Min 1Q Median 3Q Max
## -168.49 -30.21 -1.32 25.30 389.71
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 609.9425 90.2203 6.761 1.64e-11 ***
## age76 -55.4520 6.3262 -8.765 < 2e-16 ***
## age762 1.3132 0.1098 11.960 < 2e-16 ***
## black 28.2062 2.4231 11.641 < 2e-16 ***
## smsa76 -17.5543 2.2932 -7.655 2.59e-14 ***
## south76 11.1770 2.1500 5.199 2.14e-07 ***
## nearc4 -7.2510 2.2458 -3.229 0.00126 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 52.81 on 3003 degrees of freedom
## Multiple R-squared: 0.6114, Adjusted R-squared: 0.6106
## F-statistic: 787.3 on 6 and 3003 DF, p-value: < 2.2e-16
SchoolingVI <-fitted(VISchooling)#tomamos los valores ajustado de la forma reducida y los guardamos en una variable
ExperVI <-fitted(VIexper)#tomamos los valores ajustado de la forma reducida y los guardamos en una variable
Exper2VI <-fitted(VIexper2)#tomamos los valores ajustados de la forma reducida y los guardamos en una variable
TSls <- lm(lwage76~SchoolingVI + ExperVI + Exper2VI + black + smsa76 + south76)# corremos una regresión E1 solo que sustituimos las variables con los valores ajustados de sus instrumentos
summary(TSls)
##
## Call:
## lm(formula = lwage76 ~ SchoolingVI + ExperVI + Exper2VI + black +
## smsa76 + south76)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.5902 -0.2418 0.0124 0.2598 1.3706
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.0656674 0.5831172 6.972 3.82e-12 ***
## SchoolingVI 0.1329473 0.0492365 2.700 0.006969 **
## ExperVI 0.0559614 0.0249103 2.247 0.024743 *
## Exper2VI -0.0007957 0.0012844 -0.619 0.535648
## black -0.1031403 0.0741459 -1.391 0.164315
## smsa76 0.1079848 0.0476654 2.265 0.023554 *
## south76 -0.0981752 0.0275648 -3.562 0.000374 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3864 on 3003 degrees of freedom
## Multiple R-squared: 0.2436, Adjusted R-squared: 0.2421
## F-statistic: 161.2 on 6 and 3003 DF, p-value: < 2.2e-16