cps78_85 regresyon modeli
library(wooldridge)
library(rmarkdown)
data("cps78_85")
paged_table(cps78_85)
require(dplyr)
## Loading required package: dplyr
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
data("cps78_85")
head(cps78_85)
## educ south nonwhite female married exper expersq union lwage age year y85
## 1 12 0 0 0 0 8 64 0 1.2150 25 78 0
## 2 12 0 0 1 1 30 900 1 1.6094 47 78 0
## 3 6 0 0 0 1 38 1444 1 2.1401 49 78 0
## 4 12 0 0 0 1 19 361 1 2.0732 36 78 0
## 5 12 0 0 0 1 11 121 0 1.6490 28 78 0
## 6 8 0 0 0 1 43 1849 0 1.7148 56 78 0
## y85fem y85educ y85union
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
summary(cps78_85)
## educ south nonwhite female
## Min. : 1.00 Min. :0.0000 Min. :0.0000 Min. :0.000
## 1st Qu.:12.00 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000
## Median :12.00 Median :0.0000 Median :0.0000 Median :0.000
## Mean :12.77 Mean :0.2943 Mean :0.1144 Mean :0.417
## 3rd Qu.:14.00 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:1.000
## Max. :18.00 Max. :1.0000 Max. :1.0000 Max. :1.000
## married exper expersq union
## Min. :0.0000 Min. : 0.00 Min. : 0.0 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.: 8.00 1st Qu.: 64.0 1st Qu.:0.0000
## Median :1.0000 Median :15.00 Median : 225.0 Median :0.0000
## Mean :0.6541 Mean :18.28 Mean : 499.8 Mean :0.2435
## 3rd Qu.:1.0000 3rd Qu.:28.00 3rd Qu.: 784.0 3rd Qu.:0.0000
## Max. :1.0000 Max. :55.00 Max. :3025.0 Max. :1.0000
## lwage age year y85
## Min. :-0.470 Min. :18.00 Min. :78.00 Min. :0.0000
## 1st Qu.: 1.470 1st Qu.:27.00 1st Qu.:78.00 1st Qu.:0.0000
## Median : 1.833 Median :34.00 Median :78.00 Median :0.0000
## Mean : 1.867 Mean :36.54 Mean :81.45 Mean :0.4926
## 3rd Qu.: 2.225 3rd Qu.:46.00 3rd Qu.:85.00 3rd Qu.:1.0000
## Max. : 3.796 Max. :64.00 Max. :85.00 Max. :1.0000
## y85fem y85educ y85union
## Min. :0.000 Min. : 0.000 Min. :0.00000
## 1st Qu.:0.000 1st Qu.: 0.000 1st Qu.:0.00000
## Median :0.000 Median : 0.000 Median :0.00000
## Mean :0.226 Mean : 6.413 Mean :0.08856
## 3rd Qu.:0.000 3rd Qu.:12.000 3rd Qu.:0.00000
## Max. :1.000 Max. :18.000 Max. :1.00000
cps78_85 %>%
group_by(year) %>%
summarise(veri = n())
## # A tibble: 2 x 2
## year veri
## <int> <int>
## 1 78 550
## 2 85 534
benimdatam <- cps78_85 %>%
mutate(y78 = ifelse(year == 1, 0, 1))
summary(benimdatam)
## educ south nonwhite female
## Min. : 1.00 Min. :0.0000 Min. :0.0000 Min. :0.000
## 1st Qu.:12.00 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000
## Median :12.00 Median :0.0000 Median :0.0000 Median :0.000
## Mean :12.77 Mean :0.2943 Mean :0.1144 Mean :0.417
## 3rd Qu.:14.00 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:1.000
## Max. :18.00 Max. :1.0000 Max. :1.0000 Max. :1.000
## married exper expersq union
## Min. :0.0000 Min. : 0.00 Min. : 0.0 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.: 8.00 1st Qu.: 64.0 1st Qu.:0.0000
## Median :1.0000 Median :15.00 Median : 225.0 Median :0.0000
## Mean :0.6541 Mean :18.28 Mean : 499.8 Mean :0.2435
## 3rd Qu.:1.0000 3rd Qu.:28.00 3rd Qu.: 784.0 3rd Qu.:0.0000
## Max. :1.0000 Max. :55.00 Max. :3025.0 Max. :1.0000
## lwage age year y85
## Min. :-0.470 Min. :18.00 Min. :78.00 Min. :0.0000
## 1st Qu.: 1.470 1st Qu.:27.00 1st Qu.:78.00 1st Qu.:0.0000
## Median : 1.833 Median :34.00 Median :78.00 Median :0.0000
## Mean : 1.867 Mean :36.54 Mean :81.45 Mean :0.4926
## 3rd Qu.: 2.225 3rd Qu.:46.00 3rd Qu.:85.00 3rd Qu.:1.0000
## Max. : 3.796 Max. :64.00 Max. :85.00 Max. :1.0000
## y85fem y85educ y85union y78
## Min. :0.000 Min. : 0.000 Min. :0.00000 Min. :1
## 1st Qu.:0.000 1st Qu.: 0.000 1st Qu.:0.00000 1st Qu.:1
## Median :0.000 Median : 0.000 Median :0.00000 Median :1
## Mean :0.226 Mean : 6.413 Mean :0.08856 Mean :1
## 3rd Qu.:0.000 3rd Qu.:12.000 3rd Qu.:0.00000 3rd Qu.:1
## Max. :1.000 Max. :18.000 Max. :1.00000 Max. :1
summary(lm(lwage ~ y78 + y85 + (educ + south) + exper + I(exper^2) + union, data = benimdatam))
##
## Call:
## lm(formula = lwage ~ y78 + y85 + (educ + south) + exper + I(exper^2) +
## union, data = benimdatam)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.47944 -0.27428 0.01622 0.26566 1.98971
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.709e-01 8.100e-02 3.344 0.000855 ***
## y78 NA NA NA NA
## y85 3.727e-01 2.677e-02 13.922 < 2e-16 ***
## educ 8.097e-02 5.359e-03 15.111 < 2e-16 ***
## south -5.619e-02 2.946e-02 -1.907 0.056769 .
## exper 2.896e-02 3.750e-03 7.723 2.59e-14 ***
## I(exper^2) -3.855e-04 8.155e-05 -4.727 2.58e-06 ***
## union 2.395e-01 3.185e-02 7.519 1.16e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4341 on 1077 degrees of freedom
## Multiple R-squared: 0.364, Adjusted R-squared: 0.3604
## F-statistic: 102.7 on 6 and 1077 DF, p-value: < 2.2e-16
summary(lm(lwage ~ y78 + y85 + (educ + south) + exper + I(exper^2) + union -1, data = benimdatam))
##
## Call:
## lm(formula = lwage ~ y78 + y85 + (educ + south) + exper + I(exper^2) +
## union - 1, data = benimdatam)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.47944 -0.27428 0.01622 0.26566 1.98971
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## y78 2.709e-01 8.100e-02 3.344 0.000855 ***
## y85 3.727e-01 2.677e-02 13.922 < 2e-16 ***
## educ 8.097e-02 5.359e-03 15.111 < 2e-16 ***
## south -5.619e-02 2.946e-02 -1.907 0.056769 .
## exper 2.896e-02 3.750e-03 7.723 2.59e-14 ***
## I(exper^2) -3.855e-04 8.155e-05 -4.727 2.58e-06 ***
## union 2.395e-01 3.185e-02 7.519 1.16e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4341 on 1077 degrees of freedom
## Multiple R-squared: 0.9505, Adjusted R-squared: 0.9502
## F-statistic: 2954 on 7 and 1077 DF, p-value: < 2.2e-16