cps78_86 regresyon modeli
library(wooldridge)
library(rmarkdown)
data("fertil1")
paged_table(fertil1)
data("cps78_85")
paged_table(cps78_85)
require(dplyr)
## Zorunlu paket yükleniyor: 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
cps78_85 %>%
group_by(year) %>%
summarise(n= n())
## # A tibble: 2 x 2
## year n
## <int> <int>
## 1 78 550
## 2 85 534
summary(lm(lwage ~ y85*(educ + female) + exper + I(exper^2) + union, data = cps78_85,-1))
##
## Call:
## lm(formula = lwage ~ y85 * (educ + female) + exper + I(exper^2) +
## union, data = cps78_85, subset = -1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5614 -0.2579 0.0101 0.2657 2.1162
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.617e-01 9.352e-02 4.937 9.18e-07 ***
## y85 1.161e-01 1.238e-01 0.938 0.3484
## educ 7.463e-02 6.678e-03 11.176 < 2e-16 ***
## female -3.179e-01 3.665e-02 -8.673 < 2e-16 ***
## exper 2.956e-02 3.568e-03 8.286 3.46e-16 ***
## I(exper^2) -3.995e-04 7.755e-05 -5.152 3.07e-07 ***
## union 2.016e-01 3.031e-02 6.651 4.62e-11 ***
## y85:educ 1.850e-02 9.355e-03 1.978 0.0482 *
## y85:female 8.618e-02 5.133e-02 1.679 0.0935 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4128 on 1074 degrees of freedom
## Multiple R-squared: 0.4258, Adjusted R-squared: 0.4215
## F-statistic: 99.56 on 8 and 1074 DF, p-value: < 2.2e-16