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
summary(lm(lwage ~ y85*(educ + female) + exper + I(exper^2) + union, data = cps78_85))
##
## Call:
## lm(formula = lwage ~ y85 * (educ + female) + exper + I(exper^2) +
## union, data = cps78_85)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.56098 -0.25828 0.00864 0.26571 2.11669
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.589e-01 9.345e-02 4.911 1.05e-06 ***
## y85 1.178e-01 1.238e-01 0.952 0.3415
## educ 7.472e-02 6.676e-03 11.192 < 2e-16 ***
## female -3.167e-01 3.662e-02 -8.648 < 2e-16 ***
## exper 2.958e-02 3.567e-03 8.293 3.27e-16 ***
## I(exper^2) -3.994e-04 7.754e-05 -5.151 3.08e-07 ***
## union 2.021e-01 3.029e-02 6.672 4.03e-11 ***
## y85:educ 1.846e-02 9.354e-03 1.974 0.0487 *
## y85:female 8.505e-02 5.131e-02 1.658 0.0977 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4127 on 1075 degrees of freedom
## Multiple R-squared: 0.4262, Adjusted R-squared: 0.4219
## F-statistic: 99.8 on 8 and 1075 DF, p-value: < 2.2e-16
y78 Kukla Değişkeni Oluşturma
benimdata <- cps78_85 %>%
mutate(y78 = ifelse (year == 78, 1, 0) )
model1 <- lm(lwage ~ y85*(educ + female) + y78 + exper + I(exper^2) + union -1 , data = benimdata)
summary(model1)
##
## Call:
## lm(formula = lwage ~ y85 * (educ + female) + y78 + exper + I(exper^2) +
## union - 1, data = benimdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.56098 -0.25828 0.00864 0.26571 2.11669
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## y85 5.767e-01 1.015e-01 5.684 1.69e-08 ***
## educ 7.472e-02 6.676e-03 11.192 < 2e-16 ***
## female -3.167e-01 3.662e-02 -8.648 < 2e-16 ***
## y78 4.589e-01 9.345e-02 4.911 1.05e-06 ***
## exper 2.958e-02 3.567e-03 8.293 3.27e-16 ***
## I(exper^2) -3.994e-04 7.754e-05 -5.151 3.08e-07 ***
## union 2.021e-01 3.029e-02 6.672 4.03e-11 ***
## y85:educ 1.846e-02 9.354e-03 1.974 0.0487 *
## y85:female 8.505e-02 5.131e-02 1.658 0.0977 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4127 on 1075 degrees of freedom
## Multiple R-squared: 0.9553, Adjusted R-squared: 0.955
## F-statistic: 2554 on 9 and 1075 DF, p-value: < 2.2e-16
İnterceptsiz Model
model2 <- lm(lwage ~ y85*(educ + female) + exper + I(exper^2) + union -1 , data = cps78_85)
summary(model2)
##
## Call:
## lm(formula = lwage ~ y85 * (educ + female) + exper + I(exper^2) +
## union - 1, data = cps78_85)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.56331 -0.24500 0.01702 0.27741 2.16580
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## y85 4.794e-01 1.006e-01 4.767 2.13e-06 ***
## educ 1.046e-01 2.767e-03 37.816 < 2e-16 ***
## female -2.924e-01 3.667e-02 -7.973 3.92e-15 ***
## exper 3.355e-02 3.512e-03 9.552 < 2e-16 ***
## I(exper^2) -4.391e-04 7.794e-05 -5.634 2.24e-08 ***
## union 2.199e-01 3.040e-02 7.232 9.00e-13 ***
## y85:educ -8.124e-03 7.710e-03 -1.054 0.292
## y85:female 5.859e-02 5.157e-02 1.136 0.256
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4171 on 1076 degrees of freedom
## Multiple R-squared: 0.9543, Adjusted R-squared: 0.954
## F-statistic: 2810 on 8 and 1076 DF, p-value: < 2.2e-16
library(stargazer)
##
## Please cite as:
## Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.
## R package version 5.2.2. https://CRAN.R-project.org/package=stargazer
stargazer(model1, model2, type = 'text')
##
## ===========================================================================
## Dependent variable:
## -------------------------------------------------------
## lwage
## (1) (2)
## ---------------------------------------------------------------------------
## y85 0.577*** 0.479***
## (0.101) (0.101)
##
## educ 0.075*** 0.105***
## (0.007) (0.003)
##
## female -0.317*** -0.292***
## (0.037) (0.037)
##
## y78 0.459***
## (0.093)
##
## exper 0.030*** 0.034***
## (0.004) (0.004)
##
## I(exper2) -0.0004*** -0.0004***
## (0.0001) (0.0001)
##
## union 0.202*** 0.220***
## (0.030) (0.030)
##
## y85:educ 0.018** -0.008
## (0.009) (0.008)
##
## y85:female 0.085* 0.059
## (0.051) (0.052)
##
## ---------------------------------------------------------------------------
## Observations 1,084 1,084
## R2 0.955 0.954
## Adjusted R2 0.955 0.954
## Residual Std. Error 0.413 (df = 1075) 0.417 (df = 1076)
## F Statistic 2,554.399*** (df = 9; 1075) 2,810.303*** (df = 8; 1076)
## ===========================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01