library(wooldridge)## Warning: package 'wooldridge' was built under R version 4.1.3library(plm)## Warning: package 'plm' was built under R version 4.1.3data("Males")head(Males, 10)## nr year school exper union ethn married health wage
## 1 13 1980 14 1 no other no no 1.1975402
## 2 13 1981 14 2 yes other no no 1.8530600
## 3 13 1982 14 3 no other no no 1.3444617
## 4 13 1983 14 4 no other no no 1.4332133
## 5 13 1984 14 5 no other no no 1.5681251
## 6 13 1985 14 6 no other no no 1.6998909
## 7 13 1986 14 7 no other no no -0.7202626
## 8 13 1987 14 8 no other no no 1.6691879
## 9 17 1980 13 4 no other no no 1.6759624
## 10 17 1981 13 5 no other no no 1.5183982
## industry occupation residence
## 1 Business_and_Repair_Service Service_Workers north_east
## 2 Personal_Service Service_Workers north_east
## 3 Business_and_Repair_Service Service_Workers north_east
## 4 Business_and_Repair_Service Service_Workers north_east
## 5 Personal_Service Craftsmen, Foremen_and_kindred north_east
## 6 Business_and_Repair_Service Managers, Officials_and_Proprietors north_east
## 7 Business_and_Repair_Service Managers, Officials_and_Proprietors north_east
## 8 Business_and_Repair_Service Managers, Officials_and_Proprietors north_east
## 9 Trade Managers, Officials_and_Proprietors north_east
## 10 Trade Managers, Officials_and_Proprietors north_easttail(Males,10)## nr year school exper union ethn married health wage
## 4351 12534 1986 11 8 no other yes no 2.3818830
## 4352 12534 1987 11 9 no other yes no 2.3429170
## 4353 12548 1980 9 5 no other no no 1.1305453
## 4354 12548 1981 9 6 no other no no 1.3116035
## 4355 12548 1982 9 7 no other no no 0.8324815
## 4356 12548 1983 9 8 no other yes no 1.5918787
## 4357 12548 1984 9 9 yes other yes no 1.2125428
## 4358 12548 1985 9 10 no other yes no 1.7659618
## 4359 12548 1986 9 11 yes other yes no 1.7458942
## 4360 12548 1987 9 12 yes other yes no 1.4665429
## industry occupation residence
## 4351 Construction Craftsmen, Foremen_and_kindred <NA>
## 4352 Construction Craftsmen, Foremen_and_kindred <NA>
## 4353 Construction Laborers_and_farmers <NA>
## 4354 Construction Craftsmen, Foremen_and_kindred <NA>
## 4355 Construction Craftsmen, Foremen_and_kindred <NA>
## 4356 Construction Craftsmen, Foremen_and_kindred <NA>
## 4357 Construction Craftsmen, Foremen_and_kindred <NA>
## 4358 Construction Craftsmen, Foremen_and_kindred <NA>
## 4359 Professional_and_Related Service Craftsmen, Foremen_and_kindred <NA>
## 4360 Public_Administration Craftsmen, Foremen_and_kindred <NA>benimmodel <- pdata.frame(Males, index = c("nr", "year"))pdim(benimmodel)## Balanced Panel: n = 545, T = 8, N = 4360yenimodel <- plm(wage ~ union + married + health + factor(year), data= benimmodel, model = "within")summary(yenimodel)## Oneway (individual) effect Within Model
##
## Call:
## plm(formula = wage ~ union + married + health + factor(year),
## data = benimmodel, model = "within")
##
## Balanced Panel: n = 545, T = 8, N = 4360
##
## Residuals:
## Min. 1st Qu. Median 3rd Qu. Max.
## -4.15342 -0.12631 0.01106 0.16249 1.48268
##
## Coefficients:
## Estimate Std. Error t-value Pr(>|t|)
## unionyes 0.083194 0.019446 4.2781 1.931e-05 ***
## marriedyes 0.058135 0.018378 3.1633 0.001572 **
## healthyes -0.019011 0.047515 -0.4001 0.689111
## factor(year)1981 0.113534 0.021496 5.2817 1.352e-07 ***
## factor(year)1982 0.167635 0.021646 7.7444 1.223e-14 ***
## factor(year)1983 0.210851 0.021951 9.6057 < 2.2e-16 ***
## factor(year)1984 0.278506 0.022185 12.5537 < 2.2e-16 ***
## factor(year)1985 0.327320 0.022403 14.6107 < 2.2e-16 ***
## factor(year)1986 0.386705 0.022607 17.1058 < 2.2e-16 ***
## factor(year)1987 0.446951 0.022819 19.5866 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 572.05
## Residual Sum of Squares: 475.41
## R-Squared: 0.16894
## Adj. R-Squared: 0.047943
## F-statistic: 77.3507 on 10 and 3805 DF, p-value: < 2.22e-16pvar(benimmodel)## no time variation: nr school ethn
## no individual variation: yearreg_ols <- plm(wage ~ union + married + health + exper + I(exper^2)+ factor(year), data= benimmodel, model = "pooling")reg_random <- plm(wage ~ union + married + health + exper + I(exper^2)+ factor(year), data= benimmodel, model = "random")reg_fe <- plm(wage ~ union + married + health + exper + I(exper^2)+ factor(year), data= benimmodel, model = "within")library(stargazer)##
## Please cite as:## Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.## R package version 5.2.3. https://CRAN.R-project.org/package=stargazerstargazer(reg_ols, reg_random, reg_fe, type = "text", column.labels = c("pooling, random, within"))##
## ===============================================================================
## Dependent variable:
## --------------------------------------------------------------
## wage
## pooling, random, within
## (1) (2) (3)
## -------------------------------------------------------------------------------
## unionyes 0.173*** 0.101*** 0.080***
## (0.018) (0.018) (0.019)
##
## marriedyes 0.149*** 0.072*** 0.047**
## (0.016) (0.017) (0.018)
##
## healthyes -0.064 -0.023 -0.017
## (0.059) (0.047) (0.047)
##
## exper 0.030** 0.052*** 0.132***
## (0.014) (0.015) (0.010)
##
## I(exper2) -0.004*** -0.005*** -0.005***
## (0.001) (0.001) (0.001)
##
## factor(year)1981 0.101*** 0.095*** 0.019
## (0.031) (0.024) (0.020)
##
## factor(year)1982 0.152*** 0.142*** -0.011
## (0.034) (0.031) (0.020)
##
## factor(year)1983 0.200*** 0.187*** -0.042**
## (0.037) (0.039) (0.020)
##
## factor(year)1984 0.282*** 0.267*** -0.038*
## (0.040) (0.047) (0.020)
##
## factor(year)1985 0.356*** 0.339*** -0.043**
## (0.043) (0.055) (0.020)
##
## factor(year)1986 0.448*** 0.431*** -0.027
## (0.045) (0.064) (0.020)
##
## factor(year)1987 0.542*** 0.532***
## (0.047) (0.072)
##
## Constant 1.279*** 1.258***
## (0.039) (0.044)
##
## -------------------------------------------------------------------------------
## Observations 4,360 4,360 4,360
## R2 0.126 0.167 0.181
## Adjusted R2 0.123 0.164 0.061
## F Statistic 52.104*** (df = 12; 4347) 868.961*** 76.223*** (df = 11; 3804)
## ===============================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01phtest(reg_fe, reg_random)##
## Hausman Test
##
## data: wage ~ union + married + health + exper + I(exper^2) + factor(year)
## chisq = 36.093, df = 11, p-value = 0.0001633
## alternative hypothesis: one model is inconsistentp değeri 0.0001633 olduğu için anlamlı, reddedilir.
lmmodel <- lm(wage ~ union + married + health + year, data= benimmodel)summary(lmmodel)##
## Call:
## lm(formula = wage ~ union + married + health + year, data = benimmodel)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.1556 -0.2772 0.0240 0.3105 2.4280
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.32452 0.02218 59.708 < 2e-16 ***
## unionyes 0.17541 0.01775 9.884 < 2e-16 ***
## marriedyes 0.14226 0.01599 8.895 < 2e-16 ***
## healthyes -0.06803 0.05894 -1.154 0.248485
## year1981 0.10497 0.03046 3.447 0.000573 ***
## year1982 0.15244 0.03054 4.992 6.21e-07 ***
## year1983 0.18893 0.03070 6.153 8.28e-10 ***
## year1984 0.25205 0.03083 8.176 3.82e-16 ***
## year1985 0.29937 0.03095 9.671 < 2e-16 ***
## year1986 0.35710 0.03107 11.495 < 2e-16 ***
## year1987 0.40937 0.03118 13.129 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.502 on 4349 degrees of freedom
## Multiple R-squared: 0.1136, Adjusted R-squared: 0.1115
## F-statistic: 55.71 on 10 and 4349 DF, p-value: < 2.2e-16