Also available in Stata and Python versions
Load libraries
library(wooldridge)
library(nnet)
library(stargazer)
library(haven)
library(MASS)School and Employment Decisions for Young Men
#library(haven)
df <- read_dta("Wooldridge_2E/keane.dta")
#library(nnet)
mlogit<-multinom( status ~ educ + exper + expersq + black, data=df, subset=year==87)## # weights: 18 (10 variable)
## initial value 1886.317300
## iter 10 value 1034.528631
## iter 20 value 907.857379
## final value 907.857241
## convergedstargazer(mlogit, no.space = T, type="text")##
## ==============================================
## Dependent variable:
## ----------------------------
## 1 2
## (1) (2)
## ----------------------------------------------
## educ -0.674*** -0.315***
## (0.070) (0.065)
## exper -0.106 0.849***
## (0.173) (0.157)
## expersq -0.013 -0.077***
## (0.025) (0.023)
## black 0.812*** 0.311
## (0.303) (0.281)
## Constant 10.276*** 5.542***
## (1.133) (1.086)
## ----------------------------------------------
## Akaike Inf. Crit. 1,835.714 1,835.714
## ==============================================
## Note: *p<0.1; **p<0.05; ***p<0.01Asset Allocation in Pension Plans
OLS <- lm(pctstck ~ choice + age + educ + female + black + married +
finc25 + finc35 + finc50 + finc75 + finc100 + finc101 + wealth89 + prftshr,
data=pension)
pension$pctstck2 <- as.factor(pension$pctstck)
#library(MASS)
Oprobit <- polr(pctstck2 ~ choice + age + educ + female + black + married +
finc25 + finc35 + finc50 + finc75 + finc100 + finc101 + wealth89 + prftshr,
data=pension, method = "probit", Hess = TRUE )
stargazer(OLS, Oprobit, no.space = T, type="text")##
## =================================================
## Dependent variable:
## -----------------------------
## pctstck pctstck2
## OLS ordered
## probit
## (1) (2)
## -------------------------------------------------
## choice 12.048* 0.371**
## (6.298) (0.184)
## age -1.626** -0.050**
## (0.775) (0.023)
## educ 0.754 0.026
## (1.207) (0.035)
## female 1.303 0.046
## (7.164) (0.206)
## black 3.967 0.093
## (9.783) (0.282)
## married 3.303 0.094
## (7.998) (0.233)
## finc25 -18.186 -0.578
## (14.120) (0.423)
## finc35 -3.925 -0.135
## (14.486) (0.431)
## finc50 -8.129 -0.262
## (14.342) (0.427)
## finc75 -17.579 -0.566
## (16.078) (0.478)
## finc100 -6.746 -0.228
## (15.791) (0.469)
## finc101 -28.344 -0.864
## (17.905) (0.529)
## wealth89 -0.003 -0.0001
## (0.012) (0.0004)
## prftshr 15.808** 0.482**
## (7.333) (0.216)
## Constant 134.116**
## (55.705)
## -------------------------------------------------
## Observations 194 194
## R2 0.100
## Adjusted R2 0.029
## Residual Std. Error 39.134 (df = 179)
## F Statistic 1.418 (df = 14; 179)
## =================================================
## Note: *p<0.1; **p<0.05; ***p<0.01