Estimate model parameters via two-step method
twostep(selection, outcome, data = sys.frame(sys.parent()))Selection equation.
Primary Regression Equation.
Database.
Returns a numerical vector with the parameter estimates of the Classical Heckman model via a two-step method. For more information see Heckman (1979)
James J Heckman (1979). “Sample selection bias as a specification error.” Econometrica: Journal of the econometric society, 153--161.
data(MEPS2001)
attach(MEPS2001)
#> The following objects are masked from MEPS2001 (pos = 3):
#>
#> age, age2, agefem, ambexp, blhisp, dambexp, dhospexp, educ,
#> fairpoor, female, ffs, good, hospexp, income, ins, instype,
#> instype_s1, lambexp, lnambx, totchr, vgood, year01
#> The following objects are masked from PSID2:
#>
#> age, educ
#> The following objects are masked from data:
#>
#> age, educ, income
#> The following objects are masked from data3:
#>
#> age, educ, income
#> The following objects are masked from nhanes:
#>
#> age, educ, income
#> The following objects are masked from Mroz87 (pos = 8):
#>
#> age, educ
#> The following objects are masked from MEPS2001 (pos = 9):
#>
#> age, age2, agefem, ambexp, blhisp, dambexp, dhospexp, educ,
#> fairpoor, female, ffs, good, hospexp, income, ins, instype,
#> instype_s1, lambexp, lnambx, totchr, vgood, year01
#> The following objects are masked from MEPS2001 (pos = 10):
#>
#> age, age2, agefem, ambexp, blhisp, dambexp, dhospexp, educ,
#> fairpoor, female, ffs, good, hospexp, income, ins, instype,
#> instype_s1, lambexp, lnambx, totchr, vgood, year01
#> The following objects are masked from MEPS2001 (pos = 11):
#>
#> age, age2, agefem, ambexp, blhisp, dambexp, dhospexp, educ,
#> fairpoor, female, ffs, good, hospexp, income, ins, instype,
#> instype_s1, lambexp, lnambx, totchr, vgood, year01
#> The following objects are masked from Mroz87 (pos = 12):
#>
#> age, educ
#> The following objects are masked from MEPS2001 (pos = 13):
#>
#> age, age2, agefem, ambexp, blhisp, dambexp, dhospexp, educ,
#> fairpoor, female, ffs, good, hospexp, income, ins, instype,
#> instype_s1, lambexp, lnambx, totchr, vgood, year01
#> The following objects are masked from MEPS2001 (pos = 14):
#>
#> age, age2, agefem, ambexp, blhisp, dambexp, dhospexp, educ,
#> fairpoor, female, ffs, good, hospexp, income, ins, instype,
#> instype_s1, lambexp, lnambx, totchr, vgood, year01
#> The following objects are masked from MEPS2001 (pos = 15):
#>
#> age, age2, agefem, ambexp, blhisp, dambexp, dhospexp, educ,
#> fairpoor, female, ffs, good, hospexp, income, ins, instype,
#> instype_s1, lambexp, lnambx, totchr, vgood, year01
#> The following objects are masked from MEPS2001 (pos = 16):
#>
#> age, age2, agefem, ambexp, blhisp, dambexp, dhospexp, educ,
#> fairpoor, female, ffs, good, hospexp, income, ins, instype,
#> instype_s1, lambexp, lnambx, totchr, vgood, year01
selectEq <- dambexp ~ age + female + educ + blhisp + totchr + ins + income
outcomeEq <- lnambx ~ age + female + educ + blhisp + totchr + ins
twostep(selectEq, outcomeEq)
#> XS(Intercept) XSage XSfemale XSeduc XSblhisp
#> -0.668643899 0.086814848 0.663505390 0.061883892 -0.365784312
#> XStotchr XSins XSincome XO(Intercept) XOage
#> 0.795747277 0.169106526 0.002677301 5.288927373 0.202466773
#> XOfemale XOeduc XOblhisp XOtotchr XOins
#> 0.292133967 0.012388871 -0.182865733 0.500633176 -0.046509658
#> phi.IMR IMR
#> 1.290541875 -0.359316986