summary.selection: Summarizing Selection Estimations
In sampleSelection: Sample Selection Models

Description Usage Arguments Details Value Author(s) See Also Examples

Print or return a summary of a selection estimation.

   ## S3 method for class 'selection'
summary(object, ...)
   ## S3 method for class 'summary.selection'
print(x,
      digits = max(3, getOption("digits") - 3),
      part = "full", ...)

`object`	an object of class '`selection`'.
`x`	an object of class '`summary.selection`'.
`part`	character string: which parts of the summary to print: "full" for all the estimated parameters (probit selection, outcome estimates, correlation and residual variance), or "outcome" for the outcome results only.
`digits`	numeric, (suggested) number of significant digits.
`...`	currently not used.

The variance-covariance matrix of the two-step estimator is currently implemented only for tobit-2 (sample selection) models, but not for the tobit-5 (switching regression) model.

Summary methods return an object of class summary.selection. Print methods return the argument invisibly.

Arne Henningsen, Ott Toomet otoomet@ut.ee

summary, selection, and selection-methods.

## Wooldridge( 2003 ): example 17.5, page 590
data( Mroz87 )
wooldridge <- selection( lfp ~ nwifeinc + educ + exper + I( exper^2 ) +
   age + kids5 + kids618, log( wage ) ~ educ + exper + I( exper^2 ),
   data = Mroz87, method = "2step" )

# summary of the 1st step probit estimation (Example 17.1, p. 562f)
# and the 2nd step OLS regression (example 17.5, page 590)
summary( wooldridge )

# summary of the outcome equation only
print(summary(wooldridge), part="outcome")

Loading required package: maxLik
Loading required package: miscTools

Please cite the 'maxLik' package as:
Henningsen, Arne and Toomet, Ott (2011). maxLik: A package for maximum likelihood estimation in R. Computational Statistics 26(3), 443-458. DOI 10.1007/s00180-010-0217-1.

If you have questions, suggestions, or comments regarding the 'maxLik' package, please use a forum or 'tracker' at maxLik's R-Forge site:
https://r-forge.r-project.org/projects/maxlik/
--------------------------------------------
Tobit 2 model (sample selection model)
2-step Heckman / heckit estimation
753 observations (325 censored and 428 observed)
15 free parameters (df = 739)
Probit selection equation:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.270077   0.508593   0.531  0.59556    
nwifeinc    -0.012024   0.004840  -2.484  0.01320 *  
educ         0.130905   0.025254   5.183 2.81e-07 ***
exper        0.123348   0.018716   6.590 8.34e-11 ***
I(exper^2)  -0.001887   0.000600  -3.145  0.00173 ** 
age         -0.052853   0.008477  -6.235 7.61e-10 ***
kids5       -0.868328   0.118522  -7.326 6.21e-13 ***
kids618      0.036005   0.043477   0.828  0.40786    
Outcome equation:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.5781032  0.3050062  -1.895  0.05843 .  
educ         0.1090655  0.0155230   7.026 4.83e-12 ***
exper        0.0438873  0.0162611   2.699  0.00712 ** 
I(exper^2)  -0.0008591  0.0004389  -1.957  0.05068 .  
Multiple R-Squared:0.1569,	Adjusted R-Squared:0.149
   Error terms:
              Estimate Std. Error t value Pr(>|t|)
invMillsRatio  0.03226    0.13362   0.241    0.809
sigma          0.66363         NA      NA       NA
rho            0.04861         NA      NA       NA
--------------------------------------------
--------------------------------------------
Tobit 2 model (sample selection model)
2-step Heckman / heckit estimation
753 observations (325 censored and 428 observed)
15 free parameters (df = 739)
Outcome equation:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.5781032  0.3050062  -1.895  0.05843 .  
educ         0.1090655  0.0155230   7.026 4.83e-12 ***
exper        0.0438873  0.0162611   2.699  0.00712 ** 
I(exper^2)  -0.0008591  0.0004389  -1.957  0.05068 .  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Multiple R-Squared:0.1569,	Adjusted R-Squared:0.149
--------------------------------------------