predict.selection {sampleSelection}

Predict method for fitted sample selection models

Description

Calculate predicted values for sample selection models fitted with function selection.

Usage

   ## S3 method for class 'selection'
predict( object, newdata = NULL,
   part = ifelse( type %in% c( "unconditional", "conditional" ),
      "outcome", "selection" ),
   type = "unconditional", ... )

Arguments

object

a fitted object of class selection.

newdata

optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors or the fitted response values are returned.

part

character string indicating for which equation the predicted variables should be calculated: "selection" for the predicted values of the selection equation and "outcome" for the predicted values of the outcome equation; this argument is automatically chosen depending on the value of argument type.

type

if argument type is "link" and argument part is "selection", the linear predictors of the selection equation are returned; if argument type is "response" and argument part is "selection", the predicted probabilities of the selection equation are returned; if argument type is "unconditional" and argument part is "outcome", the unconditional expectations are returned, i.e. E[y|X] = X %*% beta; if argument type is "conditional" and argument part is "outcome", the conditional expectations are returned, i.e. E[y|X,Z,w=1] = X %*% beta + rho * sigma * dnorm( Z %*% gamma ) / pnorm( Z %*% gamma ).

...

further arguments (currently ignored).

Value

In most cases, a numeric vector of the predicted values is returned. However, there are three exceptions: (i) when predicting the unconditional expectations of a Tobit-5 model, a matrix with two columns is returned, where the two columns correspond to the two outcome equations (E[yo1] and E[yo2]); (ii) when predicting the conditional expectations of a Tobit-2 model, a matrix with two columns is returned, where the first column returns the expectations conditional on the observation being not selected (E[yo|ys=0]), while the second column returns the expectations conditional on the observation being selected (E[yo|ys=1]); (iii) when predicting the conditional expectations of a Tobit-5 model, a matrix with four columns is returned, where the first two columns return the conditional expectations of the first outcome equation (E[yo1|ys=0] and E[yo1|ys=1]) and the last two columns return the conditional expectations of the second outcome equation (E[yo2|ys=0] and E[yo2|ys=1]).

Author(s)

Arne Henningsen and ‘fg nu’ (the code is partly based on the code posted by ‘fg nu’ at https://stackoverflow.com/questions/14005788/predict-function-for-heckman-model)

See Also

selection, predict, predict.probit, residuals.selection, and selection-methods.

Examples

## Greene( 2003 ): example 22.8, page 786
data( Mroz87 )
Mroz87$kids  <- ( Mroz87$kids5 + Mroz87$kids618 > 0 )

# ML estimation
m <- selection( lfp ~ age + I( age^2 ) + faminc + kids + educ,
   wage ~ exper + I( exper^2 ) + educ + city, Mroz87 )
   
predict( m )
predict( m, type = "conditional" ) 
predict( m, type = "link" ) 
predict( m, type = "response" ) 
predict( m, newdata = Mroz87[ 3:9, ] )