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micEcon (version 0.4-0)

tobit2fit: Fitting Parametric Sample Selection Models

Description

These functions do the actual fitting of tobit-2 (sample selection) and tobit-5 (switching regression) models by Maximum Likelihood (ML) estimation. The arguments must be given as numeric vectors/matrices, initial value of parameters must be specified. These functions are called by selection and are intended for micEcon internal use.

Usage

tobit2fit(YS, XS, YO, XO, start, print.level = 0,
maxMethod="Newton-Raphson", ...)
tobit5fit(YS, XS, YO1, XO1, YO2, XO2, start, print.level=0, maxMethod="Newton-Raphson", ...)

Arguments

YS
numeric 0/1 vector, where 0 denotes unobserved outcome (tobit 2) or outcome 1 observed (tobit 5).
XS, XO, XO1, XO2
numeric matrix, model matrix for selection and outcome equations.
YO
numeric vector, observed outcomes. Values for unobserved outcomes are ignored (they may or may not be NA).
start
numeric vector of initial values. The order is: betaS, betaO(1), sigma(1), rho(1), betaO2, sigma2, rho2.
print.level
numeric, values greater than 0 will produce increasingly more debugging information.
maxMethod
character, a maximisation method supported by maxLik
...
Additional parameters to maxLik.

Value

  • Object of class "selection". It inherits from class "maxLik" and includes two additional components: $tobitType, numeric tobit model classifier (see Amemiya, 1985), and $method, either "ml" or "2step", specifying the estimation method.

References

Amemiya, T. (1985) Advanced Ecnometrics, Harvard University Press

See Also

selection, maxLik