gt.bpm can be used to test the hypothesis of absence of endogeneity, correlated model equations/errors or non-random sample selection
in binary bivariate models.
Usage
gt.bpm(x)
Arguments
x
A fitted SemiParBIVProbit object as produced by SemiParBIVProbit().
Value
It returns a numeric p-value corresponding to the null hypothesis that the correlation, $\theta$, is equal to 0.
WARNINGS
This test's implementation is only valid for bivariate binary models with normal errors.
Details
The gradient test was first proposed by Terrell (2002) and it is based on classic likelihood
theory. See Marra et al. (in press) for full details.
References
Marra G., Radice R. and Filippou P. (in press), Regression Spline Bivariate Probit Models: A Practical Approach to Testing for Exogeneity. Communications in Statistics - Simulation and Computation.
Terrell G. (2002), The Gradient Statistic. Computing Science and Statistics, 34, 206-215.