Nothing
## this function returns test statistic for
## the hausman test
# The m-statistic is then distributed with k degrees of freedom, where k
# is the rank of the matrix .A generalized inverse is used, as
# recommended by Hausman (1982).
hausman.systemfit <- function( results2sls, results3sls ) {
result <- list()
if( is.null( results2sls$restrict.regMat ) ) {
result$q <- coef( results2sls ) - coef( results3sls )
result$qVar <- vcov( results2sls ) - vcov( results3sls )
} else {
result$q <- coef( results2sls, modified.regMat = TRUE ) -
coef( results3sls, modified.regMat = TRUE )
result$qVar <- vcov( results2sls, modified.regMat = TRUE ) -
vcov( results3sls, modified.regMat = TRUE )
}
# if( min( eigen( hausman$qVar )$values ) < 0 ) {
# warning( "the matrix V is not 'positive definite'" )
# }
result$statistic <- crossprod( result$q, solve( result$qVar, result$q ) )
names( result$statistic ) <- "Hausman"
result$parameter <- nrow( result$qVar )
names( result$parameter ) <- "df"
result$p.value <- 1 - pchisq( result$statistic, result$parameter )
result$method = paste( "Hausman specification test for consistency of",
"the 3SLS estimation" )
if( "data" %in% names( results2sls$call ) ) {
result$data.name <- results2sls$call$data
} else {
result$data.name <- "unknown"
}
class( result ) <- "htest"
return( result )
}
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