pdynmc (version 0.9.6)

jtest.fct: Hansen J-Test.

Description

jtest.fct tests the validity of the overidentifying restrictions.

Usage

jtest.fct(object)

Arguments

object

An object of class `pdynmc`.

Value

An object of class `htest` which contains the Hansen J-test statistic and corresponding p-value for the null hypothesis that the overidentifying restrictions are valid.

Details

The null hypothesis is that the overidentifying restrictions are valid. The test statistic is computed as proposed by Han1982large;textualpdynmc. As noted by Bow2002testing;textualpdynmc and Win2005;textualpdynmc the test statistic is weakened by many instruments.

References

See Also

pdynmc for fitting a linear dynamic panel data model.

Examples

# NOT RUN {
## Load data from plm package
if(!requireNamespace("plm", quietly = TRUE)){
 stop("Dataset from package \"plm\" needed for this example.
 Please install the package.", call. = FALSE)
} else{
 data(EmplUK, package = "plm")
 dat <- EmplUK
 dat[,c(4:7)] <- log(dat[,c(4:7)])
 dat <- dat[c(140:0), ]

## Code example
 m1 <- pdynmc(dat = dat, varname.i = "firm", varname.t = "year",
    use.mc.diff = TRUE, use.mc.lev = FALSE, use.mc.nonlin = FALSE,
    include.y = TRUE, varname.y = "emp", lagTerms.y = 2,
    fur.con = TRUE, fur.con.diff = TRUE, fur.con.lev = FALSE,
    varname.reg.fur = c("wage", "capital", "output"), lagTerms.reg.fur = c(1,2,2),
    include.dum = TRUE, dum.diff = TRUE, dum.lev = FALSE, varname.dum = "year",
    w.mat = "iid.err", std.err = "corrected", estimation = "onestep",
    opt.meth = "none")
 jtest.fct(m1)
}

# }
# NOT RUN {
## Load data from plm package
if(!requireNamespace("plm", quietly = TRUE)){
 stop("Dataset from package \"plm\" needed for this example.
 Please install the package.", call. = FALSE)
} else{
 data(EmplUK, package = "plm")
 dat <- EmplUK
 dat[,c(4:7)] <- log(dat[,c(4:7)])

## Further code example
 m1 <- pdynmc(dat = dat, varname.i = "firm", varname.t = "year",
    use.mc.diff = TRUE, use.mc.lev = FALSE, use.mc.nonlin = FALSE,
    include.y = TRUE, varname.y = "emp", lagTerms.y = 2,
    fur.con = TRUE, fur.con.diff = TRUE, fur.con.lev = FALSE,
    varname.reg.fur = c("wage", "capital", "output"), lagTerms.reg.fur = c(1,2,2),
    include.dum = TRUE, dum.diff = TRUE, dum.lev = FALSE, varname.dum = "year",
    w.mat = "iid.err", std.err = "corrected", estimation = "onestep",
    opt.meth = "none")
 jtest.fct(m1)
}
# }
# NOT RUN {

# }