jtest.fct {pdynmc}

Hansen J-Test.

Description

jtest.fct tests the validity of the overidentifying restrictions.

Usage

jtest.fct(object)

Arguments

object

An object of class 'pdynmc'.

Details

The null hypothesis is that the overidentifying restrictions are valid. The test statistic is computed as proposed by Hansen (1982). As noted by Bowsher (2002) and Windmeijer (2005) the test statistic is weakened by many instruments.

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.

References

Bowsher CG (2002). “On testing overidentifying restrictions in dynamic panel data models.” Economics Letters, 77(2), 211–220. doi:10.1016/S0165-1765(02)00130-1.

Hansen LP (1982). “Large Sample Properties of Generalized Method of Moments Estimators.” Econometrica, 50(4), 1029–1054. doi:10.2307/1912775.

Windmeijer F (2005). “A finite sample correction for the variance of linear efficient two-step GMM estimators.” Journal of Econometrics, 126(1), 25–51. doi:10.1016/j.jeconom.2004.02.005.

See Also

pdynmc for fitting a linear dynamic panel data model.

Examples

## Load data
data(ABdata, package = "pdynmc")
dat <- ABdata
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)


## Load data
 data(ABdata, package = "pdynmc")
 dat <- ABdata
 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)