jtest.fct {pdynmc} | R Documentation |
jtest.fct
tests the validity of the overidentifying restrictions.
jtest.fct(object)
object |
An object of class 'pdynmc'. |
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.
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.
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.
pdynmc
for fitting a linear dynamic panel data model.
## 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)