pdynmc (version 0.9.12)

mtest.fct: Arellano and Bond Serial Correlation Test.

Description

mtest.pdynmc Methods to test for serial correlation in the error terms for objects of class `pdynmc`.

Usage

mtest.fct(object, order = 2, ...)

Value

An object of class `htest` which contains the Arellano and Bond m test statistic and corresponding p-value for the null hypothesis that there is no serial correlation of the given order.

Arguments

object

An object of class `pdynmc`.

order

A number denoting the order of serial correlation to test for (defaults to `2`).

...

further arguments.

Details

The null hypothesis is that there is no serial correlation of a particular order. The test statistic is computed as proposed by AreBon1991;textualpdynmc and Are2003;textualpdynmc.

References

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")
mtest.fct(m1, order = 2)

# \donttest{
## 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")
 mtest.fct(m1, order = 2)
# }