print.summary.pdynmc: Print Summary of Fitted Model Object.

In pdynmc: Moment Condition Based Estimation of Linear Dynamic Panel Data Models

Print Summary of Fitted Model Object.

Description

print.summary.pdynmc prints the summary for objects of class 'pdynmc'.

Usage

## S3 method for class 'summary.pdynmc'
print(
  x,
  digits = max(3, getOption("digits") - 3),
  signif.stars = getOption("show.signif.stars"),
  ...
)

Arguments

x	An object of class 'summary.pdynmc'.
digits	An integer indicating the maximum number of digits to display in the object.
signif.stars	Argument is defined as in options.
...	further arguments.

Value

Print information on objects of class 'summary.pdynmc'.

Author(s)

Markus Fritsch

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(1:140), ]

## 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")
summary(m1)


## Load data
 data(ABdata, package = "pdynmc")
 dat <- ABdata
 dat[,c(4:7)] <- log(dat[,c(4:7)])

 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")
 summary(m1)

pdynmc documentation built on Nov. 25, 2023, 1:08 a.m.