summary.plm: Summary for plm objects

In plm: Linear Models for Panel Data

Description

The summary method for plm objects generates some more information about estimated plm models.

Usage

## S3 method for class 'plm.list'
summary(object, ...)

## S3 method for class 'summary.plm.list'
coef(object, eq = NULL, ...)

## S3 method for class 'summary.plm.list'
print(
  x,
  digits = max(3, getOption("digits") - 2),
  width = getOption("width"),
  ...
)

## S3 method for class 'plm'
summary(object, vcov = NULL, ...)

## S3 method for class 'summary.plm'
print(
  x,
  digits = max(3, getOption("digits") - 2),
  width = getOption("width"),
  subset = NULL,
  ...
)

Arguments

object	an object of class "plm",
...	further arguments.
eq	the selected equation for list objects
x	an object of class "summary.plm",
digits	number of digits for printed output,
width	the maximum length of the lines in the printed output,
vcov	a variance–covariance matrix furnished by the user or a function to calculate one (see Examples),
subset	a character or numeric vector indicating a subset of the table of coefficients to be printed for "print.summary.plm",

Details

The summary method for plm objects (summary.plm) creates an object of class c("summary.plm", "plm", "panelmodel") that extends the plm object it is run on with various information about the estimated model like (inferential) statistics, see Value. It has an associated print method (print.summary.plm).

Value

An object of class c("summary.plm", "plm", "panelmodel"). Some of its elements are carried over from the associated plm object and described there (plm()). The following elements are new or changed relative to the elements of a plm object:

fstatistic	'htest' object: joint test of significance of coefficients (F or Chi-square test) (robust statistic in case of supplied argument vcov, see pwaldtest() for details),
coefficients	a matrix with the estimated coefficients, standard errors, t–values, and p–values, if argument vcov was set to non-NULL the standard errors (and t– and p–values) in their respective robust variant,
vcov	the "regular" variance–covariance matrix of the coefficients (class "matrix"),
rvcov	only present if argument vcov was set to non-NULL: the furnished variance–covariance matrix of the coefficients (class "matrix"),
r.squared	a named numeric containing the R-squared ("rsq") and the adjusted R-squared ("adjrsq") of the model,
df	an integer vector with 3 components, (p, n-p, p*), where p is the number of estimated (non-aliased) coefficients of the model, n-p are the residual degrees of freedom (n being number of observations), and p* is the total number of coefficients (incl. any aliased ones).

Author(s)

Yves Croissant

See Also

plm() for estimation of various models; vcovHC() for an example of a robust estimation of variance–covariance matrix; r.squared() for the function to calculate R-squared; stats::print.power.htest() for some information about class "htest"; fixef() to compute the fixed effects for "within" (=fixed effects) models and within_intercept() for an "overall intercept" for such models; pwaldtest()

Examples

data("Produc", package = "plm")
zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
          data = Produc, index = c("state","year"))
summary(zz)

# summary with a furnished vcov, passed as matrix, as function, and
# as function with additional argument
data("Grunfeld", package = "plm")
wi <- plm(inv ~ value + capital,
          data = Grunfeld, model="within", effect = "individual")
summary(wi, vcov = vcovHC(wi))
summary(wi, vcov = vcovHC)
summary(wi, vcov = function(x) vcovHC(x, method = "white2"))

# extract F statistic
wi_summary <- summary(wi)
Fstat <- wi_summary[["fstatistic"]]

# extract estimates and p-values
est <- wi_summary[["coefficients"]][ , "Estimate"]
pval <- wi_summary[["coefficients"]][ , "Pr(>|t|)"]

# print summary only for coefficent "value"
print(wi_summary, subset = "value")

plm documentation built on Sept. 21, 2021, 3:01 p.m.