plm (version 1.6-5)

pvcm: Variable Coefficients Models for Panel Data

Description

Estimators for random and fixed effects models with variable coefficients.

Usage

pvcm(formula, data, subset, na.action, effect = c("individual","time"), model = c("within","random"), index = NULL, ...)
"summary"(object, ...)
"print"(x, digits = max(3, getOption("digits") -2), width = getOption("width"), ...)

Arguments

formula

a symbolic description for the model to be estimated,

object, x

an object of class "pvcm",

data

a data.frame,

subset

see lm,

na.action

see lm,

effect

the effects introduced in the model: one of "individual", "time",

model

one of "within", "random",

index

the indexes, see pdata.frame,

digits

digits,

width

the maximum length of the lines in the print output,

...

further arguments.

Value

An object of class c("pvcm","panelmodel"), which has the following elements :pvcm objects have print, summary and print.summary methods.

Details

pvcm estimates variable coefficients models. Time or individual effects are introduced, respectively, if effect="time" or effect="individual" (the default value). Coefficients are assumed to be fixed if model="within" and random if model="random". In the first case, a different model is estimated for each individual (or time period). In the second case, the Swamy (1970) model is estimated. It is a generalized least squares model which uses the results of the previous model.

References

Swamy, P.A.V.B. (1970). Efficient Inference in a Random Coefficient Regression Model, Econometrica, 38(2), pp.311--323.

Examples

data("Produc", package = "plm")
zw <- pvcm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc, model = "within")
zr <- pvcm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc, model = "random")