# pvcm

From plm v2.2-5
0th

Percentile

##### Variable Coefficients Models for Panel Data

Estimators for random and fixed effects models with variable coefficients.

Keywords
regression
##### Usage
pvcm(
formula,
data,
subset,
na.action,
effect = c("individual", "time"),
model = c("within", "random"),
index = NULL,
...
)# S3 method for pvcm
summary(object, ...)# S3 method for summary.pvcm
print(
x,
digits = max(3, getOption("digits") - 2),
width = getOption("width"),
...
)
##### Arguments
formula

a symbolic description for the model to be estimated,

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(),

further arguments.

object, x

an object of class "pvcm",

digits

digits,

width

the maximum length of the lines in the print output,

##### Details

pvcm estimates variable coefficients models. Individual or time effects are introduced, respectively, if effect = "individual" (default) or effect = "time".

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 SWAM:70;textualplm model is estimated. It is a generalized least squares model which uses the results of the previous model.

##### Value

An object of class c("pvcm", "panelmodel"), which has the following elements:

coefficients

the vector (or the data frame for fixed effects) of coefficients,

residuals

the vector of residuals,

fitted.values

the vector of fitted values,

vcov

the covariance matrix of the coefficients (a list for fixed effects),

df.residual

degrees of freedom of the residuals,

model

a data frame containing the variables used for the estimation,

call

the call,

Delta

the estimation of the covariance matrix of the coefficients (random effect models only),

std.error

a data frame containing standard errors for all coefficients for each individual (within models only).

pvcm objects have print, summary and print.summary methods.

SWAM:70plm

##### Aliases
• pvcm
• summary.pvcm
• print.summary.pvcm
##### Examples
# NOT RUN {
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")

## replicate Greene (2012), p. 419, table 11.14
summary(pvcm(log(gsp) ~ log(pc) + log(hwy) + log(water) + log(util) + log(emp) + unemp,
data = Produc, model = "random"))

# }
# NOT RUN {
# replicate Swamy (1970), p. 166, table 5.2
data(Grunfeld, package = "AER") # 11 firm Grunfeld data needed from package AER
gw <- pvcm(invest ~ value + capital, data = Grunfeld, index = c("firm", "year"))
# }
# NOT RUN {

# }

Documentation reproduced from package plm, version 2.2-5, License: GPL (>= 2)

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