# pvcm

##### 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:

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

the vector of residuals,

the vector of fitted values,

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

degrees of freedom of the residuals,

a data frame containing the variables used for the estimation,

the call,

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

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

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

##### References

SWAM:70plm

##### 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)*