R: Estimation of the error components

ercomp {plm} | R Documentation

## Estimation of the error components

### Description

This function enables the estimation of the variance components of a panel model.

### Usage

    ercomp(object, ...)
    ## S3 method for class 'formula'
    ercomp(object, data, effect = c("individual", "time", "twoways"),
                             method = c("swar", "walhus", "amemiya","nerlove"),
                             dfcor = NULL, index = NULL, ...)
    ## S3 method for class 'plm'
    ercomp(object, ...)
    ## S3 method for class 'ercomp'
    print(x, digits= max(3, getOption("digits") - 3), ...)

### Arguments

`object` | a `formula` or a `plm` object,
`data` | a `data.frame`,
`effect` | the effects introduced in the model, see `lm` for details,
`method` | method of estimation for the variance components, see `lm` for details,
`dfcor` | a numeric vector of length 2 indicating which degree of freedom should be used,
`index` | the indexes,
`x` | a `ercomp` object,
`digits` | digits,
`...` | further arguments.

### Value

An object of class `"ercomp"`: a list containing a list called `sigma2` which contains the estimates of the variance components, and `theta` which is the parameters used for the transformation of the variables.

### Author(s)

Yves Croissant

### References

Amemiya, T. (1971) The estimation of the variances in a variance–components model, International Economic Review, 12(1), pp. 1–13.

Nerlove, M. (1971) Further evidence on the estimation of dynamic economic relations from a time–series of cross–sections, Econometrica, 39(2), pp. 359–382.

Swamy, P.A.V.B. and Arora, S.S. (1972) The exact finite sample properties of the estimators of coefficients in the error components regression models, Econometrica, 40(2), pp. 261–275.

Wallace, T.D. and Hussain, A. (1969) The use of error components models in combining cross section with time series data, Econometrica, 37(1), pp. 55–72.

### See Also

`plm` where the estimates of the variance components are used if a random effects model is estimated

### Examples

    data("Produc", package = "plm")
    # an example of the formula method
    ercomp(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc,
           method = "walhus", effect = "time")
    # same with the plm method
    z <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
             data = Produc, random.method = "walhus",
             effect = "time", model = "random")
    ercomp(z)
    # a two-ways model
    ercomp(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc,
           method = "amemiya",effect = "twoways")

[Package plm version 1.6-5 Index]