R: Common Correlated Effects estimators

pcce {plm} | R Documentation

## Common Correlated Effects estimators

### Description

Common Correlated Effects Mean Groups (CCEMG) and Pooled (CCEP) estimators for panel data with common factors (balanced or unbalanced)

### Usage

    pcce(formula, data, subset, na.action,
         model=c("mg", "p"),
         index = NULL, trend = FALSE, ...)
    ## S3 method for class 'pcce'
    summary(object, ...)
    ## S3 method for class 'summary.pcce'
    print(x,digits = max(3, getOption("digits") -
    2), width = getOption("width"), ...)

### Arguments

`formula` | a symbolic description of the model to be estimated,
`object, x` | an object of class `pcce`,
`data` | a `data.frame`,
`subset` | see `lm`,
`na.action` | see `lm`,
`model` | one of `c("mg","p")`, selects Mean Groups vs. Pooled CCE model,
`index` | the indexes, see `pdata.frame`,
`trend` | logical specifying whether an individual-specific trend has to be included,
`digits` | digits,
`width` | the maximum length of the lines in the print output,
`...` | further arguments.

### Details

`pcce` is a function for the estimation of linear panel models by the Common Correlated Effects Mean Groups or Pooled estimator, consistent under the hypothesis of unobserved common factors and idiosyncratic factor loadings; CCE estimators works by augmenting the model by cross-sectional averages of the dependent variable and regressors in order to account for the common factors, and adding individual intercepts and possibly trends.

### Value

An object of class `c("pcce","panelmodel")` containing:

`coefficients` | the vector of coefficients,
`residuals` | the vector of (defactored) residuals,
`stdres` | the vector of (raw) residuals,
`tr.model` | the transformed data after projection on H,
`fitted.values` | the vector of fitted.values,
`vcov` | the covariance matrix of the coefficients,
`df.residual` | degrees of freedom of the residuals,
`model` | a data.frame containing the variables used for the estimation,
`call` | the call,
`sigma` | always `NULL`, `sigma` is here only for compatibility reasons (to allow using the same `summary` and `print` methods as `pggls`),
`indcoef` | the matrix of individual coefficients from separate time series regressions.

### Author(s)

Giovanni Millo

### References

G. Kapetanios, M. Hashem Pesaran, T. Yamagata (2011), Panels with non-stationary multifactor error structures, Journal of Econometrics, 160(2), pp. 326–348.

### Examples

    data("Produc", package = "plm")
    ccepmod <- pcce(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc, model="p")
    summary(ccepmod)

[Package plm version 1.6-5 Index]