vcovPC {sandwich} | R Documentation

## Panel-Corrected Covariance Matrix Estimation

### Description

Estimation of sandwich covariances a la Beck and Katz (1995) for panel data.

### Usage

    vcovPC(x, cluster = NULL, order.by = NULL,
      pairwise = FALSE, sandwich = TRUE, fix = FALSE, ...)

    meatPC(x, cluster = NULL, order.by = NULL,
      pairwise = FALSE, kronecker = TRUE, ...)

### Arguments

`x` | a fitted model object.
`cluster` | a variable indicating the clustering of observations or a `list` (or `data.frame`) thereof. By default, either `attr(x, "cluster")` is used.
`order.by` | a variable indicating the aggregation within time periods.
`pairwise` | logical. For unbalanced panels. Indicating whether the meat should be estimated pair- or casewise.
`sandwich` | logical. Should the sandwich estimator be computed? If set to `FALSE` only the meat matrix is returned.
`fix` | logical. Should the covariance matrix be fixed to be positive semi-definite in case it is not?
`kronecker` | logical. Calculate the meat via the Kronecker-product, shortening the computation time for small matrices. For large matrices, set `kronecker = FALSE`.
`...` | arguments passed to the `meatPC` or `estfun` function, respectively.

### Details

`vcovPC` is a function for estimating Beck and Katz (1995) panel-corrected covariance matrix.

The function `meatPC` is the work horse for estimating the meat of Beck and Katz (1995) covariance matrix estimators. `vcovPC` is a wrapper calling `sandwich` and `bread` (Zeileis 2006).

Following Bailey and Katz (2011), there are two alternatives to estimate the meat for unbalanced panels. For `pairwise = FALSE`, a balanced subset of the panel is used, whereas for `pairwise = TRUE`, a pairwise balanced sample is employed.

### Value

A matrix containing the covariance matrix estimate.

### References

Bailey D & Katz JN (2011). “Implementing Panel-Corrected Standard Errors in R: The pcse Package”, Journal of Statistical Software, Code Snippets, 42(1), 1–11. URL http://www.jstatsoft.org/v42/c01/

Beck N & Katz JN (1995). “What To Do (and Not To Do) with Time-Series-Cross-Section Data in Comparative Politics”, American Political Science Review, 89(3), 634–647. URL http://www.jstor.org/stable/2082979

Zeileis A (2004). “Econometric Computing with HC and HAC Covariance Matrix Estimator”, Journal of Statistical Software, 11(10), 1–17. doi: 10.18637/jss.v011.i10

Zeileis A (2006). “Object-Oriented Computation of Sandwich Estimators”, Journal of Statistical Software, 16(9), 1–16. doi: 10.18637/jss.v016.i09

### Examples

    ## Petersen's data
    data("PetersenCL", package = "sandwich")
    m <- lm(y ~ x, data = PetersenCL)

    ## Beck and Katz (1995) standard errors
    ## balanced panel
    sqrt(diag(vcovPC(m, cluster = PetersenCL$firm, order.by = PetersenCL$year)))

    ## unbalanced panel
    PU <- subset(PetersenCL, !(firm == 1 & year == 10))
    pu_lm <- lm(y ~ x, data = PU)
    sqrt(diag(vcovPC(pu_lm, cluster = PU$firm, order.by = PU$year, pairwise = TRUE)))
    sqrt(diag(vcovPC(pu_lm, cluster = PU$firm, order.by = PU$year, pairwise = FALSE)))

[Package sandwich version 2.4-0 Index]