vcovPC {sandwich} | R Documentation |
Estimation of sandwich covariances a la Beck and Katz (1995) for panel data.
vcovPC(x, cluster = NULL, order.by = NULL, pairwise = FALSE, sandwich = TRUE, fix = FALSE, ...) meatPC(x, cluster = NULL, order.by = NULL, pairwise = FALSE, kronecker = TRUE, ...)
x |
a fitted model object. |
cluster |
a variable indicating the clustering of observations
or a |
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 |
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 |
... |
arguments passed to the |
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.
A matrix containing the covariance matrix estimate.
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
## 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)))