R Graphical Manual

Browse All

Last data update: 2014.03.03

R: Wild Cluster Bootstrapped p-Values For PLM

cluster.wild.plm

R Documentation

Wild Cluster Bootstrapped p-Values For PLM

Description

This software estimates p-values using wild cluster bootstrapped t-statistics for fixed effects panel linear models (Cameron, Gelbach, and Miller 2008). Residuals are repeatedly re-sampled by cluster to form a pseudo-dependent variable, a model is estimated for each re-sampled data set, and inference is based on the sampling distribution of the pivotal (t) statistic. The null is never imposed for PLM models.

Usage

cluster.wild.plm(mod, dat, cluster, ci.level = 0.95, boot.reps = 1000,
  report = TRUE, prog.bar = TRUE)

Arguments

`mod`	A "within" model estimated using `plm`.
`dat`	The data set used to estimate `mod`.
`cluster`	A formula of the clustering variable.
`ci.level`	What confidence level should CIs reflect? (Note: only reported when `impose.null == FALSE`).
`boot.reps`	The number of bootstrap samples to draw.
`report`	Should a table of results be printed to the console?
`prog.bar`	Show a progress bar of the bootstrap (= TRUE) or not (= FALSE).

Value

A list with the elements

`p.values`	A matrix of the estimated p-values.
`ci`	A matrix of confidence intervals (if null not imposed).

Author(s)

Justin Esarey

References

Cameron, A. Colin, Jonah B. Gelbach, and Douglas L. Miller. 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors." The Review of Economics and Statistics 90(3): 414-427. <DOI:10.1162/rest.90.3.414>.

Examples

## Not run: 

# predict employment levels, cluster on group
require(plm)
data(EmplUK)

emp.1 <- plm(emp ~ wage + log(capital+1), data = EmplUK, model = "within",
             index=c("firm", "year"))
cluster.wild.plm(mod=emp.1, dat=EmplUK, cluster="group", ci.level = 0.95,
        boot.reps = 1000, report = TRUE, prog.bar = TRUE)

# cluster on time
cluster.wild.plm(mod=emp.1, dat=EmplUK, cluster="time", ci.level = 0.95, 
            boot.reps = 1000, report = TRUE, prog.bar = TRUE)


## End(Not run)