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Last data update: 2014.03.03

R: Pairs Cluster Bootstrapped p-Values For PLM

cluster.bs.plm

R Documentation

Pairs Cluster Bootstrapped p-Values For PLM

Description

This software estimates p-values using pairs cluster bootstrapped t-statistics for fixed effects panel linear models (Cameron, Gelbach, and Miller 2008). The data set is repeatedly re-sampled by cluster, a model is estimated, and inference is based on the sampling distribution of the pivotal (t) statistic.

Usage

cluster.bs.plm(mod, dat, cluster = "group", ci.level = 0.95,
  boot.reps = 1000, cluster.se = TRUE, report = TRUE, prog.bar = TRUE)

Arguments

`mod`	A "within" model estimated using `plm`.
`dat`	The data set used to estimate `mod`.
`cluster`	Clustering dimension ("group", the default, or "time").
`ci.level`	What confidence level should CIs reflect?
`boot.reps`	The number of bootstrap samples to draw.
`cluster.se`	Use clustered standard errors (= TRUE) or ordinary SEs (= FALSE) for bootstrap replicates.
`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.

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.bs.plm(mod=emp.1, dat=EmplUK, cluster="group", ci.level = 0.95, 
          boot.reps = 1000, cluster.se = TRUE, report = TRUE, 
          prog.bar = TRUE)

# cluster on time

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


## End(Not run)