lmtest::bptest tests OLS residuals, also for FE as input

Question

I want to test a fixed effects regression for heteroscedasticity with lmtest::bptest. The test results I get from bptest are identical for a fixed effects regression and OLS.

It seems as if bptestautomatically extracts the formula from the input object and runs an OLS with those variables, regardless of the regression model of the input. From the ?bptest:

The Breusch-Pagan test fits a linear regression model to the residuals of a linear regression model (by default the same explanatory variables are taken as in the main regression model) and rejects if too much of the variance is explained by the additional explanatory variables.

No error or warning is produced to tell you that the output of the function is not based on the model you used as input.

Question

First of all, is there a way to test my plm-object for heteroscedasticity with pbtest? Since I am assuming there's not, is there a way to run a Breusch Pagan test for a fixed effects regression?

Here is a reproducible example:

# load the data:
df <- structure(list(country = c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5), year = c(2010, 
         2015, 2010, 2015, 2010, 2015, 2010, 2015, 2010, 2015), dv1 = c(28.61, 
         31.13, 38.87, 39.46, 68.42, 70.39, 79.36, 80.55, 70.14, 71.48
         ), iv1 = c(-20.68, 0, NA, NA, -19.41, -18.73, 24.98, 25.23, 21.23, 
         -21.06), iv2 = c(-4.23, NA, NA, NA, -4.92, -4.22, 9.19, 9.37, 
         4.15, -3.92)), .Names = c("country", "year", "dv1", "iv1", "iv2"
         ), row.names = c(2L, 3L, 5L, 6L, 8L, 9L, 11L, 12L, 14L, 15L),class    
         ="data.frame")
library(plm)
library(lmtest)


# Run the fixed effects regression
FEoutput <- plm(dv1 ~ iv1 + iv2, data = df, 
             model = "within", index = c("country", "year"))
bptest(FEoutput)
#   studentized Breusch-Pagan test
#
#    data:  FEoutput
#    BP = 1.9052, df = 2, p-value = 0.3857


# Run the OLS regression
OLSoutput <- lm(dv1 ~ iv1 + iv2, data = df)
bptest(OLSoutput)
#   studentized Breusch-Pagan test
#
#    data:  OLSoutput
#    BP = 1.9052, df = 2, p-value = 0.3857

Including country dummies into the OLS regression to create a fixed effects regression also didn't work, because the country dummies increase the degrees of freedom of the test:

OLSctry <- lm(dv1 ~ iv1 + iv2 + factor(country), data = df)
bptest(OLSctry)
# studentized Breusch-Pagan test
#
# data:  OLSctry
# BP = 7, df = 5, p-value = 0.2206

Thanks in advance!

Helix123 Helix123 · Accepted Answer · 2016-08-15T09:19:22

You will need a wrapper around lmtest::bptest to run it on plm object's (quasi-)demeaned data. Here is one, I called it pbptest:

pbptest <-function(x, ...) {
  ## residual heteroskedasticity test based on the residuals of the demeaned
  ## model and the regular bptest() in {lmtest}

  ## structure:
  ## 1: take demeaned data from 'plm' object
  ## 2: est. auxiliary model by OLS on demeaned data
  ## 3: apply bptest() to auxiliary model and return the result

  if (!inherits(x, "plm")) stop("need to supply a panelmodel estimated with plm()")
  model <- plm:::describe(x, "model")
  effect <- plm:::describe(x, "effect")
  theta <- x$ercomp$theta

  ## retrieve demeaned data
  demX <- model.matrix(x, model = model, effect = effect, theta = theta)
  demy <- pmodel.response(model.frame(x), model = model, effect = effect, theta = theta)

  Ti <- pdim(x)$Tint$Ti

  if (is.null(order)) order <- min(Ti)

  ## bgtest on the demeaned model:

  ## check package availability and load if necessary
  lm.ok <- require("lmtest")
  if(!lm.ok) stop("package lmtest is needed but not available")

  ## pbptest is the bptest, exception made for the method attribute
  dots <- match.call(expand.dots=FALSE)[["..."]]
  if (!is.null(dots$type)) type <- dots$type else type <- "Chisq"
  if (!is.null(dots$order.by)) order.by <- dots$order.by else order.by <- NULL

  auxformula <- demy~demX-1
  lm.mod <- lm(auxformula)
  return(lmtest::bptest(lm.mod, ...)) # call and return lmtest::bptest
} # END pbptest()

lmtest::bptest tests OLS residuals, also for FE as input

Question

1 Answers