AR_test: Anderson Rubin Test

Description

Performs the Anderson Rubin test, which is robust to weak instruments.

Usage

AR_test(data, Y, D, Z, controls, FE = NULL, cl = NULL, weights = NULL, 
  prec = 4, CI = TRUE, alpha = 0.05, parallel = NULL, cores = NULL)

Value

Fstat: F statistic, degrees of freedoms, and p-value.
ci.print: Confidence interval via intervsion (printed version).
ci: Confidence interval via intervsion (numeric version).
bounded: If the confidence interval is bounded.

Arguments

data: name of a dataframe.
Y: a string indicating the outcome variable.
D: a string indicating the treatment variable.
Z: a vector of strings indicating the instrumental variables.
controls: a vector of strings indicating the control variables.
FE: a vector of strings indicating the fixed effects variables.
cl: a string indicating the clustering variable.
weights: a string indicating the variable that stores weights.
CI: a logical flag controlling whether to calcualte the confidence interval using the inversion method.
prec: precision of results (4 by default).
alpha: level of statitical significance; the default is 0.05.
parallel: a logical flag controlling parallel computing.
cores: setting the number of cores.

References

Chernozhukov, Victor, and Christian Hansen. 2008. "The Reduced Form: A Simple Approach to Inference with Weak Instruments." Economics Letters 100 (1): 68–71.

Examples

Run this code

data(ivDiag)
AR.out <- AR_test(data = rueda, Y = "e_vote_buying", D = "lm_pob_mesa", 
    Z = "lz_pob_mesa_f", controls = c("lpopulation", "lpotencial"),
    cl = "muni_code", CI = FALSE)
library(testthat)    
test_that("Check AR results", {
  expect_equal(as.numeric(AR.out$Fstat[1]), 48.4768)
})