OneSampleMR (version 0.1.7)

fsw: Conditional F-statistic of Sanderson and Windmeijer (2016)

Description

fsw calculates the conditional F-statistic of Sanderson and Windmeijer (2016) for each endogenous variable in the model.

Usage

fsw(object)
# S3 method for ivreg
fsw(object)
# S3 method for iv_robust
fsw(object)
# S3 method for fixest
fsw(object)
# S3 method for fsw
print(x, digits = getOption("digits"), ...)

Value

An object of class "fsw" with the following elements:

fswres

matrix with columns for the conditional F-statistics, degrees of freedom, residual degrees of freedom, and p-value. 1 row per endogenous variable.

namesendog

a character vector of the variable names of the endogenous variables.

nendog

the number of endogenous variables.

n

the sample size used for the fitted model.

Arguments

object

An object of class "ivreg" / "iv_robust" / "fixest" containing the results of an IV model fitted by ivreg::ivreg() / AER::ivreg() / estimatr::iv_robust() / fixest::feols() for which to calculate the conditional F-statistics for each endogenous variable.

x

an object of class "fsw".

digits

minimal number of significant digits, see print.default.

...

further arguments passed to or from other methods.

References

Sanderson E and Windmeijer F. A weak instrument F-test in linear IV models with multiple endogenous variables. Journal of Econometrics, 2016, 190, 2, 212-221, tools:::Rd_expr_doi("10.1016/j.jeconom.2015.06.004").

Examples

require(ivreg)
require(AER)
require(estimatr)
require(fixest)
set.seed(12345)
n   <- 4000
z1  <- rnorm(n)
z2  <- rnorm(n)
w1  <- rnorm(n)
w2  <- rnorm(n)
u   <- rnorm(n)
x1  <- z1 + z2 + 0.2*u + 0.1*w1 + rnorm(n)
x2  <- z1 + 0.94*z2 - 0.3*u + 0.1*w2 + rnorm(n)
y   <- x1 + x2 + w1 + w2 + u
dat <- data.frame(w1, w2, x1, x2, y, z1, z2)
mod1 <- ivreg::ivreg(y ~ x1 + x2 + w1 + w2 | z1 + z2 + w1 + w2, data = dat)
mod2 <- AER::ivreg(y ~ x1 + x2 + w1 + w2 | z1 + z2 + w1 + w2, data = dat)
mod3 <- estimatr::iv_robust(y ~ x1 + x2 + w1 + w2 | z1 + z2 + w1 + w2,
        data = dat, se_type = "classical")
mod4 <- fixest::feols(y ~ w1 + w2 | x1 + x2 ~ z1 + z2, data = dat)
fsw(mod1)
fsw(mod2)
fsw(mod3)
fsw(mod4)