ivreg.EX: Constructing independent evidence (EX estimates) in an IV...

In ivregEX: Create Independent Evidence in IV Analyses and Do Sensitivity Analysis in Regression and IV Analysis

Description

This function uses the same arguments as ivreg and additionally outputs the EX analysis.

Usage

ivreg.EX(formula, instruments, data, subset, na.action, weights, offset,
  contrasts = NULL, model = TRUE, ...)

Arguments

formula, instruments	formula specification(s) of the regression relationship and the instruments. Either instruments is missing and formula has three parts as in y ~ x1 + x2 | z1 + z2 + z3 (recommended) or formula is y ~ x1 + x2 and instruments is a one-sided formula ~ z1 + z2 + z3 (only for backward compatibility).
data	an optional data frame containing the variables in the model. By default the variables are taken from the environment of the formula.
subset	an optional vector specifying a subset of observations to be used in fitting the model.
na.action	a function that indicates what should happen when the data contain NAs. The default is set by the na.action option.
weights	an optional vector of weights to be used in the fitting process.
offset	an optional offset that can be used to specify an a priori known component to be included during fitting.
contrasts	an optional list. See the contrasts.arg of model.matrix.default.
model	logicals. If TRUE the corresponding components of the fit (the model frame, the model matrices , the response) are returned.
...	further arguments passed to ivreg.fit.EX.

Details

See Details on the arguments and others see ivreg of AER package. Statistical analysis and sensitivity analysis based on the output of ivreg.EX is performed in coeftestIV and sensIvreg functions.

Value

ivreg.EX returns an object of class "ivregEX" (also of class "ivreg"), with the following components:

coefficients	parameter estimates.
residuals	a vector of residuals.
fitted.values	a vector of predicted means.
weights	either the vector of weights used (if any) or NULL (if none).
offset	either the offset used (if any) or NULL (if none).
n	number of observations.
nobs	number of observations with non-zero weights.
rank	the numeric rank of the fitted linear model.
df.residual	residual degrees of freedom for fitted model.
cov.unscaled	unscaled covariance matrix for the coefficients.
sigma	residual standard error.
call	the original function call.
formula	the model formula.
terms	a list with elements "regressors" and "instruments" containing the terms objects for the respective components.
levels	levels of the categorical regressors.
contrasts	the contrasts used for categorical regressors.
model	the full model frame (if model = TRUE).
y	the response vector.
x	a list with elements "regressors", "instruments", "projected", containing the model matrices from the respective components. "projected" is the matrix of regressors projected on the image of the instruments.

See Also

ivreg, coeftestIV

Examples

data("CigarettesSW", package = "AER")
CigarettesSW$rprice <- with(CigarettesSW, price/cpi)
CigarettesSW$rincome <- with(CigarettesSW, income/population/cpi)
CigarettesSW$tdiff <- with(CigarettesSW, (taxs - tax)/cpi)

fm2 <- ivreg.EX(log(packs) ~ log(rprice) + log(rincome) | tdiff + log(rincome), 
		data = CigarettesSW, subset = year == "1995")
lmfit <- lm(log(packs) ~ log(rprice) + log(rincome), data = CigarettesSW, subset = year == "1995")

coeftestIV(fm2, lmfit, 'log(rprice)')

ivregEX documentation built on May 1, 2019, 10:08 p.m.