ivregEX (version 1.0)

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

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.

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.

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.

See Also

ivreg, coeftestIV

Examples

# NOT RUN {
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)')

# }