ivreg {AER} | R Documentation |
Fit instrumental-variable regression by two-stage least squares. This is equivalent to direct instrumental-variables estimation when the number of instruments is equal to the number of predictors.
ivreg(formula, instruments, data, subset, na.action, weights, offset, contrasts = NULL, model = TRUE, y = TRUE, x = FALSE, ...)
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 from which ivreg is
called. |
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 NA s. 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, x, y |
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 . |
ivreg
is the high-level interface to the work-horse function ivreg.fit
,
a set of standard methods (including print
, summary
, vcov
, anova
,
hatvalues
, predict
, terms
, model.matrix
, bread
,
estfun
) is available and described on summary.ivreg
.
ivreg
returns an object 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. |
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. |
hatvalues |
regression hat values. |
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 (if y = TRUE ). |
x |
a list with elements "regressors" , "instruments" , "projected" ,
containing the model matrices from the respective components
(if x = TRUE ). "projected" is the matrix of regressors projected
on the image of the instruments. |
Greene, W. H. (1993) Econometric Analysis, 2nd ed., Macmillan.
## data data("CigarettesSW") CigarettesSW$rprice <- with(CigarettesSW, price/cpi) CigarettesSW$rincome <- with(CigarettesSW, income/population/cpi) CigarettesSW$tdiff <- with(CigarettesSW, (taxs - tax)/cpi) ## model fm <- ivreg(log(packs) ~ log(rprice) + log(rincome) | log(rincome) + tdiff + I(tax/cpi), data = CigarettesSW, subset = year == "1995") summary(fm) ## ANOVA fm2 <- ivreg(log(packs) ~ log(rprice) | tdiff, data = CigarettesSW, subset = year == "1995") anova(fm, fm2)