Bread for Sandwiches
Extract the estimator for the bread of sandwhiches
(see bread
).
## S3 method for class 'systemfit' bread( obj, ... )
obj |
an object of class |
... |
further arguments (currently ignored). |
Quadratic symmetric matrix,
which is an estimator for the expectation of the negative derivative
of the estimating function (see estfun.systemfit
).
The sandwich package must be loaded before this method can be used.
This method might not be suitable for specific formulas for 3SLS estimations in case of unbalanced systems or different instruments for different equations.
Arne Henningsen
data( "Kmenta" ) eqDemand <- consump ~ price + income eqSupply <- consump ~ price + farmPrice + trend system <- list( demand = eqDemand, supply = eqSupply ) inst <- ~ income + farmPrice + trend ## OLS estimation fitols <- systemfit( system, "OLS", data = Kmenta ) ## obtain the bread library( "sandwich" ) bread( fitols ) ## this is only true for OLS models all.equal( bread( fitols ), solve( crossprod( model.matrix( fitols ) ) / 40 ) ) ## 2SLS estimation fit2sls <- systemfit( system, "2SLS", inst = inst, data = Kmenta ) ## obtain the bread bread( fit2sls ) ## this is only true for 2SLS models all.equal( bread( fit2sls ), solve( crossprod( model.matrix( fit2sls, which = "xHat" ) ) / 40 ) ) ## iterated SUR estimation fitsur <- systemfit( system, "SUR", data = Kmenta, maxit = 100 ) ## obtain the bread bread( fitsur ) ## this should be true for SUR and WLS models all.equal( bread( fitsur ), solve( t( model.matrix( fitsur ) ) %*% ( ( solve( fitsur$residCovEst ) %x% diag( nrow( Kmenta ) ) ) %*% model.matrix( fitsur ) ) / 40 ), check.attributes = FALSE ) ## 3SLS estimation fit3sls <- systemfit( system, "3SLS", inst = inst, data = Kmenta ) ## obtain the bread bread( fit3sls ) ## this should be true for 3SLS and W2SLS models all.equal( bread( fit3sls ), solve( t( model.matrix( fit3sls, which = "xHat" ) ) %*% ( ( solve( fit3sls$residCovEst ) %x% diag( nrow( Kmenta ) ) ) %*% model.matrix( fit3sls, which = "xHat" ) ) / 40 ), check.attributes = FALSE )
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