library( systemfit )
data( kmenta )
attach( kmenta )
demand <- q ~ p + d
supply <- q ~ p + f + a
inst <- ~ d + f + a
labels <- list( "demand", "supply" )
system <- list( demand, supply )
## perform 2SLS on each of the equations in the system
fit2sls <- systemfit( "2SLS", system, labels, inst )
fit3sls <- systemfit( "3SLS", system, labels, inst )
## print the results from the fits
print( fit2sls )
print( fit3sls )
print( "covariance of residuals used for estimation (from 2sls)" )
print( fit3sls$rcovest )
print( "covariance of residuals" )
print( fit3sls$rcov )
## examine the improvement of 3SLS over 2SLS by computing
## the ratio of the standard errors of the estimates
improve.ratio <- se.ratio.systemfit( fit2sls, fit3sls, 2 )
print( "summary values for the ratio in the std. err. for the predictions" )
print( summary( improve.ratio ) )
Run the code above in your browser using DataLab