systemfit (version 0.5-6)

se.ratio: Ratio of the Standard Errors

Description

se.ratio.systemfit returns a vector of the ratios of the standard errors of the predictions for two equations.

Usage

se.ratio.systemfit( resultsi, resultsj, eqni )

Arguments

resultsi

an object of type systemfit.system (ols, twostage or threestage.

resultsj

an object of type systemfit.system (ols, twostage or threestage.

eqni

index for equation to obtain the ratio of standard errors

Value

• se.ratio returns a vector of the standard errors of the ratios for the predictions between the predicted values in equation i and equation j.

References

Hasenauer, H; Monserud, R and T. Gregoire. (1998) Using Simultaneous Regression Techniques with Individual-Tree Growth Models. Forest Science. 44(1):87-95

See Also

ols,twostage,surand threestage

Examples

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 <- twostage.systemfit( system, inst, labels, kmenta )
fit3sls <- threestage.systemfit( system, inst, labels, kmenta )

## print the results from the fits
print( fit2sls )
print( fit3sls )
print( "covariance of residuals used for estimation (from 2sls)" )
print( varcov.systemfit( fit2sls ) )
print( "covariance of residuals" )
print( varcov.systemfit( fit3sls ) )

## examine the correlation between the predicted values
## of suppy and demand by plotting the correlation over
## the value of q
r12 <- correlation.systemfit( fit3sls, 1, 2 )
plot( q, r12, main="correlation between predictions from supply and demand" )  

## examine the improvement of 3SLS over OLS 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 ) )