# se.ratio.systemfit: Ratio of the Standard Errors In systemfit: Estimating Systems of Simultaneous Equations

 se.ratio.systemfit R Documentation

## 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`. `resultsj` an object of type `systemfit`. `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.

### Author(s)

Jeff D. Hamann jeff.hamann@forestinformatics.com

### References

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

`systemfit` and `correlation.systemfit`

### Examples

``````data( "Kmenta" )
eqDemand <- consump ~ price + income
eqSupply <- consump ~ price + farmPrice + trend
inst <- ~ income + farmPrice + trend
system <- list( demand = eqDemand, supply = eqSupply )

## perform 2SLS on each of the equations in the system
fit2sls <- systemfit( system, "2SLS", inst = inst, data = Kmenta )
fit3sls <- systemfit( system, "3SLS", inst = inst, data = Kmenta )

## print the results from the fits
print( fit2sls )
print( fit3sls )
print( "covariance of residuals used for estimation (from 2sls)" )
print( fit3sls\$residCovEst )
print( "covariance of residuals" )
print( fit3sls\$residCov )

## 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 ) )
``````

systemfit documentation built on March 31, 2023, 9:26 p.m.