SAMPLE 1 40
READ (GHJ.txt) FOOD INCOME
* Construct the weight variable
GENR W=1/INCOME
* Weighted Least Squares
OLS FOOD INCOME / WEIGHT=W RESID=V0 PREDICT=YHAT0 
*
* Now use a manual approach to get the WLS estimates
*   Transform the data - normalize the weights 
?STAT W / MEAN=WMEAN
GENR WFOOD=FOOD*SQRT(W/WMEAN)
GENR WINC=INCOME*SQRT(W/WMEAN)
GENR CONST=SQRT(W/WMEAN)
*   Estimate the transformed model by OLS
OLS WFOOD WINC CONST / NOCONSTANT RESID=V1 PREDICT=YHAT1 COEF=BETA
*
* Verify that the two estimation approaches give the same results
* for the weighted residuals and the weighted predicted values.
PRINT V0 V1 FOOD YHAT0 YHAT1
*
*   R-square calculation based on the original data 
GENR E2=V1*V1
?STAT E2 / SUMS=WSSE
?STAT FOOD / WEIGHT=W CPDEV=WSST MEAN=YMEAN
GEN1 R2 = 1 - WSSE/WSST
PRINT R2
*   To compute elasticities at the mean we must also use the original data.
?STAT INCOME / WEIGHT=W MEAN=XMEAN
GEN1 ELAS=BETA(1)*XMEAN/YMEAN
PRINT ELAS
STOP