* PS12.1, using DATA4-5, for Example 12.1
SAMPLE 1 50
READ(data4-5) WLFP YF YM EDUC UE MR DR URB WH 
GENR LWLFP=LOG(WLFP/(100-WLFP))
*
* ESTIMATE THE LOGIT MODEL AND SAVE PREDICTED VALUES
*
OLS LWLFP YF EDUC UE URB WH / LOGLIN PREDICT=YHAT
*
* TAKE ANTILOG AND CORRECT FOR BIAS IN LOG MODEL
*
GENR Y1=EXP(YHAT+($SSE/(2*$DF)))
*
* PREDICT THE PARTICIPATION RATE AND COMPUTE THE ERRORS
*
GENR WLFPHAT=100*Y1/(1+Y1)
GENR ERROR=WLFP - WLFPHAT
*
* COMPUTE ESS AND ADJUSTED MODEL SELECTION CRITERIA FOR LOGIT MODEL 
*
GENR ESS=SUM(ERROR*ERROR)
SMPL 50 50 
GENR K=6
GENR T=50
GENR ESST=ESS/T
GENR SGMASQ=ESS/(T-K)
GENR FPE=(ESST*(T+K))/(T-K)
GENR GCV=ESST*((T/(T-K))**2)
GENR HQ=ESST*(LOG(T)**(2*K/T))
GENR RICE=ESS/(T-(2*K))
GENR SHIBATA=ESST*(T+(2*K))/T
GENR SCHWARZ=ESST*(T**(K/T))
GENR AIC=ESST*EXP(2*K/T)
PRINT SGMASQ FPE GCV HQ
PRINT RICE SHIBATA SCHWARZ AIC
*
* ESTIMATE LINEAR MODEL
*
SMPL 1 50
OLS WLFP YF EDUC UE URB WH 
*
DELETE /ALL
STOP