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The SYSLIN Procedure 
In the supply and demand model, P is an endogenous variable, and consequently the OLS estimates are biased. The following example estimates this model using twostage least squares:
proc syslin data=in 2sls; endogenous p; instruments y u s; demand: model q = p y s; supply: model q = p u; run;
The 2SLS option on the PROC SYSLIN statement specifies the twostage leastsquares method. The ENDOGENOUS statement specifies that P is an endogenous regressor for which firststage predicted values are substituted. You only need to declare an endogenous variable in the ENDOGENOUS statement if it is used as a regressor; thus although Q is endogenous in this model, it is not necessary to list it in the ENDOGENOUS statement.
Usually, all predetermined variables that appear in the system are used as instruments. The INSTRUMENTS statement specifies that the exogenous variables Y, U, and S are used as instruments for the firststage regression to predict P.
The 2SLS results are shown in Figure 19.3 and Figure 19.4. The firststage regressions are not shown. To see the firststage regression results, use the FIRST option on the MODEL statement.

The 2SLS output is similar in form to the OLS output. However, the 2SLS results are based on predicted values for the endogenous regressors from the first stage instrumental regressions. This makes the analysis of variance table and the R^{2} statistics difficult to interpret. See the sections "ANOVA Table for Instrumental Variables Methods" and "The R^{2} Statistics" later in this chapter for details.
Note that, unlike the OLS results, the 2SLS estimate for the P coefficient in the demand equation (1.115) is negative.
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