The process of computing input values that are needed to produce target results is often called goal seeking. To compute a goal-seeking solution, use a SOLVE statement that lists the variables you want to solve for and provide a data set that contains values for the remaining variables.

Consider the following demand model for packaged rice

where price is the price of the package and income is disposable personal income. The only variable the company has control over is the price it charges for rice. This model is estimated by using the following simulated data and PROC MODEL statements:

data demand;
   do t=1 to 40;
      price = (rannor(10) +5) * 10;
      income = 8000 * t ** (1/8);
      demand = 7200 - 1054 * price ** (2/3) +
               7 * income + 100 * rannor(1);
      output;
   end;
run;

data goal;
   demand = 85000;
   income = 12686;
run;

The goal is to find the price the company would have to charge to meet a sales target of 85,000 units. To do this, a data set is created with a DEMAND variable set to 85000 and with an INCOME variable set to 12686, the last income value.

The desired price is then determined by using the following PROC MODEL statements:

proc model data=demand
           outmodel=demandModel;
   demand = a1 - a2 * price ** (2/3) + a3 * income;
   fit demand / outest=demest;
   solve price / estdata=demest data=goal solveprint;
run;

The SOLVEPRINT option prints the solution values, number of iterations, and final residuals at each observation. The SOLVEPRINT output from this solve is shown in Figure 18.80.