The government plans to build a new subway and rail terminal, and is offering compensation to the land property owner where the terminal is to be developed. The government claims that the offered compensation amount is based on market prices. The property owner believes that the new development would add substantial value to the properties around it, and that she should be compensated for that as well. She obtained results of two simple regressions; Regression 1 has the current market value of properties (variable name Value, in hundreds of thousands of dollars, i.e., measured in units of $100,000) as the dependent variable, and the size of the property (variable name Size, measured in acres; 1 acre ? 4,047 square meters) as the independent variable. Regression 2 uses the same independent variable Size, but it uses percentage increase in the property value based on the size of the property after similar government developments occurred (variable name IncrValue, in percentage points, i.e., a decrease in value of 12% would correspond to IncrValue = -12).

Regression 1

Dependent Variable: Value Independent Variables: Size Regression Statistics R Square Adj.RSqr Std.Err.Reg. # Cases # Missing t(2.5%,285) 0.175 0.149 0.695 287 0 1.968 Summary Table Variable Coeff Std.Err. t-Stat. P-value Intercept 1.784 0.382 4.670 0.000 Size 2.103 0.112 18.777 0.000 Forecasted : Value Size Forecast StErrFst Fest#1 3.887 1.033 Fest#2 2 5.990 1.000 Fest#3 3 8.093 0.953Dependent Variable: IncrValue Independent Variables: Size Regression Statistics R Square Adj.RSqr Std.Err.Reg. # Cases # Missing t(2.5%,490) 0.273 0.252 2.210 492 0 1.965 Summary Table Variable Coeff Std.Err. t-Stat. P-value Intercept 14.601 0.412 35.439 0.000 Size -2. 101 0.301 -6.980 0.000 Forecasted : IncrValue Size Forecast StErrFst Fest#1 3 8.298 3.022 Fest#2 2 10.399 2.873 Fest#3 12.500 2.788