TEST Statement

The AUTOREG Procedure

TEST Statement

The AUTOREG procedure now supports a TEST statement for linear hypothesis tests.

TEST equation , ... , equation / option ;

The TEST statement tests hypotheses about the covariates in the model estimated by the preceding MODEL statement. Each equation specifies a linear hypothesis to be tested. If more than one equation is specified, the equations are separated by commas.

Each test is written as a linear equation composed of constants and parameter names. Refer to parameters by the name of the corresponding regressor variable. Each name used in the equation must be a regressor in the preceding MODEL statement. Use the keyword INTERCEPT to refer to the intercept parameter in the model.

You can specify the following option in the TEST statement:

TYPE= value

The TYPE= option specifies the test statistics to use, F or Wald. TYPE=F produces an F-test. TYPE=WALD produces a Wald test. The default is TYPE=F.

The following example of a TEST statement tests the hypothesis that the coefficients of two regressors A and B are equal:


   model y = a b c d;
   test a = b;

To test separate null hypotheses, use separate TEST statements. To test a joint hypothesis, specify the component hypotheses on the same TEST statement, separated by commas.

For example, consider the following linear model:

$y_{t} = {\beta}_{0} + {\beta}_{1}x1_{t} + {\beta}_{2}x2_{t} + {\epsilon}_{t}$

The following statements test the two hypotheses ${H_{0}: {\beta}_{0} = 1}$ and ${H_{0}: {\beta}_{1} + {\beta}_{2} = 0}$ :


   model y = x1 x2;
   test intercept = 1;
   test x1 + x2 = 0;

The following statements test the joint hypothesis ${H_{0}: {\beta}_{0} = 1}$ and ${\beta}_{1} + {\beta}_{2} = 0$ :


   model y = x1 x2;
   test intercept = 1, x1 + x2 = 0;

Chapter Contents
Previous
Next
Top