* Example of Probit Model Estimation. * Reference: Chapter 18.2.5, pp. 374-376 of * R. Carter Hill, William E. Griffiths and George G. Judge, * Undergraduate Econometrics, Second Edition, Wiley. * * Data on automobile and public transportation travel * time for 21 individuals. The variables are: * AUTO - Auto travel time * BUS - Bus travel time * X - (Bus time - Auto time) * Y - = 1 if auto transport is chosen; = 0 otherwise. SAMPLE 1 21 * The NAMES option specifies that the variable names are included * as the first line in the data set. READ (TAB18-1.shd) / NAMES * Probit estimation PROBIT Y X / COEF=BETA * Suppose travel by public transportation takes 20 minutes * longer than auto travel. * Find the increase in the probability of travel by auto. SAMPLE 1 1 GENR INDEX = (BETA:1)*20 + BETA:2 * Evaluate the standard normal probability density function. DISTRIB INDEX / PDF=FXB * Calculate the marginal effect - Equation (R18.2), p. 375. GENR PROB=FXB*BETA:1 PRINT PROB * Prediction exercise - Equation (R18.3), p. 376 DIM Y1 22 X1 22 PHAT 22 SAMPLE 22 22 GENR X1=30 FC Y1 X1 / MODEL=PROBIT COEF=BETA LIST PREDICT=PHAT PRINT X1 PHAT * Note: The forecast diagnostics listed by the FC command have * no meaningful interpretation in this example that computes * out-of-sample predictions. * The forecast diagnostics are only valid for within sample predictions. STOP