9.6 Structural Stability of Regression Models The Dummy Variable Approach The Chow test did not tell us whether the difference in these two regressions is in their intercept values or the slope values or both Y1=A1+A2X1+u1 (9.23) Y1=B1+B2X1+u2(9.24) 1. A=B, and A=B,: coincident regression, the two regressions are identical 2. A,+B, but A,=B,, parallel regressions, the two regressions have different intercepts but same slope 3. A B, but A2+B2; concurrent regressions, the two regressions have same intercepts but different slope 4. A1+B, and A2+B2, dissimilar regressions, the two regressions are different in both intercepts and slope9.6 Structural Stability of Regression Models: The Dummy Variable Approach The Chow test did not tell us whether the difference in these two regressions is in their intercept values or the slope values or both. Yt =A1 +A2Xt +u1t (9.23) Yt =B1 +B2Xt +u2t (9.24) 1. A1=B1 and A2=B2 ; coincident regression, the two regressions are identical 2. A1 ≠B1 but A2=B2 ; parallel regressions, the two regressions have different intercepts but same slope. 3. A1=B1 but A2 ≠B2 ; concurrent regressions, the two regressions have same intercepts but different slope. 4. A1 ≠B1 and A2 ≠B2 ; dissimilar regressions, the two regressions are different in both intercepts and slope