Chow test

The Chow test, proposed by econometrician Gregory Chow in 1960, is a test of whether the coefficients in two linear regressions on different data sets are equal. In econometrics, it is most commonly used in time series analysis to test for the presence of a structural break at a period which can be assumed to be known a priori (for instance, a major historical event such as a war). In program evaluation, the Chow test is often used to determine whether the independent variables have different impacts on different subgroups of the population.

At ${\displaystyle x=1.7}$ there is a structural break, regression on the subintervals ${\displaystyle [0,1.7]}$ and ${\displaystyle [1.7,4]}$ delivers a better modelling than the combined regression(dashed) over the whole interval.

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