One is to include corporate dummy variable of the intercept and see whether it's T ratio or significantly different, is, sorry it's greater than two  right or we can use an F test, right, now that F test that's given me that formula in the middle of the page is a very important  test which was developed by a chap called Chow and as a result it become known as the Chow test and it's a, it's a test for parameter constancy, er do we have constant parameters in our model  now it tells you how to compute this Chow test, in this particular case we're only dummying the intercept, the Chow test gives exactly the same results of T tests, right, erm  we won't bother going through it, if you want to go through this er sheet in your own time calculate that, that Chow test and essentially what it involves is splitting with the s the whole sample now into two sub-samples, right, the first sub-sample, right, is peacetime, the second sub-sample wartime, right, and you just compare the residual sum of the squares on the unaccounted for variation, right, between actual and fitted values, just compare the residual sum of squares between these two sub periods, right and if you use the formula that's given there that will come out with exactly the same result, well in actual fact you can square, if you square the F statistic you get  calculating one formula you will get T value, got from er the computer  right, the er, the sheet goes on to say how we can er use dummy variables in slightly more complicated ways, right, we could see actually see whether the income or price elasticities of demand changed.