implies that as tyo Xt (the log of firm size)also follows the distribution. Hence the size distribution of firms will have the Log-Normal distribution Prais generalises this model by introducing the following: xt=bxt-1+et→ Var(e,) t-1 Assume again Cov (Xt-1,e,)=Cov(e+, e+_ )=0)where t is the normally distrubuted random error and set s= b. Hence s )+s s〔1+B n的( for 0<B<1 (7) Therefore, since if 0<B<1 as t)oo B 0 we have t、1BIfo<B<1(0<b<1) In the case ofβ<1 we have the Galtonian Regression where〓 all fire y】1 grow proportionately more than large firms. The firm's growth depends on its size since from (6) we may write Xt b-1)X Then differentiating a(X -X b-1<0 In other words, a unit increase in size leads to a b-l drop in the firm s growth rate over the coming period. (That is, the Gibrat assumption that