Framework and Assumptions Assumption 3.2 [Strict Exogeneity]: E(et X)=E(et X1,...,Xt;..,Xn)=0,t=1,...,n. - Under Assumption 3.2,we have E(Xset)=0 for any (t,s),where t,s E 1,...,n.This follows because E(XsEt) =EE(Xset X)] EXgE(et X E(Xs·0) 三 0. Given E(et)=0,E(Xset)=0 implies cov(Xs,Et)=0 for all t,s E {1,,n Because X contains regressors {Xs}for both s <t and s >t,Assumption 3.2 essentially requires that the error et do not depend on both the past and future values of regressors if t is a time index.This rules out dynamic time series models for which et may be correlated with the future values of regressors. ADVANCED ECONOMETRICS Classical Linear Regression Model May11,2021 7ADVANCED ECONOMETRICS Classical Linear Regression Model May 11, 2021 7 Framework and Assumptions Assumption 3.2