Part A

Consider the following model of the relationship between the variables lit and it: yt = 1.4 + :15 art + o: $t_2 + et where 63: is a white noise process with 1irariant'e t1"2 = 1J3. Assume that it is a weakly stationary random variable with Et) = 3.0, oorlIet) =9, and match 3:14) =o.4i for all j 7e [1 Then we can compute that E(yt) is equal to Assume that Ut is a variable of interest and & is an i.i.d. white noise process. We dytth want to examine the response: IR( Utt Et) = det If h = 3, in which of the following cases is IR(Uth Et ) = 0? Select all that apply. yt = 3+ (1 + 014 + 0212) Et, with 01 = 0.5 and 02 = 0.1 yt = 2 + (1 + 0L)Et, with 0 =0.6 O (1 - QL)yt = 0.5 + Et. with = 0.7 yt = 2 + (1 + 01L + 0212 + 0313) Et, with 01 = 0.7, 02 = 0.1, and 03 = 0.02