Use INTQRT RAW for this exercise (i) In Example 18 7, we estimated an error correction model for the holding yield on six month T bills, where one lag of the holding yield on three month T bills is the explanatory variable We assumed that the co integration parameter was one in the equation hy6t hy3t 1 ut Now, add the lead change, hy3t, the contemporaneous change, hy3t 1, and the lagged change, hy3t 2, of hy3t 1 That is, estimate the equation hy6t hy3t 1 0 hy3t 1 hy3t 1 pl hy3t 2 et and report the results in equation form Test HQ f3 1 against a two sided alternative Assume that the lead and lag are sufficient so that hy3t 1 is strictly exogenous in this equation and do not worry about serial correlation (ii) To the error correction model in (18 39), add ry3t 2 and (hy6t 2 hy3t 3) Are these terms jointly significant What do you conclude about the appropriate error correction model

Question: Use INTQRT.RAW for this exercise. (i) In Example 18.7, we estimated an error correction model for the holding yield on six-month T-bills, where one lag

Use INTQRT.RAW for this exercise.
(i) In Example 18.7, we estimated an error correction model for the holding yield on six-month T-bills, where one lag of the holding yield on three-month T-bills is the explanatory variable. We assumed that the co integration parameter was one in the equation hy6t = α + βhy3t-1 + ut. Now, add the lead change, Δhy3t, the contemporaneous change, Δhy3t-1, and the lagged change, Δhy3t-2, of hy3t-1. That is, estimate the equation
hy6t = α + βhy3t-1 + ϕ0 Δhy3t + ϕ1 Δhy3t-1 + pl Δhy3t-2 + et
and report the results in equation form. Test HQ: f3 = 1 against a two-sided alternative. Assume that the lead and lag are sufficient so that {hy3t-1} is strictly exogenous in this equation and do not worry about serial correlation.
(ii) To the error correction model in (18.39), add Δ/ry3t-2 and (hy6t-2 - hy3t-3). Are these terms jointly significant? What do you conclude about the appropriate error correction model?

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