First off, there is a small typo here: eta does not have a time subscript, this should be eta_t. Sorry about that! For part (a), the question is: does it matter at all that a parameter be raised to a power for thinking about a process being serially correlated or not. For part (b), recall that the transformation strategy is nice because we don't really have to care about the degree of exogeneity of the regressors. With that in mind, what you have to do here is implement a version of the stuff as related to the transformation strategy. Consider the following data generating process,YtBo + B1at + Et,where y and x are variables and the Bs are parameters. Moreover, & is an error termthat satisfiespEt-1+ p°Et-2 +n,Et =where n is i.i.d. (i.e., 7 is white noise) and p E (0,1). Clearly, the error term associatedwith the regression of y on x is not i.i.d.(a) Regarding the non-i.i.d. issue noted above, is the issue one of serial correlation?Please explain.(b) Regardless of your answer to part (a), is there a version of the transformationstrategy that would solve the non-i.i.d. issue? If so, implement it and derive theregression equation that you would operationalize after this implementation. Ifnot, please explain.

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Answered: Consider the following data generating…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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First off, there is a small typo here: eta does not have a time subscript, this should be eta_t. Sorry about that! For part (a), the question is: does it matter at all that a parameter be raised to a power for thinking about a process being serially correlated or not. For part (b), recall that the transformation strategy is nice because we don't really have to care about the degree of exogeneity of the regressors. With that in mind, what you have to do here is implement a version of the stuff as related to the transformation strategy.