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I want to estimate the forward looking version of the Taylor rule equation using the iterative nonlinear GMM:

Model

I have the data for all the variables in the model, namely pi (inflation rate), x (unemployment gap) and i (effective federal funds rate) and what I am trying to estimate is the set of parameters i, i and i.

Where I need help is in the usage of the gmm() function in the {gmm} R package. I 'think' that the parameters of the function that I need are the parameters:

gmm(g, x, type = "iterative",...)

where g is the formula (so, the model stated above), x is the data vector (or matrix) and type is the type of GMM to use.

My problem is with the data matrix parameter. I do not know the way in which to construct it (not that I don't know of matrices in R and all the examples I have seen on the internet are not similar to what I am attempting to do here. Also, this is my first time using the gmm() function in R. Is there anything else I need to know?

Your help will be much appreciated. Thank you :)

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SavedByJESUS
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    The instruments for the inflation variable will be past values of inflation. Usually for quarterly data, four lags are usually used. Then, from my understanding, you can just estimate the equation similar to the way Chausse estimates an ARMA equation with gmm in section 3.4 of his paper http://www.jstatsoft.org/v34/i11/paper. You also might want to check out Clarida, Gali, and Gertler (2000 QJE) for further information. – chandler Mar 14 '13 at 03:55
  • perhaps this should be migrated to cross-validated – chandler Mar 14 '13 at 03:55
  • Thank you very much @chandler for your response, I'll read through the paper you just gave me. Thanks again! – SavedByJESUS Mar 14 '13 at 04:11
  • If you figure out the estimation method using the gmm package, can you send me your code? Also, you might want seek advice from the author of the package – chandler Mar 15 '13 at 22:41
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    @chandler I was able to figure out how to estimate it. I'll write an elaborate answer right here. – SavedByJESUS Mar 26 '13 at 20:09
  • may you please write how you did estimate it ? Thanks – Bob Dec 15 '14 at 10:54

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