Identification-Robust Minimum Distance Estimation of the New Keynesian Phillips Curve
Limited-information identification-robust methods on the indexation and price rigidity parameters of the new Keynesian Phillips curve yield very wide confidence intervals. Full-information methods impose more restrictions on the reduced-form dynamics, and thus make more efficient use of the information in the data. We propose identification-robust minimum distance methods for exploiting these additional restrictions and show that they yield considerably smaller confidence intervals for the coefficients of the model compared to their limited-information GMM counterparts. In contrast to previous studies that used GMM, we find evidence of partial but not full indexation, and we obtain sharper inference on the degree of price stickiness.
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