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. However, such methods are also subject to weak instrument problems. 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 generalized method of moments counterparts. In contrast to previous studies, we find evidence of partial but not full indexation, and obtain sharper inference on the degree of price stickiness. However, this parameter remains weakly identified. Copyright (c) 2010 The Ohio State University.