This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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240
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #309450 |
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Title:
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Finiteness Matters in Inference for New Keynesian Phillips Curve
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Author(s):
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Hrishikesh (Rick) D. Vinod*+
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Companies:
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Fordham University
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Address:
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, , ,
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Keywords:
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Inflation ;
Phillips Curve ;
bootstrap ;
convergence ;
simulation
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Abstract:
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Under the simultaneous presence of identification, endogeneity and non-spherical regression error problems, the choice between ordinary least squares (OLS) and generalized method of moments (GMM) should depend on finite sample evaluation of 'convergence in probability' and 'almost sure convergence.' We offer new simulation tools for this purpose. The new Keynesian Phillips curve (NKPC) estimation for US data finds little endogeneity-induced inconsistency and that using GMM seems to worsen it. The potential 'lack of identification' problem is attributed to possibly zero standard errors in the denominators of Wald pivots. We replace it by the Godambe pivot, leading to superior confidence intervals for deep parameters of the NKPC model.
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