Identification of New Keynesian Phillips Curves from a Global Perspective
European Central Bank (ECB)
M. Hashem Pesaran
University of Southern California; USC Dornsife Institute for New Economic Thinking
L. Vanessa Smith
University of York
CESifo Working Paper Series No. 2219
IEPR Working Paper No. 08.1
ECB Working Paper No. 892
New Keynesian Phillips Curves (NKPC) have been extensively used in the analysis of monetary policy, but yet there are a number of issues of concern about how they are estimated and then related to the underlying macroeconomic theory. The first is whether such equations are identified. To check identification requires specifying the process for the forcing variables (typically the output gap) and solving the model for inflation in terms of the observables. In practice, the equation is estimated by GMM, relying on statistical criteria to choose instruments. This may result in failure of identification or weak instruments. Secondly, the NKPC is usually derived as a part of a DSGE model, solved by log-linearising around a steady state and the variables are then measured in terms of deviations from the steady state. In practice the steady states, e.g. for output, are usually estimated by some statistical procedure such as the Hodrick-Prescott (HP) filter that might not be appropriate. Thirdly, there are arguments that other variables, e.g.interest rates, foreign inflation and foreign output gaps should enter the Phillips curve. This paper examines these three issues and argues that all three benefit from a global perspective. The global perspective provides additional instruments to alleviate the weak instrument problem, yields a theoretically consistent measure of the steady state and provides a natural route for foreign inflation or output gap to enter the NKPC.
Number of Pages in PDF File: 41
Keywords: Global VAR (GVAR), identification, New Keynesian Phillips Curve, Trend-Cycle decomposition
JEL Classification: C32, E17, F37, F42working papers series
Date posted: February 12, 2008
© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo6 in 0.515 seconds