The New Keynesian Phillips Curve: Lessons From Single-Equation Econometric Estimation

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					                  Economic Quarterly—Volume 94, Number 4—Fall 2008—Pages 361–395




The New Keynesian
Phillips Curve: Lessons
From Single-Equation
Econometric Estimation
                                        James M. Nason and Gregor W. Smith




T
         he last decade has seen a renewed interest in the Phillips curve that
         might be an odd awakening for a macroeconomic Rip van Winkle
         from the 1980s or even the 1990s. Wasn’t the Phillips curve tradition
discredited by the oil prices shocks of the 1970s or by theoretical critiques of
Friedman, Phelps, Lucas, and Sargent? It turns out that the New Keynesian
Phillips curve (NKPC) is consistent with both the theoretical demands of
modern macroeconomics and some key statistical properties of inflation. In
fact, the NKPC can take a sufficient number of guises to accommodate a wide
range of perspectives on inflation.
     The NKPC originated in descriptions of price setting by firms that possess
market power. For example, Rotember
				
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Description: The last decade has seen a renewed interest in the Phillips curve that might be an odd awakening for a macroeconomic Rip van Winkle from the 1980s or even the 1990s. It turns out that the New Keynesian Phillips curve (NKPC) is consistent with both the theoretical demands of modern macroeconomics and some key statistical properties of inflation. In fact, the NKPC can take a sufficient number of guises to accommodate a wide range of perspectives on inflation. Yet, putting the NKPC to use for policy analysis requires that it has a good econometric track record in describing actual inflation dynamics. In this article the authors review this record using single-equation statistical methods that study the NKPC on its own. This article outlines single-equation econometric methods for studying the NKPC and offers a progress report on the empirical evidence. Estimates of the NKPC using surveys of forecasts give very different coefficients from those using instrumental variables estimation.
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