Has the U.S. Wage Phillips Curve Flattened? a Semi-Structural Exploration

36 Pages Posted: 23 Jan 2019

See all articles by Jordi Galí

Jordi Galí

Universitat Pompeu Fabra - Centre de Recerca en Economia Internacional (CREI); Massachusetts Institute of Technology (MIT) - Department of Economics; Centre for Economic Policy Research (CEPR); National Bureau of Economic Research (NBER)

Luca Gambetti

University of Turin

Multiple version iconThere are 2 versions of this paper

Date Written: January 2019

Abstract

Unconditional reduced form estimates of a conventional wage Phillips curve for the U.S. economy point to a decline in its slope coefficient in recent years, as well as a shrinking role of lagged price inflation in the determination of wage inflation. We provide estimates of a conditional wage Phillips curve, based on a structural decomposition of wage, price and unemployment data generated by a VAR with time varying coefficients, identified by a combination of long-run and sign restrictions. Our estimates show that the key qualitative findings from the unconditional reduced form regressions also emerge in the conditional evidence, suggesting that they are not entirely driven by endogeneity problems or possible changes over time in the importance of of wage markup shocks. The conditional evidence, however, suggests that actual changes in the slope of the wage Phillips curve may not have been as large as implied by the unconditional estimates.

JEL Classification: E24, E31

Suggested Citation

Gali, Jordi and Gambetti, Luca, Has the U.S. Wage Phillips Curve Flattened? a Semi-Structural Exploration (January 2019). CEPR Discussion Paper No. DP13452. Available at SSRN: https://ssrn.com/abstract=3319767

Jordi Gali (Contact Author)

Universitat Pompeu Fabra - Centre de Recerca en Economia Internacional (CREI) ( email )

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HOME PAGE: http://www.econ.upf.es/~gali

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

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Centre for Economic Policy Research (CEPR)

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National Bureau of Economic Research (NBER)

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Luca Gambetti

University of Turin ( email )

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Torino, Turin - Piedmont 10100
Italy

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