Model Uncertainty and the Direction of Fit of the Postwar U.S. Phillips Curve(s)
Francesca Rondina ()
No 1702E, Working Papers from University of Ottawa, Department of Economics
This paper proposes a model uncertainty framework that accounts for the uncertainty about both the specification of the Phillips curve and the identification assumption to be used for parameter estimation. More specifically, the paper extends the framework employed by Cogley and Sargent (2005) to incorporate uncertainty over the direction of fit of the Phillips curve. I first study the evolution of the model posterior probabilities, which can be interpreted as a measure of the econometrician's real-time beliefs over the prevailing model of the Phillips curve. I then characterize the optimal policy rule within each model, and I analyze alternative policy recommendations that incorporate model uncertainty. As expected, different directions of fit of the same model of the Phillips curve imply very different optimal policy choices, with the “Classical” specifications typically suggesting low and stable optimal inflation rates. I also find that allowing rational agents to incorporate model uncertainty in their expectations does not change the optimal or robust policies. On the other hand, I show that the models' fit to the data and the robust policy recommendations are affected by the specific price index that is used to measure in inflation.
Keywords: Phillips curve; Model Uncertainty; Robust Policy; Bayesian Model Averaging; Expectations (search for similar items in EconPapers)
JEL-codes: C52 E37 E52 E58 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-mac and nep-upt
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