Dynamic Probabilities of Restrictions in State Space Models: An Application to the Phillips Curve

Gary M. Koop · Roberto León‐González · Rodney W. Strachan

42 citations0/0 files storedJournal of Business and Economic Statistics

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Monetary Policy and Economic Impact Statistical Methods and Bayesian Inference Markov Chains and Monte Carlo Methods

Abstract

Using the Savage–Dickey density ratio and an alternative approach that uses more relaxed assumptions, we develop methods to calculate the probability that a restriction holds at a point in time without assuming that the restriction holds at any other points in time. Both approaches use MCMC output only from the unrestricted model to compute the time-varying posterior probabilities for all models of interest. Using U.S. data, we find the probability that the long-run Phillips curve is vertical to be fairly high, but decreases over time. The probability that the NAIRU is not identified fluctuates over time, but increases after 1990.

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References

2005Time Varying Structural Vector Autoregressions and Monetary Policy 1998Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models 2004Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach 2005Drifts and volatilities: monetary policies and outcomes in the post WWII US 2001Evolving Post-World War II U.S. Inflation Dynamics 2001Model uncertainty in cross‐country growth regressions 1997The NAIRU, Unemployment and Monetary Policy 2004Understanding Trend and Cycle in Asset Values: Reevaluating the Wealth Effect on Consumption

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