Evolving Post-World War II U.S. Inflation Dynamics

Preprint

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Published in RePEc

Abstract

This paper uses a nonlinear stochastic model to describe inflation-unemployment dynamics in the U.S. after World War II. The model is a vector autoregression with coefficients that are random walks with innovations that are arbitrarily correlated with each other and with innovations to the observables. The model enables us to detect features that have been emphasized in theoretical analyses of inflation-unemployment dynamics. Those analyses involve coefficient drift in essential ways.

Keywords

STOCHASTIC MODEL
DETECT FEATURES
RANDOM WALKS
UNEMPLOYMENT
WORLD WAR
INFLATION
WALKS
DRIFT

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