Can Economic Time Series Be Differenced to Stationarity?

Stephen J. Leybourne · Brendan P. M. McCabe · Andrew R. Tremayne

129 citations0/0 files storedJournal of Business and Economic Statistics

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Monetary Policy and Economic Impact Time Series Analysis and Forecasting Diverse Scientific and Economic Studies

Abstract

This article considers a class of nonstationary varying-coefficient autoregressive models that allow stochastic variability in the autoregressive root. It is argued that such models provide a better description of the behavior of macroeconomic variables than fixed-unit-root autoregressive models because they allow more general forms of nonstationarity. We construct a test of the null hypothesis of a fixed unit root against the alternative of a randomized root with unit mean and derive its asymptotic distribution. The test is applied to several U.S. macroeconomic series generally considered to contain fixed unit roots. We find that for about half of the series the fixed-unit-root null is rejected.

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References

1982Trends and random walks in macroeconmic time series 1990Forecasting, Structural Time Series Models and the Kalman Filter 1988Trends and random walks in macroeconomic time series 2000Forecasting Economic Time Series 1980Long memory relationships and the aggregation of dynamic models 1979Forecasting Economic Time Series 1986Forecasting Economic Time Series 1994Testing for a Unit Root in Time Series With Pretest Data-Based Model Selection

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