Measuring the probability of a business cycle turning point by using a multivariate qualitative hidden Markov model

Stéphane M. Gregoir · Fabrice Lenglart

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Monetary Policy and Economic Impact Statistical Methods and Applications Forecasting Techniques and Applications

Abstract

A two-step procedure to produce a statistical measure of the probability of being in an accelerating or decelerating phase of economic activity is proposed. It consists of, first, an extraction of the individual linear innovations of a set of relevant macroeconomic variables whose signs are accumulated into a qualitative vector process and, second, of a factor analysis applied to this vector. The factor process is a two-state Markov process of order one whose states are described as favourable and unfavourable. Estimated on French business surveys, this measure appears to be a competitive coincident indicator. Copyright © 2000 John Wiley & Sons, Ltd.

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References

1988Testing for a Unit Root in Time Series Regression 1989A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle 1990Forecasting, Structural Time Series Models and the Kalman Filter 1994Automatic Lag Selection in Covariance Matrix Estimation 1968Modern Factor Analysis 1921Survey of current business 1989Latent Variable Models and Factor Analysis 1989NBER macroeconomics annual 1987

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