Does seasonality influence the dating of business cycle turning points?*

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The Markov switching regime model is often applied to dating business cycle turning points. Typically, this model is then considered for quarterly seasonally adjusted macroeconomic time series. In this paper we show through simulations and empirical examples that, when the Markov model is applied to quarterly seasonally adjusted data, one may find different peaks and troughs and hence a different characterization of the business cycle. We also find different dynamic relations between macroeconomic variables across the business cycle. In other words, we answer the question in the title affirmatively.

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The first author thanks the Royal Netherlands Academy of Arts and Sciences and the second author thanks the Netherlands Foundation for Scientific Research (N.W.O.) for their financial support. We thank James Hamilton for his comments and for providing Gauss programs. Thanks are also due to two anonymous referees for their helpful comments. An earlier version of this paper titled “Does Seasonal Adjustment Change Inference from Markov Switching Models?” was presented at the Econometric Society European Meeting 1996 in Istanbul, Turkey. Comments from Robert Engle and Svend Hylleberg proved very helpful.

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