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Analysis of the U.S. Business Cycle with a Vector-Markov-Switching Model

Author

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  • Mr. Zenon Kontolemis

Abstract

This paper identifies turning points for the U.S. business cycle using different time series. The model, a multivariate Markov-Swiching model, assumes that each series is characterized by a mixture of two normal distributions (a high and low mean) with switching determined by a common Markov process. The procedure is applied to the series that make up the composite U.S. coincident indicator to obtain business cycle turning points. The business cycle chronology is closer to the NBER reference cycle than the turning points obtained from the individual series using a univariate model. The model is also used to forecast the series, with encouraging results.

Suggested Citation

  • Mr. Zenon Kontolemis, 1999. "Analysis of the U.S. Business Cycle with a Vector-Markov-Switching Model," IMF Working Papers 1999/107, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:1999/107
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    Cited by:

    1. Moolman, Elna, 2004. "A Markov switching regime model of the South African business cycle," Economic Modelling, Elsevier, vol. 21(4), pages 631-646, July.
    2. Nan Li & Simon S. Kwok, 2021. "Jointly determining the state dimension and lag order for Markov‐switching vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 471-491, July.

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