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Extracting, Using and Analysing Cyclical Information

Author

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  • Harding, Don
  • Pagan, Adrian

Abstract

Recent events suggest that the death of the business cycle has been exaggerated; the issue of how one learns about and monitors the business cycle remains centre stage. Advent of the Euro and the potential for tensions when sovereign nations subsume their monetary policy into a single response also makes monitoring the business cycle of particular interest for Euro area policy makers. In this paper we summarize recent research on three questions relating to cycles in economic activity --- how to extract cyclical information, how to analyse it, and how to enquire into what special difficulties might be encountered when using cyclical indicators. This survey focuses on our own research which we view as a formalization of some of the procedures developed by Burns and Mitchell at the NBER. However, defence of our position goes beyond continuity with the past and is based on the view that the way in which these investigators defined the business cycle is a very natural one that connects with the way policy makers and commentators discuss the cycle.

Suggested Citation

  • Harding, Don & Pagan, Adrian, 2001. "Extracting, Using and Analysing Cyclical Information," MPRA Paper 15, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:15
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    File URL: https://mpra.ub.uni-muenchen.de/15/1/MPRA_paper_15.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Business cycle; growth cycle; synchronization; turning points;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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