Abstract
The decomposition of economic time series is motivated by the idea that distinct forces account for long-term growth, for variation over a time frame associated with the business cycle, and though the seasons. While the latter is typically suppressed by ‘seasonal adjustment’, the issue of how to separate trend from cycle in series such as GDP has been hotly debated since the 1970s and remains unsettled. Surprisingly varied patterns follow from alternative approaches, some placing the bulk of variation into the cycle/trend following a smooth line, others attributing shifts in level to ‘permanent shocks’ to the trend.
Keywords
- ARMA models
- Business cycles
- Ergodicity
- Filtering
- Identification
- Kalman filter
- Random walks
- Trend/cycle decomposition
- Unobserved components models
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Bibliography
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Nelson, C.R. (2018). Trend/Cycle Decomposition. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_2396
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DOI: https://doi.org/10.1057/978-1-349-95189-5_2396
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