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.
KeywordsARMA models Business cycles Ergodicity Filtering Identification Kalman filter Random walks Trend/cycle decomposition Unobserved components models
- Harvey, A.C. 1985. Trends and cycles in macroeconomic time series. Journal of Business and Economic Statistics 3: 216–227.Google Scholar
- Hodrick, R.J., and E.C. Prescott. 1980. Postwar US business cycles: An empirical investigation, Working paper. Pittsburgh: Carnegie-Mellon University.Google Scholar