Stochastic Technical Progress, Smooth Trends, and Nearly Distinct Business Cycles
研究技术以缓慢速度随机扩散的模型，发现去趋势后的GDP与技术进展基本无关，并比较了不同去趋势方法对周期成分的还原效果。
This paper studies a model of random technical progress where technology diffuses at realistically slow rates. It fits smooth trends to the sum of GDP series generated by this model and series representing transitory, or cyclical, fluctuations. Detrended GDP is then largely unrelated to technical progress. The detrending method proposed by Rotemberg (1999) reconstructs cyclical variations somewhat more accurately than the HP filter. With sufficiently slow diffusion it is also more accurate than a method based on VARs fitted to hours and GDP growth. Consistent with the model’s predictions, permanent shocks initially depress both hours and output in these VARs.