Trend–Cycle Decompositions with Correlated Components
Trend–Cycle Decompositions with Correlated Components
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DOI：
10.1080/07474930500545496
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发表时间：
2006-06
影响因子：
1.2
通讯作者：
Tommaso Proietti
中科院分区：
文献类型：
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作者：
Tommaso Proietti
本文提出了一些解释问题，从单变量趋势周期分解相关的干扰。特别是，它讨论了负相关的解释，作为提供证据的真实的，或供应，冲击的突出，可以支持。为此目的，它确定的条件下，相关的组件可能源于低估的周期性组件在正交分解;从存在的增长率周期，而不是偏差周期;或者，作为滞后现象的后果。最后，它考虑解释相关组件的永久-短暂的分解，其中永久组件具有更丰富的动态比纯随机游走。平滑和信号提取的后果进行了讨论：特别是，它是一个负相关意味着未来的观测进行评估周期性的立场所需的信息。因此，这些组成部分在真实的时间内将受到低估，从而受到高度订正。总体结论是，宏观经济时间序列中经济波动的特征在很大程度上仍然是一个悬而未决的问题。
This paper raises some interpretative issues that arise from univariate trend–cycle decompositions with correlated disturbances. In particular, it discusses whether the interpretation of a negative correlation as providing evidence for the prominence of real, or supply, shocks, can be supported. For this purpose it determines the conditions under which correlated components may originate from the underestimation of the cyclical component in an orthogonal decomposition; from the presence of a growth rate cycle, rather than a deviation cycle; or alternatively, as a consequence of the hysteresis phenomenon. Finally, it considers interpreting correlated components in terms of permanent–transitory decompositions, where the permanent component has richer dynamics than a pure random walk. The consequences for smoothing and signal extraction are discussed: in particular, it is documented that a negative correlation implies that future observations carry most of the information needed to assess cyclical stance. As a result, the components will be subject to underestimation in real time and thus to high revisions. The overall conclusion is that the characterization of economic fluctuations in macroeconomic time series largely remains an open issue.