Revisions of Trend-Cycle Estimators of Moving Average Seasonal Adjustment Methods
移动平均季节调整方法中趋势—周期估计量的修订AI 解读 ↓
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移动平均季节调整方法中趋势—周期估计量的修订
- 研究问题
- 移动平均季节调整在样本末端使用非对称趋势—周期滤波器时，为何产生修订，X-11 与 X-11-ARIMA 的修订大小及模式如何？
- 方法与思路
- 研究围绕 X-11 与 X-11-ARIMA 的非对称趋势—周期滤波器考察修订大小及模式，将新增观测和滤波权重或频率响应变化列为修订来源。
- 材料陈述的贡献
- 摘要明确的工作目标是量化并分析两类季节调整方法的趋势—周期修订，解释近期估计为何随新信息及非对称滤波器变化而更新。
- 阅读关注点
- 阅读时应核对修订大小的度量、非对称滤波器的权重与频率响应，以及新增观测和权重变化的作用如何分析、两种方法怎样比较。
- 阅读边界
- 摘要未报告修订幅度、数据序列或比较结论，也未交代计算所需的模型设定；无法据此判断两种方法在实际应用中的修订差异。
原文摘要
One of the main purposes of the seasonal adjustment of economic time series is to provide information on current economic conditions, particularly to determine the state of the cycle at which the economy stands. Since seasonal adjustment means removing seasonal variations, thus leaving a seasonally adjusted series consisting of trend cycle together with the irregular fluctuations, it is often very difficult to detect cyclical turning points for series strongly contaminated with irregulars. In such cases, it may be preferable to smooth the seasonally adjusted series using trend-cycle filters, which suppress as much as possible the irregulars without affecting the cyclical component. It is inherent, however, in any moving average procedure that the first and last n points of an original series cannot be smoothed with the same symmetric filters applied to middle values. The current and most recent years of data are smoothed by asymmetric filters, which change for each point in time. Hence, as new information becomes available, revisions are made because of (a) the new innovations entering the series and (b) the changes in the weight system or frequency response function of the filters. The purpose of this study is to calculate the size of the revisions of the asymmetric trend-cycle filters of X-11 and X-11-ARIMA and to analyze the pattern of these revisions.