Seasonal Adjustment of Economic Time Series and Multiple Regression Analysis
经济时间序列的季节调整与多元回归分析AI 解读 ↓
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经济时间序列的季节调整与多元回归分析
- 研究问题
- 季节调整应满足哪些一致性要求，而预先调整经济时间序列又会怎样影响回归估计、系数显著性及自相关处理？
- 方法与思路
- 作者以保和、正交和幂等要求连接季节调整与最小二乘，扩展 Frisch–Waugh 定理，比较预调整与季节虚拟变量。
- 材料陈述的贡献
- 摘要称，适当条件下预调整可支持有效估计，但有夸大系数显著性的倾向；文中建议修正，并讨论广义及两阶段最小二乘。
- 阅读关注点
- 应核对季节调整的算子要求、移动季节模式的表示、显著性修正，以及自相关下广义最小二乘和联立方程扩展的条件。
- 阅读边界
- 仅据版本未注明的 OpenAlex 索引摘要；有效估计的条件、修正公式及误差协方差处理未展开，不能声称任意季调数据均可直接回归。
原文摘要
The logical implications of certain simple consistency requirements for appraising alternative procedures for seasonal adjustment constitute the first problem considered in this paper. It is shown that any sum preserving technique of seasonal adjustment that satisfies the quite reasonable requirements of orthogonality and idempotency can be executed on the electronic computer by standard least squares regression procedures. Problems involved in utilizing seasonally adjusted data when estimating the parameters of econometric models are examined. Extending the fundamental Frisch-Waugh theorem concerning trend and regression analysis to encompass problems of seasonality facilitates the comparison of the implications of running regressions on data subjected to prior seasonal adjustment with the effects of including dummy variables with unadjusted data. Complicated types of moving seasonal patterns that may be handled by the dummy variable procedure are considered. Although efficient estimates of the parameters of the econometric model may be obtained in appropriate circumstances when data subjected to prior seasonal adjustment by the least squares procedure are employed, there is an inherent tendency to overstate the significance of the regression coefficients; a correction procedure is suggested. When seasonally adjusted data are employed, certain special complications must be taken into account in applying Aitken's generalized least squares procedure in order to deal with autocorrelated residuals. The entire argument extends to two-stage least squares estimation of the parameters of simultaneous equation models.