Lag Augmentation in Dynamic Econometric Models

动态计量经济模型中的滞后增强

基本信息

批准号：
10630021
负责人：
YAMAMOTO Taku
金额：
$ 1.34万
依托单位：
Hitotsubashi University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1998
资助国家：
日本
起止时间：
1998 至 1999
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-10630021/
关键词：
Econometric models Hypothesis test Wald test Lag augmentation Variable lag Time series model VAR models Monte Carlo experiments 非定常時系列分析ワルド検定ベクトル自己回帰モデル小標本特性

项目摘要

It has been widely known that the Wald test statistic for parameters in a dynamic model with non-stationary regressors occasionally has a non-standard asymptotic distribution. To cope with this difficulty, the lag augmentation (LA) approach has been proposed for estimating a dynamic model. It is known to be quite useful compared with other advanced but complicated methods, since the LA approach produces the Wald statistic with asymptotically chi-square distribution.In 1998, we showed that the LA approach is applicable to usual dynamic regression models, although the method was originally developed solely for vector autoregressive (VAR) models. Further, we found that the Wald test statistic tends to have higher power with a lagged variable of a longer lag length rather than that of one lag. In 1999, based upon the comprehensive experiments, we have proposed the criteria for selecting a suitable lag length, which is based upon a generalized variance of an estimated variance-covariance matrix of coefficient parameters. Further, we have generalized the application of the LA approach to simultaneous equation systems where regressors and error terms are correlated. Thus, it has been shown that the LA is applicable in conjunction with the instrumental variable (IV) method. The Monte Carlo experiment has revealed the effectiveness of approaches proposed in the present research.

众所周知，具有非平稳回归量的动态模型中参数的 Wald 检验统计量有时会呈现非标准渐近分布。为了解决这个困难，提出了滞后增强（LA）方法来估计动态模型。众所周知，与其他先进但复杂的方法相比，LA 方法非常有用，因为 LA 方法产生渐近卡方分布的 Wald 统计量。1998 年，我们表明 LA 方法适用于通常的动态回归模型，尽管该方法最初专门为向量自回归 (VAR) 模型开发。此外，我们发现 Wald 检验统计量往往对滞后长度较长的滞后变量而不是一个滞后的滞后变量具有更高的功效。 1999年，在综合实验的基础上，我们提出了选择合适滞后长度的标准，该标准基于系数参数估计方差-协方差矩阵的广义方差。此外，我们还推广了 LA 方法在回归量和误差项相关的联立方程系统中的应用。因此，已经表明 LA 可以与工具变量 (IV) 方法结合使用。蒙特卡罗实验揭示了本研究中提出的方法的有效性。