非线性多元协整回归的模型规格检验

Chaohua Dong, Jiti Gao, D. Tjøstheim, Jiying Yin
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引用次数: 0

摘要

本文考虑非线性多元协整回归的一般模型规格检验,其中回归量由单变量积分时间序列和平稳时间序列向量组成。回归量和误差都是由相同的创新产生的,因此模型可以容纳内生性。提出了一种新的、简单的检验方法,并建立了渐近理论。检验统计量是基于非参数估计值和平滑参数估计值之间的自然距离函数构造的。检验统计量在参数规范下的渐近分布与具有已知分布的局部时间随机变量的渐近分布成正比。此外,通过模拟和实际数据实例对所提出的测试的有限样本性能进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model Specification Testing for Nonlinear Multivariate Cointegrating Regressions
This paper considers a general model specification test for nonlinear multivariate cointegrating regressions where the regressor consists of a univariate integrated time series and a vector of stationary time series. The regressors and the errors are generated from the same innovations, so that the model accommodates endogeniety. A new and simple test is proposed and the resulting asymptotic theory is established. The test statistic is constructed based on a natural distance function between a nonparametric estimate and a smoothed parametric counterpart. The asymptotic distribution of the test statistic under the parametric specification is proportional to that of a local-time random variable with a known distribution. In addition, the finite sample performance of the proposed test is evaluated through using both simulated and real data examples.
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