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Nonparametric Testing for Long-Run Neutrality with Applications to US Money and Output Data

机译：长期中立性的非参数测试及其在美国货币和产出数据中的应用

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摘要

We consider a nonparametric testing procedure for long-run monetary neutrality using spectral approaches. Long-run effects between bivariate integrated series are represented as the spectral density matrix of their first-differences evaluated at the zero frequency. The long-run neutrality, the core issue in this work, reduces to zero power of the cross spectral density function near the origin. We propose a statistic based on a kernel-based cross spectral density estimator. As designed to be consistent against cross correlations of unknown forms, the test differentiates it from tests based on parametric regression models. In implementing the tests, some feasible bandwidth selection procedures are detailed in terms of mean squared error criteria and of type I and type II errors criteria. Our testing procedures can be a complementary approach for neutrality testing. Simulation studies are shown to support theoretical results. Our methods are applied to testing long-run neutrality in the US nominal money and real output quarterly data from the first quarter of 1959 to the third quarter of 2009. Our tests unanimously reject the long-run neutrality for M2 regardless of the choice of bandwidths and of kernels.
机译：我们考虑使用频谱方法对长期货币中立性进行非参数测试。双变量积分序列之间的长期影响表示为在零频率处评估的一阶差分的频谱密度矩阵。长期中立性是这项工作的核心问题，在原点附近，交叉谱密度函数的功率降低到零。我们提出了一种基于核的交叉谱密度估计量的统计量。为了与未知形式的互相关保持一致，该测试将其与基于参数回归模型的测试区分开来。在实施测试时，根据均方误差标准以及I型和II型误差标准详细介绍了一些可行的带宽选择程序。我们的测试程序可以作为中立性测试的补充方法。仿真研究表明可以支持理论结果。我们的方法用于测试从1959年第一季度到2009年第三季度的美国名义货币的长期中立性和实际输出季度数据。我们的测试一致拒绝M2的长期中立性，而不考虑带宽的选择和内核。

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