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Testing for Factor Loading Structural Change under Common Breaks

机译:共同中断下因素加载结构变化的测试

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摘要

This paper proposes a new test for factor loading structural change in dynamic factor models. The proposed test is robust to the nonmonotonic power problem that occurs if the factor loadings exhibit structural changes at common dates over cross-sections. To illustrate the usefulness of our test, we first show that the leading test proposed by Breitung and Eickmeier (2011) exhibits nonmonotonic power, essentially because the breaks are considered as spurious factors with stable factor loadings. We use both local and non-local asymptotic frameworks to investigate the power of their test. The new test eliminates the effects of the spurious factors by maximizing the test statistic over possible numbers of the original factors. This approach is effective because the original factors are not identified under the alternative hypothesis. Monte Carlo simulations and an empirical example using U.S. Treasury yield curve data clearly illustrate the validity of the asymptotic power analysis and usefulness of the proposed test.
机译:本文为动态因素模型中的因素加载结构变化提出了一种新的检验方法。拟议的测试对于非单调功率问题是稳健的,如果因子载荷在横截面上的共同日期处显示出结构变化,则该问题很健壮。为了说明我们的测试的有用性,我们首先证明了Breitung和Eickmeier(2011)提出的领先测试表现出非单调性,主要是因为中断被认为是具有稳定因子负载的杂散因子。我们使用局部和非局部渐近框架来研究其测试的能力。新测试通过在可能的原始因子数量上最大化测试统计量,消除了杂散因子的影响。该方法之所以有效,是因为在替代假设下未确定原始因素。蒙特卡洛模拟和使用美国国债收益率曲线数据的经验示例清楚地说明了渐近幂分析的有效性和拟议测试的有效性。

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