摘要翻译：
时间平均一直是处理混合采样频率的传统方法。然而，它忽略了可能嵌入高频的信息。混合数据抽样(MIDAS)回归模型提供了一种简明的方法来利用高频变量中的附加信息。本文在Durbin-Wu-Hausman测试的基础上，提出了一种在时间平均模型和MIDAS模型之间进行选择的规范测试。特别是在频率比较大的情况下，提出了一组工具变量，并进行了理论验证。结果表明，我们的方法比现有的方法更有效，通过仿真验证了这一点。
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英文标题：
《On the Choice of Instruments in Mixed Frequency Specification Tests》
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作者：
Yun Liu and Yeonwoo Rho
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最新提交年份：
2018
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  Time averaging has been the traditional approach to handle mixed sampling frequencies. However, it ignores information possibly embedded in high frequency. Mixed data sampling (MIDAS) regression models provide a concise way to utilize the additional information in high-frequency variables. In this paper, we propose a specification test to choose between time averaging and MIDAS models, based on a Durbin-Wu-Hausman test. In particular, a set of instrumental variables is proposed and theoretically validated when the frequency ratio is large. As a result, our method tends to be more powerful than existing methods, as reconfirmed through the simulations.
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PDF链接：
https://arxiv.org/pdf/1809.05503