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摘要翻译：
我们发展了一个相关趋势周期分解的推广，通过将永久分量建模为分数积分过程，并在周期分量的自回归多项式中加入分数滞后算子，避免了对长期动态特性的先验假设。该模型允许与其他模型参数联合对集成顺序进行内生估计，因此，不需要关于持久性的事先规范测试。我们将该模型与Beveridge-Nelson分解联系起来，并推导出分数分量的修正Kalman滤波估计量。给出了极大似然估计的可辨识性、相合性和渐近正态性。对于美国宏观经济数据，我们证明了与$I(1)$相关的未观测分量模型不同，新模型估计了一个平稳的趋势，同时也估计了一个冲击所有NBER衰退的周期。当数据生成机制的积分阶数大于1时，$I(1)$未观测分量模型产生向上偏置的信噪比，而分数积分模型由于分数趋势规范对长期冲击的变化较小，由于分数滞后算子对周期冲击的变化较大，导致更持久的周期和反映宏观经济常识的平滑趋势估计。
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英文标题：
《Fractional trends and cycles in macroeconomic time series》
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作者：
Tobias Hartl, Rolf Tschernig, Enzo Weber
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最新提交年份：
2020
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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：
We develop a generalization of correlated trend-cycle decompositions that avoids prior assumptions about the long-run dynamic characteristics by modelling the permanent component as a fractionally integrated process and incorporating a fractional lag operator into the autoregressive polynomial of the cyclical component. The model allows for an endogenous estimation of the integration order jointly with the other model parameters and, therefore, no prior specification tests with respect to persistence are required. We relate the model to the Beveridge-Nelson decomposition and derive a modified Kalman filter estimator for the fractional components. Identification, consistency, and asymptotic normality of the maximum likelihood estimator are shown. For US macroeconomic data we demonstrate that, unlike $I(1)$ correlated unobserved components models, the new model estimates a smooth trend together with a cycle hitting all NBER recessions. While $I(1)$ unobserved components models yield an upward-biased signal-to-noise ratio whenever the integration order of the data-generating mechanism is greater than one, the fractionally integrated model attributes less variation to the long-run shocks due to the fractional trend specification and a higher variation to the cycle shocks due to the fractional lag operator, leading to more persistent cycles and smooth trend estimates that reflect macroeconomic common sense.
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PDF链接：
https://arxiv.org/pdf/2005.05266
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