A Bayesian approach for analyzing the dynamic relationship between quarterly and monthly economic indicators
A Bayesian approach for analyzing the dynamic relationship between quarterly and monthly economic indicators
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分析季度和月度经济指标动态关系的贝叶斯方法
DOI：
10.1007/978-3-030-01174-1_2
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
K. Kyo
中科院分区：
文献类型：
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作者：
Susumu Takenaga;Susumu Takenaga;竹永 進;竹永 進;K. Kyo;K. Kyo;K. Kyo and H. Noda;K. Kyo
我们提出了一种分析季度经济指标和月度经济指标之间动态关系的方法。在这项研究中，我们使用日本的实际国内生产总值(GDP)和整体商业销售(WCS)分别作为季度和月度指标的例子。我们首先估计这些指标的原始时间序列中的平稳成分，目的是分析GDP的平稳成分与世界经济总量的动态相关性。为此，我们在WCS的平稳成分的基础上，引入滞后参数和时变系数，构建了GDP平稳成分的贝叶斯回归模型。为了验证这一分析方法，我们分析了1982-2005年间日本GDP与WCS-FAP(农业和水产品WCS)之间的关系。
We propose an approach for analyzing the dynamic relationship between a quarterly economic indicator and a monthly economic indicator. In this study, we use Japan’s real gross domestic product (GDP) and whole commercial sales (WCS) as examples of quarterly and monthly indicators, respectively. We first estimate stationary components from the original time series for these indicators, with the goal of analyzing the dynamic dependence of the stationary component of GDP on that of WCS. To do so, we construct a set of Bayesian regression models for the stationary component of GDP based on the stationary component of WCS, introducing a lag parameter and a time-varying coefficient. To demonstrate this analytical approach, we analyze the relationship between GDP and WCS-FAP, the WCS of farm and aquatic products, in Japan for the period from 1982 to 2005.