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Analyzing and Forecasting Movements of the Philippine Economy using the Dynamic Factor Models (DFM)

机译:利用动态因子模型(DFm)分析和预测菲律宾经济运行

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摘要

The country’s small and open economy is vulnerable to both internal and external shocks. Is it therefore important for policy makers to have timely forecasts on the movement of the country’s Gross Domestic Product (GDP), whether it will increase or decrease in the current quarter, to be able to guide them in coming up with appropriate policies to mitigate say, the impact of a shock. The current method used to forecast the movements of the GDP is the composite Leading Economic Indicators System (LEIS) developed by the National Economic Development Authority (NEDA) and the National Statistical Coordination Board (NSCB). The LEIS, using 11 economic indicators, provides one-quarter forecast of the movement of the GDP. This paper presents an alternative, and perhaps better, procedure to the LEIS in nowcasting the movements of the GDP using the Dynamic Factor Model (DFM). The idea behind the DFM is the stylized fact that economic movements evolve in a cycle and are correlated with co-movements in a large number of economic series. The DFM is a commonly used data reduction procedure that assumes economic shocks driving economic activity arise from unobserved components or factors. The DFM aims to parsimoniously summarize information from a large number of economic series to a small number of unobserved factors. The DFM assumes that co-movements of economic series can be captured using these unobserved common factors. This paper used 31 monthly economic indicators in capturing a common factor to nowcast movements of GDP via the DFM. The results show that the common factor produced by the DFM performed better in capturing the movements of the GDP when compared with the LEIS. The DFM is a promising and useful methodology in extracting indicators of the country’s economic activity.
机译:该国小而开放的经济易受内部和外部冲击的影响。因此,对于政策制定者来说,及时预测该国的国内生产总值(GDP)的变化(在本季度将增加还是减少)是否很重要,以便能够指导他们制定适当的政策以减轻影响,冲击的冲击。当前用于预测GDP变动的方法是由国家经济发展局(NEDA)和国家统计协调委员会(NSCB)开发的综合领先经济指标系统(LEIS)。 LEIS使用11个经济指标,提供了GDP变动预测的四分之一。本文提出了一种使用动态因子模型(DFM)来预测GDP变动的LEIS替代方法,也许是更好的方法。 DFM背后的想法是程式化的事实,即经济运动在一个周期中发展,并与大量经济系列中的共同运动相关联。 DFM是一种常用的数据精简程序,该程序假定驱动经济活动的经济冲击是由未观察到的组件或因素引起的。 DFM旨在从大量经济系列到少量未观察到的因素来简约地总结信息。 DFM假定可以使用这些未观察到的共同因素来捕获经济序列的共同运动。本文使用31个月度经济指标来捕捉通过DFM预测GDP变动的共同因素。结果表明,与LEIS相比,DFM产生的公因子在捕获GDP的变化方面表现更好。 DFM是一种用于提取该国经济活动指标的有前途且有用的方法。

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