估算新冠肺炎紧急情况对危地马拉税收的影响:时间序列方法

J. H. Cole
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引用次数: 0

摘要

时间序列模型的应用有两个不同的目的:(1)作为预测技术,它们被用来预测未来一定数量时期内感兴趣的变量的轨迹;(2)在干预分析中,它们被用来评估一个显著的干扰对被研究过程的影响。我们使用这两种类型的应用程序来研究危地马拉的每月税收收入。在第2节中,我们使用2010-2019年的数据来比较两种可选模型:(a) Box-Jenkins (ARIMA)模型和(b) Holt-Winters指数平滑模型。在第3节中,我们使用2019年后的数据来估计为遏制Covid-19大流行而实施的紧急措施的财政影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating the Impact of the Covid-19 Emergency on Tax Revenues in Guatemala: A Time Series Approach
Applications of time series models serve two different purposes: (1) as forecasting techniques, they are used to project the trajectory of a variable of interest during a certain number of future periods; (2) in the analysis of interventions, they are used to evaluate the effect of a significant disturbance on the process being studied. We use both types of application to study monthly tax revenues in Guatemala. In Section 2 we use data for 2010-2019 in order to compare two alternative models: (a) the Box-Jenkins (ARIMA) model, and (b) the Holt-Winters exponential smoothing model. In Section 3 we use post-2019 data to estimate the fiscal effects of the emergency measures implemented to contain the Covid-19 pandemic.
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