Nowcasting the Spanish Economy Using Very High Frequency Tax Data

Ángel Cuevas, Ramiro Ledo, Enrique M. Quilis
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Abstract

We present a short-term forecasting model based on tax data. The model combines daily information from the Immediate Supply of Information System for VAT declaration forms, with monthly indicators derived from tax data. The model uses the GDP as a macroeconomic synthesis. The model combines signal extraction and forecasting at the daily frequency, by means of an unobserved components model, with a mixed frequency (monthly-quarterly) dynamic factor analysis for GDP now-casting and forecasting. The daily information, plus the flexibility and efficiency of the factor models, allows a permanently updated monitoring of the short-term economic conditions of the Spanish economy.
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利用甚高频税收数据预测西班牙经济
我们提出了一个基于税收数据的短期预测模型。该模型结合了来自增值税申报表即时信息系统的每日信息,以及来自税务数据的月度指标。该模型使用GDP作为宏观经济综合指标。该模型结合了每日频率的信号提取和预测,通过一个未观察到的成分模型,与混合频率(月-季度)动态因素分析的GDP现在铸造和预测。每日信息,加上因素模型的灵活性和效率,允许对西班牙经济的短期经济状况进行永久更新的监测。
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