中国宏观经济总量的实时预报与短期预测——基于混频数据预测模型的实证研究

Nowcasting and Short-term Forecasting of Chinese Macroeconomic Aggregates: Based on the Empirical Study of MIDAS Model

季度GDP的走势与波动不仅会影响政府的财政收支、企业的盈利和财务状况,甚至还会影响家庭和个人的收入与支出,是宏观经济总量预报、预测与分析的重中之重。传统的宏观经济总量预测模型是基于同频数据进行的,高频和超高频数据必需处理为低频数据,这不仅忽略了高频数据信息的变化,还影响了模型预报和预测的及时性,降低了模型的预测精度。本文将混合数据抽样模型(MIDAS)用于中国季度GDP的预报和预测,实证研究表明,出口是造成我国金融危机时期经济增长减速的主要因素,MIDAS模型在中国宏观经济总量的短期预测方面具有精确性的比较优势,在实时预报方面具有显著的可行性和时效性。

The trend and fluctuations in quarterly GDP have great influence on the revenue and expenditure of governments, the profits and financial situation of corporate, and even have effects on the income and expenditure of families and individuals. They are the key variables in macroeconomic forecasting, prediction and analysis. Traditional macroeconomic forecasting models are based on the same frequency data, high frequency and ultra high frequency data must be change into low-frequency data, which ignored the information of high-frequency data, and timeliness of forecasts and the accuracy of prediction are decreased. Mixed data sampling （MIDAS） models are used for forecasting and noweasting Chinese quarter GDP, and empirical results show that the export is the major factor caused the depreciate of Chinese economic growth during the period of financial crisis. The results verify the comparative advantage of MIDAS models in the accuracy of macroeconomic short-term forecasting, and have significant feasibility and timeliness in nowcasting.