Using the characteristics of grey forecasting, which requires a small amount of sample data and a simple modeling process, to predict the main macroeconomic indicators in the early stage, combined with the filtering decomposition method and the production function method, establishes a short-term high-precision combination forecasting algorithm for macroeconomics based on the grey model. The algorithm uses the improved HP filter method in the HP filter method to study whether the potential economic growth rate can be more accurately measured, and the production function method is used to calculate the potential economic growth rate. First, the two methods are used to calculate the potential economic growth rate. The accuracy of this method finally established a combined model based on the two models for short-term forecasting. Under the premise of considering economic factors, the input data is preprocessed, and the high-precision combined forecast is used to finally obtain the macroeconomic forecast results. The calculation examples in the paper show that the method is feasible and effective.

中文翻译：

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基于灰色模型的宏观经济短期高精度组合预测算法

利用灰色预测需要样本数据量小、建模过程简单的特点，对前期主要宏观经济指标进行预测，结合滤波分解法和生产函数法，建立短期高——基于灰色模型的宏观经济精准组合预测算法。该算法在HP滤波法中采用改进的HP滤波法研究潜在经济增长率是否可以更准确地测算，并采用生产函数法计算潜在经济增长率。首先，用两种方法计算潜在经济增长率。该方法的准确性最终建立了基于两种模型的组合模型进行短期预测。在考虑经济因素的前提下，对输入数据进行预处理，采用高精度组合预测，最终得到宏观经济预测结果。文中的计算实例表明该方法是可行和有效的。