Macroeconomic forecasting based on mixed frequency vector autoregression and neural network models

HIGHLIGHTS

• who: Fangze Cheng from the School of Finance, Southwestern University of Finance and Economics, Chengdu, China have published the paper: Macroeconomic Forecasting Based on Mixed Frequency Vector Autoregression and Neural Network Models, in the Journal: Wireless Communications and Mobile Computing of 30/08/2022
• what: The authors propose a prediction model based on chaotic vector autoregression and neural networks for macroeconomic forecasting and the authors model and test the prediction with GDP and inflation as the main concerns and the authors find that the improvement of GDP forecasting shows an increase of expected inflation rate . . .
  

   

  

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