ARIMA Forecasting Chinese Macroeconomic Variables Based on Factor and Principal Component Backdating
Pages 91-99

Wei Wang and Yan Liu
DOI: https://doi.org/10.6000/1927-5129.2017.13.16
Published: 12 April 2017

Abstract:  In this paper the backdating methods based on factors and principal components are applied for the first time to emulate the historical macroeconomic variables in China. The numerical results show that these procedures are useful to backdate some missing or not available historical data. ARIMA forecasting experiments based on backdated historical data are conducted and compared with forecasting procedures using directly factors and principal components. Our results suggest that some key variables like GDP can indeed be forecasted more precisely with the principal components backdated data.

Keywords: Backdating, Factor model, Principal components, ARIMA forecasting, GDP of China.

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