Mixed frequency forecasts for Chinese GDP

Arbeitspapier

We evaluate different approaches for using monthly indicators to predict Chinese GDP for the current and the next quarter ('nowcasts' and 'forecasts' respectively). We use three types of mixed-frequency models, one based on an economic activity indicator (Liu et al., 2007), one based on averaging over indicator models (Stock and Watson, 2004), and a static factor model (Stock and Watson, 2002). Evaluating all models' out-of-sample projections, we find that all the approaches can yield considerable improvements over naive AR benchmarks. We also analyze pooling across forecasting methodologies. We find that the most accurate nowcast is given by a combination of a factor model and an indicator model. The most accurate forecast is given by a factor model. Overall, we conclude that these models, or combinations of these models, can yield improvements in terms of RMSE's of up to 60 per cent over simple AR benchmarks.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Bank of Canada Working Paper ; No. 2011-11

Classification and Topics

• Classification: Wirtschaft ; Econometric Modeling: General ; Forecasting Models; Simulation Methods ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications ; Money and Interest Rates: Forecasting and Simulation: Models and Applications
• Subject: Econometric and statistical methods ; International topics ; Sozialprodukt ; Prognose ; Prognoseverfahren ; Bewertung ; China

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Maier, Philipp
• Event: Veröffentlichung
• (who): Bank of Canada
• (where): Ottawa
• (when): 2011

Further information

• DOI: doi:10.34989/swp-2011-11
• Handle: http://hdl.handle.net/10419/53764
• Last update: 10.03.2025, 11:43 AM CET