Forecasting China's GDP Growth with Lagged Investment and Household Consumption
DOI:
https://doi.org/10.71465/jgs61Keywords:
China GDP growth, investment, household consumption, random forest, World Bank WDIAbstract
This study examines a narrow forecasting task: predicting China's annual real GDP growth with one-year lagged macroeconomic indicators from the World Bank World Development Indicators [1]. The predictors include lagged GDP growth, gross capital formation growth, household final consumption growth, industrial value-added growth, and CPI inflation. The training sample covers 1996-2018, and the test sample covers 2019-2024. A historical-mean benchmark, a linear regression model, and a compact random-forest model are compared. The results show that the random forest improves on the historical mean in this small test period, but it still misses the sharp movements around 2020 and 2021. The evidence supports a cautious use of machine-learning forecasts as a complement to conventional macroeconomic interpretation [4, 6].
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Copyright (c) 2026 Liangyan Cai , Hanfu Liang (Author)
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