Forecasting Imports Price Growth in China with Many Potentially Relevant Predictors: an Analysis of Forecast Methods

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Jiang 1

Forecasting Imports Price Growth in China With Many Potentially Relevant Predictors: An Analysis of Forecast Methods

Lili Jiang Saint Louis University ECON 698 Professor: Hailong Qian

Jiang 2

This paper examines to forecast monthly growth rate of import price in China in the presence of 19 potentially relevant predictors, including international trade related variables, broad economic trend measurement, world CPI and world commodity prices and indices from January 1994 to January 2013. Simulated out-of-sample autoregressive model serves as the benchmark model. Individual autoregressive distributed lag (ARDL) model, simple averaging combination forecast, approximate Bayesian model averaging combination forecast, discount MSFE combination forecast and diffusion indices forecast are built to compete the benchmark model. We found that all combination forecasts outperform benchmark forecast but are not statistically significant by using Clark & West test. The ARDL model with the predictor of China export price and China PPI beat the benchmark model significantly. Finally, resorting to Diebold and Mariano test, we found that the predictor of PPI in China performs best in forecasting the growth rate of import price in China.

Jiang 3

1. Introduction
In the past 20 years, China has undertaken market oriented economic reforms and achieved an average annual growth rate of 9.62%. The expansion of economic activities and growth of household expenditure and further decrease of custom tax level have led to a surge in demand of imported goods. China has become one of the largest importers in the world, which has a total value of imported goods of USD 1818 billion in 2012, average growth as 21% in the past 10 years(Figure 1). The import of iron ore and crude oil pushed the pace of the increase.…...

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