Measuring China's core inflation for forecasting purposes: taking persistence as weight
Yushan Hu () and
Penglong Zhang ()
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Zhiyong Fan: Renmin University of China
Empirical Economics, 2022, vol. 63, issue 1, No 3, 93-111
Abstract This paper constructs China's core inflation index based on persistence weights for monetary policy and inflation forecast. We apply the univariate autoregression model (AR), whereby the sum of autoregression coefficients is used to measure inflation persistence. Due to the possible unit root, we adopt the grid-bootstrap method to obtain the estimates for the inflation persistence. We re-weight the importance of each CPI component, according to its relative persistence. By comparing with traditional core inflation and headline inflation, we find that the persistence-weighted core inflation, is a leading indicator and an attractor of China's headline inflation, with a strong ability to predict the short-term headline inflation, as well as monetary policy decisions.
Keywords: Inflation persistence; Core inflation; Inflation forecast (search for similar items in EconPapers)
JEL-codes: C10 E31 E37 (search for similar items in EconPapers)
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