Functional Coefficient Moving Average Model with Applications to forecasting Chinese CPI
Lihua Lei and
MPRA Paper from University Library of Munich, Germany
This article establishes the functional coefficient moving average model (FMA), which allows the coefficient of the classical moving average model to adapt with a covariate. The functional coefficient is identified as a ratio of two conditional moments. Local linear estimation technique is used for estimation and asymptotic properties of the resulting estimator are investigated. Its convergence rate depends on whether the underlying function reaches its boundary or not, and asymptotic distribution could be nonstandard. A model specification test in the spirit of Hardle-Mammen (1993) is developed to check the stability of the functional coefficient. Intensive simulations have been conducted to study the finite sample performance of our proposed estimator, and the size and the power of the test. The real data example on CPI data from China Mainland shows the efficacy of FMA. It gains more than 20% improvement in terms of relative mean squared prediction error compared to moving average model.
Keywords: Moving Average model; functional coefficient model; forecasting; Consumer Price Index. (search for similar items in EconPapers)
JEL-codes: C1 C13 C5 C51 C53 (search for similar items in EconPapers)
Date: 2014, Revised 2015
New Economics Papers: this item is included in nep-cna, nep-ecm, nep-for and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:67074
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