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Deflationary Dynamics in Hong Kong: Evidence from Linear and Neural Network Regime Switching Models

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  • Paul D. McNelis

    (Georgetown University)

  • Carrie K.C. Chan

    (Hong Kong Monetary Authority)

Abstract

This paper examines Deflationary dynamics in Hong Kong with a linear and a nonlinear neural-network regime-switching (NNRS) model. The NNRS model is superior to the linear model in terms of in-sample specification tests as well as out-of-sample forecasting accuracy. As befitting a small and highly open economy, the most important variables affecting inflation and deflation turn out to be the growth rates of import prices and wealth (captured by the rates of growth of residential property prices). The NNRS model indicates that the likelihood of moving out of deflation has been steadily increasing.

Suggested Citation

  • Paul D. McNelis & Carrie K.C. Chan, 2004. "Deflationary Dynamics in Hong Kong: Evidence from Linear and Neural Network Regime Switching Models," Working Papers 212004, Hong Kong Institute for Monetary Research.
    • Handle: RePEc:hkm:wpaper:212004
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