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Modelling the Density of Inflation Using Autoregressive Conditional Heteroscedasticity, Skewness, and Kurtosis Models

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  • Doaa Akl Ahmed

    (University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom, and University of Benha, Egypt.)

Abstract

The paper aimed at modelling the density of inflation based on time-varying conditional variance, skewness and kurtosis model developed by Leon, Rubio, and Serna (2005) who model higher-order moments as GARCH-type processes by applying a Gram-Charlier series expansion of the normal density function. Additionally, it extended their work by allowing both conditional skewness and kurtosis to have an asymmetry term. The results revealed the significant persistence in conditional variance, skewness and kurtosis which indicate high asymmetry of inflation. Additionally, diagnostic tests reveal that models with nonconstant volatility, skewness and kurtosis are superior to models that keep them invariant.

Suggested Citation

  • Doaa Akl Ahmed, 2011. "Modelling the Density of Inflation Using Autoregressive Conditional Heteroscedasticity, Skewness, and Kurtosis Models," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 1-28, November.
    • Handle: RePEc:ere:journl:v:xxx:y:2011:i:2:p:1-28
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    References listed on IDEAS

    as
    1. Michael F. Bryan & Stephen G. Cecchetti, 1999. "Inflation And The Distribution Of Price Changes," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 188-196, May.
    2. Mr. Scott Roger, 2000. "Relative Prices, Inflation and Core Inflation," IMF Working Papers 2000/058, International Monetary Fund.
    3. Laurence Ball & N. Gregory Mankiw, 1995. "Relative-Price Changes as Aggregate Supply Shocks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(1), pages 161-193.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Kenneth F. Wallis, 2004. "An Assessment of Bank of England and National Institute Inflation Forecast Uncertainties," National Institute Economic Review, National Institute of Economic and Social Research, vol. 189(1), pages 64-71, July.
    6. Wilson, Bradley Kemp, 2006. "The links between inflation, inflation uncertainty and output growth: New time series evidence from Japan," Journal of Macroeconomics, Elsevier, vol. 28(3), pages 609-620, September.
    7. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Huang, Zhuo & Liang, Fang & Wang, Tianyi & Li, Chao, 2021. "Modeling dynamic higher moments of crude oil futures," Finance Research Letters, Elsevier, vol. 39(C).
    2. Doaa Akl Ahmed & Mamdouh M. Abdelsalam, 2015. "Modelling the Density of Egyptian Quarterly CPI Inflation," Working Papers 936, Economic Research Forum, revised Aug 2015.
    3. Durán-Vázquez, Rocio & Lorenzo-Valdes, Arturo & Ruiz-Porras, Antonio, 2012. "Un modelo GARCH con asimetría condicional autorregresiva para modelar series de tiempo: Una aplicación para el Indice de Precios y Cotizaciones [A GARCH model with autorregresive conditional asymme," MPRA Paper 42548, University Library of Munich, Germany.

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    More about this item

    Keywords

    inflation targeting; conditional volatility; skewness and kurtosis; modelling uncertainty of inflation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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