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Understanding the dynamics of inflation volatility in Nigeria: A GARCH perspective

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  • Omotosho, Babatunde S.
  • Doguwa, Sani I.

Abstract

The estimation of inflation volatility is important to central banks as it guides their policy initiatives for achieving and maintaining price stability. This paper employs three models from the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family with a view to providing a parsimonious approximation to the dynamics of Nigeria’s inflation volatility between 1996 and 2011. Of the competing models, the asymmetric TGARCH (1,1) provides an appropriate paradigm for explaining the dynamics of headline and core CPI volatilities in Nigeria, while the symmetric GARCH (1,1) was found to be adequate for food CPI. The results are quite revealing. Firstly, model outcomes indicate high persistence parameters for the core and food CPI, implying that the impacts of inflation shocks on their volatilities die away very slowly. However, the impact of inflation shocks on headline volatility die out rather quickly. Secondly, substantial evidence of asymmetric effect was found for both headline and core inflation types while the contrary was confirmed for food inflation. Thirdly, positive inflationary shocks yielded higher volatilities in headline and core inflation than negative innovations, implying the absence of leverage effect in them. The paper finds that periods of high inflation volatility are associated with periods of specific government policy changes, shocks to food prices and lack of coordination between monetary and fiscal policies.

Suggested Citation

  • Omotosho, Babatunde S. & Doguwa, Sani I., 2012. "Understanding the dynamics of inflation volatility in Nigeria: A GARCH perspective," MPRA Paper 96125, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:96125
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    References listed on IDEAS

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    Cited by:

    1. Yaya, OlaOluwa S. & Olayinka, Hammed Abiola & Adebiyi, Aliu A & Atoi, Ngozi Victor & Olugu, Mercy U. & Akinkunmi, Wasiu B., 2024. "Rural and Urban price inflation components in Nigeria: Persistence, Connectedness and Spillovers," MPRA Paper 121106, University Library of Munich, Germany.
    2. Kris Boudt & Hong Anh Luu, 2022. "Estimation and decomposition of food price inflation risk," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 295-319, June.
    3. Terhemba Iorember, Paul & Usar, Terzungwe & Hannafi Ibrahim, Kabiru, 2018. "Analyzing inflation in Nigeria: a fractionally integrated ARFIMA-GARCH modelling Approach," African Journal of Economic Review, African Journal of Economic Review, vol. 6(1), January.

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    More about this item

    Keywords

    Inflation volatility; Conditional heteroscedasticity; GARCH models; Asymmetric effects; Volatility persistence;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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