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Forecasting the Romanian inflation rate: An Autoregressive Integrated Moving-Average (ARIMA) approach

Author

Listed:
  • Rareș-Petru MIHALACHE

    (National Institute for Economic Research "Costin C. Kirițescu", Romanian Academy, Romania)

  • Dumitru Alexandru BODISLAV

    (Bucharest University of Economic Studies, Romania)

Abstract

The primary objectives of this paper are to empirically create an univariate Autoregressive Integrated Moving-Average (model) using Box-Jenkins methodology to forecast Romanian inflation and inspect the prediction performance of the estimated model between October 2021 and October 2022. This study uses Ordinary Least Squares (OLS) technique for estimation purposes. On the foundation of different selection assessment and diagnostic criteria, the best model is selected to predict inflation in Romania in the short-run. We find that ARIMA (7, 1, 1) model is a suitable one under model identification, parameters estimation, diagnostic checking, and inflation prediction. In-sample forecasting is performed and the estimated ARIMA model reasonably tracks the actual inflation in the sample period.

Suggested Citation

  • Rareș-Petru MIHALACHE & Dumitru Alexandru BODISLAV, 2023. "Forecasting the Romanian inflation rate: An Autoregressive Integrated Moving-Average (ARIMA) approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(1(634), S), pages 67-76, Spring.
    • Handle: RePEc:agr:journl:v:1(634):y:2023:i:1(634):p:67-76
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    References listed on IDEAS

    as
    1. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Forecasting Irish inflation using ARIMA models," Research Technical Papers 3/RT/98, Central Bank of Ireland.
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