The role of oil prices in Philips curve modelling and forecasting of inflation

Orientation: The availability of an accurate and a reliable quantitative method for forecasting the behaviour of inflation is of importance, given the emphasis on price stability by central banks. Research purpose: The conventional Phillips curve predictive model to explain the role of oil prices a...

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Main Authors: Ojo J. Adelakun, Harold Ngalawa
Format: Article
Language:English
Published: AOSIS 2020-06-01
Series:Journal of Economic and Financial Sciences
Subjects:
Online Access:https://jefjournal.org.za/index.php/jef/article/view/499
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author Ojo J. Adelakun
Harold Ngalawa
author_facet Ojo J. Adelakun
Harold Ngalawa
author_sort Ojo J. Adelakun
collection DOAJ
description Orientation: The availability of an accurate and a reliable quantitative method for forecasting the behaviour of inflation is of importance, given the emphasis on price stability by central banks. Research purpose: The conventional Phillips curve predictive model to explain the role of oil prices and associated implications in the forecasting of inflation using data from oil-exporting and oil-importing countries. Motivation for the study: To determine whether augmenting the traditional demand-side Phillips curve with oil price supply-side shocks matters for the accuracy of predicting inflation using the Phillips curve. Study to investigate the role of oil prices in the Phillip curve accuracy to predict inflation from the perspective of oil exporting –oil importing dichotomy. Research approach/design and method: We extend the conventional Phillips curve predictive model to explain the role of oil prices and associated implications in the forecasting of inflation using data from oil-exporting and oil-importing countries. The study demonstrates that the forecast performance of the traditional (demand-based) Phillips curve improves when it is augmented with oil prices. Main findings: We also find that, contrary to previous findings in the literature, the augmented Phillips curve model, which incorporates oil prices as a supply-side factor, outperforms the random walk model. Practical/managerial implications: The robustness of these findings is evident across different sub-sample periods, forecast horizons and individual oil-exporting and oil-importing countries under consideration. Contribution/value-add: The comparison outcome further reaffirms that the augmented Phillips curve with changes in oil prices as a proxy for the supply-side factor is the preferred predictive model in both in-sample and out-of-sample forecast performance.
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spelling doaj.art-c9e75d998e3145838e02aa668118373e2022-12-21T21:18:09ZengAOSISJournal of Economic and Financial Sciences1995-70762312-28032020-06-01131e1e1110.4102/jef.v13i1.499400The role of oil prices in Philips curve modelling and forecasting of inflationOjo J. Adelakun0Harold Ngalawa1Department of Economics, School of Accounting, Economics and Finance, College of Law and Management Studies, University of KwaZulu-Natal, Durban,Department of Economics, School of Accounting, Economics and Finance, College of Law and Management Studies, University of KwaZulu-Natal, DurbanOrientation: The availability of an accurate and a reliable quantitative method for forecasting the behaviour of inflation is of importance, given the emphasis on price stability by central banks. Research purpose: The conventional Phillips curve predictive model to explain the role of oil prices and associated implications in the forecasting of inflation using data from oil-exporting and oil-importing countries. Motivation for the study: To determine whether augmenting the traditional demand-side Phillips curve with oil price supply-side shocks matters for the accuracy of predicting inflation using the Phillips curve. Study to investigate the role of oil prices in the Phillip curve accuracy to predict inflation from the perspective of oil exporting –oil importing dichotomy. Research approach/design and method: We extend the conventional Phillips curve predictive model to explain the role of oil prices and associated implications in the forecasting of inflation using data from oil-exporting and oil-importing countries. The study demonstrates that the forecast performance of the traditional (demand-based) Phillips curve improves when it is augmented with oil prices. Main findings: We also find that, contrary to previous findings in the literature, the augmented Phillips curve model, which incorporates oil prices as a supply-side factor, outperforms the random walk model. Practical/managerial implications: The robustness of these findings is evident across different sub-sample periods, forecast horizons and individual oil-exporting and oil-importing countries under consideration. Contribution/value-add: The comparison outcome further reaffirms that the augmented Phillips curve with changes in oil prices as a proxy for the supply-side factor is the preferred predictive model in both in-sample and out-of-sample forecast performance.https://jefjournal.org.za/index.php/jef/article/view/499inflation-forecastspredictive modelphillips curveoil pricesrmsearmseardl
spellingShingle Ojo J. Adelakun
Harold Ngalawa
The role of oil prices in Philips curve modelling and forecasting of inflation
Journal of Economic and Financial Sciences
inflation-forecasts
predictive model
phillips curve
oil prices
rmse
armse
ardl
title The role of oil prices in Philips curve modelling and forecasting of inflation
title_full The role of oil prices in Philips curve modelling and forecasting of inflation
title_fullStr The role of oil prices in Philips curve modelling and forecasting of inflation
title_full_unstemmed The role of oil prices in Philips curve modelling and forecasting of inflation
title_short The role of oil prices in Philips curve modelling and forecasting of inflation
title_sort role of oil prices in philips curve modelling and forecasting of inflation
topic inflation-forecasts
predictive model
phillips curve
oil prices
rmse
armse
ardl
url https://jefjournal.org.za/index.php/jef/article/view/499
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