Re-validating the Phillips Curve hypothesis in Africa and the role of oil prices: A mixed-frequency approach

Abstract

This paper investigates the relationship between unemployment and inflation in 29 African economies by re-examining the Phillips Curve hypothesis and evaluating the role of global oil prices in predicting inflation. Existing studies often use uniform-frequency variables, which can lead to biased results by omitting information from high-frequency series. We employ a mixed data sampling regression model to analyze inflation in selected African countries by regressing monthly inflation rates on annual unemployment rates and daily oil price returns. Our findings show that the Phillips Curve hypothesis holds in a few countries across Central Africa (Cameroon, the Central African Republic, Chad, and Republic of the Congo), East Africa (Rwanda), North Africa (Algeria), Southern Africa (Botswana and Malawi), and West Africa (Burkina Faso and Mauritania). In the other countries, the hypothesis does not hold, potentially indicating a predominance of cost-push inflation. Our analysis demonstrates that global oil prices impact inflation differently across these countries. Additionally, daily oil price data significantly enhance inflation forecasting compared to monthly data. Incorporating additional economic variables, such as exchange rates and interest rates, further improves forecast accuracy. We recommend targeted monetary policies to mitigate the impacts of oil price fluctuations and unemployment on inflation.