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

Abstract

This paper investigates the nexus between unemployment and inflation in 29 African economies, re-examining the Phillips Curve hypothesis and evaluating the role of global oil prices in inflation prediction. Uniform-frequency variables often used in existing studies can lead to biased results by omitting information from low-frequency series. We address this by using a mixed data sampling regression model to analyze inflation rates in selected countries, regressing monthly inflation rates on annually measured unemployment rates and daily oil price returns. Our findings show that the Phillips Curve hypothesis holds in a few countries across Central (Cameroon, Central African Republic, Chad, and Congo Republic), Eastern (Rwanda), Northern (Algeria), Southern (Botswana and Malawi), and Western (Burkina Faso and Mauritania) Africa, with demand-driven inflation predominant in Central Africa. In other countries, the hypothesis does not hold, indicating a predominance of supply-driven inflation. Our analysis demonstrates that global oil prices impact inflation variably across countries, depending on specific economic fundamentals. Daily oil price data significantly enhance inflation forecasting over monthly data. Including additional economic variables like exchange and interest rates improves forecast accuracy and highlights their importance. We recommend targeted monetary policies to address the impacts of oil price fluctuations and unemployment on inflation.