Post-COVID inflation and monetary policy in Morocco: analysis using a Bayesian VAR model

Purpose This study investigates the key drivers of inflation in Morocco and assesses the effectiveness of post-COVID monetary policy interventions in managing inflationary dynamics. Design/methodology/approach The analysis is based on a Bayesian Vector Autoregression (BVAR) model that captures the dynamic interactions between inflation, energy prices, GDP growth, exchange rate and policy rate. Structural shocks were identified using a recursive identification scheme. Findings The results indicate that energy prices and economic growth are the main drivers of inflationary pressures, jointly accounting for over 30% of the variance in inflation, while the exchange rate contributes approximately 6%. The inflation in Morocco shows strong persistence over the short term. The post-COVID monetary policy had limited immediate effects on inflation but played a crucial role in anchoring expectations and supporting medium-term price stability. Originality/value This study is among the first to apply a BVAR and a TVP-VAR framework to inflation dynamics in Morocco by incorporating newly constructed quarterly real GDP data. It provides novel empirical evidence on the relative importance of supply and demand shocks in a developing economy context, and highlights the structural constraints affecting the transmission of monetary policy in the post-pandemic period.