Determinants of Agricultural Commodity Price Fluctuations: Evidence from Time Series Data

Price instability in agricultural markets undermines farm incomes, threatens food security and creates macroeconomic uncertainty. This article investigates the drivers of monthly agricultural commodity price fluctuations from January 2000 to September 2024 using an extensive time series data set compiled from the International Monetary Fund’s primary commodity price database and complementary series. The study develops a conceptual framework linking prices to supply and demand fundamentals, expectations, macro financial conditions and institutional factors. A rich body of literature is reviewed to situate the work within recent debates on food price volatility. Empirically, the paper employs unit root and cointegration tests, vector error correction and vector autoregressive models, Granger causality, impulse response analysis, forecast error variance decomposition and an ARCH–GARCH volatility model. Results show that major food and input prices are non-stationary but cointegrated; shocks in oil and industrial inputs spill over to food and fertiliser indices; and a GARCH (1,1) model highlights persistent volatility clustering in food prices. Structural drivers—including growing population and income, biofuel demand, energy prices, climate shocks, low stocks, exchange rate swings and financial speculation—are discussed in light of empirical findings. Policy recommendations emphasise improving market transparency, strengthening grain reserves, investing in climate-resilient agriculture, enhancing risk management tools and fostering multilateral coordination to mitigate excessive volatility. The study contributes to the econometric evidence base on food price dynamics and offers actionable insights for governments, development agencies and market participants.