Arima-Based Forecasting of Poultry Egg and Meat Prices in Key Markets of Karnataka

Poultry production, a key contributor to India's agricultural sector, faces challenges such as price volatility, seasonal fluctuations and external market influences. Accurate price forecasting for poultry products like eggs and meat is crucial for stabilizing markets and ensuring the livelihood of stakeholders. This study employs the ARIMA (Auto-Regressive Integrated Moving Average) model to forecast egg and meat prices in Karnataka's major markets, including Bengaluru, Hubballi and Mysuru, using monthly price data from January 2017 to March 2025. The Box-Jenkins methodology was applied for model identification, estimation and diagnostic checking. The optimal models were selected based on the Mean Absolute Percentage Error (MAPE), showing high forecast accuracy for meat prices in Hubballi (MAPE = 3.27%) and Bengaluru (MAPE = 4.54%), while egg prices in Bengaluru (MAPE = 7.12%) and Mysuru (MAPE = 7.51%) displayed higher variability, suggesting the influence of external factors not captured by the basic model. In Bengaluru market, poultry meat price is going to an increase from ₹271 to ₹277 per kg in the forecasted period. In Hubballi market the poultry meat price is going to decrease from ₹262 to ₹260 per kg in the forecasted period. In Bengaluru and Mysuru market egg price is going to decrease from ₹632 to ₹509 and ₹576 to ₹497 per 100 eggs. The forecast indicates a steady price increase in poultry meat price and fluctuation in egg prices, reflecting ongoing market dynamics. These findings demonstrate the effectiveness of ARIMA models for market forecasting, while highlighting the need for refinement to consider factors affecting egg prices. The study underscores the value of such models in informed decision-making, market interventions and policy development to improve the stability and sustainability of Karnataka's poultry industry. The study suggests staking holders plan the production of meat and egging accordingly the price forecasted. The forecasting is based on the historic data so the price may vary due to external environment.