Modelling and Forecasting Pulse Crop Production: An Econometric Approach to Agricultural Decision-Making

This paper explores the use of econometric time series models for forecasting pulse production. Pulses, including lentils, chickpeas, and beans, play a crucial role in global food security, agriculture, and economy. Accurate forecasting of pulse production is essential for ensuring food supply stability, policy planning, and market prediction. This study evaluates time series models—such as ARIMA (AutoRegressive Integrated Moving Average), to forecast pulse production. By analyzing historical production data, we demonstrate the predictive accuracy of these models and assess their potential in decision-making. The results show that econometric time series models are effective tools for improving pulse production forecasting, thus contributing to better agricultural planning and policy formulation

Pules crops, ARMA, ARIMA, SPSS, Forecast.

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