FORECASTING OF WHEAT PRODUCTION FOR PAKISTAN USING ADVANCE TIME SERIES MODELS

Abstract

It is a pillar of global food security because wheat is so full of nutrients-carbohydrates, proteins, fiber, vitamins (especially B vitamins), and important minerals. Worldwide, wheat continues to be the most common food grain. To guarantee food security, it is essential to comprehend and predict patterns in wheat production. The Department of Agriculture's Statistics Bureau provided the historical wheat production statistics for Pakistan from 1947 to 2019, which were the subject of this study's analysis. statistical techniques, Numerous methods, including moving averages, Holt's exponential smoothing, and autoregressive integrated moving average (ARIMA) models, were employed for a comprehensive analysis. The evaluation criteria, mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE), illustrate an increasing tendency among intrinsic historical data variations and demonstrate the durability of the forecasting skills of Holt's Exponential Smoothing approach. These results offer crucial information for strategic planning and policy decisions to maximize wheat output and maintain Pakistan's food security.