17 Q. Mehmood M. H. Sial M. Riaz N. Shaheen Journal of Animal and Plant Sciences JAPS 20192019/10/01 29 5 1396-1401 1018-7081 NA <p>Agriculture is the mainstay of Pakistan&rsquo;s economy and contributes 24 percent of&nbsp;the&nbsp;<em>GDP. Considering its vital role</em>, planners and policy makers are always keen to have timely forecasts for the important crops such as wheat, cotton, rice and&nbsp;<em>sugarcane. Of these sugarcane</em>&nbsp;is a major cash crop and an important source of income for farmers in Pakistan.&nbsp;The present study is focused on developing and estimating time series models to forecast sugarcane production in Pakistan. Box-Jenkin (1976) methodology was employed to estimate production forecasting model using annual time series data as available from Pakistan Bureau of Statistics (PBS) and various issues of Pakistan Economic Survey for the years 1947-2017.&nbsp;An appropriate ARIMA (2, 1, 1) model was estimated to forecast the production of sugarcane crop in Pakistan for the years 2018-2029.&nbsp;Over this period the model predicts a significant increase (6.56%) in sugarcane output. These forecasts can be very useful for agricultural policy makers, sugar industry as well as farmers in making prudent resource allocation and production decisions for sugarcane in Pakistan.</p> Autoregressive Integrated Moving Average, Model, Error, production, forecast Pakistan Agricultural Scientists Forum https://thejaps.org.pk/AbstractView.aspx?mid=2019-JAPS-521