Forecasting Milled Rice Production in Ghana Using Box-Jenkins Approach

نویسندگان

  • Nasiru Suleman Department of Statistics, Faculty of Mathematical Sciences, University for Development Studies, P. O. Box 24 Navrongo,Ghana, West Africa
  • Solomon Sarpong Department of Statistics, Faculty of Mathematical Sciences, University for Development Studies, P. O. Box 24 Navrongo,Ghana, West Africa
چکیده مقاله:

The increasing demand for rice in Ghana has been a major concern to the government and other stakeholders. Recent concerns by the coalition for African Rice Development (CARD) to double rice production within ten years in Sub-Saharan countries have triggered the to implement strategies to boost rice production in the government. To fulfill this requirement, there is a need to monitor and forecast trends of rice production in the country. This study employs the Box-Jenkins approach to model milled rice production using time series data from 1960 to 2010. The analysis revealed that ARIMA (2, 1, 0) was the best model for forecasting milled rice production. Although, a ten years forecast with the model shows an increasing trend in production, the forecast value at 2015 (283.16 thousand metric tons) was not good enough to compare with the current production of Nigeria (2700 thousand metric tons), the leading producer of rice of rice in West Africa.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

forecasting milled rice production in ghana using box-jenkins approach

the increasing demand for rice in ghana has been a major concern to the government and other stakeholders. recent concerns by the coalition for african rice development (card) to double rice production within ten years in sub-saharan countries have triggered the to implement strategies to boost rice production in the government. to fulfill this requirement, there is a need to monitor and foreca...

متن کامل

Forecasting Tuberculosis Incidence in Iran Using Box-Jenkins Models

BACKGROUND Predicting the incidence of tuberculosis (TB) plays an important role in planning health control strategies for the future, developing intervention programs and allocating resources. OBJECTIVES The present longitudinal study estimated the incidence of tuberculosis in 2014 using Box-Jenkins methods. MATERIALS AND METHODS Monthly data of tuberculosis cases recorded in the surveilla...

متن کامل

forecasting tuberculosis incidence in iran using box-jenkins models

background: predicting the incidence of tuberculosis (tb) plays an important role in planning health control strategies for the future, developing intervention programs and allocating resources. objectives: the present longitudinal study estimated the incidence of tuberculosis in 2014 using box-jenkins methods. materials and methods: monthly data of tuberculosis cases recorded in the surveillan...

متن کامل

Multivariate Forecasting of Electricity Production using Neural Network and Box-Jenkins Methodologies

The aim of this paper is to prove the validity of an alternative prediction technique to another classical one, which is Box-Jenkins methodology, in order to produce multivariate prediction. In particular, one-step ahead forecasts will be obtained for two time series: thermic and hydraulic power production. These forecasts are based on the past values of those series.

متن کامل

The Svm Approach for Box–jenkins Models

• Support Vector Machine (SVM) is known in classification and regression modeling. It has been receiving attention in the application of nonlinear functions. The aim is to motivate the use of the SVM approach to analyze the time series models. This is an effort to assess the performance of SVM in comparison with ARMA model. The applicability of this approach for a unit root situation is also co...

متن کامل

Case Study : Analysis and Forecasting of Salinity in Apalachicola Bay , Florida , Using Box - Jenkins Arima Models

The Apalachicola Bay is one of the most productive estuaries in Florida. Variations of salinity directly influence the productivity of the aquatic habitats. Physical conditions that affect the salinity include tidal elevations, wind and current velocities, precipitation, and the discharge of the Apalachicola River. In the present paper, cross-correlation techniques, autoregressive integrated mo...

متن کامل

منابع من

با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ذخیره در منابع من قبلا به منابع من ذحیره شده

{@ msg_add @}


عنوان ژورنال

دوره 2  شماره 2

صفحات  79- 84

تاریخ انتشار 2012-06-01

با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.

میزبانی شده توسط پلتفرم ابری doprax.com

copyright © 2015-2023