Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania
A journal article published in the Business Analyst Journal by Emerald Publishing Limited.
محفوظ في:
| المؤلفون الرئيسيون: | , |
|---|---|
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
Emerald Publishing Limited
2024
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://scholar.mzumbe.ac.tz/handle/123456789/428 |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
| _version_ | 1820347767686430720 |
|---|---|
| author | Lwaho, Joseph Ilembo, Bahati |
| author_facet | Lwaho, Joseph Ilembo, Bahati |
| author_sort | Lwaho, Joseph |
| collection | DSpace |
| description | A journal article published in the Business Analyst Journal by Emerald
Publishing Limited. |
| format | Article |
| id | oai:41.59.85.69:123456789-428 |
| institution | Mzumbe University |
| language | English |
| publishDate | 2024 |
| publisher | Emerald Publishing Limited |
| record_format | dspace |
| spelling | oai:41.59.85.69:123456789-4282024-03-21T08:21:51Z Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania Lwaho, Joseph Ilembo, Bahati ARIMA Time series Maize production Forecast A journal article published in the Business Analyst Journal by Emerald Publishing Limited. Purpose – This paper was set to develop a model for forecasting maize production in Tanzania using the autoregressive integrated moving average (ARIMA) approach. The aim is to forecast future production of maize for the next 10 years to help identify the population at risk of food insecurity and quantify the anticipatedmaize shortage. Design/methodology/approach – Annual historical data on maize production (hg/ha) from 1961 to 2021 obtained from the FAOSTAT database were used. The ARIMA method is a robust framework for forecasting time-series data with non-seasonal components. The model was selected based on the Akaike Information Criteria corrected (AICc) minimum values and maximum log-likelihood. Model adequacy was checked using plots of residuals and the Ljung-Box test. Findings – The results suggest that ARIMA (1,1,1) is the most suitable model to forecast maize production in Tanzania. The selected model proved efficient in forecasting maize production in the coming years and is recommended for application. Originality/value – The study used partially processed secondary data to fit for Time series analysis using ARIMA (1,1,1) and hence reliable and conclusive results. Private 2024-03-21T08:21:47Z 2024-03-21T08:21:47Z 2023 Article APA 2754-6721 DOI 10.1108/BAJ-07-2023-0055 https://scholar.mzumbe.ac.tz/handle/123456789/428 en application/pdf Emerald Publishing Limited |
| spellingShingle | ARIMA Time series Maize production Forecast Lwaho, Joseph Ilembo, Bahati Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania |
| title | Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania |
| title_full | Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania |
| title_fullStr | Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania |
| title_full_unstemmed | Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania |
| title_short | Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania |
| title_sort | unfolding the potential of the arima model in forecasting maize production in tanzania |
| topic | ARIMA Time series Maize production Forecast |
| url | https://scholar.mzumbe.ac.tz/handle/123456789/428 |
| work_keys_str_mv | AT lwahojoseph unfoldingthepotentialofthearimamodelinforecastingmaizeproductionintanzania AT ilembobahati unfoldingthepotentialofthearimamodelinforecastingmaizeproductionintanzania |