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Time series and power law analysis of crop yield in some east African countries

We carry out a time series analysis on the yearly crop yield data in six east African countries (Burundi, Kenya, Somalia, Tanzania, Uganda and Rwanda) using the autoregressive integrated moving average (ARIMA) model. We describe the upper tail of the yearly crop yield data in those countries using t...

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Autores principales: Okorie, Idika E., Afuecheta, Emmanuel, Nadarajah, Saralees
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10263363/
https://www.ncbi.nlm.nih.gov/pubmed/37310978
http://dx.doi.org/10.1371/journal.pone.0287011
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author Okorie, Idika E.
Afuecheta, Emmanuel
Nadarajah, Saralees
author_facet Okorie, Idika E.
Afuecheta, Emmanuel
Nadarajah, Saralees
author_sort Okorie, Idika E.
collection PubMed
description We carry out a time series analysis on the yearly crop yield data in six east African countries (Burundi, Kenya, Somalia, Tanzania, Uganda and Rwanda) using the autoregressive integrated moving average (ARIMA) model. We describe the upper tail of the yearly crop yield data in those countries using the power law, lognormal, Fréchet and stretched exponential distributions. The forecast of the fitted ARIMA models suggests that the majority of the crops in different countries will experience neither an increase nor a decrease in yield from 2019 to 2028. A few exceptional cases correspond to significant increase in the yield of sorghum and coffee in Burundi and Rwanda, respectively, and significant decrease in the yield of beans in Burundi, Kenya and Rwanda. Based on Vuong’s similarity test p–value, we find that the power law distribution captured the upper tails of yield distribution better than other distributions with just one exceptional case in Uganda, suggesting that these crops have the tendency for producing high yield. We find that only sugar cane in Somalia and sweet potato in Tanzania have the potential of producing extremely high yield. We describe the yield behaviour of these two crops as black swan, where the “rich getting richer” or the “preferential attachment” could be the underlying generating process. Other crops in Burundi, Kenya, Somalia, Tanzania, Uganda and Rwanda can only produce high but not extremely high yields. Various climate adaptation/smart strategies (use of short-duration pigeon pea varieties, use of cassava mosaic disease resistant cassava varieties, use of improved maize varieties, intensive manuring with a combination of green and poultry manure, early planting, etc) that could be adapted to increase yields in east Africa are suggested. The paper could be useful for future agricultural planning and rates calibration in crop risk insurance.
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spelling pubmed-102633632023-06-15 Time series and power law analysis of crop yield in some east African countries Okorie, Idika E. Afuecheta, Emmanuel Nadarajah, Saralees PLoS One Research Article We carry out a time series analysis on the yearly crop yield data in six east African countries (Burundi, Kenya, Somalia, Tanzania, Uganda and Rwanda) using the autoregressive integrated moving average (ARIMA) model. We describe the upper tail of the yearly crop yield data in those countries using the power law, lognormal, Fréchet and stretched exponential distributions. The forecast of the fitted ARIMA models suggests that the majority of the crops in different countries will experience neither an increase nor a decrease in yield from 2019 to 2028. A few exceptional cases correspond to significant increase in the yield of sorghum and coffee in Burundi and Rwanda, respectively, and significant decrease in the yield of beans in Burundi, Kenya and Rwanda. Based on Vuong’s similarity test p–value, we find that the power law distribution captured the upper tails of yield distribution better than other distributions with just one exceptional case in Uganda, suggesting that these crops have the tendency for producing high yield. We find that only sugar cane in Somalia and sweet potato in Tanzania have the potential of producing extremely high yield. We describe the yield behaviour of these two crops as black swan, where the “rich getting richer” or the “preferential attachment” could be the underlying generating process. Other crops in Burundi, Kenya, Somalia, Tanzania, Uganda and Rwanda can only produce high but not extremely high yields. Various climate adaptation/smart strategies (use of short-duration pigeon pea varieties, use of cassava mosaic disease resistant cassava varieties, use of improved maize varieties, intensive manuring with a combination of green and poultry manure, early planting, etc) that could be adapted to increase yields in east Africa are suggested. The paper could be useful for future agricultural planning and rates calibration in crop risk insurance. Public Library of Science 2023-06-13 /pmc/articles/PMC10263363/ /pubmed/37310978 http://dx.doi.org/10.1371/journal.pone.0287011 Text en © 2023 Okorie et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Okorie, Idika E.
Afuecheta, Emmanuel
Nadarajah, Saralees
Time series and power law analysis of crop yield in some east African countries
title Time series and power law analysis of crop yield in some east African countries
title_full Time series and power law analysis of crop yield in some east African countries
title_fullStr Time series and power law analysis of crop yield in some east African countries
title_full_unstemmed Time series and power law analysis of crop yield in some east African countries
title_short Time series and power law analysis of crop yield in some east African countries
title_sort time series and power law analysis of crop yield in some east african countries
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10263363/
https://www.ncbi.nlm.nih.gov/pubmed/37310978
http://dx.doi.org/10.1371/journal.pone.0287011
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