Por favor, use este identificador para citar o enlazar este ítem: http://repositorio.ufc.br/handle/riufc/77397
Tipo: Artigo de Periódico
Título : Temporal rainfall variations induce forecast errors in rainfed agriculture in the Brazilian State of Ceará, Brazil
Título en inglés: Temporal rainfall variations induce forecast errors in rainfed agriculture in the Brazilian State of Ceará, Brazil
Autor : Lemos, José de Jesus Sousa
Bezerra, Filomena Nádia Rodrigues
Paiva, Elizama Cavalcante
Ipolito, Antonia Leudiane Mariano
Sousa, Erika Costa
Costa Filho, João da
Palabras clave en inglés: Occurrence of droughts;Rainfall instability;Brazilian semi-arid region;Synergy of events;Potential evapotranspiration
Áreas de Conocimiento - CNPq: CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO
Fecha de publicación : 2024
Editorial : International Journal of Business Administration
Citación : LEMOS, Jose De Jesus Sousa; BEZERRA, Filomena Nadia Rodrigues ; PAIVA, Elizama Cavalcante ; IPOLITO, Antonia Leudiane Mariano ; SOUSA, Erika Costa ; COSTA FILHO, Joao Da. Temporal rainfall variations induce forecast errors in rainfed agriculture in the Brazilian State of CearÃ, Brazil. International Journal of Business Administration, Ontario, v. 15, n.3, p. 36-48, 2024.
Abstract: The research aims to: a) assess the instabilities associated with rainfall and the variables that define the production of rice, beans, cassava and corn in the state of Ceará between 1945 and 2020; b) estimate models that can be used to make projections of harvested areas, yields and prices for these crops between 1945 and 2020; c) assess the impact of rainfall on the estimated forecasting models; d) assess how rainfall affects the likelihood of farmers making forecasts of the variables that define agricultural production. Rainfall data was obtained from the National Centers for Environmental Information (NOAA). Crop yield data came from the Brazilian Institute of Geography and Statistics (IBGE). Instabilities were measured by the coefficients of variation. ARIMA models (autoregressive, integrated and moving average model) were used to make the forecasts. The hypothesis that the residuals generated by the models are influenced by annual rainfall was tested. The results showed high instabilities in annual rainfall, which spread to the variables that define crop yields. Parsimonious and robust adjustments were obtained from a statistical point of view and it was shown that the errors generated, including their magnitudes, in the models used to forecast all the variables that define bean and corn yields, harvested areas and rice yields, as well as cassava yields, are influenced by annual rainfall in Ceará between 1945 and 2020.
URI : http://repositorio.ufc.br/handle/riufc/77397
ISSN : 1923-4007
ORCID del autor: https://orcid.org/0000-0002-4496-8190
https://orcid.org/0000-0002-4625-4474
https://orcid.org/0000-0003-3267-2779
Lattes del autor:  http://lattes.cnpq.br/5498218246827183
http://lattes.cnpq.br/0332719484661039
http://lattes.cnpq.br/2236239894671202
http://lattes.cnpq.br/8132763986254099
http://lattes.cnpq.br/5597065736818875
http://lattes.cnpq.br/0203969106474687
Derechos de acceso: Acesso Aberto
Aparece en las colecciones: DEA - Artigos publicados em revista científica

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