A latent class analysis of improved agro-technology use behavior in Uganda: Implications for optimal targeting
This study uses a large dataset that covers a wide geographical and agricultural scope to describe the use patterns of improved agro-technology in Uganda. Using latent class analysis with data on more than 12,500 households across the four regions of Uganda, we classify farmers based on the package...
| Autores principales: | , |
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| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
International Food Policy Research Institute
2018
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/146609 |
| _version_ | 1855526086402637824 |
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| author | Bizimungu, Emmanuel Kabunga, Nassul Ssentamu |
| author_browse | Bizimungu, Emmanuel Kabunga, Nassul Ssentamu |
| author_facet | Bizimungu, Emmanuel Kabunga, Nassul Ssentamu |
| author_sort | Bizimungu, Emmanuel |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This study uses a large dataset that covers a wide geographical and agricultural scope to describe the use patterns of improved agro-technology in Uganda. Using latent class analysis with data on more than 12,500 households across the four regions of Uganda, we classify farmers based on the package of improved agro-technologies they use. We find that the majority of farmers (61 percent) do not use any improved agricultural practices (the “nonusers”), whereas only 5 percent of farmers belong to the class of “intensified diversifiers,” those using most of the commonly available agro-technologies across crop and livestock enterprises. Using multinomial regression analysis, we show that education of the household head, access to extension messages, and affiliation with social groups are the key factors that drive switching from the nonuser (reference) class to the other three (preferred) classes that use improved agrotechnologies to varying degrees. Results reveal the existence of heterogeneous farmer categories, certainly with different agrotechnology needs, that may have implications for optimal targeting. |
| format | Artículo preliminar |
| id | CGSpace146609 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1466092025-11-06T06:18:24Z A latent class analysis of improved agro-technology use behavior in Uganda: Implications for optimal targeting Bizimungu, Emmanuel Kabunga, Nassul Ssentamu technology adoption agricultural technology technology capacity development multinomial regression agriculture innovation adoption productivity This study uses a large dataset that covers a wide geographical and agricultural scope to describe the use patterns of improved agro-technology in Uganda. Using latent class analysis with data on more than 12,500 households across the four regions of Uganda, we classify farmers based on the package of improved agro-technologies they use. We find that the majority of farmers (61 percent) do not use any improved agricultural practices (the “nonusers”), whereas only 5 percent of farmers belong to the class of “intensified diversifiers,” those using most of the commonly available agro-technologies across crop and livestock enterprises. Using multinomial regression analysis, we show that education of the household head, access to extension messages, and affiliation with social groups are the key factors that drive switching from the nonuser (reference) class to the other three (preferred) classes that use improved agrotechnologies to varying degrees. Results reveal the existence of heterogeneous farmer categories, certainly with different agrotechnology needs, that may have implications for optimal targeting. 2018-01-27 2024-06-21T09:07:45Z 2024-06-21T09:07:45Z Working Paper https://hdl.handle.net/10568/146609 en https://hdl.handle.net/10568/148500 https://hdl.handle.net/10568/151158 https://hdl.handle.net/10568/149588 https://hdl.handle.net/10568/148230 Open Access application/pdf International Food Policy Research Institute Bizimungu, Emmanuel; and Kabunga, Nassul Ssentamu. 2018. A latent class analysis of improved agro-technology use behavior in Uganda: Implications for optimal targeting. IFPRI Discussion Paper 1704. Washington, DC: International Food Policy Research Institute (IFPRI). https://hdl.handle.net/10568/146609 |
| spellingShingle | technology adoption agricultural technology technology capacity development multinomial regression agriculture innovation adoption productivity Bizimungu, Emmanuel Kabunga, Nassul Ssentamu A latent class analysis of improved agro-technology use behavior in Uganda: Implications for optimal targeting |
| title | A latent class analysis of improved agro-technology use behavior in Uganda: Implications for optimal targeting |
| title_full | A latent class analysis of improved agro-technology use behavior in Uganda: Implications for optimal targeting |
| title_fullStr | A latent class analysis of improved agro-technology use behavior in Uganda: Implications for optimal targeting |
| title_full_unstemmed | A latent class analysis of improved agro-technology use behavior in Uganda: Implications for optimal targeting |
| title_short | A latent class analysis of improved agro-technology use behavior in Uganda: Implications for optimal targeting |
| title_sort | latent class analysis of improved agro technology use behavior in uganda implications for optimal targeting |
| topic | technology adoption agricultural technology technology capacity development multinomial regression agriculture innovation adoption productivity |
| url | https://hdl.handle.net/10568/146609 |
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