Designing Quasi-Experimental Impact Studies of Agricultural Research at Scale
Providing credible and quantifiable measures of the impact of CGIAR innovations at scale has always been a challenge. Recent SPIA-supported research has attempted to address this challenge using quasi-experimental approaches to assessing impact. This technical note details some of these completed an...
| Main Authors: | , , |
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| Format: | Informe técnico |
| Language: | Inglés |
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CGIAR Advisory Services
2021
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| Online Access: | https://hdl.handle.net/10568/114085 |
| _version_ | 1855536612424810496 |
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| author | Meenakshi, J.V. Johnson, Nancy Karasalo, Mina |
| author_browse | Johnson, Nancy Karasalo, Mina Meenakshi, J.V. |
| author_facet | Meenakshi, J.V. Johnson, Nancy Karasalo, Mina |
| author_sort | Meenakshi, J.V. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Providing credible and quantifiable measures of the impact of CGIAR innovations at scale has always been a challenge. Recent SPIA-supported research has attempted to address this challenge using quasi-experimental approaches to assessing impact. This technical note details some of these completed and ongoing studies and approaches, focusing on the identification strategies used to infer causal impact, and the kinds of diverse data sets that may be brought to bear in making these inferences. A key message is also to integrate impact evaluation designs as part and parcel of monitoring and evaluation efforts. |
| format | Informe técnico |
| id | CGSpace114085 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | CGIAR Advisory Services |
| publisherStr | CGIAR Advisory Services |
| record_format | dspace |
| spelling | CGSpace1140852025-10-27T13:13:02Z Designing Quasi-Experimental Impact Studies of Agricultural Research at Scale Meenakshi, J.V. Johnson, Nancy Karasalo, Mina research impact assessment Providing credible and quantifiable measures of the impact of CGIAR innovations at scale has always been a challenge. Recent SPIA-supported research has attempted to address this challenge using quasi-experimental approaches to assessing impact. This technical note details some of these completed and ongoing studies and approaches, focusing on the identification strategies used to infer causal impact, and the kinds of diverse data sets that may be brought to bear in making these inferences. A key message is also to integrate impact evaluation designs as part and parcel of monitoring and evaluation efforts. 2021-06 2021-06-23T10:31:06Z 2021-06-23T10:31:06Z Report https://hdl.handle.net/10568/114085 en Open Access application/pdf CGIAR Advisory Services Meenakshi, J.V., Johnson, Nancy and Karasalo, Mina. (2021). Designing Quasi-Experimental Impact Studies of Agricultural Research at Scale. SPIA Technical Note 10. Rome: Standing Panel on Impact Assessment. |
| spellingShingle | research impact assessment Meenakshi, J.V. Johnson, Nancy Karasalo, Mina Designing Quasi-Experimental Impact Studies of Agricultural Research at Scale |
| title | Designing Quasi-Experimental Impact Studies of Agricultural Research at Scale |
| title_full | Designing Quasi-Experimental Impact Studies of Agricultural Research at Scale |
| title_fullStr | Designing Quasi-Experimental Impact Studies of Agricultural Research at Scale |
| title_full_unstemmed | Designing Quasi-Experimental Impact Studies of Agricultural Research at Scale |
| title_short | Designing Quasi-Experimental Impact Studies of Agricultural Research at Scale |
| title_sort | designing quasi experimental impact studies of agricultural research at scale |
| topic | research impact assessment |
| url | https://hdl.handle.net/10568/114085 |
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