| dc.contributor.author | Olagunju, K.O. |
| dc.contributor.author | Ogunniyi, A.I. |
| dc.contributor.author | Awotide, B.A. |
| dc.contributor.author | Adenuga, A.H. |
| dc.contributor.author | Ashagidigbi, W.M. |
| dc.date.accessioned | 2022-07-27T07:46:54Z |
| dc.date.available | 2022-07-27T07:46:54Z |
| dc.date.issued | 2019-12-23 |
| dc.identifier.citation | Olagunju, K.O., Ogunniyi, A.I., Awotide, B.A., Adenuga, A.H. & Ashagidigbi, W.M. (2019). Evaluating the distributional impacts of drought-tolerant maize varieties on productivity and welfare outcomes: an instrumental variable quantile treatment effects approach. Climate and Development, 12(10), 865-875. |
| dc.identifier.issn | 1756-5537 |
| dc.identifier.uri | https://hdl.handle.net/20.500.12478/7578 |
| dc.description.abstract | In an attempt to go beyond the conventional mean impact assessment of agricultural interventions, this paper examines the distributional impacts of adoption of drought-tolerant maize varieties (DTMVs) on the productivity and welfare outcomes of rural farming households in Nigeria. The study employed a conditional instrumental variable quantile treatment effects approach to control for selection bias that may arise from both observed and unobserved factors. The empirical findings revealed that adoption significantly impacts the distributions of maize yield and farming households’ welfare. In particular, the effects of adoption are larger at the lower tails of the distributions of yield and welfare outcomes, suggesting that the strategic roles of DTMVs adoption in raising productivity and reducing poverty are better among poor farming households. These findings emphasize that effective targeting and dissemination of improved agricultural technologies are critical for increasing maize yield and improving welfare outcomes of rural farmers in Nigeria. Policy measures targeted at tackling dissemination constraints, such as the promotion of informal seed sector, may help enhance the successful dissemination and adoption of DTMVs or any agricultural intervention without masking out any sub-groups. |
| dc.description.sponsorship | Bill & Melinda Gates Foundation |
| dc.format.extent | 865-875 |
| dc.language.iso | en |
| dc.subject | Distribution |
| dc.subject | Impact Assessment |
| dc.subject | Drought Tolerance |
| dc.subject | Maize |
| dc.subject | Varieties |
| dc.subject | Yields |
| dc.subject | Nigeria |
| dc.subject | Livelihoods |
| dc.subject | Impact Assessment |
| dc.title | Evaluating the distributional impacts of drought tolerant maize varieties on productivity and welfare outcomes: an instrumental variable quantile treatment effects approach |
| dc.type | Journal Article |
| cg.contributor.affiliation | Agri-food and Biosciences Institute, UK |
| cg.contributor.affiliation | International Food Policy Research Institute |
| cg.contributor.affiliation | International Institute of Tropical Agriculture |
| cg.contributor.affiliation | Federal University of Technology, Akure |
| cg.coverage.region | Africa |
| cg.coverage.region | West Africa |
| cg.coverage.country | Nigeria |
| cg.coverage.hub | Headquarters and Western Africa Hub |
| cg.researchtheme | Social Science and Agribusiness |
| cg.identifier.bibtexciteid | OLAGUNJU:2019 |
| cg.isijournal | ISI Journal |
| cg.authorship.types | CGIAR and developing country institute |
| cg.iitasubject | Climate Change |
| cg.iitasubject | Impact Assessment |
| cg.iitasubject | Maize |
| cg.journal | Climate and Development |
| cg.notes | Published online: 23 Dec 2019 |
| cg.accessibilitystatus | Limited Access |
| cg.reviewstatus | Peer Review |
| cg.usagerightslicense | Copyrighted; all rights reserved |
| cg.targetaudience | Scientists |
| cg.identifier.doi | https://dx.doi.org/10.1080/17565529.2019.1701401 |
| cg.iitaauthor.identifier | Kehinde Oluseyi Olagunju: 0000-0002-5619-054X |
| cg.iitaauthor.identifier | Adebayo Isaiah Ogunniyi: 0000-0002-2952-2959 |
| cg.iitaauthor.identifier | Adewale Henry Adenuga: 0000-0002-1017-2717 |
| cg.futureupdate.required | No |
| cg.identifier.issue | 10 |
| cg.identifier.volume | 12 |
