Estimating the productivity impacts of technology adoption in the presence of misclassification
This article examines the impact that misreporting adoption status has on the identification and estimation of causal effects on productivity. In particular, by comparing measurement error-ridden self-reported adoption data with measurement-error-free DNA-fingerprinted adoption data, we investigate...
| Autores principales: | , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2018
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/96132 |
| _version_ | 1855529504085114880 |
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| author | Assfaw Wossen, Tesfamicheal Abdoulaye, Tahirou Alene, A. Nguimkeu, P. Feleke, S. Rabbi, Ismail Y. Haile, M.G. Manyong, Victor M. |
| author_browse | Abdoulaye, Tahirou Alene, A. Assfaw Wossen, Tesfamicheal Feleke, S. Haile, M.G. Manyong, Victor M. Nguimkeu, P. Rabbi, Ismail Y. |
| author_facet | Assfaw Wossen, Tesfamicheal Abdoulaye, Tahirou Alene, A. Nguimkeu, P. Feleke, S. Rabbi, Ismail Y. Haile, M.G. Manyong, Victor M. |
| author_sort | Assfaw Wossen, Tesfamicheal |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This article examines the impact that misreporting adoption status has on the identification and estimation of causal effects on productivity. In particular, by comparing measurement error-ridden self-reported adoption data with measurement-error-free DNA-fingerprinted adoption data, we investigate the extent to which such errors bias the causal effects of adoption on productivity. Taking DNA-fingerprinted adoption data as a benchmark, we find 25% “false negatives” and 10% “false positives” in farmers’ responses. Our results show that misreporting of adoption status is not exogenous to household characteristics, and produces a bias of about 22 percentage points in the productivity impact of adoption. Ignoring inherent behavioral adjustments of farmers based on perceived adoption status has a bias of 13 percentage points. The results of this article underscore the crucial role that correct measurement of adoption plays in designing policy interventions that address constraints to technology adoption in agriculture. |
| format | Journal Article |
| id | CGSpace96132 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace961322024-11-22T12:11:49Z Estimating the productivity impacts of technology adoption in the presence of misclassification Assfaw Wossen, Tesfamicheal Abdoulaye, Tahirou Alene, A. Nguimkeu, P. Feleke, S. Rabbi, Ismail Y. Haile, M.G. Manyong, Victor M. cassava misclassification adoption technology dna fingerprinting This article examines the impact that misreporting adoption status has on the identification and estimation of causal effects on productivity. In particular, by comparing measurement error-ridden self-reported adoption data with measurement-error-free DNA-fingerprinted adoption data, we investigate the extent to which such errors bias the causal effects of adoption on productivity. Taking DNA-fingerprinted adoption data as a benchmark, we find 25% “false negatives” and 10% “false positives” in farmers’ responses. Our results show that misreporting of adoption status is not exogenous to household characteristics, and produces a bias of about 22 percentage points in the productivity impact of adoption. Ignoring inherent behavioral adjustments of farmers based on perceived adoption status has a bias of 13 percentage points. The results of this article underscore the crucial role that correct measurement of adoption plays in designing policy interventions that address constraints to technology adoption in agriculture. 2018-04-16 2018-07-13T10:02:31Z 2018-07-13T10:02:31Z Journal Article https://hdl.handle.net/10568/96132 en Limited Access Wiley Wossen, T., Abdoulaye, T., Alene, A., Nguimkeu, P., Feleke, S., Rabbi, I.Y., ... & Manyong, V. (2018). Estimating the productivity impacts of technology adoption in the presence of misclassification. American Journal of Agricultural Economics. 1-16 |
| spellingShingle | cassava misclassification adoption technology dna fingerprinting Assfaw Wossen, Tesfamicheal Abdoulaye, Tahirou Alene, A. Nguimkeu, P. Feleke, S. Rabbi, Ismail Y. Haile, M.G. Manyong, Victor M. Estimating the productivity impacts of technology adoption in the presence of misclassification |
| title | Estimating the productivity impacts of technology adoption in the presence of misclassification |
| title_full | Estimating the productivity impacts of technology adoption in the presence of misclassification |
| title_fullStr | Estimating the productivity impacts of technology adoption in the presence of misclassification |
| title_full_unstemmed | Estimating the productivity impacts of technology adoption in the presence of misclassification |
| title_short | Estimating the productivity impacts of technology adoption in the presence of misclassification |
| title_sort | estimating the productivity impacts of technology adoption in the presence of misclassification |
| topic | cassava misclassification adoption technology dna fingerprinting |
| url | https://hdl.handle.net/10568/96132 |
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