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The economic impact of climate change on Kenyan crop agriculture: A Ricardian approach

Kabubo-Mariara, Jane, Karanja, Fredrick K.·2007·Global and Planetary Change

Abstract

This paper measures the economic impact of climate on crops in Kenya. The analysis is based on cross-sectional climate, hydrological, soil, and household level data for a sample of 816 households, and uses a seasonal Ricardian model. Estimated marginal impacts of climate variables suggest that global warming is harmful for agricultural productivity and that changes in temperature are much more important than changes in precipitation. This result is confirmed by the predicted impact of various climate change scenarios on agriculture. The results further confirm that the temperature component of global warming is much more important than precipitation. The authors analyze farmers' perceptions of climate variations and their adaptation to these, and also constraints on adaptation mechanisms. The results suggest that farmers in Kenya are aware of short-term climate change, that most of them have noticed an increase in temperatures, and that some have taken adaptive measures.

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Metadata

Authors
Kabubo-Mariara, J., & Karanja, F. K.
Venue
Global and Planetary Change
Publisher
Elsevier BV
Published
2007-06
Volume
57
Issue
3-4
Pages
319-330
ISSN
0921-8181 (ISSN-L)
OpenAlex
W2168528003
Cited by
227
References
0
FWCI
3.66
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The economic impact of climate change on Kenyan crop agriculture: A Ricardian approach. https://app.cochat.ai/papers/10.1016/j.gloplacha.2007.01.002
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Kabubo-Mariara, J., & Karanja, F. K. (2007). The economic impact of climate change on Kenyan crop agriculture: A Ricardian approach. Global and Planetary Change. https://doi.org/10.1016/j.gloplacha.2007.01.002

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.