Food Security

, Volume 8, Issue 3, pp 643–664 | Cite as

What determines farmers’ adaptive capacity? Empirical evidence from Malawi

  • Solomon AsfawEmail author
  • Nancy McCarthy
  • Leslie Lipper
  • Aslihan Arslan
  • Andrea Cattaneo
Original Paper


This paper assesses farmers’ incentives and conditioning factors that hinder or promote adaptation strategies and evaluates their impact on crop productivity by using data from nationally representative sample households in Malawi. We employed multivariate probit (MVP) and multinomial treatment effect (MTE) techniques to model adoption decisions and their yield impact. Exposure to delayed onset of rainfall and greater climate variability was positively associated with the choice of risk-reducing agricultural practices such as tree planting, legume intercropping, and soil and water conservation (SWC) but reduced the use of inputs (such as inorganic fertilizer) whose risk reduction benefits are uncertain. Concerning household adaptive capacity, wealthier households were more likely to adopt both modern and sustainable land management (SLM) inputs and were more likely to adopt SLM inputs on plots that were under greater security of tenure. In terms of system-level adaptive capacity, rural institutions, social capital and supply-side constraints were key in governing selection decisions for all practices considered, but particularly for tree planting and both organic and inorganic fertilizer applications. A combination of practices gave rise to higher yields suggesting that this might be a course of action that would sustain growth of yield in Malawi in the future.


Climate change Adaptation Impact Malawi 

JEL classification

Q01 Q12 Q16 Q18 



This research forms part of the Economic and Policy Innovation for Climate-Smart Agriculture (EPIC) Project (, supported financially by EU and SIDA. We would also like to acknowledge the World Bank for sharing the Malawi IHS3 dataset with us and particularly Mr. Talip Kilic and Ms. Siobhan Murray of the World Bank for their valuable support during the construction of the dataset. We are grateful to Giulio Marchi, Geospatial Analyst at FAO, for his valuable support for the extraction of the climate data. The authors would also like to thank the staff at the Headquarters and the Malawi office of FAO for their comments and suggestions during the preparation of this paper. Errors are the responsibility only of the authors, and this paper reflects the opinions of the authors, and not the institutions which they represent or with which they are affiliated.


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Copyright information

© Springer Science+Business Media Dordrecht and International Society for Plant Pathology 2016

Authors and Affiliations

  • Solomon Asfaw
    • 1
    Email author
  • Nancy McCarthy
    • 2
  • Leslie Lipper
    • 1
  • Aslihan Arslan
    • 1
  • Andrea Cattaneo
    • 1
  1. 1.Food and Agricultural Organization of the United Nations, Agricultural Development Economics Division (ESA)RomeItaly
  2. 2.LEAD Analytics, Inc.WashingtonUSA

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