Impact of climate smart agriculture on farm productivity under extreme weather events in Malawi

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dc.contributor.advisor Mungatana, Eric D.
dc.contributor.postgraduate Pangapanga-Phiri, Innocent
dc.date.accessioned 2022-02-14T11:33:08Z
dc.date.available 2022-02-14T11:33:08Z
dc.date.created 2022-05-12
dc.date.issued 2021-07-01
dc.description Thesis (PhD (Environmental Economics))--University of Pretoria, 2022. en_ZA
dc.description.abstract Agricultural productivity in Malawi continues to decline and frustrate the food security agenda despite massive investments, namely, farm input subsidy programs and climate-smart agriculture (CSA) –related practices. Households have further adopted integrated pest management (IPM), and sustainable landscape management (SLM) strategies, which are responsive to extreme weather events, like droughts, fall armyworms (FAW), and tropical cyclones -related floods (TCRFs). High poverty levels, poor agricultural practices, fragmented landholding sizes, missing credit markets, and declining soil fertility are some of the fundamental constraints limiting household agricultural productivity. Additionally, extreme weather events have exasperated the situation, pushing more households into further food insecurity and poverty. In containing the negative effects of different extreme weather events, Government of Malawi and other stakeholders, including households, have adopted various CSA, IPM, and SLM-related practices, such as, organic manure application, intercropping, timely planting, improved crop varieties, mulching, zero tillage, soil and water conservation, liming, and chemical pesticides’ application. Though CSA, IPM, and SLM –related practices have presented opportunities to address the adverse effects of the extreme weather events, households fail to derive the maximum potential farm productivity. Furthermore, households engaging in rural – urban migration (RUM), as a climate adaptive strategy, do not yield the intended results due to missing market infrastructures for improved agricultural inputs and outputs. This thesis, thus, examines the impacts of climate smart agriculture on household farm productivity under varying extreme weather events by posing four empirical questions: (i) Do drought, FAW, and TCRFs significantly affect farm productivity? (ii) Do household and farm-level factors, namely, age, education, total farm size, and soil types drive the adoption of CSA, IPM, and SLM-related practices under the different extreme weather events? (iii) Do CSA, IPM and SLM-related practices substantially induce farm productivity? Finally, (iv) does RUM, which is an climate adaptive strategy, improve the technical efficiency of maize production in the study area under extreme weather events? This thesis uses data from the Integrated Household Panel Survey, compiled by the National Statistics Office (NSO) and the World Bank, between 2010 and 2020. In this thesis, Chapter two (2) employs the conditional fixed effect logit model, the panel-based Cobb-Douglas stochastic frontier analysis (SFA) model, and the triple-hurdle panel-based Tobit regression model to investigate the drivers of CSA practices’ adoption and their influence on the technical efficiency of maize production under drought episodes. Chapter three (3) adopts the panel-based Endogenous Switching Regression (ESR) to interrogate the effects of FAW and IPM-related practices on farm productivity and food security. Similarly, Chapter four (4) applies the ESR to ascertain the impact of TCRFs and SLM-related practices on the farm productivity. Chapter five (5) uses the two-stage panel based Tobit regression to examine the influence of RUM on the technical efficiency of maize production under extreme weather events. The results from Chapter two (2) show that households affected by drought are 76 percent more likely to adopt organic manure and 29 percent more probable to invest in soil and water conservation techniques relative to their counterparts. Based on panel-based ESR model, Chapter three (3) demonstrates that FAW significantly reduces farm productivity by 12 percent, on the one hand, but enhanced the likelihood of adopting IPM –related practices by 6 percent, on the other hand. The study reveals that adoption of IPM –related practices improves farm productivity by at least 21 percent. Findings from Chapter four (4) show that TCRF reduces farm productivity by 31 percent while augmenting the likelihood of investing in SLM-related practices, which consequently enhance farm productivity by 27 percent. Moreover, after interacting TCRFs and SLM, chapter (4) reveals that 24 percent improvement in farm productivity. Unless RUM is interacted with the adoption of other CSA –related practices, chapter five (5) reveals that RUM negatively and considerably influences maize farm productivity by 9 percent due to low family labour supply. The thesis concludes that droughts, FAW, TCRFs, and RUM have negative and significant effects on farm productivity. Households affected by any extreme weather events are distinctly more likely to adopt any of the CSA, IPM, and SLM-related practices, which positively enhance farm productivity and ultimately improve household food security. Consequently, the study recommends an extension delivery mechanism that significantly promotes the adoption of any of the CSA, IPM, and SLM-related practices to improve the household farm productivity, which would eventually boost food security under different extreme weather events. Furthermore, the study proposes creation of accessible credit markets, which should allow households access farm inputs, namely, hired labour, inorganic fertilizer, and improved crop varieties, critical for the sustainable adoption of various CSA, or IPM, or SLM –related practices in the study area. The study results inform the policy making process in Malawi in four broad-ways. First, it provides evidence regarding the drivers of CSA, IPM, and SLM-related practices’ adoption and their effects on farm productivity. These adaptation strategies are appropriate when the climate models project frequent, intense, and severe extreme weather events in Malawi in the coming decades. Second, the study isolates the most efficient adaptation practices, which enhance farm productivity and minimize the dis-adoption decision of the CSA, IPM, and SLM-related practices at the household level. Third, the study enhances climate-resilient farm productivity under different extreme weather events. Additionally, the study findings mainstream indigenous experiences in climate adaptation, ensuring CSA, IPM, and SLM-related practices’ suitability, flexibility, and sustainability. Ultimately, the study results are relevant to the current debate on achieving the Sustainable Development Goal (SDGs) on agricultural productivity under different extreme weather events en_ZA
dc.description.availability Unrestricted en_ZA
dc.description.degree PhD (Environmental Economics) en_ZA
dc.description.department Agricultural Economics, Extension and Rural Development en_ZA
dc.identifier.citation * en_ZA
dc.identifier.other A2022 en_ZA
dc.identifier.uri http://hdl.handle.net/2263/83891
dc.language.iso en en_ZA
dc.publisher University of Pretoria
dc.rights © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
dc.subject Farm Productivity en_ZA
dc.subject Climate-Smart Agriculture en_ZA
dc.subject Integrated Pest and Sustainable Land Management en_ZA
dc.subject Rural-Urban Migration en_ZA
dc.subject Panel-Based Stochastic Frontier Analysis en_ZA
dc.subject Panel-Based Endogenous Switching Regression Model en_ZA
dc.subject Conditional Fixed Effect Model en_ZA
dc.subject Triple Hurdle Tobit Model en_ZA
dc.subject UCTD
dc.title Impact of climate smart agriculture on farm productivity under extreme weather events in Malawi en_ZA
dc.type Thesis en_ZA


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