2018
DOI: 10.1111/rode.12516
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Impact of improved maize varieties on food security in Eastern Zambia: A doubly robust analysis

Abstract: This study investigates the impact of improved maize varieties on household food security in eastern Zambia using household survey data from a sample of over 800 rural households. Since treatment effect estimates are

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Cited by 103 publications
(91 citation statements)
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References 42 publications
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“…The results also show that farmers who completed at least 6 years of education were more likely to adopt ICV. Education has been widely cited as an important determinant of adoption of improved agricultural technologies in Africa with the main reason behind its importance being that educated farmers have better access to information and are able to understand the importance and benefits of growing improved varieties (Abdulai, 2016, Alene and Manyong, 2007, Foster and Rosenzweig, 2010, Manda et al, 2018). Information plays a very important role in the adoption of improved agricultural technologies as it is expected that farmers will only adopt an improved variety if they have enough information about the benefits of a particular technology (Adegbola & Gardebroek, 2007).…”
Section: Empirical Results and Discussionmentioning
confidence: 99%
“…The results also show that farmers who completed at least 6 years of education were more likely to adopt ICV. Education has been widely cited as an important determinant of adoption of improved agricultural technologies in Africa with the main reason behind its importance being that educated farmers have better access to information and are able to understand the importance and benefits of growing improved varieties (Abdulai, 2016, Alene and Manyong, 2007, Foster and Rosenzweig, 2010, Manda et al, 2018). Information plays a very important role in the adoption of improved agricultural technologies as it is expected that farmers will only adopt an improved variety if they have enough information about the benefits of a particular technology (Adegbola & Gardebroek, 2007).…”
Section: Empirical Results and Discussionmentioning
confidence: 99%
“…Previous studies investigating the effects of information technology adoption or policy programme intervention have used a propensity score matching (PSM) method (e.g. Fentie and Beyene 2019;Hou et al 2019) and an inverse-probability weighted regression adjusted (IPWRA) estimator (Manda et al 2018;Adolwa et al 2019;Tambo and Mockshell 2018). For example, using the PSM approach, Fentie and Beyene (2019) have analysed the impact of row planting technology on the welfare of rural households in Ethiopia.…”
Section: Selection Bias Issue and Model Selectionmentioning
confidence: 99%
“…Previous studies have used either a propensity score matching technique or an inverseprobability weighted regression adjusted estimator to estimate the effects of a binary treatment variable (e.g. Adolwa et al 2019;Fentie and Beyene 2019;Hou et al 2019;Manda et al 2018;Tambo and Mockshell 2018). However, the two approaches fail to address the selection bias arising from unobserved factors.…”
Section: Introductionmentioning
confidence: 99%
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“…The ATT of the SWC can be obtained by comparing the mean outcomes between treatment and control groups (Imbens and Wooldridge 2008; Wooldridge 2002; World Bank 2010). This approach is widely applied in the literature (e.g., Amare et al 2012;Dillon 2011;Kassie et al, 2010Manda et al 2018 and we do not present the detail methodology here. For a detailed specification and the steps of PSM, see Imbens and Wooldridge (2008), Wooldridge (2002), and World Bank (2010).…”
Section: Endogenous Switching Regression (Esr)mentioning
confidence: 99%