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Introduction
The development challenge addressed by this study is whether an agroforestry technology for enriching soil fertility is being used by poor people in a way that improves their welfare. This article addresses the methodological complexities inherent in research on poverty. The research challenges lie in how to differentiate the poor; and how to assess whether, which, and how factors symptomatic of poverty affect the use of the technology by the poor. Our hypothesis is that a combination of specific types of quantitative and qualitative methods is needed to understand the complex interactions between poverty and technology adoption. By combining methods we can be more confident about what we are observing, measuring, analyzing and finding.
The combined use of quantitative and qualitative methods is still a new, though growing, practice in the field of poverty studies.4 Poverty studies remain largely compartmentalized in disciplines and methodologies. In assessing agricultural technology adoption and impacts, the use of combined methods is even more rare. What was unique about this study was that it formed part of the first multi-country research project attempting to use integrated economic and social analysis to assess the impact of agricultural research/new technologies on poverty. Until this study, impact assessment was largely focused on measuring adoption, yields, and economic gains —poverty reduction was assumed to follow.5 Little attention was given to differentiating between farmers with different levels of assets and different social characteristics that determine their social and economic status, ability to adopt, and the ultimate outcomes of adoption. This multi-country study recognized that understanding poverty impacts in this way would require mixed research methods. It was thus the first study of its kind to undertake this approach in a systematic way.6
This article attempts to analyze how and when to combine quantitative and qualitative research methods to improve our understanding of how to identify the poor, the nature of poverty, its causes, and its consequences for agricultural practices. In section 2 we briefly describe the study areas and the background of technology dissemination in the region. Section 3 describes the different research methods combined, including their sequencing and interaction. Section 4 discusses how different methods were used in generating the key empirical findings. The final section evaluates the areas in which integration of methods was instrumental in achieving key empirical results, followed by a critical analysis of why other envisaged benefits from integration did not occur.
Footnotes:
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Authorship has been assigned equally.
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This paper will not review the recent literature that examines the benefits and challenges in integrating qualitative and quantitative methods. Those are aptly covered in other publications, notably Kanbur (2003) and White (2002).
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Since the 1970s, impact assessment in the CGIAR has evolved from crop management research, to returns to investment, equity consequences, spillover effects and sectoral linkages in the 1980s, and to gender, health and the environment in the 1990s (Pingali 2000). The dominant tradition within which this impact assessment has taken place has been economic evaluation, supplemented by peer review and external review by expert panels. Social and environmental impact assessment and participatory evaluation have been minor branches of evaluation (Horton 1998).
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This wider project was commissioned by the CGIAR’s Standing Panel on Impact Assessment and coordinated by IFPRI. The other country studies were in Bangladesh, Zimbabwe and Mexico. For more on this project and the experience using mixed-research methods and integrated social and economic analysis, see Meinzen-Dick et. al. 2004; Adato and Meinzen-Dick 2003. The full substantive findings of the Kenya case study are reported in Place et al., 2005.
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