Fuzzy Set Approach to Poverty Reduction Compared with Growth Modelling

Olsen, Wendy and Nomura, Hisako (2005) Fuzzy Set Approach to Poverty Reduction Compared with Growth Modelling. Other. NCRM. (Unpublished)

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Econometric growth models operate under the assumption that their core economic theories of growth are explanatorily adequate. However even in growth models, non-economic variables are effective because they offer complementary explanatory power. This paper supports the hypothesis that women's labour force participation positively helps poverty reduction. But we also find that the deeper causes of economic change, such as state intervention, are critical to human development trajectories. Using realist methodology, we ask 'what would have to have been true for the fuzzy set patterns to emerge as they did during 1992-2002?" The changes in poverty over time are very diverse so fuzzy set analysis proves useful in identifying small sets of countries whose characteristics helped them to achieve poverty reduction in that decade.

Item Type: Working Paper (Other)
Uncontrolled Keywords: QualQR
Subjects: 4. Qualitative Data Handling and Data Analysis > 4.21 Qualitative Comparative Analysis
5. Quantitative Data Handling and Data Analysis > 5.10 Latent Variable Models > 5.10.11 Correspondence analysis
6. Mixed Methods Data Handling and Data Analysis > 6.2 Combining Qualitative and Quantitative Approaches
Depositing User: NCRM users
Date Deposited: 22 Nov 2022 22:11
Last Modified: 22 Nov 2022 22:11
URI: https://eprints.ncrm.ac.uk/id/eprint/4889

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