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Evaluating the Efficacy of Social Innovation Programming at Advancing Rural Development in the Context of Exogenous Shocks

Author

Listed:
  • Mauricio Espinoza

    (Grupo de Análisis para el Desarrollo, Lima 15063, Peru
    Development Economics, Wageningen University & Research, 6708 WG Wageningen, The Netherlands)

  • Rodrigo Rivarola

    (Grupo de Análisis para el Desarrollo, Lima 15063, Peru)

  • Ricardo Fort

    (Grupo de Análisis para el Desarrollo, Lima 15063, Peru)

  • Joshua Fisher

    (Network for Education and Research on Peace and Sustainability, Hiroshima University, Hiroshima 739-0046, Japan
    Columbia Climate School, Columbia University, New York, NY 10115, USA)

Abstract

In this paper, we design and deploy an experimental approach to evaluate the efficacy of a social innovation initiative implemented in rural communities situated in the highlands of Peru, which confronted the challenges posed by the COVID-19 pandemic in the midst of its implementation. Using three rounds of information collected before, during, and after participation, we examine the efficacy of the social innovation economic development approach at increasing household livelihoods. We present robust, statistically significant improvements in household economic well-being, food security satisfaction, and community outlook for participating households compared to non-participating households following program engagement. The results presented in this study suggest that the social innovation program facilitated a notable restructuring of the portfolio of household income and livelihood activities towards more lucrative and value-added pursuits. This transition manifested in increased involvement in entrepreneurial ventures and specialized labor associated with both agricultural and non-agricultural sectors while distancing from traditional agricultural and livestock-related endeavors. The income gains stemming from self-employment activities and wage labor outweigh the losses incurred from reduced agricultural and livestock earnings. Furthermore, our analysis underscores the resilience of innovative income-generating pathways in the face of the COVID-19 pandemic, outperforming traditional agrarian value chains. These findings highlight the efficacy of social innovation programming in facilitating economic development and also shed light on sustainable strategies for economic resilience amidst unforeseen challenges such as the recent global health crisis.

Suggested Citation

  • Mauricio Espinoza & Rodrigo Rivarola & Ricardo Fort & Joshua Fisher, 2024. "Evaluating the Efficacy of Social Innovation Programming at Advancing Rural Development in the Context of Exogenous Shocks," Sustainability, MDPI, vol. 16(13), pages 1-20, July.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:13:p:5664-:d:1427780
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    References listed on IDEAS

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    1. Angelo Cozzubo & Javier Herrera & François Roubaud & Mireille Razafindrakoto, 2021. "El impacto de políticas diferenciadas de cuarentena sobre la mortalidad por COVID-19: el caso de Brasil y Perú," Working Papers DT/2021/05, DIAL (Développement, Institutions et Mondialisation).
    2. Michel Marée & Sybille Mertens, 2012. "The Limits of Economic Value in Measuring the Performance of Social Innovation," Palgrave Macmillan Books, in: Alex Nicholls & Alex Murdock (ed.), Social Innovation, chapter 4, pages 114-136, Palgrave Macmillan.
    3. Pol, Eduardo & Ville, Simon, 2009. "Social innovation: Buzz word or enduring term?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(6), pages 878-885, December.
    4. Susana B. Guerrero-Ocampo & José M. Díaz-Puente, 2023. "Social Network Analysis Uses and Contributions to Innovation Initiatives in Rural Areas: A Review," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    5. Duflo, Esther & Glennerster, Rachel & Kremer, Michael, 2008. "Using Randomization in Development Economics Research: A Toolkit," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 61, pages 3895-3962, Elsevier.
    6. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
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