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Impact of soil and water conservation practices on household vulnerability to food insecurity in eastern Ethiopia: endogenous switching regression and propensity score matching approach

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Abstract

Governmental and developmental partners invest substantial resources to reduce land and water degradation in order to upgrade agricultural productivity, thus reducing food insecurity and related vulnerability in Sub-Saharan Africa. Understanding the impact of soil and water conservation on food insecurity outcomes would be a significant step toward improving environmental conditions, while ensuring sustainable and increased agricultural production. Therefore, this article analyzes the impact of adopting soil and water conservation on food insecurity and related vulnerability outcomes of farming households using a sample of 408 households selected using a multi-stage stratified sampling procedure from three districts in eastern Ethiopia. Vulnerability as expected poverty (three-step Feasible General Least Squares) is employed to analyze the vulnerability of sample households in the context of food insecurity. In addition, endogenous switching regressions with propensity score matching methods are combined to obtain consistent impact estimates. The study findings reveal that education and sex of household head, use of irrigation and fertilizer, source of information, and cultivated land are the main factors influencing the adoption of soil and water conservation practices. Moreover, the adoption of soil and water conservation not only positively impacts the per capita food consumption expenditure and net crop value, but it also significantly reduces the probability of farmers being food insecure, vulnerable to food insecurity, as well as being transient and chronically food insecure. Therefore, policymakers and development organizations should consider soil and water conservation as a main strategy to reduce land degradation and improve the livelihoods of the rural farm households.

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Notes

  1. Birr is Ethiopia currency (1USD = 23.32 Birr).

  2. “Two successive Poverty Reduction Strategic Papers (PRSP), i.e., the Sustainable Development andPoverty Reduction Program (SDPRP) launched in 2002 and the Plan for Accelerated and Sustained Development to End Poverty (PASDEP) were instituted in 2005. The two broad strategies of PASDEP are to reduce poverty by stimulating rural growth through agriculture and rural development, and to strengthen public institutions to deliver services” (Gelaw and Sileshi2013).

  3. Kebele is usually a named peasant association and is the lowest administrative unit in the country.

  4. Instrument variable are jointly statistically significant in the selection equation [χ2 = 25.30 (p = 0.0000)] but not outcome functions: for example binary food insecurity status of adopter [χ2 = 1.11 (p = 0.5742)] and non-adopter; [χ2 = 1.04 (p = 0.5937)] as well as the PCFCE for adopters [F = 0.43 (p = 0.6520)] and non-adopters [F = 0.87 (p = 0.4188)]. We also find similar results for other outcome functions (net crop value and binary chronic and transitory food insecurity, VFI).

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Authors and Affiliations

  1. School of Agricultural Economics and Business Studies, Sokoine University of Agriculture, Morogoro, Tanzania

    Million Sileshi, Reuben Kadigi & Khamaldin Mutabazi

  2. Department of Rural Development and Agricultural Extension, Haramaya University, Dire-dawa, Ethiopia

    Million Sileshi

  3. Department of Agricultural Economics, Humboldt-University Berlin, Berlin, Germany

    Stefan Sieber

  4. Sustainable Land Use in Developing Countries, Leibniz Centre for Agricultural Landscape Research (ZALF e.V.), Müncheberg, Germany

    Stefan Sieber

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Appendix

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Table 9 Three-step Feasible Generalized Least Squares result for determinant of vulnerability to food insecurity (N = 408)
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Table 10 Second stage ESR estimates result
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Sileshi, M., Kadigi, R., Mutabazi, K. et al. Impact of soil and water conservation practices on household vulnerability to food insecurity in eastern Ethiopia: endogenous switching regression and propensity score matching approach. Food Sec. 11, 797–815 (2019). https://doi.org/10.1007/s12571-019-00943-w

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