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Identifying beneficiaries for sustainable development in low- and middle-income countries

Abstract

Implementation projects on sustainable development have already triggered the global transfer of funds through multi-lateral agencies. The selection of beneficiaries at the local level is an intriguing problem in the developmental sector and does not have a single-window solution. In absence of equitable selection, a fraction of beneficiaries might be benefitted over and over again and the rest remain deprived. The proposed opinion will discuss the challenges of selecting beneficiaries in the developing countries and shade lights in some of the probable solutions which can be used. The present opinion also suggest measures needs to be taken by funding agency, and implementing agency to create more transparent framework and assure maximal utilization of available funds.

The grant makers and the implementation agencies often represent their work through a series of visual narrative of elevated condition of the beneficiaries after fulfilling the project. While applying for any such grant, the implementation agency must mention the targeted number of beneficiaries upon project completion. However, one question remains unaddressed. How an implementation agency is selecting beneficiaries? The science of identifying beneficiaries is one of the poorly understood challenges of sustainable development.

The “rule of thumb” for selecting a group of beneficiaries is to approach the present political representative or key over-enthusiastic members of the community for a list of possible beneficiaries [1]. This approach has an inherent bias as it solely depends on the person of contact and his or her political and personal relationship with the community [2]. This approach could lead to selection of a large number of beneficiaries but does not guarantee that all of them have urgent requirements. The second approach is to conduct a survey or use official census data to compute an index for prioritizing the underprivileged fraction of the population [3,4]. The major limitation of this method is the absence of high-resolution datasets on the ground. Conducting surveys for such indexing are often time intensive and expensive. Considering drastic migration and developmental pressure on Low- and Middle-Income Countries (LMIC), existing beneficiaries datasets for such decision making processes are often found to be outdated. In addition, household level socio-economic data for LMIC is not open-sourced. Without household level information, it would be difficult for the implementation agency to select the most vulnerable beneficiaries and therefore, evaluation of the implementation program can be a major challenge.

An example of the challenges faced by implementing agencies

After receiving a fund for commissioning multiple water purification plants over a country, an implementation agency is required to narrow down to a region according to water scarcity, the occurrence of water-borne diseases, groundwater levels and contaminations, buying capacity of the consumers etc [5]. Ideally, the data should be updated and the spatial resolution should be very high. The on the ground reality is that it is extremely difficult to get these data for LMIC, and therefore, choosing the data-driven approach could lead to wrongful selection of area of intervention.

Now, for implementation of an individually focused project, i.e. installing solar powered light in low-income households, the implementation agency usually approaches local leaders/urban local bodies and asks for a list of probable beneficiaries [6]. The leader takes the opportunity and suggests the name of only the supporters of his/her political party. Now, considering a region where multiple implementation agencies are working and all of them are approaching the same leader, a huge inequality can be created among the population as a fraction of them might be benefitted over and over again and the rest remain deprived [7].

Alternatives and future outlook

Selection of proper beneficiaries are one of the key aspects of sustainable development, but unfortunately this issue has not been addressed scientifically [8]. Policy for beneficiary selection is absent for most of the country and even if present, it’s not available to the general public due to lack of open sourcing [9]. One of the available alternatives of these conventional systems is to identify a relatively large area according to the available data and then conduct a need assessment survey to identify household-level vulnerability [10]. As the available resources are limited, identification of true beneficiaries is extremely necessary.

For prioritizing the section of the population in relatively higher need, a unified database needs to be developed and open-sourced. A good alternative is to open-source the beneficiary selection criteria while implementing a project [11]. The open-sourcing can be done through newspaper advertisement and other mode of communication in local language providing the contact address of both the funding and implementing agency. If the funding agency could make this mandatory, then this could establish mutual communication between potential beneficiaries, funding agency and implementation agency. It would be much easier for monitoring and evaluation purposes and potentially improve the transparency and long-term sustainability of the entire process.

Academic institutions can play a pivotal role in creating an open-sourced knowledge portal for mapping the vulnerable population. There are sporadic studies for identifying vulnerability through a ground-based survey [12,13]. However, these studies are not synchronized and often lack a long-term outlook. Conducting a survey is an essential tool for multiple academic departments and involving students to create a long-term open- sourced database could serve the purpose of academic research as well as implementation projects by governmental and non-governmental organization. The top-down approach will involve the potential beneficiaries reaching out to the implementation and funding agencies and the bottoms up approach will involve ground-based surveys by academic institutions and implementation agencies. Together, this would help to create a more transparent framework where “no one left behind” can be achieved.

As there is no single-window solution to this problem, the funding agencies need to understand the importance of a proper beneficiary selection process and that predetermined selection of intervention areas and communities might neglect the “real potential beneficiaries”. Open-sourcing of the ground information also helps to bring transparency and accountability in the entire process. Another option is to allocate extra funding on monitoring and reporting beyond the time of project completion to validate the beneficiary selection. Selection of beneficiaries is a multi-dimensional problem and the strategy could vary depending upon socio-political situation for a given area; therefore, its also of the utmost importance to revisit the results of previously implemented projects to understand the long-term effect of beneficiary selection strategies [14].

References

  1. 1. Schwartz T. A Model for Humanitarian Aid Beneficiary Targeting. 2019. https://timothyschwartzhaiti.com/a-model-for-humanitarian-aid-beneficiary-targeting/
  2. 2. Mahlati V., Hall R., Karaan M., Kriek D., Mabasa B., Moagi et, al. Final report of the Presidential Advisory Panel on Land reform and Agriculture. Presidential Advisory Panel on Land Reform and Agriculture: Pretoria, South Africa. 2019.
  3. 3. Sullivan C, Meigh J. Targeting attention on local vulnerabilities using an integrated index approach: the example of the climate vulnerability index. Water Science and Technology. 2005 Mar;51(5):69–78. pmid:15918360
  4. 4. World Bank Brief. Design & Implementation: Targeting and Selection. 2013. https://www.worldbank.org/en/topic/communitydrivendevelopment/brief/cdd-targeting-selection
  5. 5. Ghosh, S. Beneficiary Participation in Rural Water Supply and Sanitation. IABSE Conference: Role of Structural Engineers towards Reduction of Poverty, New Delhi, India, 19–22 February 2005
  6. 6. Sarkar P, Kumar J. Impact of MGNREGA on Reducing Rural Poverty and Improving Socio-economic Status of Rural Poor: A Study in Burdwan District of West Bengal §. Agricultural Economics Research Review. 2011;24(conf):437–48.
  7. 7. Awokuse TO. Food aid impacts on recipient developing countries: A review of empirical methods and evidence. Journal of International Development. 2011 May;23(4):493–514.
  8. 8. Zantsi S, Greyling JC. Land redistribution in South Africa’s land reform policy: a better way to select beneficiaries. Agrekon. 2021 Apr 8:1–20.
  9. 9. Ramantsima K., Mtero F., Gumede N., Du Toit A., & Hall R. Amendment submission: National policy for beneficiary selection and land allocation. 2020.
  10. 10. Skoufias E, Davis B, De La Vega S. Targeting the poor in Mexico: an evaluation of the selection of households into PROGRESA. World development. 2001 Oct 1;29(10):1769–84.
  11. 11. Tarko V. Open-Sourcing Civil Society. In Exploring the Social and Political Economy of Alexis de Tocqueville 2020 (pp. 225–252). Palgrave Macmillan, Cham.
  12. 12. Kaabi A, Rousta K, Mohammadzadeh S, Baradaran R. Solutions to Reduce the Vulnerability of Farmers and Beneficiaries of Agricultural Sector to Climate Change.
  13. 13. Nedumaran S, Nandi R, Padmanabhan J, Reddy SS, Kadiyala DM, Kumar S. Household Vulnerability to Climate Change and Identification of Target Beneficiaries to Implement Household-Specific Adaptation Strategies: A Quantitative Assessment. Asian Journal of Agriculture and Development. 2021 Dec 22;18(1362-2022-003):17–34.
  14. 14. Bouguen A., Huang Y., Kremer M., & Miguel E. Using RCTs to Estimate Long-Run Impacts in Development Economics (No. w25356). National Bureau of Economic Research. 2018.