The role of extension and financial services in boosting the effect of innovation investments for reducing poverty and hunger: A DEA approach

Increasing investment and spending in agricultural innovation is not enough to meet Sustainable Development Goal (SDG) targets of ending poverty and hunger because the effectiveness of investments in low- and middle-income (LMI) countries is affected by the low quality of infrastructure and services provided, and by different norms and practices that create a considerable gap between financing known technical solutions and achieving the outcomes called for in the SDGs. As an important part of a nation’s common innovation infrastructure, financial and extension services are major “enablers” of investments, favorably contributing to national innovative capacity. However, the contribution of these services to innovation in LMI countries has been limited. Financial services in LMI countries face low rates of return; high risks and lack of acceptable collateral; and limited outreach in rural areas. Similarly, the performance of extension services has been affected by ineffective and costly strategies that have promoted rigid recommendations with poor understanding of how farmers learn and lacked context-specific focus on solving problems.

At present, a wide variety of information and communications technology (ICT) tools and innovations in financial and extension services offer new opportunities to improve performance, increase access and reduce costs through economies of scale and more efficient operations. Recent innovations in financial technology offer new ways of expanding the inclusion of the financially excluded into the financial system by providing them with a wider range of financial services and products; reaching sparse customer bases spread over difficult-to-access rural geography; reducing costs through economies of scale and more efficient operations; and enabling profitable inclusion of low-cost products or services that meet the needs of previously excluded populations. In the case of extension, the new ICT technologies can make services more demand-driven, up-to-date and inclusive, contributing to revitalizing the interaction between extension services and farmers.

Considering the new opportunities that ICT innovations bring to improve performance of financial and extension services, this study looks at the potential contribution of financial and extension services to the SDGs. The approach used extends the standard Data Envelopment Analysis (DEA) model to include longer-term management goals and find a solution that balances the efficient use of innovation investments and the achievement of policy goals, making this approach well suited for the analysis of the SDGs.

How does the extended DEA approach work? First, DEA is not a foresight model to make projections based on economic theory, nor a model that needs to be calibrated to historical data and that can be evaluated based on its accuracy in “predicting” historical events. Instead, it is a powerful method for comparing and analyzing data. Specifically, in this case, it compares poverty and undernourishment levels across countries, relating those levels with the resources that each country has allocated to reduce poverty and undernourishment. It then finds out which countries have achieved the best results in terms of poverty and malnutrition alleviation given the quantity of resources allocated to this goal. These countries constitute the best-practice frontier in the use of investment for poverty and malnutrition alleviation. Countries that do not lie on the frontier are less efficient in the use of investments. In other words, a country is deemed inefficient because comparisons show that other viii countries, using the same level of resources as this country, have achieved better policy results. The model allows the setting of policy targets (levels of poverty and undernourishment) and provides three major results for each country: a) it determines if the country can or cannot achieve the policy target given investments; b) it gives the minimum level of poverty and undernourishment a country can reach; and c) it estimates the level of investment needed to achieve the policy goals if the country falls short of the target.

The model is solved for the 69 LMI countries, setting as a policy target the reduction of the poverty headcount (PHC) and the prevalence of undernourishment (PoU) to 5% or less to obtain the maximum level of output (minimum level of poverty and undernourishment) that the country can achieve, given public and private levels of investment in innovation and of fixed or structural variables. PHC and PoU were chosen to measure policy targets because they are among the main indicators used to quantify the achievement of SDG 1 (eradicate extreme poverty for all people everywhere) and SDG 2 (end hunger, achieve food security and improve nutrition). The analysis is conducted using average values of variables for the period 2000-2018. Results of the impact of increased access to financial and extension services are obtained from a scenario that determines the levels of financial and extension services that maximize achievement of policy goals.

Results show that LMI countries fall short of achieving the policy target of 5% PHC and PoU. The attainable poverty and undernourishment levels calculated by the model were 25% and 15%, respectively. This is equivalent to an attainable poverty reduction of 100 million people, bringing the number of poor people from 618 million to 518 million. The number of undernourished can be reduced by 96 million, from 560 to 463 million people.

To further reduce poverty and malnutrition, countries could increase investment in innovations and services like finance and extension that facilitate producers’ access to those innovations. The DEA model is then used to determine how far countries can go on the reduction of poverty and undernourishment if they improve access to financial and extension services without changing levels of innovation investment in agriculture. Results show that the combined effect of improved access to financial and extension services is a reduction in the attainable number of poor people from 518 to 488 million (a reduction of 30 million poor people) and in the attainable number of undernourished people from 463 to 428 million (a reduction of 35 million undernourished people).