# **1. Introduction**

The adoption of modern agricultural inputs like fertilizers and improved seeds has been credited with the quadrupling of agricultural yields in Asia and South America. In countries like India, Mexico, Pakistan, and <mark>Türkiye,</mark> the Green Revolution—spurred by the increased application of these inputs—has transformed the agriculture sector, significantly increased farming household incomes, and reduced food insecurity. Generous agricultural input subsidies, as well as investments in research and development, irrigation, and rural infrastructure have accelerated this transformation.

Unlike most of the rest of the developing world, however, countries in Sub-Saharan Africa have seemingly failed to realize a Green Revolution. Here, yields continue to lag the rest of the world, as do fertilizer application and adoption of other modern inputs (Carter, Laajaj, and Yang 2021a). In response, many countries in Sub-Saharan Africa began implementing input subsidies in the 1990s, with the goal of increasing agricultural productivity. In 2016, government budgets allocated to input subsidy programs in Sub-Saharan Africa ranged from US$13 million in Rwanda to US$1.1 billion in Kenya.<sup>3</sup> Understanding the impact of input subsidies in agriculture on outcomes such as yields and income remains an important policy question for many countries that continue to allocate resources to such programs or attempt to reform existing programs. There is a large literature that has shown the effects of input subsidy programs on various outcomes of interest, including input usage (Duflo, Kremer, and Robinson 2011; Kim et al. 2021), technology adoption (Koppmair, Kassie, and Qaim 2017; Mason and Smale 2013), yields (Carter, Laajaj, and Yang 2021; Wossen et al. 2017), income (Mason et al; 2017, Yi et al, 2016), welfare (Gemessa, n.d.) and labor market outcomes (Ricker-Gilbert 2014), but a synthesis of the impacts of input subsidies is limited (Jayne et al. 2018; Ricker-Gilbert, Jayne, and Shively 2013).

We contribute to this literature by conducting a meta-analysis to summarize the impact of widely implemented subsidies for fertilizer and improved seeds on agricultural productivity in developing countries. A meta-analysis allows for a systematic summary of the results and conclusions from an overall body of evidence from multiple studies. The method is a statistical technique that combines results from existing studies to create a “pooled” common estimate and also identify sources of disagreement. Our approach is similar to a recent meta-analysis that examines the impact of digital agricultural programs on yields (Fabregas et al. 2019; Fabregas, Kremer, and Schilbach 2019).

The program effects vary depending on the program details, institutional details, and other factors. For instance, input subsidy programs are sometimes administered using vouchers, and in more recent years, e-vouchers (Wossen et al. 2017), while a few programs use cash (Yi, Lu, and Zhou 2016). The interventions and programs that provide input subsidies vary in their design and target populations. For instance, beneficiary targeting can be done at the community level or at the household level, based on land ownership (Osorio et al. 2011; Chirwa and Dorward 2013). The methods used to evaluate the

> 3 The numbers presented are the Total Support Estimate, obtained from Gautam et al. (2022), originally from the Food and Agriculture Organization’s Monitoring and Analysing Food and Agricultural Policies (MAFAP) program (Angelucci et al. 2013).

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