Lemon Technologies and Adoption: Measurement, Theory and Evidence from Agricultural Markets in Uganda*

Abstract

To reduce poverty and food insecurity in Africa requires raising productivity in agriculture. Systematic use of fertilizer and hybrid seed is a pathway to increased productivity, but adoption of these technologies remains low. We investigate whether the quality of agricultural inputs can help explain low take-up. Testing modern products purchased in local markets, we find that 30% of nutrient is missing in fertilizer, and hybrid maize seed is estimated to contain less than 50% authentic seeds. We document that such low quality results in low average returns. If authentic technologies replaced these low-quality products, however, average returns are high. To rationalize the findings, we calibrate a learning model using data from our agricultural trials. Because agricultural yields are noisy, farmers' ability to learn about quality is limited and this can help explain the low quality equilibrium we observe, but also why the market has not fully collapsed.

Do Beliefs About Herbicide Quality Correspond with Actual Quality in Local Markets? Evidence from Uganda

“…Improving productivity on smallholder farms is essential to reducing poverty rates and to improving food security (Bravo-Ortega & Lederman, 2005;Byerlee, De Janvry, & Sadoulet, 2009;Hirvonen & Hoddinott, 2016;Irz, Thirtle, & Wiggins, 2001). High quality agricultural inputs such as hybrid seeds, fertiliser, and pesticides can enhance productivity, reduce the need for labour, and increase profits, but their use in Africa remains puzzlingly low (Aker, 2011;Bold, Kaizzi, Svensson, & Yanagizawa-Drott, 2017;Duflo, Kremer, & Robinson, 2008;Kelly, Adesina, & Gordon, 2003). Reviews of the literature highlight several possible explanations (see Jack, 2011;and Foster and Rosenzweig, 2010): credit and risk market inefficiencies (Karlan, Osei, Osei-Akoto, & Udry, 2014); input and output market inefficiencies (Aggarwal, 2015;Shamdasani, 2016;Suri, 2011); behavioural constraints (Duflo, Kremer, & Robinson, 2011); and lack of knowledge about profitability and proper use (Foster & Rosenzweig, 2010).…”

“…Recent literature documents that many agricultural inputs in East Africa are substantially lower quality than advertised, and this literature suggests that farmers may choose not to purchase inputs they fear may be fake (Bold et al, 2017;Deloitte, 2014;Twinamatsiko, Mwanja, & Dramadri, 2010). That fertiliser and hybrid seeds are low quality in East Africa is no longer under much dispute.…”

“…Using DNA sequencing, Kilic, Ilukor, Kilian, and Stevenson (2017) find that 23 per cent of hybrid maize seeds in Uganda are not the variety they are claimed to be. Bold et al (2017) estimate that the 110 samples of hybrid maize seed they collected in Uganda contain only 50 per cent authentic seeds on average. They also find that fertiliser samples (n = 369) are missing 30 per cent of the active ingredient on average.…”

“…Bold et al (2017) introduce and calibrate a Bayesian learning model showing that farmers should be able to learn the fraction of inputs that are low quality when counterfeiting rates are either very high or very low. How well farmers have learned is an empirical question: Do farmers know what fraction of inputs are low quality in their local shops?…”

“…On these questions, we have very little evidence. Bold et al (2017) show that farmers in Uganda in general know that some fertiliser is low quality. In a survey of 292 farmers, they find that on average farmers expect the fertiliser sold in their local shop contains 38 per cent less active ingredient than it should, while the average fertiliser sample is missing 30 per cent of the active ingredient.…”