A small literature has studied the effects of the timing of non-labor inputs application. Jagani et al. (2021) use a household panel in Kenya to show that farmers respond to variation in temperature within the growing season, adjusting input application and labor use to short-run temperature shocks. Islam and Beg (2021) randomize farmers into a treatment that improved the timing of urea application among rice farmers in Bangladesh, reducing urea use by 8% without reducing yields. They find in their baseline survey that farmers are applying urea earlier than recommended in the growing season, and are applying more than recommended quantities. Farmers who experience outreach about this issue reduce applications of urea early in the season, when returns to application are low.

Though accurate measurement of application quantity is undoubtedly important, there has been minimal research to date on this topic. Beegle et al. (2012) suggest that because fertilizer purchase and application are generally salient and singular events, this particular domain of agricultural data is less prone to recall bias than other domains, such as agricultural labor. Indeed, they generally support this hypothesis in their analysis of data from national surveys in Malawi and Kenya, taking advantage of the 12-month fieldwork design to assess the impact of recall duration on quantity reported, where they find no evidence of recall bias with respect to fertilizer use (binary), and minimal evidence of recall bias with respect to quantity of application, though findings do differ slightly by crop type and household headship. More recently, Wollburg et al. (2021) find that longer recall periods lead to recall bias both in fertilizer use (binary) and in the quantity of application. With increasing recall periods, farmers are less likely to report the use of fertilizers but report higher quantities applied.<sup>25</sup> While differences in methods of elicitation exist across research and data collection efforts, head-to-head within-survey experiments to compare methods for measuring quantity of input application does not seem to have been undertaken as yet. Within-survey experiments about mineral fertilizer and pesticide quantity application could center on recall periods or applications over different units (by plot vs by crop, for example) compared against a benchmark of farmer diaries or weekly calls to assess week-by week quantities applied, also with a view to best addressing measurement issues associated with nonstandard reporting units. Similar within-survey experiments about agricultural non-labor input timing could be conducted. We have encountered no research empirically exploring methods for measuring the quantity of fertilizer or pesticide applied using within-survey variation in recall periods or input application diaries.

# **VIII. Conclusions**

Agricultural input quality in Sub-Saharan Africa is beginning to receive needed attention from researchers and policy makers; however, the focus so far has been on urea fertilizer nutrient quality and on glyphosate herbicide. Results in this review document that urea quality does meet listed specifications, but that nutrient shortages can characterize other market-available fertilizers,

> 25Recent work by Mueller et al. (2022) assesses recall bias in reported pesticide use, disaggregated by active ingredient, over a two-year period, finding that reported prevalence rates (irrespective of quantity applied) of most of the main pesticides increased after a two-year recall period relative to the baseline.

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