# **1. Introduction**

Agriculture is the backbone of the economy in rural areas that house nearly 70 percent of the population in low-income countries. The importance of agriculture for development is recognized recently during the formulation of the Sustainable Development Goal (SDG) Target 2.3, which requires doubling of agricultural productivity and incomes of small-scale food producers. In Africa, the average share of rural household income tied to agriculture could be as high as 69 percent (Davis et al., 2017), and the research has shown that compared to non-agricultural growth, agricultural growth translates into higher rates of poverty reduction (Dorosh and Thurlow, 2016).

Yet, despite the importance of agriculture for livelihoods, obtaining accurate and timely estimates on crop production and yields remains a significant challenge. The weaknesses in agricultural data in turn undermine the ability to gauge the performance of the sector; assess the extent to which interventions translate into gains in production, productivity and welfare, both within and across agricultural households; and ultimately, anchor policies in evidence (Carletto et al., 2015). In the context of root, tuber and tree crops, the primary concern around the accuracy of prevailing approaches to data collection in large-scale household and farm surveys that underlie official statistics is arguably the reliance on respondent recall.

For cassava, the crop that is at the center of our analysis and that could be planted to hedge against the risk of seasonal crop failure and/or food insecurity during the lean season, harvesting typically takes place over an extended period and as needed. Irrespective of using a given agricultural season, or a more extended time frame, such as 12 months, as a reference period, respondents are likely to underestimate production as they attempt to recall the accounts of continuous harvests that take place throughout the year and often in small quantities (Friedman et al., 2017; de Nicola and Gine; 2014).P1F<sup>2</sup> And in the specific case of using an agricultural season as the reference period, the recall-based data on production may be incomplete if cassava harvests take place outside the reference season. Other factors that complicate the prospects of reliable production data solicited by household and farm surveys include using non-standard measurement units in farmer-reported crop productionP2F<sup>3</sup> ; and control of plots by household members different from the respondents.P3F<sup>4</sup>

> 2 “Rule of thumb error” may too plague reporting under long recall periods, when respondents cease trying to enumerate each harvest but use a rule of thumb to estimate them (Friedman et al., 2017). However, there is no obvious direction of bias associated with rule of thumb error, with household-specific temporal patterns of cassava harvest playing a significant role in its potential manifestation.

> 3 Common units in which cassava production can be reported include sack, heap and piece, whose size/weight can vary dramatically across farmers – based on locality and cassava variety-specific harvest calendars – and even for the same farmer, as in the case of a farmer reporting two 50-kilogram sacks, of which one could have been 80 percent full while the other could have been overflowing.

> 4 Recall-based interviews are often conducted in a specific time frame that revolves less around the schedule of plot managers, resulting in a greater potential for relying on proxy respondents.

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