# 1. Introduction

In early 2020, the COVID-19 pandemic forced the suspension of in-person data collection around the world. As data is a critical means to better understand the impacts of the pandemic, many governments, national statistical offices (NSOs), international organizations, and researchers came to rely on phone surveys in lieu of in-person interviewing. Phone surveys offered advantages for rapid data collection in an emergency both in terms of cost and flexibility (United Nations and World Bank, 2020). While already commonly used tools in high-income countries (National Research Council, 2008; Slavec and Toninelli, 2015), prior to the COVID-19 emergency phone surveys were far less prevalent in low- and middle-income countries where limited phone penetration had in the past been an obstacle to their implementation (GSMA, 2018, 2020). Phone surveys had for instance been used for specific populations and purposes, such as in response to the 2014 Ebola outbreak (Etang and Himelein, 2020) and the 2017 drought and conflict crisis in the Republic of Yemen, Somalia, South Sudan, and Nigeria (Hoogeveen and Pape, 2020), but only in a handful of regional or national projects (Ballivian et al., 2015; Dabalen et al., 2016). The COVID-19 emergency, however, prompted a rapid and wide-scale uptake of phone surveys in these countries, supported not only by the urgent need for real-time data but also by recent expansions in mobile network coverage (Tomlinson et al., 2009; Dillon, 2012; Demombynes et al., 2013; Ballivian et al., 2015; Larmarange et al., 2016; Lau et al., 2019).

This surge in phone surveys provided an unprecedented opportunity for NSOs and international organizations operating in low- and middle-income countries to build experience and the necessary infrastructure to implement such surveys at scale. Gourlay et al. (2021) provide an overview of how this acceleration materialized, drawing on the experience of the Living Standards Measurement Study (LSMS) survey program as well as other survey initiatives. In this paper, we approach the problem specifically from an agricultural and rural angle with a view to informing data collection activities going forward.

Agriculture, especially smallholder farming, comes with several specific challenges for data collection whether conducted in-person or remotely. Among other factors, agricultural production processes are seasonal and irregular, agricultural outcome variables have different timeframes, non-standard units are very common, respondents are more often illiterate, and access to mobile phones is persistently and comparatively low in rural areas (Carletto et al., 2021). To address some of these challenges, survey programs such as the World Bank’s LSMS – Integrated Surveys on Agriculture (LSMS-ISA), FAO’s AGRISurvey, and the 50x2030 Initiative often plan multiple field visits to improve data quality by reducing the length of recall period, but this can increase the burden for survey respondents and add to the cost of survey operations. Despite improvements brought about by many recent methodological developments, agricultural outcome variables continue to be plagued by measurement error related to respondent recall (Beegle et al., 2012a; Carletto et al., 2013; Deininger et al., 2012; Gourlay et al., 2019; Wollburg et al., 2020). Phone surveys, if adequately integrated with traditional survey operations, offer an opportunity to enrich the toolbox of agricultural statisticians in low- and middle-income countries, by providing an additional mode to collect data in a cost-effective and timely manner, taking some of the burden off the in-person interviews. Far from being a panacea, phone data collection has its own challenges.

Phone surveys cannot be expected to be a substitute for in-person surveys when it comes to administering long and complex survey instruments and can face serious issues with coverage bias when phone ownership and network coverage are less than complete in the population of interest. It is critical for data 2