调查模式对数据质量的影响：来自尼日利亚的实验证据（英）

The Effect of Survey Mode on Data Quality Experimental Evidence from Nigeria Yannick MarkhofPhilip WollburgAmparo Palacios-LopezPauline CastaingAkiko SagesakaIvette Contreras Development EconomicsDevelopment Data GroupFebruary 2026 A verified reproducibility package for this paper isavailable athttp://reproducibility.worldbank.org,clickherefor direct access. Policy Research Working Paper11302 Abstract This paper uses a large-scale experiment in rural Nigeriato study the role of survey mode—in-person versus overthe phone—in survey measurement and data quality.The experimental design isolates mode effects from othercommon sources of errors in surveys and covers 20 out-come measures across topics such as health, labor, shocks,wellbeing, and food security. The findings indicate consis-tent mode effects across outcomes, with phone responsesdiffering from in-person responses by 17–18 percent atthe median. These effects are large relative to other errorsin phone surveys, such as under-coverage of households without phones. A within-respondent design enables cap-turing the full, respondent-level distribution of mode effectsand finds them to vary much more than the averages reveal.Respondents with higher education levels are less proneto mode effects, whereas mode effects sharply increase inprevalence as respondents face more answer options. As thereliance on phone surveys in low- and middle-income coun-tries grows, these findings indicate areas with large potentialfor data quality gains and have first-order implications foreconomic research in low- and middle-income countries. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about developmentissues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry thenames of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely thoseof the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank andits affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. The Effect of Survey Mode on Data Quality: Experimental Evidence fromNigeria Yannick Markhof1ⓡPhilip WollburgⓡAmparo Palacios-LopezⓡPauline CastaingⓡAkikoSagesakaⓡIvette Contreras Keywords:Data quality, Survey data, Phone survey, Measurement error, Survey modeJEL codes:C81, C83, O12 1Introduction High-quality socioeconomic data is fundamental for advancing research and for guiding, targeting, andmonitoring humanitarian and development interventions. In low- and middle-income countries (LMICs),surveys remain a critical source of representative data and a key tool for “ground truthing” socioeconomicoutcomes. In recent years, phone surveys have become an increasingly important mode of data collectionin these settings, particularly following the COVID-19 pandemic, which temporarily forced a shift from in-person to remote interviews (Gourlay et al., 2021a; Zezza et al., 2023). Their appeal is clear: phone surveysare less costly than traditional face-to-face surveys and can be implemented quickly and flexibly to providetimely and higher-frequency data. As such, phone surveys offer a pragmatic response to two convergingpressures. On the one hand, the growing number and frequency of crises and shocks in LMICs has increaseddemand for timely, high-frequency data to inform rapid response and to analyze household resilience andrecovery (Headey and Barrett, 2015). On the other hand, constrained budgets in both research andinternational development have reinforced the push for cost-effective approaches to data collection. Againstthis backdrop, phone surveys have become a prominent and likely enduring feature of the data landscapein LMICs. Yet, as phone surveys have proliferated, concerns about their data quality remain. Like all data sources,phone (and in-person) surveys are subject to errors from multiple sources, but the survey mode itself isincreasingly recognized as an important source of measurement error and bias. Despite growing evidenceon phone survey data quality, important gaps remain in understanding the magnitude, direction, and driversof mode effects, systematic differences in responses attributable to the data collection mode rather than truedifferences in underlying outcomes, and in developing strategies to mitigate them. Literature on mode effects is an active field in its nascency, with limited and somewhat inconclusiveexperimental evidence . Mode effects have been documented for outcomes such as agricultural yields andproduction(Anderson et al., 2024; Kilic et al., 2021), consumption (Abate et al., 2023), microenterprisedata(Garlick et al., 2020), and contraceptive use (Greenleaf et al., 2020), while other outcomes such asdietary diversity and health ap