ESRA 2027 sessions by theme
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Toward a Better Understanding of Survey Participation and Nonresponse |
| Coordinator 1 | Mr Ádám Stefkovics (ELTE-Centre for Social Sciences) |
| Coordinator 2 | Ms Anna Sára Ligeti (ELTE-Centre for Social Sciences) |
| Coordinator 3 | Mr Ferenc Mújdricza (Hungarian Central Statistical Office) |
| Coordinator 4 | Mr Mátyás Gerencsér (Hungarian Central Statistical Office) |
| Coordinator 5 | Mr Henning Silber (University of Michigan) |
Session Details
Response rates continue to fall across modes and countries, and differential nonresponse increasingly threatens the inferential value of survey data. Addressing this challenge requires a more comprehensive understanding of the decision-making processes underlying survey (non)participation, yet important gaps remain in our knowledge. First, theory is fragmented and potentially incomplete. Benefit-cost, leverage-saliency, social exchange, planned behaviour, social isolation, and compliance-based accounts have developed largely in isolation from one another, and they rarely connect their constructs to the design decisions surveyors actually make. Second, the empirical literature consists mostly of single-factor quantitative experiments that estimate the marginal effect of one design element within an otherwise fixed protocol. Such estimates are conditional on whatever was left unvaried, and they tell us neither the relative importance of the determinants nor how these interact. More theory-driven research and qualitative evidence on how sample members reason about survey requests is needed. We especially invite contributions that consider multiple determinants in the participation decision. Relevant work includes:
- theoretical papers that integrate existing theories of survey participation, adjudicate between them, improve or suggest alternatives to them;
- multifactor designs (field-, factorial experiments, responsive designs, and randomised comparisons of entire data collection protocols) that estimate the relative weight of competing determinants of participation;
- mixed-method designs that test (large-scale) effectiveness of insights gathered from theoretical and/or qualitative studies on quantitative, probability samples of the target population;
- analyses of heterogeneity in the participation decision, as leverage-saliency would predict: how determinants interact, and how their effects differ across sociodemographic groups, modes, sponsors and country contexts;
- Quantitative and qualitative studies of the decision process itself, including interviews, focus groups, analysis of doorstep interaction, and refusal follow-ups that collect data from nonrespondents;
- Paradata, responsive and adaptive designs, and machine learning applied to modelling
