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Same Question but Different Answer Experimental Evidence on Questionnaire Design's Impact on Pverty Measured by Proxies

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  • Kilic, Talip
  • Sohnesen, Thomas

Abstract

Does the same question asked of the same population yield the same answer in face-to-face interviews when other parts of the questionnaire are altered? If not, what would be the implications for proxy-based poverty measurement? Relying on a randomized household survey experiment implemented in Malawi, this study finds that observationally equivalent as well as same households answer the same questions differently when interviewed with a short questionnaire versus the longer counterpart that, in a prior survey round, would have informed the prediction model for a proxy-based poverty measurement exercise. The analysis yields statistically significant differences in reporting between the short and long questionnaires across all topics and types of questions. The reporting differences result in significantly different predicted poverty rates and Gini coefficients. While the difference in predictions ranges from approximately 3 to 7 percentage points depending on the model specification, restricting the proxies to those collected prior the variation in questionnaire design, namely demographic variables from the household roster and location fixed effects, leads to same predictions in both samples. The findings emphasize the need for further methodological research, and suggest that short questionnaires designed for proxy-based poverty measurement should be piloted, prior to implementation, in parallel with the longer questionnaire from which they have evolved. The fact that at the median it took 25 minutes to complete the food and non-food consumption sections in the long questionnaire also implies that the implementation of these sections might not be as overly costly as usually assumed.

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  • Kilic, Talip & Sohnesen, Thomas, 2015. "Same Question but Different Answer Experimental Evidence on Questionnaire Design's Impact on Pverty Measured by Proxies," 2015 Conference, August 9-14, 2015, Milan, Italy 211850, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae15:211850
    DOI: 10.22004/ag.econ.211850
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    Cited by:

    1. Fiala, Nathan & Rose, Julian & Aryemo, Filder & Peters, Jörg, 2022. "The (very) long-run impacts of cash grants during a crisis," Ruhr Economic Papers 961, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    2. Adan Silverio‐Murillo & Jose Roberto Balmori de la Miyar, 2022. "Remittances and domestic violence," Review of Development Economics, Wiley Blackwell, vol. 26(4), pages 2274-2295, November.
    3. Abay, Kibrom A. & Berhane, Guush & Hoddinott, John F. & Tafere, Kibrom, 2021. "Assessing response fatigue in phone surveys: Experimental evidence on dietary diversity in Ethiopia," IFPRI discussion papers 2017, International Food Policy Research Institute (IFPRI).
    4. Joachim De Weerdt & John Gibson & Kathleen Beegle, 2020. "What Can We Learn from Experimenting with Survey Methods?," Annual Review of Resource Economics, Annual Reviews, vol. 12(1), pages 431-447, October.
    5. Brown, Caitlin & Ravallion, Martin & van de Walle, Dominique, 2018. "A poor means test? Econometric targeting in Africa," Journal of Development Economics, Elsevier, vol. 134(C), pages 109-124.
    6. Jeong, Dahyeon & Aggarwal, Shilpa & Robinson, Jonathan & Kumar, Naresh & Spearot, Alan & Park, David Sungho, 2023. "Exhaustive or exhausting? Evidence on respondent fatigue in long surveys," Journal of Development Economics, Elsevier, vol. 161(C).
    7. Abate, Gashaw T. & de Brauw, Alan & Hirvonen, Kalle & Wolle, Abdulazize, 2023. "Measuring consumption over the phone: Evidence from a survey experiment in urban Ethiopia," Journal of Development Economics, Elsevier, vol. 161(C).
    8. Deepti Sharma & Hema Swaminathan & Rahul Lahoti, 2024. "Does it matter who you ask for time-use data?," WIDER Working Paper Series wp-2024-1, World Institute for Development Economic Research (UNU-WIDER).
    9. Dang, Hai-Anh & Kilic, Talip & Hlasny, Vladimir & Abanokova, Kseniya & Carletto, Calogero, 2024. "Using Survey-to-Survey Imputation to Fill Poverty Data Gaps at a Low Cost: Evidence from a Randomized Survey Experiment," GLO Discussion Paper Series 1392, Global Labor Organization (GLO).
    10. Thomas Pave Sohnesen & Niels Stender, 2017. "Is Random Forest a Superior Methodology for Predicting Poverty? An Empirical Assessment," Poverty & Public Policy, John Wiley & Sons, vol. 9(1), pages 118-133, March.
    11. Ligon, Ethan & Christiaensen, Luc & Sohnesen, Thomas P, 2020. "Should Consumption Sub-Aggregates be Used to Measure Poverty?," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt9b9929jh, Department of Agricultural & Resource Economics, UC Berkeley.
    12. Dang,Hai-Anh H. & Kilic,Talip & Carletto,Calogero & Abanokova,Kseniya, 2021. "Poverty Imputation in Contexts without Consumption Data : A Revisit with Further Refinements," Policy Research Working Paper Series 9838, The World Bank.
    13. Pave Sohnesen,Thomas & Stender,Niels, 2016. "Is random forest a superior methodology for predicting poverty ? an empirical assessment," Policy Research Working Paper Series 7612, The World Bank.
    14. Fiala, Nathan & Masselus, Lise, 2022. "Whom to ask? Testing respondent effects in household surveys," Ruhr Economic Papers 935, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    15. Astrid Mathiassen & Bjørn K. Wold, 2019. "Challenges in predicting poverty trends using survey to survey imputation. Experiences from Malawi," Discussion Papers 900, Statistics Norway, Research Department.

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