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@article{ Maligalig2013,
 title = {Developing a Master Sample Design for Household Surveys in Developing Countries: A Case Study in Bangladesh},
 author = {Maligalig, Dalisay S. and Martinez Jr., Arturo},
 journal = {Survey Methods: Insights from the Field},
 pages = {25},
 year = {2013},
 issn = {2296-4754},
 doi = {https://doi.org/10.13094/SMIF-2013-00009},
 urn = {https://nbn-resolving.org/urn:nbn:de:0168-ssoar-349343},
 abstract = {For evidence-based policy making, socio-economic planners need reliable data to evaluate existing economic policies. While household surveys can serve as a rich source of socio-economic data, conducting them often entails a great deal of administrative, technical and financial resources. With limited resources for data collection, this often puts pressure on national statistical systems to meet the continuously growing data demand of its stakeholders, especially in developing countries. Using a master sample design that can be used to select samples for multiple household surveys provides an opportunity to minimize the resources needed to collect household survey data regularly. In particular, using the same sampling design and frame to select samples either for multiple surveys of different content or for different rounds of the same survey could induce significant cost-savings instead of developing an independent design each time a household survey is to be carried out. This paper provides a step-by-step guide for developing a master sample design for household surveys in developing countries. Using Bangladesh as a case study, issues like effective sample allocation to ensure the reliability of domain estimates, stratification measures to reduce design effects and introducing household sample size adjustment when to maintain uniform selection probability within domain are discussed.},
 keywords = {Stichprobe; sample; Privathaushalt; private household; Befragung; survey; Bangladesch; Bangladesh; Entwicklungsland; developing country; Datengewinnung; data capture; Erhebungsmethode; data collection method; Forschungsplanung; research planning; Analyseverfahren; analysis procedure; Fallstudie; case study}}