Michael Wild is a Senior Statistician in the Analytics and Tools Unit of the Development Data Group at the World Bank. As a survey and sampling expert, Michael’s main research interest is on the improvement of (survey) data quality in official statistics in developing countries as well as the promotion of evidence-based policymaking.
Michael's current research focuses on new ways of data collection in census and survey operations in particular through the application of new technologies like CAPI, CATI, and CAWI; the use of Big and Geo-Spatial Data in Official Statistics; as well as the application of innovative sampling methods. Besides the applied nature of his research, his emphasis is on making the results of this research available to statisticians in developing countries by programming SPAs (Special Purpose Applications) mostly in R’s SHINY framework accompanied by long term capacity building initiatives.
Michael joined the Bank in 2014, while holding a tenure track position at the Department for Social Statistics and Demography at the University of Southampton, UK, where he has taught classes in Introductory Statistics, Impact Evaluation as well as Sampling Methods. Prior to that, he worked as a resident adviser and senior adviser in several statistical agencies in developing and transition countries.
