Dynamic Population Estimates for Low- and Middle Income Countries based on Mobile Phone Data

WIC Colloquium Dynamic Population Estimates for Low- and Middle Income Countries based on Mobile Phone Data Roland Hosner Flowminder Foundation Abstract: While mobile phone data constitute a promising new data source for granular population statistics, they remain partial in terms of population coverage, and prone to representation biases which are difficult to measure and correct for in the absence of independent auxiliary data. The use of mobile phone data to estimate changes of sub-regional population counts over time often relies on a series of assumptions (e.g. the assumption that movements observable for mobile phone users are similar to the movements of the general population. Mobile phone users differ from the general population in many (socio-demographic) characteristics. Flowminder has developed and applied a methodology to produce estimates of internal migration and sub-regional population change in Ghana, Haiti and the DRC. These dynamic population estimates can be used for a wide range of use cases, from the health sector, humanitarian work, disaster preparedness to official statistics. About the presenter: Roland Hosner is a sociologist, migration researcher and statistician, currently working on the estimation of internal mobility and bias-adjustment of statistics derived from mobile phone data. He is Flowminder’s Senior Statistician and leads all work on survey design and analysis, as well as on data triangulation of mobile phone data, survey and census data, to produce mobility and population estimates for Haiti, the DRC and Ghana.