Human mobility, both short and long term, are important considerations in the study of numerous systems. Economic and technological advances have led to a more interconnected global community, further increasing the need for considerations of human mobility. While data on human mobility are better recorded in many developed countries, availability of such data remains limited in many low- and middle-income countries around the world, particularly at the fine temporal and spatial scales required by many applications. In this study, we used 5-year census-based internal migration microdata for 32 departments in Colombia (i.e., Admin-1 level) to develop a novel spatial interaction modeling approach for estimating migration, at a finer spatial scale, among the 1,122 municipalities in the country (i.e., Admin-2 level). Our modeling approach bridges a significant gap in the availability of migration data at administrative unit levels finer than those at which migration data are typically recorded. Due to the widespread availability of census-based migration microdata at the Admin-1 level, our modeling approach opens up for the possibilities of modeling migration patterns at Admin-2 and Admin-3 levels across many other countries where such data are currently lacking. 

We developed a novel spatial interaction modeling approach for Colombia using previously identified economic, socio-demographic and geographic factors including the regional equivalent of the gross domestic product, relative population size, proportion of urban population and geographic contiguity of locations, in addition to the absolute population size and distance between locations to fit a municipality level (i.e., Admin-2 level) model to observed census-based department level (i.e., Admin-1 level) migration data. 

The dataset contains estimated migration between 2000 and 2005 between 1122 municipalities in Columbia.  The first three columns identify the municipalities. While the remainder are estimated figures of migrant numbers from the munucipality identified by the row to the minicipality identified by the column.  All rows and columns are sorted the same way.