Dataset for Multidimensional Poverty Index in Cali-Colombia.

This article presents data collected through in-person surveys conducted in the city of Santiago de Cali, Colombia, to characterize the population registered in the city's Social Program Beneficiary Identification System (SISBÉN, by its Spanish acronym). The sample includes 1605 observations, representing individuals between 18 and 87 years of age. The survey covered various aspects of the population's general characteristics, such as gender, age, race, and education level. Additionally, information was requested about people's employment conditions (whether they are employed or seeking employment, the sector of the economy in which they work, their monthly income, whether they have health insurance, whether they contribute to a pension, in the other questions). Individuals register at the SISBÉN service points in the city and fill out the SISBÉN IV survey (which constitutes the secondary data). We randomly interviewed them at the SISBÉN points to collect additional primary data necessary to achieve the study's objectives. Using the identification, we match the SISBÉN IV survey data (secondary data) with the primary data collected at the service points, thus generating the integrated database presented in this article. The survey was designed within the framework of Interadministrative Agreement No. 4132.010.32.1.376-2024, signed between the University of Valle Foundation and the Administrative Planning Department of the District Municipality of Santiago de Cali, whose objective is to "Pool efforts and resources to administer, update, and maintain the SISBÉN database under its Methodology IV, in order to improve the quality of life of the vulnerable population by the procedures and guidelines established for this purpose by the National Planning Department" drawing on the expertise of the team of researchers in areas related to the labor market, employment quality, and multidimensional poverty. To our knowledge, no other Cali database allows the Multidimensional Poverty Index calculation. The data have also not been used in previous articles. The sampling does not fully represent the Santiago de Cali population. However, it is representative of individuals registered in SISBÉN. Potential selection bias could happen if the researcher's problem is different, for example, occupational and unemployment rates in Cali or urban locations. However, in poverty, SISBÉN classifies individuals to social benefits through a cut-off in the score. The location where individuals are registered is where the probability of poverty is high, and the data could be representative of poverty conditions in Santiago de Cali City. For example, following the DANE [1] methodology of MPI, 11.3 % of individuals registered in Cali's SISBÉN were in multidimensional poverty. These estimations were based on a sample of 44,693 households, representing a total of 112,655 individuals. The data provided in this article constitute a valuable resource for researchers, public administrators, and other stakeholders, as they allow for the analysis of employment quality and poverty among the population registered in SISBÉN.