The relationship between education and dimensions of demography (fertility, mortality and migration) has been well studied; and the idea of integrating education routinely to demographic research is not new. It has been argued that this addition can bring the “quality” dimension to the discipline, which has the quantity of people at its core. However, data on past populations by educational attainment come from patchy data that are subject to different measurement errors and biases and that are not consistent across sources, countries and time. Back projections and other methods have been applied to reconstruct the level of educational attainment of the population, however, they do not provide the uncertainty around the estimates which are due mostly to differences in data source qualities. Bayesian modeling has been used to reconstruct past populations and allows for simultaneously estimating population by age and vital rates. However, its application to multistate population is new, it has only been tested in few countries; and it does not incorporate full measurement error models. The aim of the project is to combine available demographic data to provide true estimates of population sizes, and vital rates by educational attainment with uncertainty around them. For this purpose, we will enhance Bayesian population reconstruction method for multistate population, and combine it with measurement error models.