Countries are different in terms of territory, population, income, their traditions and habits vary, and also the ways, how they handle their public sector real estate management is not the same. Still, there are a lot of common features, which are universal to bear in mind while making decisions over the use of taxpayers’ money. On one hand, in every country the government has to administrate in terms of budgetary constraint, but on the other hand, in every democratic country the public sector has been evoked to serve the interest of the citizens of that country. On the public sector level, there is a general agreement that government authorities need to make state-concerning financial decisions prudently, weighing carefully the consequences in executing different scenarios of action. Smaller countries like Estonia have fewer opportunities and scantier resources (both human and financial) to deal with the complex problems concerning large amounts of capital assets, and therefore decisions over public sector real estate issues need to be made even more diligently.

The paper fills the gap in the literature, where no quantitative level analysis of public sector real estate management has been elaborated. In this paper, an Estonian example has been taken in order to analyse the results from four different state real estate asset management scenarios, called as models. Therefore, the aim of the paper is to draw the implications of public sector real estate asset management models, based on the quantitative fiscal impact analysis on state budget and government sector account. The state real estate assets are viewed in two separated classes – as general-purpose properties and special-purpose properties.

On the one hand, the research shows an extreme complexity of the implementation of public sector real estate asset management (PREAM), but on the other hand, the paper shows that the model-based asset management decision-making and quantitative evaluation of fiscal impact on the level of public sector real estate is applicable also in practice. Implications made out of the research should give some broader enlightment about the problems arising from the similar kind of model-based analysis of the performance of PREAM in other countries.