In the academic literature about construction of housing price indexes, administrative geographic areas are mostly used. Very rarely discusses and analyzes the question what is the optimal regional division from a statistical point of view as well as a practical point of view. In the design of the housing price indexes, we will always have a problem that certain housing markets have very few observations and it is therefore not possible to publish a robust and reliable monthly index series. On way to remedy this problem is to, instead of estimating a monthly index, estimate a quarterly index. The question of periodicity is therefore an issue that must be solved simultaneously with the issue of regional division. The aim of this paper is to construct an index family for an entire nation (in this case Sweden). The goal is to construct a housing price index for Sweden as a whole, but also for a number of regions. The number of regions is, however, an open question. Our main purpose is therefore to optimize the regional division of the estimation of regional housing price index. The paper will make use of the traditional hedonic methodology, where we relate the price of houses against value-influencing attributes such as floor space, standard and age. In addition, we will control for the attributes in the neighborhood such as distance to the CBD and lake views. The study will be based on a unique database provided by Valueguard AB. The database contains about 70% of all house sales in Sweden since 2005. The database has been constructed by linking data from real estate agents and official property register. This makes it possible to relate the price at the transaction date, with value-influencing attributes as opposed to the official index, where the price of land registration date related to the attributes. Preliminary results suggest that it is possible to create a family of housing price indices in a nation that are more robust and reliable by optimizing the regional division.