Estimation of house prices in regions with small sample sizes

House price indexes had become important economic indicators worldwide, since movements in house prices have been closely correlated with the economic cycle. In order to compute these kind of indexes it is imperative to produce reliable estimates of the average transaction price of houses, not only at the macrolevel (e.g. national and state level), but also at the microlevel (e.g. district, municipalities or further disaggregate regional level). In Portugal, there is a rapidly growing demand of such microlevel statistics since the beginning of the recent financial and economic crisis. The Portuguese Statistical Office provides a range of invaluable data at national level; however, this data cannot be used directly to produce reliable regional-level estimates due to small sample sizes. In this paper we employ small area estimation techniques to produce design and model-based estimates of average transaction price of houses for Portuguese regions with small sample sizes. Our results show that the model-based estimates based on spatial and temporal models are more accurate than the traditional direct design-based estimates. The use of these techniques allows the production of information at disaggregated regional levels that would not be available under the traditional direct estimation approaches. Furthermore, it is even possible to produce reliable model-based estimates for geographical areas without sample. The estimates are expected to provide invaluable information to policy-analysts and decision-making.