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In almost each country, the housing market makes up a substantial part of the economy. Therefore, changing house prices may destabilise a country’s economy. It is thus of great importance to have knowledge on what causes house prices to change. In this thesis is investigated how house prices are affected on a national scale and how this differs between countries. Of course, this thesis is not the first to address this topic. A large range of scientific articles dealing with this topic already exist. However, no overview of the results of all these separate studies on house price determinants is available. This thesis deals with this problem by conducting a meta-analysis on the core literature about house price determinants. In total, 78 variables are found to be (potentially) significant in determining house prices on a national scale. This literature overview table provides information on what is already known about house price determinants, but it also shows which gaps still exist in this research field. Most studies investigate only a limited number of countries; English-speaking and the larger European countries. Therefore, in addition to the already existing literature about house price modelling, other countries belonging to the Global North are included so all countries of the Global North are covered in this thesis. The influence of 19 variables, a combination of variables often found to be significant or not often included in house price models before, on house prices of Global North countries is investigated by the use of regression analyses. Regression analyses performed on each country-variable combination separately showed that the extent to which the variables influence annual house prices differs greatly between the 47 countries. For each variable, a country exists for which this variable is significant, and no variable is significant for each country. The results of the regression analyses are structured and made applicable for policy purposes by a cluster analysis, as an answer is provided to the question ‘in which countries are house prices determined by similar variables?' In the cluster analysis presented here, seven types of countries are distinguished. But, since the results of this cluster analysis are strongly influenced by the limited availability of data for several variables, a third regression analysis is performed where the variables are grouped together in four categories in order to overcome the data availability problems. The results from these regression analyses are similar to the results of the regression analyses on each country-variable combination; for each category, a country exists for which this category is significant, and no category is significant for all countries. From this cluster analysis, six groups of countries are distinguished. The results of both cluster analysis differ considerably; there are no clusters that contain exactly the same countries in both analyses. The main conclusion is that the way in which house prices are determined differs largely between countries and variables. This thesis also provides a clear overview of the knowledge concerning house price developments and hereby addresses some knowledge gaps by investigating countries and variables that were not or not often included in house price models before. Moreover, this thesis is of social relevance by providing a country typology based on the extent to which house prices are influenced by (categories of) variables