Welcome to the second issue in the eleventh volume of the International Journal of Housing Markets and Analysis. This year represents the tenth anniversary of the commencement of this journal, and over this period, there have been many changes in both the journal and the discipline of housing market analysis. Continually over the preceding decade, the journal has expanded both the number of issues and the total papers in each issue, as the level of submissions and the quality of housing

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... have increased substantially. Prior to the commencement of this journal, the emphasis in the property and real estate discipline was largely placed on the commercial areas such as retail and office property, where housing was predominantly viewed as providing shelter rather than as an alternative investment medium. Today there is substantial interest in housing, which is both the largest urban land use and also equates to the highest aggregate value for individual land use. Many journals also focus on the developed countries and the operation of housing markets therein. However, another strength of this journal is the emphasis on research into emerging and developing markets, which will be tomorrow's developed housing markets. Let's look forward to the next decade of The International Journal of Housing Markets and Analysis and the ongoing contribution to knowledge about the evolution of our housing markets. The eight countries examined in the nine papers in this issue are typical of the broad coverage of countries, with the topics ranging from the effect of "graves" on house values to the relevance of a mortgage foreclose on the overall market. The first paper from Italy compares two innovative research methodologies, namely, "utility additive" and "evolutionary polynomial regression", for the mass appraisal of residential properties. The data are sourced from three Italian cities, including Rome, Naples and Bari in southern Italy. The findings confirm both the potential and the limitations of the two methodologies used in this research, as well as the potential to use both approaches jointly to interpret and predict changes in the real estate market. The second paper from Ireland seeks to quantify and measure the (dis)amenity effects on house price levels within specific housing submarkets based on their geographic location. The methodology used a quantile regression approach to examine the marginal impacts for different quantiles of the price distribution based on data relating to 3,780 house sale transactions in the Belfast housing market. The findings confirm that housing characteristics are valued differently between quantiles and that conditional quantiles are asymmetrical. The third paper examines over 3,000 house transactions in South Africa and investigates the application of particle swarm optimisation and back-propagation in the weight optimisation and the training of artificial neural networks within the mass appraisal industry. It also compared the performance with stand-alone back-propagation, genetic algorithm with back-propagation and regression models. The findings confirmed that combining particle swarm optimisation with back-propagation in global and local searches for attribute weights enhanced the predictive accuracy of artificial neural networks. In addition, this also enhanced the level of transparency because it highlighted the relative importance of the attributes. The fourth paper from Malta uses an aggregate misalignment index based on a multiple indicator approach to identify the under-or overvaluation of house prices. The methodology used principal components analysis, and the analysis confirmed that the house prices in Malta were overvalued by about 20 to 25 per cent in the pre-crisis boom period. It was argued that this level of house price misalignment has implications for both the economy and overall financial stability.