Purpose This study aims to present the findings from a series of case studies that examine the problems faced by countries seeking to introduce value-based recurrent property taxes to replace the ones levied on the basis of area or inventory value. It identifies that two of the most significant barriers are the absence of comprehensive list of taxable properties and inadequate data on transaction prices. Both of these can be overcome with sufficient resources, but this raises the question as to why governments are reluctant to do so, in spite of the advantages of such a change. Design/methodology/approach The paper makes particular use of case studies of Moldova, Poland, Serbia and Turkey, which have explored the potential of introducing value-based recurrent property taxes and the issues they have faced. The case studies have been produced by participant observers who have had the opportunity to examine developments over long periods of time. The case studies are set against a wider statistical analysis of the role of recurrent property taxes in tax systems. Findings Putting in place comprehensive systems for registering properties and recording their characteristics and systematically collecting data on transaction prices require significant investment over a long period of time. This requires commitment on behalf of governments. Governments may be reluctant to support this because of the opposition such reforms can face unless confronted with compelling fiscal or external pressures to act. Research limitations/implications The issues identified are the ones that many countries seeking to introduce value-based recurrent property taxes will face and puts forward how they can be tackled. The case study countries are middle-income ones with relatively well-developed infrastructure, which low-income countries may lack. Practical implications The solutions to overcoming the barriers to value-based recurrent property taxes encountered in the case study countries are the ones that are applicable to many other countries, who can learn from their experience. Originality/value The paper provides a perspective on overcoming the issues encountered in introducing value-based property taxes from the viewpoint of those who have been involved in working out ways of overcoming them and so provides insight that is a useful addition to the literature.

Advanced statistical models have been widely used in real estate valuations for various purposes over the last fifty years, and hedonic approaches with their simple and easy interpretable features are still the most popular among these models. However, spatial heterogeneity and spatial autocorrelation are the two major features of the housing markets, and traditional regression cannot reflect these locational effects into the model sufficiently. This study employs a Geographically Weighted Regression (GWR) model to explore the spatial heterogeneity in the metropolitan area housing market in the city of Ankara. By applying a Gaussian kernel weighting function with adaptive bandwidth based on cross-validation approach on a house listing dataset, it is found that the GWR fit the data better than the traditional ordinary least squares regression which mostly ignore the spatial effects, and there is spatial heterogeneity in the housing market. Explanatory power of the GWR model and parameter estimations are non-stationary over the geographical area. The variations in the coefficients of the variables are depicted on the map and is supported with the spatial correlations between the housing prices and attributes as well.

This paper investigates the impacts of several macroeconomic variables on Turkey's volume of mortgage loans. Johansen cointegration test, vector error correction model, Granger causality tests, variance decomposition, and impulse-response analysis is employed for the econometric analysis to show short and long-run relationships between the variables using time series monthly data from January 2010 to March 2020. Paper results demonstrate that growth of housing credit size negatively correlates with mortgage interest rates, US Dollar/Turkish Lira exchange rate and level of real estate supply. At the same time, there is a positive correlation with house prices. Causal relationships between mortgage volume and macroeconomic indicators are bidirectional for all variables, except for mortgage interest rates. There is a one-way causality relationship from mortgage rates to mortgage loan volume. Econometric analyses show that the recent steep depreciation in the Turkish Lira hurts the Turkish mortgage market. In conclusion, a stable economic environment is essential to build a robust mortgage market.