In both cases, nonlinearity is introduced into the model using appropriate bases functions. In particular, we develop a spatial semiparametric M-quantile model to capture both the potential nonlinear effects of the cultural environment on pricing and spatial trends. The suggested methodology can generally be used to analyse nonlinear interactions between prices and predictors. We show how M-quantile modelling is a rich and flexible tool for empirical market price data analysis, allowing us to obtain a robust estimation of the hedonic price function whilst accounting for different sources of heterogeneity in market prices. This paper proposes an M-quantile regression approach to address the heterogeneity of the housing market in a modern European city.
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