This paper proposes an M-quantile regression approach to address the heterogeneity of the housing market in a modern European city. 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. The suggested methodology can generally be used to analyse nonlinear interactions between prices and predictors. 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. In both cases, nonlinearity is introduced into the model using appropriate bases functions. We show how the implicit price associated with the variable that measures cultural amenities can be determined in this semiparametric framework. Our findings show that the effect of several housing attributes and urban amenities differs significantly across the response distribution, suggesting that buyers of lower-priced properties behave differently than buyers of higher-priced properties.

Schirripa Spagnolo, F., Borgoni, R., Carcagni, A., Michelangeli, A., Salvati, N. (2024). A spatial semiparametric M-quantile regression for hedonic price modelling. ASTA ADVANCES IN STATISTICAL ANALYSIS, 108(1), 159-183 [10.1007/s10182-023-00476-w].

A spatial semiparametric M-quantile regression for hedonic price modelling

Borgoni R.;Carcagni A.;Michelangeli A.;
2024

Abstract

This paper proposes an M-quantile regression approach to address the heterogeneity of the housing market in a modern European city. 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. The suggested methodology can generally be used to analyse nonlinear interactions between prices and predictors. 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. In both cases, nonlinearity is introduced into the model using appropriate bases functions. We show how the implicit price associated with the variable that measures cultural amenities can be determined in this semiparametric framework. Our findings show that the effect of several housing attributes and urban amenities differs significantly across the response distribution, suggesting that buyers of lower-priced properties behave differently than buyers of higher-priced properties.
Articolo in rivista - Articolo scientifico
Hedonic regression; Penalised splines; Robust method; Spatial data;
English
30-mar-2023
2024
108
1
159
183
open
Schirripa Spagnolo, F., Borgoni, R., Carcagni, A., Michelangeli, A., Salvati, N. (2024). A spatial semiparametric M-quantile regression for hedonic price modelling. ASTA ADVANCES IN STATISTICAL ANALYSIS, 108(1), 159-183 [10.1007/s10182-023-00476-w].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/409455
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