Abstract:

This study aims to determine the relationship between housing demand and economic growth in all provinces of Turkiye in 2019In this study, horizontal section data was used to reveal the spatial effects. In this study, spatial econometric models were used since cities have spatial neighborhood status and the effects of dependent and independent variables on each other are to be determined according to their proximity to each other. The spatial weight matrix was created according to the border neighborhood and its standardized form was obtained. Within the scope of the study, General Nested Spatial Model (GNS), General Spatial Model (SAC), Spatial Durbin Error Model (SDEM), Spatial Durbin Model (SDM), Spatial Lag Model (Spatial Autoregressive Model: SAR), Spatial Error Model (SEM), Spatial Lagged X Model (Independent Variable Spatial Lagged Model: SLX) results were determined. As a result of the research, it is determined that the GDP variable is a significant and positively effective parameter in all models. The spatially lagged GDP parameter is also found to be significant in models where spatial lags are taken into account, negatively effective in SDM and GNS models, and positively effective in SDEM, SLX, and SDEM-GMM models. According to the results of the Global and Local Moran's I test, the GDP variable, which is the determinant of housing demand in all provinces of Turkiye, is positively spatially autocorrelated with the neighboring provinces, and the shocks or effects occurring in the GDP variable also affect the housing demand in other provinces.