Earticle

The Seoul Metropolitan Government has launched an urban housing program to help ease the housing shortage in small cities and strengthen the stability of the housing due to the increase in single and double households in the city. In general, a survey of the price premium of local and surrounding environmental characteristics for housing found that little is known to the extent of its impact on housing rents in small and medium cities. We use geographic information system techniques to measure the variables while investigating the impact of these features on monthly rents of urban residential housing by estimating and comparing traditional and spatial header pricing models. We found that spatial HPMs perform better than traditional HPM in terms of fitness. Most of the variables related to location characteristics and the surrounding environment had a significant impact on rent. Rent rates are low in areas near universities. However, access to the park does not seem to be important to residents. We conclude that people living in small urban housing tend to pay rent in different ways.

The ordinary least squares based estimator of the disturbance variance in a regression model for spatial panel data is shown to be asymptotically unbiased and weakly consistent in the context of SAR(1), SMA(1) and SARMA(1,1)-disturbances when there is measurement error in the regressor matrix.