Price changes of repeat-sales houses in Kaohsiung city: analyses based on hierarchical linear growth models

Abstract

This study adopts the hierarchical linear growth modeling approach to analyze the differences in the changes of repeat-sales house prices in Kaohsiung City from 2012 to 2020. The Level 1 time-varying factors include house age and the time of repeat-sales; the Level 2 factors include house attributes such as house area, house type, and house location. Based on the results of the null model, the estimated variance is 0.42816, with a 1% level of significance. This shows that significant differences exist in the mean repeat-sales prices between houses. The interclass correlation coefficient is 91.65%, showing that the interclass variation and intraclass variation of the mean repeat-sales prices are 91.65% and 8.35%, respectively. The estimation results of the non-randomly varying slope model indicate that the sales time and sales time squared significantly affect repeat-sales prices. The annual growth rate and quadratic growth of sales prices do not differ by house type (luxury condominiums and apartment buildings) but are affected by house area and house location. The effect of house age on repeat-sales prices is moderated by house area, house type, and house location.

Keywords

• hierarchical linear growth modeling
• repeat-sales
• house prices
• house area
• house type
• house location