Analysis of Apartment Price Growth Trajectories in Seoul, Korea

Housing is a very important asset for both individuals and the state. It involves large transaction amounts and high property taxes, making long-term ownership common. Therefore, it is necessary to predict future price changes before investment. The aim of this study is to analyze the predictability of changes in apartment prices and the impact of urban renewal on future price trajectories. To that end, we applied the latent class growth model to all apartments (total population) in Seoul, Korea, and obtained the following results. Seoul apartments were categorized into three classes: low growth, medium growth, and high growth. Our multidisciplinary approach is a very early-stage application of data and methodology in housing research. The long-term price increases for expensive apartments were found to be greater than the returns for cheaper apartments. Areas with high apartment prices had higher returns than areas with low prices. The economic effects of reconstruction varied by district. In Gangnam district, pursuing an apartment reconstruction project had the effect of transferring apartments from the low-growth class to the high-growth class. Despite the efficient market hypothesis, we can identify which apartments belong to which class 18 years in advance. We can also predict the transition between classes probabilistically. This study provides practical insights for apartment portfolio investors.