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Trends of Determinants of Housing Price in Seoul, Korea: A Quantile Regression Analysis

임재만 1

1세종대학교

Accredited

ABSTRACT

This article is written from idea that determinants of house prices are different across distribution of house prices. Ordinary least squares method, which estimates conditional mean function, and quantile regression method, estimated for each quantile of conditional distribution of house prices, are used to estimate hedonic price model. The results show that buyers of higher-priced homes value certain housing characteristics differently from customers of lower-priced homes. For Example, the age of house is negative to house prices below 50% quantiles, however positive above 60% quantiles of house price distribution. Hedonic price models are estimated on the data from year 2000 to year 2009 of apartment sales prices in Seoul, Korea, the magnitude and importance of regression coefficients vary with the cycles of general and housing business. Trends of coefficients of two estimation methods show some similarities and differences, especially redevelopment and residential-commercial complex are differ across quantiles of house prices.

Citation status

* References for papers published after 2023 are currently being built.