Koji KaratoBack to index

  • Separating the Age Effect from a Repeat Sales Index: Land and Structure Decomposition

    Abstract

    Since real estate is heterogeneous and infrequently traded, the repeat sales model has become a popular method to estimate a real estate price index. However, the model fails to adjust for depreciation, as age and time between sales have an exact linear relationship. This paper proposes a new method to estimate an age-adjusted repeat sales index by decomposing property value into land and structure components. As depreciation is more relevant to the structure than land, the property’s depreciation rate should depend on the relative size of land and structure. The larger the land component, the lower is the depreciation rate of the property. Based on housing transactions data from Hong Kong and Tokyo, we find that Hong Kong has a higher depreciation rate (assuming a fixed structure-to-property value ratio), while the resulting age adjustment is larger in Tokyo because its structure component has grown larger from the first to second sales.

    Introduction

    A price index aims to capture the price change of products free from any variations in quantity or quality. When it comes to real estate, the core problem is that it is heterogeneous and infrequently traded. Mean or median price indices are simple to compute, but properties sold in one period may differ from those in another period. To overcome this problem, two regression-based approaches are used to construct a constant-quality real estate price index (Shimizu et al. (2010)).

  • Estimation of Redevelopment Probability using Panel Data -Asset Bubble Burst and Office Market in Tokyo-

    Abstract

    Purpose: When Japan’s asset bubble burst, the office vacancy rate soared sharply. This study targets the office market in Tokyo’s 23 special wards during Japan’s bubble burst period. It aims to define economic conditions for the redevelopment/conversion of offices into housing and estimate the redevelopment/conversion probability under the conditions.
    Design/methodology/approach: The precondition for land-use conversion is that subsequent profit excluding destruction and reconstruction costs is estimated to increase from the present level for existing buildings. We estimated hedonic functions for offices and housing, computed profit gaps for approximately 40,000 buildings used for offices in 1991, and projected how the profit gaps would influence the land-use conversion probability. Specifically, we used panel data for two time points in the 1990s to examine the significance of redevelopment/conversion conditions.
    Findings: We found that if random effects are used to control for individual characteristics of buildings, the redevelopment probability rises significantly when profit from land after redevelopment is expected to exceed that from present land uses. This increase is larger in the central part of a city.
    Research limitations/implications: Limitations stem from the nature of Japanese data limited to the conversion of offices into housing. In the future, we may develop a model to generalize land-use conversion conditions.
    Originality/value: This is the first study to specify the process of land-use adjustments that emerged during the bubble burst. This is also the first empirical study using panel data to analyse conditions for redevelopment.
    Key words: hedonic approach, random probit model, urban redevelopment, Japan’s asset bubble Paper type: Research paper

    Introduction

    Sharp real estate price hikes and declines, or the formation and bursting of real estate bubbles, have brought about serious economic problems in many countries.

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