Estimation of redevelopment probability using panel data. Asset bubble burst and office market in Tokyo
| DOI | https://doi.org/10.1108/14635781011058893 |
| Date | 13 July 2010 |
| Pages | 285-300 |
| Published date | 13 July 2010 |
| Author | Chihiro Shimizu,Koji Karato,Yasushi Asami |
| Subject Matter | Property management & built environment |
Estimation of redevelopment
probability using panel data
Asset bubble burst and office market in Tokyo
Chihiro Shimizu
International School of Economics and Business Administration,
Reitaku University, Chiba, Japan and Center for Spatial Information Science,
The University of Tokyo, Tokyo, Japan
Koji Karato
Faculty of Economics, University of Toyama, Toyama, Japan, and
Yasushi Asami
Center for Spatial Information Science, University of Tokyo, Tokyo, Japan
Abstract
Purpose – When Japan’s asset bubble burst, the office vacancy rate soared sharply. This study seeks
to target 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. Regarding hedonic functions for offices and housing and computed profit gaps for
approximately 40,000 buildings used for offices in 1991, it was projected how the profit gaps would
influence the land-use conversion probability. Specifically, panel data for two time points in the 1990s
were used to examine the significance of redevelopment/conversion conditions.
Findings – It was 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, a model may be developed 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 analyze
conditions for redevelopment.
Keywords Redevelopment,Office buildings, Economic cycles,Ubran areas, Japan
Paper type Research paper
1. Study objectives
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.
Japan in particular experienced fast real estate price hikes and declines between the
mid-1980s and mid-1990s. The hikes were described as the largest real estate bubbles
in the 20th century. After the bubble burst, Japan saw a long economic slump labelled a
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Estimation of
redevelopment
probability
285
Received January 2010
Accepted March 2010
Journal of Property Investment &
Finance
Vol. 28 No. 4, 2010
pp. 285-300
qEmerald Group Publishing Limited
1463-578X
DOI 10.1108/14635781011058893
“lost decade”. What happened in the Japanese real estate market in the bubble
formation and burst process? How did the microstructure of the real estate market
change amid the large macro fluctuations of real estate prices?
While speculative real estate transactions were repeated in urban areas during the
so-called bubble period, undesirable land-use conversions came under fire. In a typical
case, urban centre houses were converted into small office buildings called “pencil
buildings”. Even in suburban areas, large office buildings and commercial facilities
were constructed.
After the bubble burst, vacancy rates soared for many office buildings with massive
real estate assets left idle, even in central Tokyo with the highest economic
concentration in Japan.
An economic explanation of the phenomenon is that the distribution of land
resources was distorted within the metropolis, bringing about strong inefficiencies.
When inefficiencies exist in the land-use market, conversion/redevelopment is required
to achieve a new equilibrium. This means that land-use inefficiencies are resolved
through conversion to optimize the distribution of resources anew.
Earlier studies analyzed land-use adjustment processes, treating them as urban
redevelopment problems and specifying conditions for redevelopment.
The dynamic urban redevelopment model by Wheaton (1982) assumes that housing
stock developed at one point in time exists at multiple time points. Capital costs emerge
at the development point and are sunk at other points. Therefore, rents after the
development are different from those upon the development and are based on housing
stock after the development. Redevelopment is implemented when post-redevelopment
rent income minus capital costs for the redevelopment is projected to exceed the level
based on the existing housing stock.
Rosenthal and Helsley (1994) used an empirical analysis to verify Wheaton’s
conditions for redevelopment. Using a structural probit model considering a selection
bias, they found that housing redevelopment is implemented when the price of the land
for the redevelopment is projected to exceed the existing land price plus housing
capital destruction costs.
Munneke (1996) used the Rosenthal and Helsley empirical analysis framework for
commercial real estate. This study also indicates that the redevelopment probability
rises as land prices after redevelopment are projected to increase from present levels.
McGrath (2000) conducted an empirical analysis of commercial real estate by
considering redevelopment conditions while taking into account soil pollution risks of
land for redevelopment.
These studies used data at a given point in time for analyses. They apparently
targeted snapshots of the Wheaton model as temporary economic conditions to
consider the advisability of redevelopment conditions. These empirical analyses are
based on cross-section data at a point in time and may fail to identify individual
characteristics of lands or buildings in a city.
In this study we observe rental office and housing rents and building use
conversions, define economic conditions for the redevelopment/conversion of buildings
and estimate the redevelopment/conversion probability under these conditions.
Specifically, we use panel data for buildings at two time points in the 1990s to examine
the significance of conditions for converting offices into housing while controlling
effects of individual characteristics.
JPIF
28,4
286
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