Analysis of Japanese Land Prices Using Prefectural Data
by
Kenji Kamio
B.A. in Law
Keio University, 1986
Submit to
the Department of Urban Studies and Planning
in Partial Fulfillment of the Requirements for
the Degree of Master of Science in Real Estate Development
at the
Massachusetts Institute of Technology
© 2000 Kenji Kamio
All Rights Reserved
The author hereby granted to MIT permission to reproduce and to distribute publicly
paper and electrical copies of this thesis document in whole or in part.
Signature of the Author
Kenji Kamio
Department of Urban Studies and Planning
August 4, 2000
Certified by
William C. Wheaton
Professor of Economics and Urban Studies and Planning
Thesis Advisor
Accepted by
William C. Wheaton
Chairman
Interdepartmental Degree Program in Real Estate
ASSiUSliEfTS INTITRT
OF TECHNOLOGY
SEP:)1 4 2000
LIBRARIES
ROTCH,
Analysis of Japanese Land Prices Using Prefectural Data
By
Kenji Kamio
Submitted to the Department of Urban Studies and Planning
on August 4, 2000
in Partial Fulfillment of the Requirements for the Degree of
Master of Science in Real Estate Development
at the Massachusetts Institute of Technology
Abstract
The purpose of the thesis is to examine what economic factors determined or strongly
influenced the Japanese land prices especially in the Bubble Period using prefectural
data.
This paper provides a Land Price Table which makes possible an understanding of real
movements from 1970 through 1999 in land prices in each prefecture and compares
the differences among prefectures. The table indicates the two peaks where land price
jumped and then sharply fell within quite a short period in almost all prefectures. This
paper provides explanations of the reason for the phenomena from both time-series
and cross section levels.
Utilizing the data in the Land Price Table, the research runs several cross
regression analyses setting up movements in land prices in each prefecture
dependent variable and four fundamental data, density, population growth, job
and stock growth as independent variables. The analyses show unique features
section
as the
growth,
in land
prices movements in each prefecture in each of three periods: Pre-Bubble Period
(1975-1985), Bubble Period (1986-1991) and Post-Bubble Period (1992-1999). The
results show which economic and other factors determined these movements of land
price in each period.
Thesis supervisor: William C. Wheaton
Title: Professor of Economics and Urban Studies and Planning
TABLE OF CONTENTS
Chapter 1. Introduction & Thesis Outline
Introduction ...........................................
1.1.
1.2.
5
-................
-
6
Thesis O utline ........................................................................
Chapter 2. Definitions
..... 8
2.1.
Prefecture................................................
2.2.
2.3.
10
Land Price ...............................................
Characteristics of Japanese Real Estate Market (In General).............12
2.4.
Bubble................................................15
Chapter 3. Methodology
3.1.
General...............................................18
3.2.
Land Price Table.........................................
3.3.
Independent Variables...........................................................20
...
- .........
3.3.1.
Density...................................................20
3.3.2.
Population Growth....................................................
3.3.3.
Job Growth.............................................
19
21
..... 21
22
Stock Growth...........................................................
22
...............................
Tim e Period......................................
Pre-Bubble Period (1975-1985)..................................22
3.4.1.
3.3.4.
3.4.
3.4.2.
3.4.3.
Bubble Period (1986-1991).......................................23
Post-Bubble Period (1992-1999).....................................23
Chapter 4. Results 1 - From Land Price Table
Observations...............................................................24
4.1.
R eal Basis..................................................................24
4.1.1.
... 26
Geographical Gaps..............................................
4.1.2.
4.1.3.
4.2.
Gaps between Commercial and residential Properties.......30
Analyses................................................................32
........... 32
Peak of 1974.........................
4.2.1.
4.2.2.
Peak of 1990.....................................
3
-33
-...........-
Chapter 5. Results 2 - From Cross Section Analyses
5.1.
1975-1985 (Pre-Bubble Period)................................................36
5.2.
1986-1991 (Bubble Period)...................................................38
5.3.
1992-1999 (Post-Bubble period)..................................................41
5.4.
Limit of Analyses..................................................................43
5.4.1
Prefectural Internal Problems..................................43
5.4.2.
Gaps in Observation Points......................................43
Chapter 6. Conclusion
6.1.
Findings from Land Price Table.................................................45
6.2.
Findings from Cross Section Regression Analyses.........................46
Appendices:
Appendix 1
Land Price Table............................................................48
Appendix 2
Data Set (1975-1985)......................................................72
Appendix 3
Data Set (1986-1991)......................................................73
Appendix 4
Data Set (1992-1999)......................................................74
Bibliography.................................................................................................75
Chapter 1
Introduction and Thesis Outline
1.1. Introduction
Until the early 1990's, land was considered the safest and the most profitable asset in
Japan. Actually, land prices increased year by year and experienced an almost 130-fold
in the 45 years from 1955 through 1990. The conventional Japanese customs of
clinging to land, the taxation giving advantages to landowners, the continuous
speculative activities in real estate by companies made Japanese people believe that
land would perpetually increase its value and, thus, this belief created a symbolic
phrase "Tochi Shinwa" (Myth of the Land), meaning that land price rises perpetually.
However, after the climax of Japanese economic prosperity accompanying the
surprisingly substantial rise in real estate values from the mid 1980's through early
1990's, (which gives it the name "Bubble Economy"), land prices dramatically fell. As it
was the first time that Japan had experienced a decline of land price and the
magnitude of collapse was so drastic, Japanese people and companies fell into chaos.
The government could not implement proper remedies to treat it so far, and, as the
result, overall land prices are still declining even in 2000.
It has been believed that this Bubble and its crash were an anomaly based on only
speculation. However, in economics, boom and bust behaviors of land are not
necessarily products of speculations and irrational activities. Land prices even in a
Bubble period might be determined or strongly influenced by economic factors.
The objective of this thesis is to make clear such influence of economics in land price.
This thesis attempts to model the Japanese land price mainly focusing on its
movements in the Bubble Period on a prefectural basis. The results should give us an
idea of the characteristic of the overall Japanese real estate market as well as regional
movements in land prices.
1.2. Thesis Outline
The thesis is comprised of six chapters.
Chapter 2 provides the definitions of Japanese prefecture and land price, and
introduces historical trends of the key characteristics of the Japanese real estate
market. Also, the chapter explains the concept of the Bubble from the economics side.
Chapter 3 explains the methodologies and tables that this thesis uses in analyzing the
movements of Japanese land price. It also explains the concept of the dependent
variable and independent variables for the regression analysis the thesis runs.
Chapter 4 indicates the findings from the Land Price Table about movements of land
price in each prefecture and makes explanations about the results.
Chapter 5 builds up three data sets from the table used in Chapter 4 and four
economic fundamentals and runs several cross section regression analyses. The results
of the analyses indicate the characteristics of land prices movements in each of the
three periods, Pre-Bubble Period, Bubble Period, and Post-Bubble Period. Also, the
chapter analyzes which factors influenced the movements in land prices in each
period.
Chapter 6 concludes the thesis with findings from the Land Price Table and the cross
section regression analyses.
Chapter 2
Definitions
2.1 Prefecture
As this paper's data in land prices are almost all drawn from prefectures, I will first
explain Japanese prefectures.
There are 47 prefectures in Japan as shown in Figure 2.1. A prefecture is a local
government that controls its subordinating cities, towns and villages. A prefecture has
a parliament as its legislative organization
and a governor as its executive
organization and has a right to impose local taxes and to issue local bonds for its
budget. There are several geographical and demographical features among prefectures.
For example, prefectures range from 83,452 square kilometers (Hokkaido) to 1,861
square kilometers (Kagawa) in area size, from 5,403 (Tokyo) to 68 (Hokkaido) in
density (number of persons per square kilometer) in 1995, and from 86,226,108 million
yen (Tokyo) to 2,103,690 million yen (Tottori) in 1996 in Gross Regional Output.
In general, the following three zones are urban areas where big cities are located and
people, jobs, capitals, and information mainly concentrate.
(1) Greater Tokyo area (Tokyo, Kanagawa, Saitama, Chiba)
(2) Aichi (the prefecture including Nagoya City, the fourth densest city)
(3) Osaka area (Osaka, Hyogo, Kyoto)
Figure 2.1. Japanese Prefectures
Toyama
Fukui
Tochigi
Okayama-
iunma
Kyot
- Saitama
Yamagu6hi
Tokyo'
Fukuoka
.. '
n... ...
Saga
Kumamoto
/
Kagawa
Okinawa
Miyazaki
Kagoshima
Q
4
'
2.2 Land Price
In Japan, several public and private organizations regularly issue Land Price for
several purposes. I will explain typical four land prices that are frequently referred to
in real estate transactions and as inheritance benchmarks.
(1) Koji Chika
The National Land Agency issues Koji Chika, land prices that are measured every
year on January 1st on all Japanese land depending on property types such as
residential, commercial, industrial and so on. The prices are shown on a square meter
basis. The observation points are revised annually and amounted to 30,800 points in
1999's survey. Each point is evaluated by certified real estate appraisers based on the
actual real estate transactions. Koji Chika is usually utilized as one of the most
reliable indices in evaluating properties and a standard of expropriations.
(2) Kijunchi Kakaku
Each prefecture annually issues Kijunchi Kakaku for the land prices within its
prefecture as of July 1st. Observation points are determined by each prefecture and
total number of points amounts 30,000 points all over Japan in 1999. Kijunchi Kakaku
is measured by the same method as Koji Chika and is also mainly used as an index of
real estate transactions.
(3) Rosen Kakaku
For the index of inheritance and donation tax, the National Tax Administration issues
Rosen Kakaku. It adopts a unique evaluation method that determines values of facing
roads and calculates the land value adjusting the ratio of adjoined roads and the land
shape. Rosen Kakaku is arranged to be 80% of Koji Chika to relieve the burden for
taxpayers.
(4) Koteishisan Hyokagaku
Cities, towns, and villages determine Koteishisan Hyokagaku every three years to
evaluate the bases of the property tax. Like Rosen Kakaku, Koteishisan Hyokagaku is
also restricted; it is 70% of Koji Chika for the purpose of relieving tax burden of
landowners who hold huge properties.
Among these land prices, for the paper, I chose Koji Chika as the index for the
following two reasons.
First, the main purpose of this paper is trying to explain characteristics of the
movements in Japanese land prices by reviewing 47 prefectures' data. For this work, it
is vital to choose land prices that were evaluated by the same method among
prefectures. Koji Chika is the best index since it has been issued by the same
organization (The National Land Agency) in relatively long term (from 1975 to all
prefectures) by the same method (evaluated by certified real estate appraisers based
on recent real transactions).
Second, Koji Chika is considered to be the most reliable index reflecting real land
prices among land price indices. As described, other methods such as Rosen Kakaku
and Koteishisan Hyoukagaku adjust land prices for virtues of taxpayers and
intentionally reduce the issued price.
2.3. Characteristics of Japanese Real Estate Market
(In General)
After World War II, Japanese land price consistently rose until the early 1990's, except
for 1975 right after the oil crisis. Figure 2.2. explains the land price movement
compared to those of stock and nominal GDP. Though other assets such as stocks and
bonds had cyclical trends in their price movements, real estate values went up
regardless of surrounding economic conditions
Figure 2.2.
Long-Term Trend of Land, Stock, and GDP
14000
12000
10000
8000
6000
4000
2000
A04
0 4
01*PO4b14
qA,14
J
0
"'
'
Year
Source: The Ministry of Construction
The reasons for this continuous rise in Japanese land price are considered to be
derived from the following three situations.
First, overall Japanese area is very small, amounting to only 378 thousand square
kilometers, about 4% of that of the United States. Furthermore, areas where people
can live are very restricted because about 67% of the land is mountain area. On the
other hand, Japan is a highly populated country (126 million in 1999) and population
growth rates were relatively high, annually growing over 1% until the 1970's. In
general, as land price is determined by population growth and supply of land, this
geographical and demographical characteristic deeply influenced the continuous rise
in land price.
The second reason comes from specific Japanese customs and systems. Traditionally,
Japanese people have tended to regard land as the special property that their
ancestors presented to them. So they thought that land was their heritage and they
rarely disposed of it unless they had considerable reasons. Also, as there was no public
market for trading real estate and valuation and pricing was done on a case-by-case
basis, price competitions hardly ever occurred in real estate transactions. In addition,
high transaction costs, especially income gain tax and transaction fees, also prevented
trading of real estate.
The third reason was derived from the banking system. Japanese banks heavily
stressed the value of land for their loan collateral, based on their belief that land was
the safest asset. As Japanese companies usually raised their capital through bank
loans until the late 1980's, the importance of land value as collateral increased in
parallel with Japanese economic expansion.
2.4. Bubble
According to Noguchi (1992), Bubble can be defined as the price gap between real
asset price and fundamentals price.
Fundamentals price can be described as the discounted cash flow (DCF) model. The
DCF model explains that the asset price will be determined by the future profitability
of the property and discount rate. This concept can be described with the following
equation.
Pt =dt+1/r-g
where, P is the present asset price, d is the cash flow from the land, r is the discount
rate, and gis the expected growth rate.
In the real estate market, land price (1P can be determined by the change of the real
rent (d and the capitalization rate (r-g). If rents grow as the same pace as the
consumer price index (CPI), the causes of the increase in rents is economic
fundamentals even if the magnitude is very large.
However, if growth of rents occurs following after that of CPI, it means that investors'
expectation forces to decline capitalization rate and, thus, causes a Bubble in the near
future. This Bubble can be called as the rational Bubble because the rise in land price
can be expectable in some extent in advance from the movements of fundamentals.
If the growth of rent has no relation with CPI and rise in land price cannot be
explained by economic fundamentals, it can be defined that the increase in land price
is the irrational Bubble.
I will apply above concepts of Bubble to the Japanese real estate market. Following
Figure 2.3. compares historical movements in annual percentage change of real rent in
Tokyo with that of CPI.
Figure 2.3
Historical Movements of growth rates in Real Rent and CPI
60%
50%
40%
-+-Rent
+U
30%
zCPI
-
20%
10%
0%
-20%-----
-
Source: Real Rent: Japan Building Association
CPI: Economic Planning Agency of Japan
From the graph, we can see two significant peaks in the movements in real rent,
around 1974 and around 1988. However, the two peaks are quite different in the
relation with the movements of CPI.
In 1973, the annual percentage change of CPI jumped from 5.6% to 11.8% while that of
real rent fell from 7.8% to 3.8%. At that point, investors expected that rent would rise
in the near future and became aggresive to invest to properties. This attitude forced
the capitalization rate to fall sharply and, as the result, rent jumped 55.8% in 1974.
This sudden soaring in rent also reflected to investors' future expectation to continue
this trend and it caused a shot up of land price. Though growth gap between real rent
and CPI was quite outstanding in this period as shown in Figure 2.3., this rise in rent
and land price were predictable, so it can be defined to be the rational Bubble.
On the other hand, in the late 1980's, CPI was continuing to decline and was quite
stable through 1986 to 1988. However, the rent was suddenly shot up especially in the
CPI's stable period. As the sudden rise around 1988 cannot be explained by the
fundamental prices, it can be thought to be the irrational Bubble.
Chapter 3
Methodology
3.1. General
The purpose of this paper is to explain what determined geographical gaps in the
Japanese land price movements, what kind of factors caused and influenced the
"Bubble" land price, and why the land price collapse occurred so suddenly.
To resolve these problems, first, I developed a Land Price Table as the core index for
observing Japanese land prices.
Second, I chose several fundamental factors that might be expected to determine or
deeply influence the fluctuation of land prices in terms of prefecture-basis. After
consideration, I determined four independent variables: density, population growth,
job growth, and stock growth in all prefectures.
Third, I ran several cross-section regression analyses and tried to find what
independent variables really influence the movement of land prices. The dependent
variable is the annual average percentage changes of commercial and residential land
prices in all 47 prefectures, and independent variables are four fundamental factors
described above. Also, I divided the observation period into three parts, Pre-Bubble
Period from 1975 to 1985, Bubble Period from 1986 to 1991, and Post-Bubble Period
from 1992 to 1999, because movements of land prices are quite unique in each of three
periods.
Finally, I tried to find proper independent variables that fit the movements of land
price in each period and explain whether fundamentals influenced movements of land
price especially in the Bubble Period or not, and if so, what kind of factors determined
or influenced the unique movements in Japanese land prices.
3.2. Land Price Table
The Land Price Table is shown in Appendix 1. For the land price standard, I adopted
Koji Chika for the reasons explained in Section 2. I picked land prices from 1970, the
year Koji Chika was first issued. But, as it had not been applied to all prefectures until
1975, the data set is not fully equipped in the first five years, so cross-section
regression analyses were run from 1975.
For the observing property type, I picked commercial zones and residential zones of
each prefecture because land price movements in these zones are quite sensitive to
fundamentals and other economic factors. For each prefecture of commercial and
residential zones, I set up time series data, (1) Land price (yen/rM), (2) Land price
index under the condition that the price of 1990 equals 100, (3) Year-to-year
percentage change in land price (nominal), (4) Year-to-year percentage change in land
price (real), and (5) Number of observation points, respectively.
For (3) and (4), I implemented some adjustments to make up for a significant
disadvantage of Koji Chika. As each prefecture's observation points have been revised
over the course of years, the year-to-year percentage change in land price might
fluctuate because of merely the revision of the observation points.
To resolve this structural disadvantage, I devised the year-to-year percentage change
by comparing the prices between the previous year's prices and the next year's prices,
adjusting to previous year's position. Continuing this method for all comparisons, the
objectivity of the data can be maintained, making possible to make apple-to-apple
comparisons among all prefectures'land prices.
3.3.
3.3.1.
Independent Variables
Density
Density is the key factor to determine the land price. According to DiPasquale and
Wheaton (1996), the relationship between density and land value moves in both
directions: a higher value not only encourages greater density, but a greater density
also increases the value of land.
To determine the density per prefecture, I used data from the National Census that
has been held every five years and the Population Estimation that has been calculated
every year except census years. Both of these have been issued by the Statistics
Bureau. Dividing population of each prefecture by its area, I fixed each prefecture's
density, the number of persons per square kilometer.
3.3.2. Population Growth
Population growth is also a prime determinant of land prices. Faster growth causes
increasing land rents and the capitalized value of these increases forms the basis of
increasing land prices. By examining the difference in dynamic of population growth
among prefectures, the movements and magnitudes in change in land price can be
predicted.
To make this time series data, I use the same resources as with the density data and
calculated the population growth rate.
3.3.3. Job Growth
According to DiPasquale and Wheaton (1996), the real estate market is deeply related
to the output market and labor market. If the demand for a region's products expands,
output prices, wages, and real estate prices all rise, as do the quantities of output
produced, employment, and stock of real estate. On the other hand, from the supply
side, excessive supply of labor leads the fall in output price and wages, while the
quantity of output produced and employment both rise, resulting in the increase in
stock of real estate and a rise in real estate prices.
To examine this relationship, I referred to the annual number of employees who work
in the prefecture from the data issued by the Economic Planning Agency. The number
includes employees who work in one prefecture while living in another prefecture.
3.3.4 Stock Growth
From the same reason as that of Job Growth, I picked Stock Growth as one of probable
determinants that influence the fluctuation of land prices.
I referred to the number of annual construction starts issued by The Ministry of
Construction. As it was impossible to sum up commercial buildings into a prefectural
level, I only adopted residential buildings by using the unit of households.
3.4. Time Periods
For the time series, I divided the period from 1975 to 1999 into following three parts in
terms of the different trends of land prices.
3.4.1
Pre-Bubble Period (1975-1985)
I defined the period from 1975 to 1985 as Pre-Bubble Period. In this period, land prices
of both commercial and residential properties have calmly risen year by year
accompanying the Japanese economic expansion. This period's land price movements
have a good contrast with those of after periods in that overall price change is very
small.
3.4.2. Bubble Period (1986-1991)
From 1986, land prices suddenly soared especially in urban prefectures. For example,
the change in residential land price in Greater Tokyo area, Osaka area, and Nagoya
area in this Bubble Period were 227%, 228%, and 181%, respectively. As explained in
Chapter 2, the rise in land price in this period was an anomaly in that consumer prices
were quite stable, but, prices of investment objects such as real estate and stock
skyrocketed
3.4.3. Post-Bubble Period (1992-1999)
In 1992, land price suddenly declined in contrast to the rising tendencies of the
previous years. For example, the change in residential land price in Tokyo, Osaka, and
Kyoto prefectures in 1992 were annually -15.1%, -23.8%, and -27.5% respectively.
Though the downward magnitudes improved year-by-year, land prices still continued
declining even in 1999.
Chapter 4
Results 1 - From Land Price Table
By reviewing movements in land price in each prefecture from the Land Price Table, I
found that almost all prefectures experienced two peaks when land prices dramatically
jumped, around 1974 and around 1990. These two periods are also similar in that the
expanded overvalued land prices suddenly fell in quite a short time. However, the
table shows different characteristics between the two periods as follows,
4.1. Observations
4.1.1.
Real Basis
The rises in land price in 1974 closely correlated to the movements in the consumer
price index (CPI). For example, in Kanagawa, the third densest prefecture and a part
of the Greater Tokyo area, percentage change of land price in commercial areas in
1974 is 31.2%, while the percentage change of CPI was 23.2%. On the other hand,
percentage change of land price in commercial areas in 1988 was 90.6%, while
percentage change of CPI in 1988 was only 0.7%. The correlation and gap between CPI
and land prices are made clear by comparing following Figure 4.1. (nominal-base) and
Figure 4.2. (real-base).
Figure 4.1 Year-to-year Percentage Change of Land Price in Kanagawa (nominal)
Figure 4.2 Year-to-year Percentage Change of Land Price in Kanagawa (real)
100%
80%
60%
40%
20%
0%
-20%
-40%
-4-commercial
-4--residential
As the inflation rate was extremely high around 1974, land prices were drastically
declined when measured and illustrated by its real base. Around 1990, land price
jumped while CPI remained very stable, so if we compare two peaks in real level, the
rise in land prices of the Bubble Period turn out to be more outstanding.
4.1.2. Geographical Gaps
Around 1974, increases of land price in undeveloped prefectures were significant. For
example, in Niigata, the mid-north prefecture with low density, increased its real
residential land prices by 50.4% in 1974 compared to previous year, while, Tokyo, the
densest prefecture, raise its real residential land price by 11.7% in the same year.
On the other hand, around 1990, increases of land price in urban prefectures were
significant, while those in undeveloped prefectures were not so high. In Tokyo, the
annual percentage change in real residential land price in 1988 was 67.0% compared
to the previous year, while in Niigata, the value was only 0.7%.
Following figures illustrate above trends graphically. Figure 4.3. shows the percentage
changes of commercial land prices in undeveloped prefectures (Hokkaido, Niigata, and
Kagoshima) and Figure 4.4. shows those in urban prefectures (Tokyo, Aichi, and
Osaka). We can see that peaks in undeveloped areas are significant in 1974 while
those in urban areas are outstanding in 1990.
Figure 4.3. Year-to-year Percentage Change in Land Prices of Undeveloped
Prefectures (commercial, real)
-30%
Figure 4.4. Year-to-year Percentage Change in Land Price of Urban Prefecture
(commercial, real)
--
Tokyo-Commercial
-+--
Aichi-Commercial
-A-
Osaka-Commercial
Also, the graphs of land index that fix land price in 1990 to be 100 indicate that land
prices of undeveloped prefectures (Aomori, Shimane, and Miyazaki) did not soared in
the Bubble Period, so the curves look "Plateau Shape" (Figure 4.5.). But, as land prices
of urban prefectures (Tokyo, Aichi, and Osaka) soared in the Bubble Period, clear
peaks can be seen in that period (Figure 4.6.).
Figure 4.5. Land Price Index in Undeveloped Prefecture (commercial)
140
Price Index-Aomori
--
-U--Price Index-Shimane
120
-A-
Price Index-Miyazaki
~Y
100
80
-
'J-
60
40
20
0
Figure 4.6. Land Price Index in Urban Prefecture (commercial)
140
+4-Price
V O In
1201--Price In
120
+Price
100
80
60
40
20
0 1111. . . ... . . .
ACV
'A"I
A%
QD
'V
Z
Ir
4.1.3. Gaps between Commercial and Residential Properties
By reviewing the Land Price Table, we can find that, in the Bubble Period, the
percentage change in land prices of commercial zone are much higher than those in
land prices of residential zones in almost all prefectures. For example, in Chiba, a part
of Greater Tokyo with relatively high density, the percentage change in commercial
land price was 87.0% in 1989 in real basis while that in residential land price was
60.7%. Also, in Toyama, mid-northern prefecture with lower density, the percentage
change in commercial land price was 10.3% in 1989 in real level while that in
residential land price was 4.7%. Following Figure 4.5. and Figure 4.6. illustrate these
features clearly.
Figure 4.5. Year-to-year Percentage Change of Land Price in Chiba (real)
Figure 4.6. Year-to-year Percentage Change of Land Price in Toyama (real)
15%
10%
5%
0%
-5%
-10%
-15%
-20%
-25% '
4.2 Analyses
These differences can be explained as follows.
4.2.1 Peak of 1974
Around 1974, "Nixon Shock" (1971) and the change to a floating currency exchange
system (1973) led to an excessively strong Japanese yen. After that, the oil crisis
(1973) attacked the Japanese economy from supply side and caused a serious shortage
of materials. Also, a drastic cut of the official discount rate (from 6.25% to 4.25%)
created hyper-inflation and promoted skyrocketing land prices. To make matters worse,
"The Plan for Remodeling the Japanese Archipelago" (1972) advocated by Prime
Minister Kakuei Tanaka to improve the wealth gap between urban and undeveloped
areas induced speculative investment to undeveloped areas.
The radical rise in land price was soon restrained in 1975 by the monetary policy of
raising the official discount rate from 4.25% to 9.00% during only about one year and
the scandal and downfall of Tanaka (Dec.1974). The inflation was suddenly suppressed
and the land price calmed down in the same way as consumer prices.
As
described,
in this period,
the
fundamentals
dramatically
changed
and
hyper-inflation pushed up the land price. As fundamentals can explain the rise in land
price except for the radical rise in that of undeveloped prefectures, it can be said that
the phenomenon in this period was the rational Bubble.
4.2.2. Peak of 1990
The rise in land price in the early 1990s, the Bubble Period, can be also considered to
have been triggered by a steep decline in interest rates and a strong Japanese yen, the
same as same those for 1974's rise.
In September 1985, the Plaza Accord was held to remedy financial deficits in the
United States by cutting the other developed countries' interest rates. In Japan,
within only one year after that, the official discount rate was pushed down from 5.25%
to 2.75%, and as a result, the Japanese yen grew from $1=252 yen to $1=153 yen. The
internationalization and strength of the Japanese yen made both domestic and foreign
investors expect that Tokyo must be a future international financial center and, thus,
made speculative investments into especially commercial properties in the Greater
Tokyo, Nagoya, and Osaka area. This fact explains the trend that, in the Bubble
Period, commercial land price was much dramatically soared than residential land
especially in urban prefectures.
Other than economic factors as described above, financial factors spurred the extreme
rise of land price much more.
Though Japanese companies had usually capitalized their funds from bank loans until
that period, the continuous rise in the stock market and financial deregulation in the
mid-1980's made it possible for these Japanese companies to raise cheap capital from
equity markets. This condition forced Japanese banks to change their main customer
from major companies to other customers. In addition, in June 1988, the decision of
Bank for International Settlements (BIS) to force international bankers to ensure risk
asset ratio more than 8% made Japanese banks rush to increase their loans. In this
situation, Japanese banks chose as their new customers developers and investors who
mainly invest stocks and real estate. Because of these changes in bank lending stances,
the amount of investment for real estate especially in urban areas soared as described
in the following graph (Figure 4.5).
Figure 4.5 Real Estate Investment Index (1970=100)
1400
1200
-*-
Tokyo Central 3 Wards
---
Osaka City
-*r
Nagoya City
*
Nationwide
1000
800
600
400
200
0A
'gl 'C 'U '0''
AC
'D
Source: MTB-IKOMA Real Estate Investment Index
The magnitude of increase in land price was very surprising. For example, the
percentage change in Koji Chika in commercial land price was 376% in Tokyo
prefecture, 481% in Aichi prefecture, 576% in Osaka prefecture.
This unprecedented rise in land price, especially in urban areas caused drastic
reactionary falls because of the monetary policy to raise the official interest rate from
2.75% to 6.25% in about three and a half years, immediate financial re-regulation to
let banks strictly restrict lending to real estate investors, and the raising of the bad
loan problems among Japanese banks caused by hasty lending to speculative real
estate investors. The land prices in commercial areas have fallen almost the same
level or below those in 1985 and the prices are still declining even in 2000.
Unlike the soaring of land prices around 1974, the case of 1990 cannot be explained by
the change of fundamentals; it must be defined as the irrational Bubble.
Chapter 5
Results 2 - From Cross-Section Analyses
5.1.
1975-1985 (Pre-Bubble Period)
For the Pre-Bubble Period, I ran cross-section regression analyses to try to find what
factors influenced the movements in land price in each prefecture using the data set
shown in Appendix 2.
Since correlations among independent variables, population growth, job growth, and
stock growth are too strong as shown in Table 5.1., I tried to combine density and one
of these three growth rates and ran regression analyses by two independent variables.
If I can find significant correlations by this method, it can be considered that land
prices were influenced by all these independent variables.
Table 5.1.
Density
Density
Pop growth
Job growth
Stock growth
1
0.034709
0.310236
0.121182
Population
growth Job growth
1
0.848728
0.878858
1
0.834814
Stock
growth
1
The result is that none of those growth rates correlated to the movements of land
prices. When I ran regression analysis by setting density as single independent
variable, the result indicated relatively high correlation with the movements in land
prices by R square scoring 0.58 for commercial land price and 0.40 for residential land
price.
The result shows that, against the economics theory, in this period in Japan,
population growth, job growth, and stock growth did not influence the variance in land
price in each prefecture.
I considered two reasons for this result.
(1) In this period, gaps of percentage change among prefectures in population growth, job
growth, and stock growth are almost the least among three periods. Standard
deviations in each independent variable in each period are indicated in Figure 5.2..
Table 5.2.
Standard Deviations in Independent Variables
Annual Population
Growth
Annual Job
Growth
Annual Stock
Growth
Pre-Bubble Period
(76-85)
0.00445
0.00633
0.00522
Bubble Period
(86-91)
0.03569
0.04470
0.03846
Post-Bubble Period (92-99)
0.00894
0.00379
0.00597
From reviewing the data set, it can be recognized that the growth rates in urban
prefectures such as Greater Tokyo (Tokyo, Kanagawa, Chiba, Saitama), Aichi, and
Osaka area (Osaka, Hyogo, Kyoto) are outstanding in this period. However, it can be
seen that the magnitude of these gaps between urban and other prefectures were not
so significant that annual percentage change of land price could not be determined or
influenced by these three independent variables.
(2) It can also be thought that in this period, there was still much available vacant land
within and surrounding urban areas enough to absorb people and jobs from other
areas. So the inflow of people and jobs to such an extent into urban areas were not
reflected in the land prices, but only made expand city borders in the urban
prefectures. The high growth rates in surrounding Greater Tokyo area such as Tochigi
and Ibaragi and surrounding Osaka area such as Shiga and Nara also indicate the
efficiency of this hypothesis.
5.2.
1986-1991 (Bubble Period)
Using the data set shown in Appendix 3, I tried the same analysis as that of the
Pre-Bubble Period. Since correlation among independent variables in three growth
rates are too strong as in the case of the Pre-Bubble Period, I tried to combine density
and one of these three growth rates and ran regression analyses by two independent
variables. The results were that independent variables were well fitted to average
percent change of land prices. Following are the equations that I could obtained from
these regression analyses.
ZIP commercial = 3.11E-0.5ZD + 1.10POP+ 0.059
R2= 0.67
ZP residential = 2.86E-0.5ZD + 0.95ZPOP + 0.036
R2= 0.69
where, P = percentage change of annual land price, D = density, POP = percentage
change of annual population growth:
In the same way, equations when the independent variables are density and job
growth, and density and stock growth, are following
ZP commercial = 2.46E-0.5ZD + 0.86ZJOB + 0.044
R2= 0.62
ZP residential = 2.34E-0.5ZD + 0.73ZJOB + 0.023
R2= 0.63
where JOB = percentage change of annual job growth.
ZP commercial = 3.3E-0.5ZID + 0.87ZSTOCK - 0.022
R2=
0.59
ZP residential = 3.03E-0.5ZD + 0.76ZSTOCK + 0.035
R2=
0.61
where STOCK = percentage change of annual stock growth.
In the Bubble Period, the Japanese economy was in good condition especially in
service businesses such as finance and real estate because of the background that I
explained in Chapter 4. Almost all these companies located their headquarters in
urban areas especially Tokyo and Osaka, and employees concentrated on these areas.
Also, foreign firms, especially in financial business, launched in Tokyo to expand or
start their business in the expected future global financial center. This situation
created many jobs in the urban areas and, thus, people outside those areas came to get
good opportunities and jobs. Actually, the growth rates gaps between eight urban
prefectures and other prefectures comparing Pre-Bubble Period, Bubble Period, and
Post-Bubble Period are almost the largest in the Bubble Period as shown in Table 5.3..
Table 5.3. Gaps in Growth Rates between Urban and Other Prefectures
Pre-Bubble Period (1975-1985)
Population
Growth
Job Growth Stock Growth
0.93%
0.58%
0.35%
Urban Prefectures
Others Prefectures
Gap
1.41%
0.62%
0.79%
2.14%
1.60%
0.54%
Bubble Period (1986-1991)
Population
Growth
Job
GrowthStock
Growth
Urban Prefectures
Others Prefectures
0.93%
0.22%
1.68%
0.62%
2.48%
1.84%
Gap
0.71%
1.06%
0.64%
Post-Bubble Period (1992-1999)
Population
Growth
Urban Prefectures
Others Prefectures
Gap
Job
1.25%
0.36%
0.89%
GrowthStock
0.30%
0.37%
-0.07%
Growth
2.43%
2.05%
0.38%
* Numbers are averages of each categorized prefecture's growth rates.
The gaps of these independent variables among prefectures in the Bubble Period
became so significant that the land prices in urban prefectures were influenced to soar
by these fundamentals' changes.
On the other hand, prefectures without such big cities could not attract financial
businesses and were obliged to reduce their population and job supplies. As a result,
land prices did not rise as much as those of urban prefectures.
However, relatively low R square scores indicate that independent variables cannot be
described as determinants of land prices. As described in the last chapter, financial
factors strongly influenced the movements in land price.
In sum, fundamentals such as density, population, job, and stock growth influenced,
but did not determine the land price in the Bubble Period.
5.3.
1992-1999 (Post-Bubble Period)
For the Post-Bubble Period, I tried the same analysis as these in previous two periods
using data set shown in Appendix 4. That is, I tried to combine density and one of these
three growth rates and ran regression analyses by two independent variables.
The results were that density and three growth rates turn out to have negative
correlation to land prices and high t ratios indicate strong significance. It can be
explained that the more the population, job and stock grew, and the more densely it is,
the more steeply the land price declined in the Post-Bubble Period. The results
indicate that, in this period, land price moved quite against the economics theory.
To find the real determinant, I picked the data of percentage changes in land price of
the Bubble Period as the independent variable because I found in the data set that
urban prefectures' decreases in land prices were significant in the Post-Bubble Period.
I thought it could be explained from the concept of cyclical movement of land price.
I
reran cross-section regression analyses setting annual average percentage changes in
land prices in 1992-1999 as the dependent variable and those in land prices during
1986-1991 as the independent variable
The results were that both commercial and residential land price indicated significant
negative correlations to the percentage change of land prices in the Bubble Period. For
example, R square of commercial land price in Post-Bubble period scored to 0.90 and
that of residential scored 0.91.
As explained Chapter 3, it can be said that two big factors, drastic monetary policy to
suddenly increase the interest rate and re-regulation to restrict real estate investment,
triggered the decline in land prices. In addition, several shocks, such as the breaking
of banks' bad loan problems and the pulling out of foreign companies, promoted the
falling tendency of land price still more. As the rises in the Bubble Period were
extremely high in urban areas, the rebounds suffered the steep drops in land price in
the same areas.
5.4.
Limit of the Analyses
The methods that I utilized in this chapter are statistically reliable in that they apply
objective data (Koji Chika and four independent variables) into homogeneous
geographical units (prefectures). On the other hand, the stiff methods might have
some notable disadvantages such as the following
5.4.1. Prefectural Internal Problem
As introduced in Chapter 2, each prefecture has its indigenous characteristics. Among
these, demographical factors influence much in this analysis. For example, though
Hokkaido is least dense prefecture amounting only 68 persons per square kilometer,
Sapporo, the fifth most populated city (1,809 thousands people) in Japan is located in
this prefecture. It goes without saying that movements of land prices are quite
different between Sapporo and a village in a great plain in Hokkaido. Each prefecture
has such population gaps within it and their magnitudes are quite different depending
on prefecture. This factor makes it difficult to compare land prices on a prefectural
basis.
5.4.2 Gaps in Observation Points
Among prefectures, numerical gaps of observation points in Koji Chika are very
significant. For example, in 1999, there were 2,906 observation points in Tokyo, but
only 152 points in Tottori. Also, the revisions in number of observation points have
been arbitrarily implemented year by year. In addition, in the earlier period that Koji
Chika was issued, observation points were very few compared to these of the current
period. For example, Akita had only 20 observation points for commercial areas in
1975.
Numerical gaps among prefectures, arbitrary revision, and lack of samples in the early
period might cause statistical inefficiency in regression analyses outputs.
Chapter 6
Conclusion
6.1. Findings from Land Price Table
"
After World War II, Japan experienced two significant peaks in which land price
jumped and then sharply declined within quite a short period, around 1974 and
around 1990. For each period, extremely law interest rate and expected growth
rent pushed up the land price. However, as the peak in 1974 was correlated with
overall CPIs, the significance in boom and bust of land prices was much declined
on a real level. On the other hand, the peak in 1990 was a kind of anomaly in that
CPI was quite stable but speculative objects such as real estate and stocks raised
their prices. To the extent that fundamentals can explain the movements of land
prices, the peak in 1974 can be called to be the rational Bubble, but the peak in
1990 as the irrational Bubble.
"
In the 1974 peak, the rises of land prices in undeveloped prefectures were
significant but those of urban prefectures were not. In contrast, in the 1990 peak,
rises in land prices in urban prefectures were much larger than those in
undeveloped prefectures. In the 1974 peak, land prices were derived mainly by the
policy to adjust the economic gaps between urban areas and other areas. On the
other hand, in the 1990 peak, growth expectation in the urban office market and
the changes of banks stance to focus on lending real estate investors induced
speculation into urban prefectures especially in commercial properties.
6.2. Findings from Cross Section Regression Analyses
"
In the Pre-Bubble Period, land prices were influenced only by density among
fundamentals. Population growth, job growth, and stock growth, all of which are
thought to be the determinants in economics, did not influence the movements in
land prices on the prefectural level. The reason for the unexpected result can be
explained in the following way. The gaps among these growth rates were not so
significant that the difference could not influence the movements in land prices.
Also, urban and surrounding prefectures had much vacant land enough to absorb
the inflows of people and jobs in that period.
"
In the Bubble Period, contrary to the notion that the Bubble was caused only by
speculation, fundamentals such as density, population growth, job growth, and
stock growth strongly influenced the movements in land prices. Stimulated by
good economic conditions, people flew into urban prefectures to get good jobs and,
thus, job and housing stock grew. These changes in fundamentals pushed up the
soaring of the urban land prices.
"
In the Post-Bubble period, though growth rates were still increasing in urban
prefectures, the collapse in land prices in these areas was the most significant
among all the prefectures. It can be said that shocks such as breakout of banks'
bad loan problems, pulling out of foreign capital from real estate investment, and
sudden changes in monetary policy and re-regulation caused falling trend in land
price and it suffered the areas where land prices mostly soared in the Bubble
Period.
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Appendix 2
DATA SET (1975-1985)
Hokkaido
Aomori
Iwate
Miyagi
Akita
Yamagata
Fukushima
[baragi
Tochigi
Gunma
Saitama
Chiba
Tokyo
Kanagawa
Niigata
Toyama
Ishikawa
Fukui
Yamanashi
Nagano
Gifu
Shizuoka
Aichi
Mie
Shiga
Kyoto
Osaka
Hyogo
Nara
Wakayama
Tottori
Shimane
Okayama
Hiroshima
Yamaguchi
Tokushima
Kagawa
Ehime
Kochi
Fukuoka
Saga
Nagasaki
Kumamoto
Oita
Miyazaki
Kagoshima
Okinawa
Commercial Residential
Land Price Land Price
Growth
Growth
2.85%
5.08%
2.82%
4.60%
4.60%
2.70%
4.63%
3.30%
3.07%
5.17%
2.40%
3.76%
5.19%
3.42%
2.72%
4.79%
5.20%
2.61%
2.09%
4.82%
3.32%
5.86%
2.89%
5.93%
6.62%
6.05%
3.52%
6.29%
4.52%
2.71%
4.98%
3.26%
4.97%
3.31%
3.22%
5.02%
2.88%
5.30%
2.44%
4.83%
4.90%
3.59%
3.14%
5.96%
3.35%
5.82%
5.11%
3.04%
4.96%
3.41%
5.10%
3.73%
4.75%
5.86%
4.27%
6.07%
5.25%
2.70%
5.32%
3.24%
5.03%
2.62%
2.78%
4.70%
2.76%
5.03%
5.13%
3.21%
5.05%
2.67%
4.64%
3.41%
4.64%
3.62%
5.02%
3.01%
5.36%
3.45%
5.70%
3.81%
5.51%
3.51%
4.99%
3.10%
5.01%
3.46%
3.59%
5.39%
2.24%
4.62%
4.05%
2.86%
3.21%
5.13%
Density
66
157
93
284
108
134
147
415
278
289
1407
902
5335
2414
194
258
266
189
180
153
184
441
1199
291
266
545
4469
611
322
171
171
117
262
322
259
198
530
264
116
909
353
388
240
193
147
193
486
Population
Growth
0.6%
0.4%
0.3%
1.0%
0.2%
0.3%
0.5%
1.4%
0.8%
0.8%
1.8%
2.0%
0.1%
1.3%
0.3%
0.4%
0.7%
0.5%
0.5%
0.5%
0.7%
0.7%
0.7%
0.6%
1.4%
0.6%
0.4%
0.5%
1.8%
0.1%
0.5%
0.3%
0.5%
0.6%
0.3%
0.3%
0.5%
0.3%
0.3%
0.9%
0.4%
0.1%
0.6%
0.4%
0.7%
0.5%
1.0%
Job
Growth
0.6%
0.4%
0.6%
1.1%
0.0%
0.4%
0.4%
1.3%
1.2%
0.8%
2.7%
2.3%
1.1%
1.9%
0.1%
0.3%
0.7%
0.6%
0.9%
0.7%
0.7%
1.1%
1.3%
0.7%
1.2%
0.6%
0.8%
0.5%
1.9%
0.1%
0.4%
0.2%
0.3%
0.6%
0.0%
0.1%
0.4%
0.3%
0.0%
0.7%
0.5%
0.3%
0.8%
0.3%
0.7%
0.4%
2.5%
Stock
Growth
2.0%
1.6%
1.3%
2.1%
1.0%
0.9%
1.4%
2.7%
1.7%
1.9%
2.8%
3.1%
1.4%
2.4%
1.2%
0.9%
1.9%
1.1%
1.9%
1.5%
1.6%
1.7%
1.9%
1.6%
2.2%
2.5%
1.5%
1.6%
2.7%
1.2%
1.5%
0.9%
1.5%
1.6%
1.3%
1.5%
1.5%
1.5%
1.3%
2.1%
1.2%
1.4%
1.7%
1.5%
1.7%
1.7%
2.6%
Appendix 3
DATA SET (1986-1991)
Commercial Residential
Land Price Land Price
Growth
Hokkaido
Density
Population
Growth
Job
Growth
Stock
Growth
Growth
9.65%
5.00%
68
0.8%
2.0%
1.02%
2.00%
12.98%
1.82%
2.10%
-0.02%
1.12%
8.63%
0.55%
0.63%
156
93
305
107
135
-0.5%
-0.2%
0.8%
-0.4%
0.0%
0.2%
0.7%
1.4%
-0.1%
0.1%
1.5%
1.4%
2.8%
1.0%
0.9%
7.20%
5.97%
4.30%
6.55%
152
459
0.3%
1.1%
0.4%
1.2%
1.8%
2.7%
8.80%
12.33%
20.78%
28.70%
22.12%
21.83%
9.37%
10.50%
15.62%
21.68%
19.57%
16.02%
298
306
1628
1046
5428
2414
0.9%
0.6%
2.0%
1.8%
0.2%
1.7%
1.6%
1.1%
2.9%
2.4%
1.5%
2.1%
2.7%
2.5%
3.7%
3.2%
1.9%
3.3%
4.05%
3.88%
197
0.0%
0.4%
1.4%
Nagano
Gifu
6.08%
8.30%
6.57%
12.63%
6.78%
11.45%
3.20%
5.53%
5.47%
11.63%
4.20%
8.33%
264
277
196
189
158
194
0.1%
0.3%
0.2%
0.7%
0.3%
0.5%
0.5%
0.8%
0.8%
1.0%
0.4%
1.2%
1.7%
2.0%
1.5%
2.7%
1.8%
1.8%
Shizuoka
13.18%
10.15%
467
0.7%
1.1%
2.1%
Aichi
14.32%
8.78%
18.63%
22.22%
24.33%
21.33%
17.55%
12.37%
5.40%
1.78%
12.02%
10.57%
7.00%
13.45%
19.90%
20.73%
16.33%
15.50%
8.53%
2.87%
1.07%
8.33%
1281
307
297
564
4611
638
365
176
176
117
271
0.9%
0.6%
1.4%
0.2%
0.2%
0.6%
1.3%
-0.2%
0.0%
-0.3%
0.2%
2.3%
1.0%
2.2%
0.3%
1.2%
0.8%
1.6%
0.6%
0.2%
-0.4%
0.4%
2.4%
2.0%
2.5%
1.8%
1.7%
1.8%
3.0%
1.2%
1.3%
1.1%
1.9%
11.50%
3.70%
3.95%
6.83%
2.50%
2.62%
335
260
201
0.3%
-0.3%
-0.1%
0.6%
0.2%
0.0%
2.1%
1.3%
1.7%
8.82%
5.62%
2.33%
7.03%
6.40%
6.35%
6.60%
5.10%
6.55%
3.58%
-0.42%
4.22%
1.87%
1.53%
2.83%
2.18%
546
268
117
961
360
385
249
196
0.1%
0.1%
-0.3%
0.5%
0.0%
-0.4%
0.1%
-0.2%
0.5%
0.0%
0.0%
1.4%
0.5%
0.2%
0.3%
0.2%
1.6%
1.8%
1.5%
2.2%
1.6%
1.2%
2.0%
1.7%
3.02%
6.60%
0.95%
2.83%
152
197
-0.1%
-0.2%
0.2%
-0.1%
1.5%
1.5%
6.13%
4.45%
532
1.0%
1.5%
3.1%
Aomori
Iwate
Miyagi
Akita
Yamagata
Fukushima
lbaragi
Tochigi
Gunma
Saitama
Chiba
Tokyo
Kanagawa
Niigata
Toyama
Ishikawa
Fukui
Yamanashi
Mie
Shiga
Kyoto
Osaka
Hyogo
Nara
Wakayama
Tottori
Shimane
Okayama
Hiroshima
Yamaguchi
Tokushima
Kagawa
Ehime
Kochi
Fukuoka
Saga
Nagasaki
Kumamoto
Oita
Miyazaki
Kagoshima
Okinawa
-0.1%
Appendix 4
DATA SET (1992-1999)
Commercial
Land Price
Growth
I
Hokkaido
Aomori
Iwate
Miyagi
Akita
Yamagata
Fukushima
lbaragi
Tochigi
Gunma
Saitama
Chiba
Tokyo
Kanagawa
Niigata
Toyama
Ishikawa
Fukui
Yamanashi
Nagano
Gifu
Shizuoka
Aichi
Mie
Shiga
Kyoto
Osaka
Hyogo
Nara
Wakayama
Tottori
Shimane
Okayama
Hiroshima
Yamaguchi
Tokushima
Kagawa
Ehime
Kochi
Fukuoka
Saga
Nagasaki
Kumamoto
Oita
Miyazaki
Kagoshima
Okinawa
Q9-QQ
-6.54%
-3.00%
-1.05%
-6.78%
-1.03%
-1.29%
-4.10%
-4.90%
-3.68%
-5.64%
-11.33%
-15.10%
-14.94%
-10.55%
-2.45%
-4.19%
-5.03%
-3.49%
-6.59%
-2.24%
-6.94%
-8.63%
-10.14%
-3.95%
-8.89%
-13.68%
-16.28%
-10.75%
-9.54%
-8.93%
-3.31%
0.03%
-6.59%
-6.41%
-0.04%
-4.23%
-3.95%
-5.10%
-2.54%
-5.15%
-1.88%
-2.75%
-4.21%
-2.04%
-2.09%
-4.35%
-5.13%
Residential Commercial Residential
Land Price Land Price Land Price
Growth
Growth
Growth
Q92-QQ
-1.34%
0.74%
1.14%
-1.76%
1.70%
1.54%
0.35%
-2.16%
-0.46%
-1.16%
-5.75%
-8.64%
-7.75%
-4.21%
0.81%
0.16%
-0.29%
0.44%
-2.04%
0.89%
-1.65%
-2.56%
-4.08%
-0.73%
-4.00%
-7.58%
-7.93%
-5.93%
-5.79%
-3.45%
1.70%
0.75%
0.24%
-2.00%
1.39%
1.75%
-0.73%
0.50%
0.51%
-0.04%
1.31%
2.05%
0.75%
1.24%
0.93%
0.26%
0.43%
86-91
86-91
9.65%
1.02%
2.00%
12.98%
1.82%
2.10%
7.20%
5.97%
8.80%
12.33%
20.78%
28.70%
22.12%
21.83%
4.05%
6.08%
8.30%
6.57%
12.63%
6.78%
11.45%
13.18%
14.32%
8.78%
18.63%
22.22%
24.33%
21.33%
17.55%
12.37%
5.40%
1.78%
12.02%
11.50%
3.70%
3.95%
8.82%
5.62%
2.33%
7.03%
6.40%
6.35%
6.60%
5.10%
3.02%
6.60%
6.13%
86-91
86-91
5.00%
-0.02%
1.12%
8.63%
0.55%
0.63%
4.30%
6.55%
9.37%
10.50%
15.62%
21.68%
19.57%
16.02%
3.88%
3.20%
5.53%
5.47%
11.63%
4.20%
8.33%
10.15%
10.57%
7.00%
13.45%
19.90%
20.73%
16.33%
15.50%
8.53%
2.87%
1.07%
8.33%
6.83%
2.50%
2.62%
6.55%
3.58%
-0.42%
4.22%
1.87%
1.53%
2.83%
2.18%
0.95%
2.83%
4.45%
Density
92-99
92-99
68
154
93
320
104
135
155
485
310
315
1782
1126
5402
2416
198
264
282
197
197
162
198
483
1337
319
321
569
4639
649
387
175
175
115
274
340
254
200
547
265
115
993
362
377
251
194
152
195
563
Population
Growth
Job
Growth
Stock
Growth
92-99
92-99
92-99
92-99
92-99
0.1%
-0.5%
-0.2%
1.4%
-0.7%
-0.1%
0.5%
1.7%
1.3%
0.9%
3.0%
2.4%
0.0%
2.2%
0.1%
0.1%
0.5%
0.3%
1.2%
0.7%
0.7%
0.9%
1.3%
1.1%
2.4%
0.3%
0.3%
0.6%
1.8%
-0.2%
0.0%
-0.6%
0.4%
0.4%
-0.6%
-0.1%
0.1%
-0.3%
-0.6%
1.0%
0.1%
-0.7%
0.3%
-0.3%
0.0%
-0.3%
1.7%
0.4%
0.6%
0.4%
0.6%
-0.2%
0.1%
-0.1%
1.1%
-0.6%
0.3%
0.7%
0.7%
0.0%
-0.1%
0.3%
0.4%
0.4%
0.7%
0.7%
0.7%
0.3%
0.6%
0.3%
0.5%
-0.7%
0.4%
0.2%
0.2%
1.0%
0.1%
0.2%
-0.1%
0.7%
0.4%
-0.2%
0.3%
0.5%
0.3%
0.4%
0.3%
0.8%
0.6%
0.4%
0.5%
0.6%
0.1%
1.2%
1.8%
1.5%
1.9%
2.9%
1.6%
1.9%
2.0%
2.9%
2.6%
2.4%
2.9%
3.3%
1.8%
2.7%
1.9%
2.1%
2.3%
2.0%
3.0%
2.8%
2.3%
2.5%
2.6%
2.8%
3.6%
1.9%
2.1%
2.2%
2.8%
1.6%
1.5%
1.8%
2.1%
2.0%
1.5%
1.4%
2.3%
1.3%
0.8%
2.2%
2.2%
1.4%
1.7%
1.8%
1.8%
1.0%
2.3%
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