機会費用に着目した持ち家帰属家賃の推計

Diewert & Shimizu
住宅土地経済研究会
機会費用に着目した持ち家帰属家賃の推計
-東京都のケース東京都 ケ
July 23,
23 2012
清水千弘
(Reitaku University & University of British Columbia).
W.Erwin Diewert
(University of British Columbia & New South Wales University).
2012/07/23
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page. 1
Diewert & Shimizu
Ⅰ. Housing
g prices
p
and OOH rent for CPI.
and Watanabe(2010), Diewert and Nakamura 3
2.8
2011, Goodhart 2001)
2.6
2012/07/23
2.2
Single family house price
Condominium pprice
2
1.8
16
1.6
1.4CPI OOH Rent
1.2
1
0.8
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19986
19987
19988
19989
19990
19991
19992
19993
19994
19995
19996
19997
19998
19999
20000
20001
20002
20003
20004
20005
20006
20007
20008
20009
20010
2. Imputed Rent for OOH also
represents a weight of
approximately 10% in the SNA
2009= 10.1%, 2010 =9.85%
In
ndex 1986=11.0
1. Housing rents account for more
than one fourth
f
off personal
spending.
2.4
100
80
60
40
20
0
-20
-40
-60
-80
-100
page. 2
Annual cchange rate: %
The most important link between asset prices
and goods & services prices is the one
through
h
h hhousing
i rents (Shimizu, Nishimura
Diewert & Shimizu
日本の問題
• 荒井 晴仁(2005),『国民経済計算における持ち家の帰属家賃推
計に
計について』
て』 ESRI Discussion Paper Series No.141国民経済計
国民経済計
算では，支出系列である家計最終消費の内訳として「持ち家
の帰属家賃」（表章項目としては「帰属家賃」） : 平成12 年
には49.9 兆円。
• 推計方法「総家賃＝総床面積（m2）×家賃単価（円／m2）」
• 「総床面積」と「家賃単価」は「住宅・土地統計調査」(総務
省）により ンチ
省）によりベンチマークを得たうえで，各四半期の推計では
クを得たうえで，各四半期の推計では
，「総床面積」は「建設着工統計」と「建築物滅失統計」，
また，「家賃単価」は「消費者物価指数」を用いて補間，ま
たは補外推計を行っている。
補 推計 行
2012/07/23
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page. 3
Diewert & Shimizu
• 『県民経済計算支出系列』県民所得（実額）表「企業所得
（法人企業 分配所得受払後）
（法人企業の分配所得受払後）」の内訳として「持ち家」
内訳と
「持ち家
が掲載。平成12 年度は21.1 兆円（全県計）。
• 持ち家の「企業所得」とは持ち家の所有者が不動産賃貸業
を営んでいると擬制した場合の不動産業所得を言い，収入
である持ち家の帰属家賃から 諸経費である中間投入（修
である持ち家の帰属家賃から，諸経費である中間投入（修
繕等），固定資本減耗，純間接税（固定資産税等），住宅
ローン支払利子，支払地代を差し引いたもの。
• これに対応する国民経済計算の計数は，「国民所得・国民
可処分所得の分配」の表に「企業所得（法人企業の分配所
得受 後）
得受払後）」の内訳として「持ち家」が掲載されており，
内
「持ち家
掲載さ
平成12 年度には24.2 兆円である。
2012/07/23
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page. 4
Diewert & Shimizu
Ⅱ. How should we estimate OOH Imputed
p
rent?.
The User Cost Approach
The Equivalent Rent Approach
t
t 1
t  m  v 1
y
y
y
v 1
m 1
Vvt  v t 



1 r
(1  r t )(1  r t 1 )
 ti tmv 1 (1  r i )
Ovt
Ovt 11
Omt m1 v 1


   t  mv 1
t
t
t 1
1  r (1  r )(1  r )
 i t
(1  r i )
•
•
•
•
2012/07/23
Vvt : the initial asset value for the period t.
y vt : the income corresponding to Vvt .
O vt
: the operating income to be paid at the end of the period t.
rt : the expected nominal discount (interest) rate for period t.
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page. 5
Diewert & Shimizu
Estimation Problems in the User Cost Approach.
Approach
Basic User Cost: Asset Value
t 1
v 1
u  r V  O  (V
t
v
t
t
v
t
v
V )
t
v
Interest Rate Expense Asset Value
Increase
• Estimation Method:
•
The estimation method is complicated.
• Negative problem:
•
The value becoming negative during periods of dramatic price increases.
• Volatility problem:
•
2012/07/23
Housing price volatility becoming greater than what it is perceived by
market
k t players.
l
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page. 6
Diewert & Shimizu
Estimation Problems in the Equivalent Rent Approach.
• 11. Market
M k t structure
t t
disparities
di
iti between
b t
the
th owner-occupied
i d
housing and the rental housing.
•
•
•
•
•
The average floor space (size) of housing in Tokyo: Housing and Land Survey
2008.
Single-family houses:
110.71 square meters for owner-occupied housing and 79.36 square meters for
rental housing
Condominiums:
65.84 square meters for owner-occupied housing and 36.06 square meters for
rental housing
• 2. Problem in Rent Survey.
•
The rent surveyed via consumer price statistics is the household's paying rent, there
i a strong
is
t
possibility
ibilit that
th t there
th is
i a major
j discrepancy
di
with
ith the
th rentt determined
d t
i d by
b
the current market. Paying rent not opportunity cost.
•
Shimizu,C, K.G.Nishimura and T.Watanabe(2010), “Residential Rents and Price Rigidity: Micro
St t
Structure
and
dM
Macro Consequences,”Journal
C
”J
l off Japanese
J
and
d IInternational
t
ti
l Economy,Vol.24,
E
V l 24
pp282-299.
2012/07/23
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page. 7
1.00
2012/07/23
Market Rent
QT2006//1
QT2005//1
QT2004//1
QT2003//1
QT2002//1
QT2001//1
QT2000//1
QT1999//1
QT1998//1
QT1997//1
QT1996//1
QT1995//1
QT1994//1
QT1993//1
QT1992//1
QT1991//1
QT1990//1
QT1989//1
QT1988//1
QT1987//1
QT1986//1
Diewert & Shimizu
Market Rent vs. CPI Rent
1.40
1.35
1.30
1.25
1.20
1 15
1.15
1.10
1.05
CPI Rent
page.
8
Diewert & Shimizu
Stickiness of housing rent:
Di
Discrepancy
between
b t
H
Hedonic
d i and
d CPI rents
t may b
be
created by The Land Lease and House Lease Law.
•
CPI rents covers both new and rollover
contracts, while the Recruit data include
only new ones.
•
It is difficult for a landlord to raise the rent
level: the court would not allow rent hikes
beyond verifiable cost increases (such as
those
h
due
d to a change
h
in
i property taxes)) or
beyond an average of neighborhood rent
increases.
118
Thus rental prices adopted in rollover
contracts with existing renters could
substantially
subs
y ddiffer
e from
o those
ose adopted
dop ed in
new contracts with new renters.
104
•
116
New contracts
114
Rollover contracts
112
110
108
106
102
100
98
96
page.
Year 9
Year 8
Year 7
Year 6
Year 5
Year 4
Year 3
2012/07/23
Year 2
“Marking to market” occurs only when one
tenant leaves
l
andd another
h one arrives.
i
Year 1
•
9
Diewert & Shimizu
Panel data for housing rents
35
10 thoussand yen peer month
30
25
Unit 11
20
Unit 219
Unit 220
Unit 245
Unit 298
Unit 308
Unit 339
15
10
5
0
2
26-Nov-07
1
1-Mar-05
5
5-Jun-02
9
9-Sep-99
1
13-Dec-96
1
19-Mar-94
2
23-Jun-91
2
26-Sep-88
2012/07/23
Duration time and
Rent Change
10
10
page.
Diewert & Shimizu
State-Dependent or Time-Dependent Pricing:
Caballero-Engel’s definition of price flexibility
 log Rit*  t  it
Caballero-Engel(1993)
g (
)
:Adjustment Hazard
X it  log Rit 1  log Rit*
 ( x)  Pr(Rit  0 | X it  x)
 log Rt
t  0
t
lim

 ( x)h( x)dx
Caballero-Engel’s
Intensive margin
measure off price
i flexibility
fl ibilit
( x) 

 x '( x)h( x)dx
Extensive margin
C b ll
Caballero-Engel(2007)
E
l(2007)
Pr(Rit  0 | I itN  1,
1 X it  x) Pr( I itN  1| X it  x)
 Pr(Rit  0 | I itR  1, X it  x) Pr( I itR  1| X it  x)
2012/07/23
11
page.
Diewert & Shimizu
Frequency of Rent Adjustments in March 2008
T bl 3 R t G
Table3.Rent
Growth
th iin March
M h 2008
Genesove (2003) reported that the proportion of cases in which the housing rent
remained unchanged at a rollover contract was 36% in the US.
2012/07/23
page. 12
Diewert & Shimizu
Caballero-Engel’s
Caballero
Engel s (2007) definition of price flexibility
F
=
Measure of price flexibility
in terms of the impulse
response function
 log Rt
lim

t  0
t
A
E
+
Intensive margin
 ( x)h( x)dx
Extensive margin

 x '( x)h( x)dx
0.0097 = 0.0084 + 0.0013
Shimizu,C,
Shimizu
C K.G.Nishimura
K G Nishimura and T.Watanabe(2010),
T Watanabe(2010) “Residential
Residential Rents and Price Rigidity: Micro Structure and
Macro Consequences,”Journal of Japanese and International Economy,Vol.24, pp282-299.
2012/07/23
page.
13
Diewert & Shimizu
Ⅲ.. OOH Opportunity Cost Approach.
• Diewert(2006):
• “Perhaps the correct opportunity cost of housing for an owner
occupier is not his or her internal user cost but the
maximum of the internal user cost, which is the
financial opportunity cost of housing, and what the property
could
ld rentt for
f on the
th rental
t l market.
k t After
Aft all,
ll the
th conceptt off
opportunity cost is supposed to represent the maximum
sacrifice that one makes in order to consume or use
some object.”
• OOH Opportunity Cost Approach:
•
2012/07/23
(Financial) User Cost > or < Equivalent rent
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Diewert & Shimizu
Diewert’s Financial User Cost.
Generalized Case: Type B. Homeowner do not fully own
their homes, but have positive home equity:
Asset Value
u
t
typeB
Expense
 r D  r (V  D )  O  (V
t
D
t
t
t
t
t
t 1
 V ).
t
Interest
Interest
Debt
Expected Capital Gain
Rate for Rate for
Mortgage Investment
In estment
Type A. Homeowner owns their home (full equity):
ut
typeA
 r tV t  O t  (V t 1  V t ).
)
Type C. Homeowner have zero home equity:
ut
2012/07/23
typeC
 rDt D r  O t  (V t 1  V t ).
)
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Diewert & Shimizu
Diewert'ss OOH Opportunity Cost Approach.
Diewert
• The term opportunity cost refers to the cost of the best alternative
that must be fforgone
g
in takingg the option
p
chosen.
• Option0:Homeowner continue to live the home.
• →Opportunity Cost associated with Option0.
Option0
• Option1: Selling
S lli att the
th beginning
b i i off period
i d t andd bbuy bback
k att the
th
t+1 .→ User Cost.
• Option2
O i 2: Renting out from t to t+1. →Equivalent
E i l
Rent.
R
• t+0, Option1 (User Cost) > Option2 (E. Rent) = Option1
• t+1, Option1 (User Cost) < Option2 (E. Rent) = Option2
2012/07/23
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Diewert & Shimizu
Single family house data:
Data:
P :price
i (10,000
(10 000 Yen)
Y ) off unitit
2
S : Floor space (m )
P / S (10,000 Yen)
A : Age of building (years)
TS : DIstance to the nearest station (meters)
TT : Travel time to terminal station ((minutes))
W: Road Width
Mean
Std. Dev.
Min.
Max.
Sibngle family house price data (251,473 observations)
6 623 83
6,623.83
3 619 20
3,619.20
1 280
1,280
29 990
29,990
105.48
38.93
50
448
72.47
30.11
25
479
15.20
8.34
0
55
811.68
374.22
80
2,800
34.48
11.12
1
144
4.88
1.88
2
20
Condominium price data:
P :price (10,000
(10 000 Yen) of unit
2
S : Floor space (m )
P / S (10,000 Yen)
A : Age of building (years)
TS : DIstance to the nearest station (meters)
TT : Travel time to terminal station (minutes)
Mean
Std. Dev.
Min.
Condominium price data (330,247 observations)
3 717 52
3,717.52
2 250 71
2,250.71
390
57.83
18.29
15
66.22
35.73
25
14.23
8.74
0
682.68
366.10
80
30.10
12.63
1
Max.
33,500
33
500
110
315
55
2,480
144
Land price data:
P / S (10,000 Yen) per square meter
2
L : Land area (m )
TS : DIstance to the nearest station (meters)
TT : Travel time to terminal station (minutes)
W: Road Width
Mean
Std. Dev.
Min.
Land price data (37,479 observations)
43.11
40.90
5
191 66
191.66
128 75
128.75
40
1,142.28
1,001.50
60
42.90
16.70
7
5.44
2.45
2
Max.
1,230
44,069
069
9,200
126
38
Housing rent data:
P :rent (10,000 Yen/month) of unit
2
S : Floor space (m )
P / S (10,000 Yen)
A : Age of building (years)
TS : DIstance to the nearest station (meters)
TT : Travel time to terminal station (minutes)
2012/07/23
Mean
Std. Dev.
Min.
Housing rent data (1,155,078 observations)
11.23
6.48
2
38.27
20.85
10
0.31
0.09
0.1
9 74
9.74
8 11
8.11
0
614.87
350.25
80
30.45
11.56
1
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Max.
60
120
2.0
55
7,040
126
page. 17
Diewert & Shimizu
Estimated
s
ed Result
esu oof Hedonic
edo c Equations.
qu o s.
 ijt  X it  t   it
Housing rent: For Equivalent Rent.
Single family house price,
price Condominium
price, and land price: For User Cost.
Single
g family
y house p
price model
Year Intercept
logS
logW
logA
logTS
logTT
Number
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
-0.08
-0.05
-0.03
0 03
-0.06
-0.08
-0
11
-0
08
-0
08
-0
13
-0
08
-0
07
-0
08
-0
03
-0
06
-0
-0 05
04
-0.04
-0.07
-0
0.08
08
-0.20
-0.22
0.25
0.20
0 14
0.14
0.14
0.12
0
09
0
11
0
11
0
09
0
04
0
06
0
06
0
03
0
04
0
0 02
01
0.01
0.00
0 02
0.02
0.01
0.03
-0.02
-0.03
-0.05
0 05
-0.04
-0.03
-0
04
-0
04
-0
03
-0
03
-0
04
-0
03
-0
04
-0
03
-0
02
-0
-0 03
04
-0.04
-0.03
-0
0.04
04
-0.04
-0.04
-0.07
-0.09
-0.10
0 10
-0.07
-0.04
-0
03
-0
03
-0
04
-0
03
-0
03
-0
03
-0
03
-0
02
-0
04
-0
-0 04
04
-0.05
-0.04
-0
0.07
07
-0.06
-0.06
-0.28
-0.27
-0.23
0 23
-0.18
-0.13
-0
13
-0
13
-0
04
-0
07
-0
07
-0
11
-0
10
-0
15
-0
16
-0
-0 17
12
-0.15
-0.17
-0
0.19
19
-0.17
-0.19
2,414
2,430
2 586
2,586
2,747
3,775
4
800
5
9 022
706
12
511
11
217
11
151
14
212
15
761
18
022
18
20 731
732
20,805
19,208
16 177
16,177
14,429
14,620
6.10
6.02
5 82
5.82
5.46
5.16
5
25
4
99
4
67
4
98
4
77
4
72
4
71
4
58
4
86
4
4 89
63
4.82
5.06
5 36
5.36
5.70
5.86
Adj.R
0.54
0.52
0 52
0.52
0.51
0.49
0
49
0
46
0
46
0
44
0
50
0
50
0
59
0
53
0
54
0
0 51
55
0.58
0.62
0 61
0.61
0.63
0.63
2
*The dependent variable in each case is the log price per square meter.
The table indicate the coefficient of main variables which a part of hedonic estimation results per year.
year
**The
***Estimation Method: Robust Regression
2012/07/23
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Diewert & Shimizu
Tokyo
y Prefecture:2010.
Tokyo:
-Population: 13,161,751
-Households: 6,403,219
,
,
-SNA: 71.181 trillion JPY
All Japan:
-Population: 128,057,352
-Households: 51,950,504
-SNA:
SNA 490.647
490 647 trillion JPY
Building Survey
Single family
house
e)Total*
Condominium
(units)**
f)Total*
(units)***
1990
148,834,033 1,857,722
107,274,134
367,734
1995
160,654,688 1,854,315
135,778,868
374,807
2000
174,379,864 1,897,345
161,698,203
381,216
2005
181,977,956 2,011,068
186,759,564
417,872
*unit: square meter
**Number of single family houses
***Number of condominium buildings(not unit)
2012/07/23
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page. 19
Diewert & Shimizu
Hedonic Price and Rents Indexes
100
60
40
3
2.8
2.6
Indexx 2000=1.0
2.4
22
2.2
20
C d i i price
Condominium
i
0
-20
Single
g familyy house pprice
-40
-60
60
-80
2
Annual chaange rate: %
A
80
-100
1.8
1.6
1.4
12
1.2
Condominium rent
Si l family
Single
f il house
h
rentt
1
19866
19877
198 8
19899
19900
199 1
19922
19933
19944
199 5
19966
19977
199 8
19999
20000
200 1
20022
20033
20044
200 5
20066
20077
200 8
20099
20100
0.8
2012/07/23
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Diewert & Shimizu
Estimation Results of Hedonic Indexes for
Housing Prices and Rents
Rent / Price
ratio:
Condominium
(%)
-
-
-
-
-
-
Condominium
price
Single family
house rent
Condominium
rent
(10 000yen/m2)
(10,000yen/m2)
(10 000yen/m2)
(10,000yen/m2)
(10 000yen/m2)
(10,000yen/m2)
(10 000yen/m2)
(10,000yen/m2)
1986
49.48
41.43
-
1987
90.24
73.83
-
Year
2012/07/23
Rent / Price
ratio: Single
family
house(%)
Single family
house price
1988
96.74
72.05
-
-
-
1989
100.03
81.86
-
-
-
-
1990
118.88
101.79
2.70
2.97
2.31%
2.96%
1991
106.19
90.96
2.94
3.28
2.82%
3.68%
1992
90.46
79.64
2.94
3.11
3.32%
3.97%
1993
80.50
71.59
2.77
3.02
3.49%
4.25%
1994
72 43
72.43
64 84
64.84
2 72
2.72
2 98
2.98
3 77%
3.77%
4 62%
4.62%
1995
67.19
53.41
2.68
2.95
4.02%
5.56%
1996
62.83
48.99
2.67
2.94
4.25%
6.04%
1997
60.97
47.80
2.65
2.92
4.37%
6.15%
1998
60.15
45.19
2.63
2.87
4.41%
6.37%
1999
53 84
53.84
43 17
43.17
2 62
2.62
2 83
2.83
4 88%
4.88%
6 60%
6.60%
2000
52.20
41.76
2.57
2.76
4.93%
6.65%
2001
48.97
40.85
2.54
2.76
5.21%
6.79%
2002
46.63
41.16
2.58
2.80
5.53%
6.85%
2003
47.81
41.17
2.54
2.74
5.34%
6.70%
2004
46 03
46.03
41 43
41.43
2 53
2.53
2 70
2.70
5 54%
5.54%
6 60%
6.60%
2005
46.03
42.10
2.49
2.67
5.47%
6.41%
2006
48.77
44.18
2.51
2.71
5.21%
6.22%
2007
53.09
49.60
2.57
2.68
4.93%
5.51%
2008
52.26
50.40
2.52
2.61
4.92%
5.28%
2009
51.21
47.12
2.46
2.57
4.96%
5.56%
2010
53.09
49.67
2.40
2.50
4.73%
5.13%
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page. 21
Diewert & Shimizu
The Verbrugge Variant (VV) of the User Cost Approach
Poole, Ptacek and Verbrugge (2005) , Verbrugge (2008), Diewert (1974)
u  r V   V  E[]V
t
t
t
H
t
1 .3
1 .3
1 .2
1 .2
M edian
1 .1
M axmum
1
0 .9
Annual change rate( t+1
1 / t)
Annual change rate( t+1
1 / t)
t
The rate of
expected
house price
appreciation
t
M edian
1 .1
M axmum
1
M inimum
0 .9
M inimum
i i
0 .8
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
0 .8
Condomini m
Condominium
Si l family
Single
f il house
h
2012/07/23
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page. 22
Diewert & Shimizu
Ratio: Diewert User Cost >Equivalent Rent: (%)
2012/07/23
1 10
1 00
90
80
70
60
50
40
30
20
10
0
-10
Si l family
Single
f il house
h
Condominium
19991
19992
19993
19994
19995
19996
19997
19998
19999
20000
20001
20002
20003
20004
20005
20006
20007
20008
20009
20010
Ratio: Disew
R
wert User C
Cost >Equiivalent Ren
nt : (%)
Ratio: Option1 (User Cost) > Option2 (E. Rent) = Option1
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page. 23
Diewert & Shimizu
Estimation results of User Costs.
Year
a)
b) Basic
Equivalent
User Cost*
Rent*
5,381.91
1991
5,283.60
1992
5,021.95
1993
4 933 06
4,933.06
1994
5,268.97
1995
5,256.77
1996
5,219.79
1997
5,155.46
1998
5,157.14
1999
5,864.61
2000
5,831.36
2001
5,925.69
2002
5,818.97
2003
5,782.20
2004
6,001.29
2005
6,062.71
2006
6,113.83
2007
5,951.92
2008
5,815.37
2009
*One billion yen
2012/07/23
c) VV User
Cost*
34,917.15
-17,249.25
29,172.85
9,414.64
22,840.21
11,742.15
18 828 92
18,828.92
14 916 87
14,916.87
11,404.91
18,786.03
8,446.97
16,425.49
8,231.11
12,849.09
10,184.68
9,831.25
5,429.53
8,858.19
9,214.74
7,984.24
3,620.13
7,063.19
1,923.76
6,600.24
4,383.36
5,395.85
1,577.33
4,767.56
-3,359.14
,
-6,546.35
4,168.27
6,050.27
-111.39
13,441.22
129.20
-11,388.15
388 15
1,594.28
2,303.28
d) Diewert
Financial
User Cost*
e) Diewert
OOHOC
Index*
-16,969.24
9,141.06
11,524.01
14 639 22
14,639.22
18,624.62
16,498.50
13,223.56
10,367.09
9,112.25
8,189.68
7,673.58
7,223.75
6,012.84
5,376.14
5,011.60
,
3,323.47
1,053.99
1,376.28
2,877.89
5,381.91
10,419.92
11,589.21
14 639 23
14,639.23
18,886.70
16,498.50
13,223.57
10,368.52
9,127.37
8,494.76
7,729.83
7,427.48
6,714.04
6,331.98
6,446.76
,
6,082.47
6,114.15
5,952.16
5,817.18
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d) -b)*
-51,886.39
-20,031.78
-11,316.20
-4,189.69
4 189 69
d) - c)*
e) - a)*
280.01
0.00
-273.58
5,136.32
-218.14
6,567.26
-277.64
277 64
9 706 16
9,706.16
7,219.71
-161.42
13,617.73
8,051.53
73.01
11,241.73
4,992.45
374.47
8,003.78
182.41
535.84
5,213.06
3,682.72
254.06
3,970.22
-1,025.07
205.43
2,630.15
4,053.45
610.39
1,898.46
5,299.99
623.51
1,501.79
1,629.48
617.00
895.07
3,798.81
608.58
549.78
8,370.73
843.33
445.47
9,869.83
1,020.20
19.76
-4,996.28
1,165.38
0.32
-12,064.94
1,247.07
0.24
4,266.04
1,283.61
1.80
page. 24
Diewert & Shimizu
Diewert’s OOHOC Index and User Cost Indexes.
Userr Cost / Eq
quivalent R
Rent : On
ne billion yyen
35,000
30 000
30,000
b) B
Basic
i User
U C
Costt
25,000
20,000
,
d) Diewert OOHOC Index
15,000
10,000
5,000
0
-5,000
a) Equivalent Rent
-10,000
-15,000
c) VV User Cost
19991
19992
19993
19994
19995
19996
19997
19998
19999
20000
20001
20002
20003
20004
20005
20006
20007
20008
20009
-20,000
2012/07/23
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page. 25
Diewert & Shimizu
quasi Diewert’s
ewe s OO
OOHOC
OC Index.
de .
Diewert OOHOCt   Max UCit , ERit 


quasi OOHOCt  Max   UCit , ERit 

I
I

2 0 ,0 0 0
5 ,0 0 0
1 8 ,0 0 0
4 ,0 0 0
3 ,0 0 0
1 6 ,00 0 0
a)-b)
1 4 ,0 0 0
1 ,0 0 0
1 2 ,0 0 0
1 0 ,0 0 0
2 ,0 0 0
0
a) Diewert OOHOC
-1 ,0 0 0
-2 ,0 0 0
8 ,0 0 0
6 ,0 0 0
b) quasi Diewert OOHOC
-4 ,0 0 0
-5 ,0 0 0
19991
19992
19993
19994
19995
19996
19997
19998
19999
20000
20001
20002
20003
20004
20005
20006
20007
20008
20009
4 ,0 0 0
-33 ,00 0 0
a) - b) : biillion yen
Diewerrt's OOHOC : billlion yen
I
2012/07/23
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page. 26
Diewert & Shimizu
Estimation results of User Costs
Natinal Accont (All Japan)
Tokyo
A.GDP*
B.Imputed
rent(National
Account)*
B/A
C. Imputed
rent(Prefecture
Account)*,**
C/B
C.Prefecture
C
Prefecture
Account*
D: Equivalent
Rent
Estimate*
D/C
1990
442,781.0
27,654.6
6.25%
-
-
-
4,925.89
-
1991
469,421.8
29,595.3
6.30%
-
-
-
5,381.91
-
1992
480,782.8
31,429.6
6.54%
-
-
-
5,283.60
-
1993
483,711.8
33,324.3
6.89%
-
-
-
5,021.95
-
1994
488,450.3
35,052.7
7.18%
14,892.63
0.42
1,217.25
4,933.06
4.05
1995
495,165.5
36,627.2
7.40%
15,686.02
0.43
1,352.16
5,268.97
3.90
1996
505,011.8
38,211.6
7.57%
16,440.75
0.43
1,442.76
5,256.77
3.64
199
1997
515,644.1
1 644 1
39 89 8
39,895.8
7.74%
4%
1 128 0
17,128.05
0 43
0.43
1 660 33
1,660.33
5,219.79
219 9
3 14
3.14
1998
504,905.4
41,144.5
8.15%
17,743.71
0.43
1,834.53
5,155.46
2.81
1999
497,628.6
41,866.3
8.41%
18,657.19
0.45
2,066.12
5,157.14
2.50
2000
502,989.9
42,772.5
8.50%
19,405.15
0.45
2,174.47
5,864.61
2.70
2001
497,719.7
43,615.6
8.76%
20,229.68
0.46
2,444.69
5,831.36
2.39
2002
491,312.2
44,202.3
9.00%
20,957.04
0.47
2,467.60
5,925.69
2.40
2003
490,294.0
44,754.0
9.13%
21,934.66
0.49
2,769.61
5,818.97
2.10
2004
498,328.4
45,170.6
9.06%
22,913.61
0.51
3,047.01
5,782.20
1.90
2005
501,734.4
45,570.9
9.08%
23,686.68
0.52
3,255.94
6,001.29
1.84
Year
2006
507 364 8
507,364.8
46 025 5
46,025.5
9 07%
9.07%
24 152 70
24,152.70
0 52
0.52
3 402 53
3,402.53
6 062 71
6,062.71
1 78
1.78
2007
515,520.4
46,358.9
8.99%
24,802.42
0.54
3,529.88
6,113.83
1.73
2008
504,377.6
46,660.3
9.25%
25,269.59
0.54
3,619.23
5,951.92
1.64
2009
470,936.7
46,724.1
9.92%
26,411.03
0.57
3,621.54
5,815.37
1.61
2010
-
-
-
-
-
-
5,655.68
-
*Unit: One billion yen
**Sum of 47 prefectures
2012/07/23
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page. 27
Diewert & Shimizu
Ⅳ. Conclusions:
• Having an extremely large weight in national accounting and
consumer price statistics,
statistics imputed rent for owner-
occupied housing plays an important role.
• Traditional equivalent approach and user cost approach
have a several problem in estimating it.
Diewert’ss OOH Opportunity Cost Approach is one of the a
• Diewert
powerful estimation method for imputed rent of OOH.
• quasi Diewert
Diewert’ss OOH Opportunity Cost Index can be
approximated with true Diewert’s OOH Opportunity Cost.
• In the coming new RPPI, we should consider to improve
the estimation of the OOH imputed rent in National
Account and CPI.
2012/07/23
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page. 28
Diewert & Shimizu
Decomposing Prices into L and S Components
Model 1 :The Builder’s Model with Quality Adjusted
Structures:
(1) Pnt = tLnt + t(1  Ant)Snt + nt ; t = 1,...,T; n = 1,...,N(t).
• Note the common depreciation rate  across time periods.
• This is a supply side hedonic model (or cost of production
model) as opposed to a demand side model.
• t can be interpreted as the price of a m2 of Land in period t
• t can be interpreted as the price of a quality adjusted (for
g ) m2 of a Structure in p
period t.
age)
• Form separate Land and Structures price indexes, PL and
PS.
• Finally use chained Fisher formula to aggregate PL and PS
2012/07/23
page. 29
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into an overall price index
P.
Diewert & Shimizu
Decomposing Prices into L and S Components
Model 2: Linear Model with Splines on the Plot Size
We know that the price of land per m2 tends to decrease for
l
large
lots.
l
Thus
Th as iin DHH
DHH, we try a spline
li model
d l for
f the
h
price of land. For observations that fall into the small land
size group
group, use (2); for the medium group
group, use (3) and for the
large land size group, use (4): (break points L1, L2, L3):
(2) Pnt = StLnt + t(1  Ant)Snt + nt ;
t = 1,...,T; nNS(t).
(3) Pnt = St[L1] + Mt[Lnt  L1] + t(1  Ant)Snt + nt ;
t = 1,...,T;
1 T; nNM(t).
(t)
(4) Pnt = St[L1] + Mt[L2-L1] + Lt[Lnt  L2]
+ t(1  Ant)Snt + nt ;
t = 1,...,T;
1 T; nNL(t).
(t)
2012/07/23
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Diewert & Shimizu
The Basic Builder’s Model for Tokyo with Ward Dummy
Variables (cont)
1= mean; 2 = median; 3 = P; 4 = PL; 5 = PS
•For
F Tokyo,
T k
our hedonic
h d i overall
ll index
i d P is
i above
b
th mean and
the
d median
di
series whereas for “B”, it was below.
1.6
1.4
12
1.2
1
0.8
06
0.6
0.4
0.2
0
1
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43
Series1
2012/07/23
Series2
Series3
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Series4
Series5
page. 31
Diewert & Shimizu
Handbook of Residential Property Price Index
•
•
•
•
•
•
•
•
•
•
•
•
2012/07/23
Chapter 1. Introduction
Chapter 2. Uses of Residential Property Price Indices
Chapter 33. Elements for a Conceptual Framework
Chapter 4. Stratification or 'mix adjustment' methods
Chapter
p 5. Hedonic regression
g
methods
Chapter 6. Repeat sales methods
Chapter 7. Appraisal-based methods
Chapter 8. Decomposing an RPPI into Land and Structures Components
Chapter 9. Data sources
Chapter 10.
10 Methods currently used
Chapter 11. Empirical examples
Chapter 12. Recommendations
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page. 32
Diewert & Shimizu
New Japanese Residential Property Price Indexes
120
110
100
90
All
80
Residential Land
70
Single Famuly House
60
Condominium
50
2012/07/23
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page. 33
Diewert & Shimizu
Co c
Contact:
・Chihiro Shimizu (Reitaku University& University of British Columbia)
[email protected]
[email protected]
・W.Erwin Diewert (University of British Columbia& New South Wales University)
[email protected]
• Our ppaper
p and ppresentation slides are available at:
• http://www.cs.reitaku-u.ac.jp/sm/shimizu/English.html
http://www cs reitaku-u ac jp/sm/shimizu/English html
2012/07/23
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page. 34