CHIEN-WEN PENG
NATIONAL TAIPEI UNIVERSITY
I-CHUN TSAI
NATIONAL UNIVERSITY OF KAOHSIUNG
STEVEN BOURASSA
UNIVERSITY OF LOUISVILLE06/25/ 2010
Determinants of Long-Run Homeownership Rates: Evidence from Taiwan
Homeownership Rate
s HouseholdofNumber
Units Houinsgoccupied-Owner ofNumber
Accumulated results of individual household’s housing tenure choice.
Benefits of Homeownership
Positive impacts on people’s behavior, especially during the childhood. (Green and White 1997; Haurin et al. 2002; Lien et al. 2008) higher test scores
Increase people’s attachment to their property and community, which tends to have stabilizing effect on society. (Rossi and Weber 1996; Dipasquale and Glaeser 1999) better neighbor, better citizen
Policies to Promote Homeownership Rate
Supply Side Subsidy Affordable Public Housing
Demand Side Subsidy
Preferential Interest Mortgage
Mortgage Interest Deduction from Income Tax
Lower Property Tax Rate
Lower down payment Required (Higher LTV)
Costs of Homeownership
Obscure costs with respect to Limited economic resource allocationEconomic developmentHousing market operation
Homeownership Rates in US-1965~2008
0
10
20
30
40
50
60
70
80
1965 1970 1975 1980 1985 1990 1995 2000 2006
63.4%
67.5%
+4.1%
Case & Shiller House Price Index-1987~2009
507090
110130150170190210
1987Q1 1989Q1 1991Q1 1993Q1 1995Q1 1997Q1 1999Q1 2001Q1 2003Q1 2005Q1 2007Q1 2009Q1
-25%-20%-15%-10%-5%0%5%10%15%20%
IndexAnnual Change
62.03
189.93
132.64
+206.2%
-30.16%
House Price and Homeownership Rate
House Price Relative Cost of Owning vs. Renting House Price Affordability (wealth and income
constrains)
House price ↑ User Cost of Owning ↑
Affordability ↓
Ownership Rate ↓Exp. House Price Appreciation↑ Ownership Rate↑
Homeownership Rates and House Price in US
61
62
63
64
65
66
67
68
69
70
0
20
40
60
80
100
120
140
160
180
200
Ownership
HPI
Positive or Negative?
Painter and Redfearn(2002)
Interest rates had an influence on both housing supply and timing of changes of tenure status from renter to owner, the long-term homeownership rate appears independent of interest rates.
To promote homeownership rates, low down payment and improved technology for assessment of credit risk may be more effective.
Homeownership Rates in Taiwan:1976~2008
60
65
70
75
80
85
90
1976 1981 1986 1991 1996 2001 2006
%
+20%87.4%
67.4%
Ownership Rates in Taiwan and USA-1976~2008
60
65
70
75
80
85
90
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
%
Taiwan USA
64.8% 67.5%
+2.7%
+20%
67.4%
87.4%
Ownership Rates and House Price of Taipei City
Taipei City
0
5
10
15
20
25
30
50%
55%
60%
65%
70%
75%
80%
85%
pown
Ownership Rates and House Price of Taipei County
Taipei County
0
2
4
6
8
10
12
14
16
50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
p
own
Ownership Rates and House Price of Taichung City
Taichung City
0
2
4
6
8
10
12
14
50%
55%
60%
65%
70%
75%
80%
85%
90%
p own
Ownership Rates and House Price of Kaohsiung City
Kaohsiung City
0
2
4
6
8
10
12
14
50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
p
own
Research Questions
Both of the patterns of long-run homeownership rates and house prices in US. and Taiwan are strange.
What are the determinants of long-run homeownership rates? (Does it implies Taiwan’s homeownership promotion policies are more effective than U.S.? )
Literature Review
Abundant Literature on Determinants of Individual Household’s Tenure Choice
Some studies focus on Homeownership Rates Differences in different Nations /Regions
Rare on the Determinants of Long- run Homeownership Rates
Tenure Choice- Market Factors
Housing Price, HP Fluctuation Risk ↑ Rent
Borrowing Constrains (LTV↓, Interest Rate↑) ↑ Rent
Rent, Rent Fluctuation Risk ↑ Buy
Expected Housing Price Appreciation ↑Buy
Tenure Choice-Institution Factors
Property Tax ↑ Rent
Relative Cost of Owning vs. Renting ↑ Rent
Deduction of Mortgage Interest from Income Tax↑ Buy
Owner-occupied Housing Subsidies↑ Buy
Tenure Choice- Household’s Characteristics
Expected Mobility ↑ Rent
Household Income↑ Buy
Household Head’s Age↑, Married Buy
Family Size ↑ Buy
Number of Dependent Children↑ Buy
Selected Variables (no institutional factors )
House Price (p) Household Income (I) House Price to Income Ratio (pI)Rent Growth Rate (red)House Price Growth Rate (pd)Income Growth Rate (ld)Household Growth (h) Mobility Rates (mov)Proportion of Married Couples (mar)Proportion of Elderly People (old)
Empirical Study
Investigate the Determinants of Long-Run Homeownership Rates
Data: Taipei City, Taipei County, Taichung City, Kaohsiung City, 1980~2007,Sample Size 112
Methodology: Panel Co-integration
Panel Co-integration
Cointegration is an econometric property of time series variables.
If two or more series are themselves non-stationary, but a linear combination of them is stationary, then the series are said to be cointegrated.
Panel Co-integration= Cross Section + Time Series More Samples, More Information
Panel Unit Root Test IPS ADF-Fisher
VariablePanel Unit Root Test
IPS ADF - Fisher Chi-square
Levels
own 0.27 9.62
mar 7.08 0.12
mov -1.35 21.53 ***
old 6.55 0.19
h -1.58 13.32
p 0.01 6.03
I -0.10 5.56
pI -1.19 10.75
pd -2.00 ** 17.70 **
Id -4.92 *** 38.68 ***
red -0.67 8.22
VariablePanel Unit Root Test
IPS ADF - Fisher Chi-square
Differences
△own -13.23 *** 105.03 ***
△mar -6.09 *** 48.18 ***
△mov -8.49 *** 69.03 ***
△old -6.37 *** 49.81 ***
△h -9.62 *** 77.28 ***
△p -2.05 ** 17.65 **
△I -5.71 *** 45.45 ***
△pI -5.70 *** 44.67 ***
△pd -11.70 *** 88.14 ***
△Id -7.38 *** 61.41 ***
△red -4.22 *** 32.36 ***
Results of Panel Unit Root Test
Can not reject the null hypothesis of having a unit root for the levels of most variables, except house price appreciation rate (pd) and income growth rate (Id).
The differences of all variables are significantly to reject the null hypothesis which implies most variables are I(1).
own and mar mov old h (demographic)
own and I, p, pI (affordability)
own and red (consumption)
Model 1 without trend Model 2 with trend
Panel Co-integration Test
Panel StatisticsWeighted
Panel StatisticsGroup Statistics
Series: own mar mov old h
PP statistic -4.605 *** -4.605 *** -6.181
ADF statistic -4.519 *** -4.519 *** -6.048
Series: own mar
PP statistic -2.875 *** -3.336 *** -3.652
ADF statistic -2.499 ** -3.031 *** -3.334
Series: own mov
PP statistic -3.161 *** -3.339 *** -3.504
ADF statistic -3.118 *** -3.295 *** -3.455
Series: own old
PP statistic -4.875 *** -4.821 *** -5.551
ADF statistic -5.269 *** -5.416 *** -5.418
Series: own h
PP statistic -0.436 -0.658 -0.065
ADF statistic -0.385 -0.726 0.084
Panel Statistics WeightedPanel Statistics Group Statistics
Series: own p I
PP statistic -3.563 *** -2.823 *** -3.248 ***
ADF statistic -4.160 *** -3.856 *** -4.338 ***
Series: own p
PP statistic -1.723 -1.919 -1.054
ADF statistic -1.674 -1.860 -1.043
Series: own I
PP statistic -4.203 *** -2.986 *** -3.736 ***
ADF statistic -3.644 *** -3.089 *** -3.247 ***
Series: own pI
PP statistic 0.919 1.246 2.053 **
ADF statistic 1.195 1.305 2.190 **
Panel Statistics
WeightedPanel
Statistics
Group Statistics
Series: own red
PP statistic -0.421 -0.216 0.464
ADF statistic -0.523 -0.314 0.361
Panel Co-integration Test without trend
Long-run equilibrium relationship between own and I, mar, old, mov
No cointegration relationship between own
and h, p, red
own and mar mov old h (demographic)
own and I, p, pI (affordability)
own and red (consumption)
Panel Co-integration Test -With Trend
Panel StatisticsWeighted
Panel Statistics Group Statistics
Series: own mar mov old h
PP statistic -6.77 *** -7.02 *** -8.20 ***
ADF statistic -6.71 *** -6.70 *** -6.39 ***
Series: own mar
PP statistic -5.95 *** -5.99 *** -5.76 ***
ADF statistic -5.93 *** -5.97 *** -5.72 ***
Series: own mov
PP statistic -5.30 *** -5.12 *** -4.94 ***
ADF statistic -5.28 *** -5.12 *** -5.00 ***
Series: own old
PP statistic -6.92 *** -6.17 *** -6.52 ***
ADF statistic -6.92 *** -6.17 *** -6.48 ***
Series: own h
PP statistic -5.47 *** -4.43 *** -4.98 ***
ADF statistic -5.49 *** -4.49 *** -5.05 ***
Panel StatisticsWeighted
Panel Statistics Group Statistics
Series: own p I
PP statistic -7.51 *** -6.76 *** -8.65 ***
ADF statistic -7.33 *** -6.61 *** -7.41 ***
Series: own p
PP statistic -8.08 *** -8.91 *** -7.82 ***
ADF statistic -8.03 *** -8.76 *** -7.47 ***
Series: own I
PP statistic -7.08 *** -5.19 *** -6.88 ***
ADF statistic -7.93 *** -6.38 *** -6.68 ***
Series: own pI
PP statistic -5.63 *** -4.82 *** -5.31 ***
ADF statistic -5.61 *** -4.83 *** -5.39 ***
Panel Statistics WeightedPanel Statistics
Group Statistics
Series: own red
PP statistic-7.28
***-6.79
***-6.55
***
ADF statistic-7.29
***-6.79
***-6.57
***
Panel Co-integration Test with trend
All variables have cointegration relationships with homeownership rates.
A trend in homeownership rate serial.
FMOLS_ Taipei City
variable coefficient t value
MAR 2.41 7.19
MOV 0.25 1.30
OLD 4.02 8.15
H -0.09 -0.33
P 0.16 1.81
I 0.01 0.56
RED 0.07 1.09
FMOLS_ Taipei County
variable coefficient t value
MAR -0.23 -1.19
MOV 0.28 2.48
OLD 4.77 5.36
H -0.61 -2.77
P 0.22 1.47
I -0.12 -2.90
RED -0.07 -1.02
FMOLS_ Taichung City
variable coefficient t value
MAR -0.44 -1.10
MOV -0.31 -1.06
OLD -0.42 -0.24
H -0.44 -1.31
P 0.49 1.04
I 0.16 3.84
RED -0.02 -0.08
FMOLS_ Kaohsiung
variable coefficient t value
MAR 0.77 0.23
MOV -0.07 -0.18
OLD 2.76 0.55
H 0.25 0.36
P -0.04 -0.09
I 0.22 2.06
RED 0.24 0.97
FMOLS_ Panel
variable coefficient t value
MAR 0.63 2.57
MOV 0.04 1.27
OLD 2.78 6.90
H -0.22 -2.02
P 0.21 2.12
I 0.07 1.78
RED 0.06 0.48
Results of FMOLS
• the most influential variables of own
are different in the four cities.•Taipei City: old(+), mar(+), p(+)•Taipei County: old(+), mov(+), l(-), h(-) •Taichung City and Kaohsiung City: I
(+) • In General, old, mar, p, I (+) , h (-)
Conclusions
A trend exists in Taiwan’s homeownership rates, not explainable by selected variables which may contributed to the influence of institutional factors.
If not consider the trend, long-run equilibrium relationships only between ownership rates and
household incomeproportion share of married couplesProportion of elderly peoplemobility rates
Conclusions
If consider the trend, can find co-integration between homeownership rates and house prices, household growth rate, rent growth rate.
From FMOLS, the most influential variables of own are different
in the four cities. In general, proportion of elderly people, proportion
of married couple, house price are most influential vars.
Policies Implications
Why there is a trend in Taiwan’s homeownership rates?
Possible explanation: Low owning cost which due to low property
tax and high expectation of house price appreciation, especially in Taipei City
® effective property tax rate↑® better rental housing market
Thanks for your Attention
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