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