Supply Elasticity of Houses in Regional NSW

Xiang Ling Liu &

Glenn Otto UNSW

EMG Workshop 5 November 2014

2

Perception that Housing Supply in Australia is Inelastic “…there have been a number of factors on the supply side that have combined to keep the supply of new housing below where it would have been in a more responsive environment. As a result, we have had the combination of higher prices and lower supply than might otherwise have occurred.” (Tony Richards, 2009, RBA)

3

What is the supply elasticity of residential housing in Australia?

All Housing Ball, Meen and Nygaard (2010) Australia 0.55 Gitelman and Otto (2012) Sydney 0.33 Liu and Otto (2014) Sydney 0.51 Houses Apartments Gitelman and Otto (2012) 0.18 0.53 Liu and Otto (2014) 0.22 0.80

4

Why Regional NSW? Relatively good disaggregated data on house prices

Is housing supply more elastic in regional NSW than in Sydney?

5

Data Cross-section unit: Local Government Area (LGA) 101 LGAs Prices Median sales price for non-strata dwellings Raw data are quarterly observations beginning in 1991:1 Missing observations for some LGAs are “guesstimated” Converted to annual frequency by averaging quarterly calendar

year obs Sample 1991 – 2012 All series converted to real house prices using Sydney CPI

6

Real House Prices in LGAs of Griffith and Nambucca

0

50

100

150

200

250

300

350

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Tho

usa

nd

s ($

)

Griffith Nambucca

7

House Stocks Number of private non-strata dwellings Census data provide estimates for 1991, 1996, 2001, 2006 and 2011 Inter-censual years are interpolated using data on building approvals for

LGAs No accounting for quality of housing In most regional LGAs, non-strata dwelling = detached house

8

Number of Non-Strata Dwellings in LGAs of Griffith and Nambucca

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Nu

mb

er

of

Ho

use

s

Griffith Nambucca

9

Regional Groupings for LGAs 11 regions (Number of LGAs) Coastal Inland Hunter (11) Central West (13) Illawarra (5) Far West (1) Mid-North Coast (7) Murrumbidgee (12) Richmond-Tweed (6) Murray (9) South-Eastern (14) North-Western (11) Northern (12) Coastal means that at least some LGAs have a coastline.

10

Regional Map

11

Growth of Housing Stock and Real Prices by Region, 1991-2011

-20.0

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

Rich

mo

nd

-Twe

ed

Mid

-No

rth C

oast

Hu

nte

r

Illawarra

Sou

th-Easte

rn

No

rthern

Ce

ntral W

est

No

rth-W

este

rn

Mu

rrum

bid

gee

Mu

rray

Far We

st

% c

han

ge

Non-Strata Houses Real Prices

12

Increase in House Prices: 2002-2004 Feature of the data is a large increase in real house prices in most LGAs

from 2002-2004

13

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

1985 1990 1995 2000 2005 2010 2015

Normalised Real House Prices for Richmond-Tweed

14

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

1985 1990 1995 2000 2005 2010 2015

Normalised Real House Prices for North Western Region

15

NSW-Wide Common Shock Increase in demand curve for houses Reduction in supply curve for houses

If we assume the former, then can use the increase in house prices over 2002-2004 to estimate supply elasticity:

% Δ in stock of houses 2001 to 2005 _______________________________ % Δ in real house prices 2001 to 2005

16

Naïve Estimate of Supply Elasticity by Region

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

0.12

CW FW HT IW MN MB MR NW NT RT SE

Elas

tici

ty

17

Formal Supply Elasticity Estimates Use annual time-series data from 1991-2012 to estimate supply elasticity

for each of 101 regional LGAs

18

(Very) Simple Model Supply Curve

𝑙𝑛𝐻𝑡𝑖 = 𝛼𝑖 + 𝛽𝑖𝑙𝑛𝑃𝑡

𝑖 + 𝑢𝑡𝑖

Reduced Form

𝑙𝑛𝑃𝑡𝑖 = 𝜋0𝑖 + 𝜋1𝑖𝑙𝑛𝑌𝑡

𝑖 + 𝜋2𝑖𝑙𝑛𝑁𝑡𝑖 + 𝜋3𝑖𝑅𝑡 + 𝑣𝑡

𝑖 H = stock of non-strata properties P = real median price of non-strata properties Instruments Y = real income per taxpayer N = resident population R = real 10 year bond rate

19

Instrument Quality (income and real rate)

0

50

100

150

200

250

300

350

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 100

F-st

at

LGA

20

Density Functions for Regional and Metropolitan Supply Elasticity

-1

0

1

2

3

4

5

-0.2 0 0.2 0.4 0.6 0.8 1 1.2

Supply Elasticity

Regional Houses Sydney Houses

21

Estimating Supply Elasticity: Nambucca (IV Estimate = 0.41)

y = 0.3106x + 7.1505 R² = 0.6852

8.6

8.65

8.7

8.75

8.8

8.85

8.9

8.95

9

9.05

5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9

Log

Ho

use

s

Log Price

22

Estimating Supply Elasticity: Nambucca (1/2.21 = 0.45)

y = 2.2064x - 14.07 R² = 0.6852

4.9

5

5.1

5.2

5.3

5.4

5.5

5.6

5.7

5.8

5.9

8.6 8.65 8.7 8.75 8.8 8.85 8.9 8.95 9 9.05

Log

Pri

ce

Log Houses

23

Another Estimator ARDL Bounds Procedure (Pesaran, Shin and Smith, 2001)

∆𝑙𝑛𝐻𝑡𝑖 = 𝛿𝐻0

𝑖 + 𝛿𝐻𝑃𝑖 𝑙𝑛𝑃𝑡−1

𝑖 + 𝛿𝐻𝐻𝑖 𝑙𝑛𝐻𝑡−1

𝑖 + 𝜔𝐻𝑃𝑖 𝑙𝑛∆𝑃𝑡

𝑖 + 𝑣𝑡𝑖

𝐻0: 𝛿𝐻𝑃𝑖 = 𝛿𝐻𝐻

𝑖 = 0 Test for levels relationship between lnH and lnP If F-stat is “sufficiently small” then don’t reject null If F-stat is “sufficiently large” then reject null Range for F-stat where you need to pre-test for variables being I(1) or I(0)

If null is rejected, then estimate long-run supply elasticity by 𝛿𝐻𝑃𝑖

𝛿𝐻𝐻𝑖⁄

24

Correlation between IV and ARDL Estimates

-0.2

0

0.2

0.4

0.6

0.8

1

-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2

IV E

stim

ate

s

ARDL Estimates

25

Growth in Real House Prices and Supply Elasticity

“As a result, we have had the combination of higher prices and lower supply than might otherwise have occurred.” (Tony Richards) Do LGAs with lower supply elasticity have higher average capital gains?

26

Supply Elasticity and Real Capital Gains: Coastal Regions

y = -2.0525x + 4.3696 R² = 0.0771

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Re

al C

apit

al G

ain

(%

pa)

Supply Elasticity

27

Supply Elasticity and Real Capital Gains: Inland Regions

y = -0.9877x + 2.7978 R² = 0.0206

-2

-1

0

1

2

3

4

5

6

7

8

-0.2 0 0.2 0.4 0.6 0.8 1

Re

al C

apit

al G

ain

(%

pa)

Supply Elasticity

28

Why is Housing Supply in Regional NSW so Inelastic? 2 observations Average supply elasticity for houses in regional NSW (0.32) is not much

greater than in Sydney (0.2)

There are no regional LGAs with elastic housing supply 5 largest: Murray (0.9), Hastings (0.85), Great Lakes (0.79), Port Stephens (0.67) and Bathurst (0.64)

Why no regions like Dallas, Tampa-St Petersburg or Phoenix?

All of NSW looks like San Francisco

29

NSW Planning System Legislation

Planning and Environmental Assessment Act 1979 Environmental Planning and Assessment Regulation 2000

State Environmental Planning Policies (SEPPs) NSW-wide planning policies and procedures

Local Environmental Plan (LEP) zones all land within an LGA; including what developments and land uses can occur and under what criteria

LEPs need State Government approval

30

Some Unresolved Questions What criteria do Local Councils use to decide on the quantity of

land to zone as residential in their LEPs? Answer seems to be that they use population growth projections

What is the current stock of unused land that is currently zoned as

residential in regional LGAs?

Difficult to calculate this figure

31

Additional Slides

32

Supply Elasticity and Area of LGA

y = -0.066x + 0.7638 R² = 0.124

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 2 4 6 8 10 12

Elas

tici

ty

Log of Area

33

Estimates of Supply Elasticity by LGA

-0.2

0

0.2

0.4

0.6

0.8

1

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 100

Elas

tici

ty