The Housing Market across the Greek Islands - PowerPoint Presentation

Slide1

The Housing Market across the Greek Islands

Dimitra KavarnouUniversity of Readingd.kavarnou@pgr.reading.ac.ukSlide2

A bit more of Geography…

Dimitra Kavarnou - Henley Business School, University of ReadingSlide3

A bit more of Geography…

>

than 6,000 islands/isles117 inhabited islands79 islands >100 (population)53 islands>1,000Dimitra Kavarnou - Henley Business School, University of ReadingSlide4

Ionian Islands

Sporades Islands

Argo Saronic Islands

Cyclades Islands

North East Aegean Sea Islands

Dodecanese Islands

Dimitra Kavarnou - Henley Business School, University of ReadingSlide5

Size…

GroupNumber of Islands in this Research

PopulationGeographical Size (m2)Ionian Islands5203,2102,200North East Aegean Sea Islands5194,8203,685Argo – Saronic Islands345,270167

Sporades Islands4

16,700

417.5

Cyclades Islands

11

108,370

1,947.36

Dodecanese Islands

8

185,950

2,345

Total

36

754,320

10,761.86

Dimitra Kavarnou - Henley Business School, University of ReadingSlide6

Attributes of the Housing Market - I

Heterogeneity

Heterogeneity in many levels Property/ Neighbourhood/ Settlement (Villages/towns)/ Islands/ Groups of IslandsHousing Submarkets Islands – Groups of Islands2. DurabilityCommunity formation (trade/ piracies/ occupations/ wars)Horizontal ownership (bequests)Ownership rate 80% - Cultural AspectFinancial CourseBooms and RecessionsDimitra Kavarnou - Henley Business School, University of ReadingSlide7

Attributes of the Housing Market - II

3. Political EconomyPlethora of laws/ rules/ regulation

Tax Regime continuously changing – UnstableNew Laws and additional taxation established and applied from 01-01/2014Taxation constitutes a Disincentive to be a homeowner – investor4. Transactional CostsHigh Transaction CostsAmong the highest in EUDimitra Kavarnou - Henley Business School, University of ReadingSlide8

Attributes of the Housing Market - III

Imperfect InformationLack of an well-

organised information institutionInsufficient National CadastreThe area of the islands is not mappedCompetitive, unprofessional, non-accredited brokerage industryImmovabilityAny real estate/housing market is immovableIncreased demand for spatial development (amenities, infrastructure, employment, etc.)More evident to islands which have physical boundariesDimitra Kavarnou - Henley Business School, University of ReadingSlide9

Attributes of the Housing Market – IV

7. External EffectsMain focus on the heterogeneity in island/ group of islands level:

the public amenities (Presence of public amenities on the islands/ distance from properties)Port (distance)Hospital (presence)Airport (presence and distance)University (presence)Tourism rate Luxury rate Density (population/ geographical size)Dimitra Kavarnou - Henley Business School, University of ReadingSlide10

Hedonic Research: Idea

This research assesses and analyses the variables that compose the house prices in the islands of Greece

This research examines the impact/ significance of local public amenities on house prices across 36 islands of GreeceThe model controls for several structural and locational characteristics of the properties as well as economic and demographic attributes of the islandsDimitra Kavarnou - Henley Business School, University of ReadingSlide11

Methodology - I

Hedonic Regression Method

(The method that decomposes the dependant variable under the scope into its constituent characteristics, and obtains assessments of the contributory value of each specific characteristic)(Rosen; 1974, Roback;1982, Bajari and Benkard; 2005) In this research, the dependant variable (Y) is the Assessed Housing Prices

- AHP or P for every property (i) , island(j), group of island(k)

P

i,j,k

=

α + ∑β

X

i,j,k

+

ε

i,j,k

In

order to mitigate the problem of

heteroskedasticity

as well as to compare percentage-wise the effect on the Assessed Housing

Prices

(1)

log(

P

i,j,k

)=

α + ∑β

X

i,j,k

+

ε

i,j,k

Υ

i

=

α + β

1

Χ

1

+ β

2

Χ

2

+

…+

β

i

X

i

+

ε

i

Dimitra Kavarnou - Henley Business School, University of ReadingSlide12

Methodology - II

But

Τhere are also island characteristics for each island (j):(2) log(Pi,j,k) = α + ∑β Xi,j,k + ∑γZj,k + εi,j,k

Controlling the

Fixed Effects

for each island:

(3)

log(P

i,j,k

) =

α + ∑β

X

i,j,k

+

δ

j

+ ε

i,j,k

(Boundary fixed effects model: Black;1999, Clapp, Nanda and Ross; 2008)

where

δ

is the total unobserved effects for each island (j) - dummies

Dimitra Kavarnou - Henley Business School, University of ReadingSlide13

Data - I

Two files from the

Bank of Greece including properties in the islands that have been evaluated from 2005-2013 with property characteristics:The property characteristics (Xi,j,k) included are:Some details about the property location (not exact)The living space (m2)The land area (m2

)The date/year of permit, completion, evaluation

The property type (flat/detached house/ maisonette) and the floor

Some information about the construction quality, the neighbourhood, the view (limited)

Some information about the store rooms and the parking spaces

file 1

11,553

file 2

3,384

Total

14,937 pr.

Dimitra Kavarnou - Henley Business School, University of ReadingSlide14

Data -

II

Limitations of the datasetNot exact location (address/number, to many cases only local toponyms of settlements)Either because of incomplete dataset from the estimatorsButMainly because the properties in the Islands do not have an address themselves but they refer to the closest village/settlementWith this very limited information about their location, it was VERY difficult and time-consuming to spot the properties and calculate their distances from the amenities (ports/airports)Lots of missing/ incomplete values from the evaluators (view, land, year of completion/permit)

Dimitra

Kavarnou

- Henley Business School, University of ReadingSlide15

Data - III

Data Set Cleaning:Out of the

14,937 properties I received, I excluded:3,620 properties in Evvoia and Crete (separate analysis – research) 850 approx. duplications 500 approx. did not concern properties on islands (incorrect entries)3,000 approx. to which the land area was not available 300 approx. to which the year of completion or the year of permit was not available (not able to calculate the age of the property) 300 approx. concerned islands with population<1,000p. or islands with insufficient number of observations/island (<15) 6,350 properties approx. in 36 islands to be spotted and calculated2,000 properties approx. not able to spot/ find the approx. location of the closer village in Google Earth/ Google maps 4, 369 properties spotted in the final dataset

Dimitra Kavarnou - Henley Business School, University of ReadingSlide16

Data - IV

Spotting the properties in Google Earth (approximately)

Dimitra Kavarnou - Henley Business School, University of ReadingSlide17

Data -

V

Dimitra Kavarnou - Henley Business School, University of ReadingSlide18

Data -

VICalculating time distances in Google maps

to port: to airport:Dimitra Kavarnou - Henley Business School, University of ReadingSlide19

Data Analysis - II

Dimitra Kavarnou - Henley Business School, University of ReadingSlide20

Data Analysis - III

Deflation of Assessed Housing Prices

The Prices are deflated and expressed in December 2012 prices:where:HICPDec2012= 123.28HICPt = the HICP of the month year of the evaluation(Source of the HICP tables: Hellenic Statistic Authority)Dummy Variables Xi,j,k for the property types:FlatDetached HouseMaisonette

Dimitra Kavarnou - Henley Business School, University of ReadingSlide21

Data Analysis -

IV

Dummy Variables (Zj,k) for controlling:The Presence of Airport on the islandThe Presence of Prefectural General Hospital on the islandThe Presence of University on the islandDummy Variables (δj) for the fixed effects - controlling the unobserved heterogeneity of the islands (one dummy for each island)Dummy Variables (Xi,j,k) for controlling:View (whether the property has view to the sea or not)Proximity to Capital

(whether the property is located in the island’s capital or not)Coastal Settlement

(whether the property is located in a coastal settlement or not)

Dimitra

Kavarnou

- Henley Business School, University of ReadingSlide22

Descriptive Statistics – of the Groups

Ionian IslandsNorth-East Aegean IslandsSporades Islands

Variable

N

Mean

Median

SD

N

Mean

Median

SD

N

Mean

Median

SD

Assessed Values

980

363,409

208,389

201,879

848

219,071

166,450

189,111

232

287,149

236,294

257,949

Living Space

980

139

119

90

848

131

113

112

232

149

119

157

Land

980

1,061

313

2,373

848

636

131

1541

232

2080

517

6890

Age

980

14

6

18

848

30

23

22

232

19

11

22

Tourism(1000s)

980

25.0271

0.0420

43.6460

848

6.0631

0.9480

9.6050

232

-

-

-

Density(1000s/m

2

)

980

0.1041

0.0331

0.1707

848

0.0566

0.0330

0.0688

232

0.0437

0.0141

0.1273

Argo-Saronic Islands

Cyclades Islands

Dodecanese Islands

Variable

N

Mean

Median

SD

N

Mean

Median

SD

N

Median

SD

Assessed Values

355

325,058

251,804

258,350

966

434,331

290,441830,450988237,470196,683191,292Living Space3551371207596614711910898812410393Land355536304944966173335238419887071332162Age35588496617824988201913Tourism(1000s)355---9664.32980.163011.838098850.94700.459085.6460Density(1000s/m2)3550.33710.03960.41289660.08980.01350.25449880.09390.01350.1504

Dimitra Kavarnou - Henley Business School, University of ReadingSlide23

Results OLS - Groups

Dependent Variable: LOG(REAL_ASSESSED_VALUES)

Variables (Xi,j,k)Ionian IslandsNorth East Aegean Islands

Sporades Islands

ArgoSaronic Islands

Cyclades Islands

Dodecanese Islands

C

10.35***

(81.62)

8.23***

(48.10)

9.34***

(25.64)

9.00***

(28.42)

8.94***

(72.85)

8.41***

(45.56)

Log(

Living_Space

)

0.67***

(20.75)

0.80***

(19.15)

0.61***

(7.73)

0.70***

(11.35)

0.71***

(20.32)

0.68***

(17.85)

Log(land)

0.13***

(6.45)

0.04*

(1.68)

0.03

(0.73)

0.13**

(2.05)

0.05**

(2.33)

0.17***

(6.89)

Age

-0.004***

(-5.40)

-0.005***

(-9.19)

-0.006***

(-3.87)

-0.005***

(-4.16)

-0.005***

(-7.82)

-0.005***

(-7.58)

t2

-0.21***

(-7.69)

-0.16***

(-5.93)

-0.121*

(-1.84)

-0.16***

(-3.29)

-0.11***

(-3.68)

-0.10***

(-3.88)

t3

-0.007

(-0.11)

0.25***

(5.66)

-0.053

(-0.35)

-0.24*

(-1.76)

0.03

(0.40)

0.02

(0.31)

PUR

0.0004

(0.94)

-0.001***

(-3.01)

-0.001

(-1.59)

-0.0002

(-0.21)

-0.0006

(-1.17)

0.002***

(3.05)

Floor

0.01

(0.65)

-0.006

(-0.62)

0.056

(1.29)

0.06**

(2.00)

0.002

(0.22)

-0.02

(-1.51)

View

0.25***

(5.41)

0.22***

(5.92)

0.07

(0.95)0.252***(4.90)0.22***(7.45)0.17***(5.55)Presence_Hospital1.04***(13.02)---0.04(0.58)0.42*(1.88)Presence_University-0.13(1.25)---0.171(-0.59)-0.21***(-3.48)Presence_Airport-2.39***(-30.69)-0.009(0.14)--0.007(-0.14)-0.50***(-4.42)PtCapital0.21***(5.32)0.04(1.27)0.03(0.45)0.071(1.53)0.05(1.50)0.06*(1.93)Coastal_Settlement0.03(0.88)0.10***(2.69)0.05(0.61)0.11(1.10)0.07**(2.34)0.08***(2.80)Tourism 0.16***(32.76)0.001(0.21)---0.03(-1.46)-0.02***(-9.16)Luxury 0.36***(16.06)-0.06(-1.63)--0.37***(8.09)0.09***(36.11)Density-56.26***-26.33)-1.24(-0.80)1.46(1.60)-2.05***(-9.76)-0.02(-0.02)-3.59**(-2.07)R20.630.680.520.670.680.71N975844231353958965Dimitra Kavarnou - Henley Business School, University of ReadingSlide24

Results Fixed Effects- Groups

Dimitra Kavarnou - Henley Business School, University of ReadingSlide25

RESULTS –I Individual Islands

For 33/36 islands the

living space is positively very significant to the prices (1% significance level) while the rest 3 islands (are the islands with very small sample 15-21 obs)1% increase in living space 0.34-1.07% increase to the prices ( 0.72% increase - weighted average)For 21/36 islands the land space is positively (very) significant (1% or 5%)

1% increase in the land area 0.07-0.50% increase to the prices

(0.14% increase - weighted average)

The

Property Utilisation Ratio

is relatively not significant for most of the islands (gardens/yards not significant – only in 6 islands)

The

floor number

is relatively not significant for most of the islands (only in 6 islands)

Dimitra Kavarnou - Henley Business School, University of ReadingSlide26

RESULTS - II

The

property type (flats/detached houses/ maisonettes) seems to be very significant for some of the islandsDetached houses to 14/36 islands negatively very significant (1-5%) compared to flatsi.e. The flats are more expensive compared to detached houses

Maisonettes

to 5/22 islands negatively very significant (1-5%)

compared to flats

i.e.

The flats are

more expensive

compared to

maisonettes

Maisonettes

to 4/22 islands

positively

very significant (1-5%)

compared to flats

i.e.

The flats are

less expensive

compared to maisonettes – probably because of their construction/ property characteristics/ extra facilities/ landscape

The

Age

is

negatively

very significant (1-5%) for most of the islands (26/36)

Every Additional Year 0.3-1.4% decrease of house prices

(0.7% decrease - weighted average)

Dimitra Kavarnou - Henley Business School, University of ReadingSlide27

RESULTS – III

View

For 23/36 islands the view is positively (very) significant (1-5% significance level) Approx. 13.1 – 64.2% more expensive compared to the properties without view (30.2% weighted average) Proximity to CapitalFor 7/36 islands the PtCapital is positively (very) significant (1-5% significance level) while for 2/36 islands the

PtCapital is negatively

(very) significant (1-5% significance level)8/36 Approx. 30.3% (weighted average) more expensive

2/36 Approx. 25.2% (weighted average) less expensive

Coastal Settlement

For

5/36

islands if the property is located in a coastal settlement, it is

positively

(very) significant (1-5% significance level)

Approx. 15.3% more expensive compared to a non coastal settlement

while for

1/36

islands Coastal Settlement is

negatively

(very) significant (1-5% significance level)

Dimitra Kavarnou - Henley Business School, University of ReadingSlide28

RESULTS – V

Time Distance to Port:

For the bigger islands (big distances) the time distance to the port is negatively very significant (1-5%) - the closer to the port, the more expensive (Corfu, Kefallonia, Rhodes)- apart from specific cases (eg. Lesvos)For the smaller islands (not very big in size) the time distance to the port was not very significant - apart from specific cases (eg. Paros – Milos – Salamina commuting purposes)11/36 islands showed significance in some of the regressionsWhere: 10-13 had negative significance (the less the time - the closer to the port- the more expensive)

While: 3/13 had positive significance (the less the time – the closer to port – the less expensive)

Dimitra Kavarnou - Henley Business School, University of ReadingSlide29

RESULTS – VI

Time Distance to Airport:For some of the islands the time distance to the airport is

positively very significant (1-10%) – the closer to the airport the less expensive - apart from specific cases (eg. Milos) - Probably because of the noise and disturbance.8/22 islands showed significance in some of the regressionsWhere: 5/8 had positive significance (the less the time - the closer to the airport- the less expensive)While: 3/8 had negative significance (the less the time – the closer to airport – the more expensive)Dimitra Kavarnou - Henley Business School, University of ReadingSlide30

Thank you

Dimitra Kavarnou - Henley Business School, University of Reading