The housing market across the greek islands
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The Housing Market across the Greek Islands. Dimitra Kavarnou University of Reading d.kavarnou @ pgr . reading.ac.uk. A bit more of Geography…. A bit more of Geography…. > than 6,000 islands/isles 117 inhabited islands 79 islands >100 (population) 53 islands>1,000.

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The Housing Market across the Greek Islands

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The housing market across the greek islands

The Housing Market across the Greek Islands

Dimitra Kavarnou

University of Reading

[email protected]


A bit more of geography

A bit more of Geography…

Dimitra Kavarnou - Henley Business School, University of Reading


A bit more of geography1

A bit more of Geography…

  • >than 6,000 islands/isles

  • 117 inhabited islands

  • 79 islands >100 (population)

  • 53 islands>1,000

Dimitra Kavarnou - Henley Business School, University of Reading


The housing market across the greek islands

North East Aegean Sea Islands

Ionian Islands

Sporades Islands

Argo Saronic Islands

Cyclades Islands

Dodecanese Islands

Dimitra Kavarnou - Henley Business School, University of Reading


The housing market across the greek islands

Size…

Dimitra Kavarnou - Henley Business School, University of Reading


Attributes of the housing market i

Attributes of the Housing Market - I

  • Heterogeneity

  • Heterogeneity in many levels

    Property/ Neighbourhood/ Settlement (Villages/towns)/ Islands/ Groups of Islands

  • Housing Submarkets

    Islands – Groups of Islands

    2. Durability

  • Community formation (trade/ piracies/ occupations/ wars)

  • Horizontal ownership (bequests)

  • Ownership rate 80% - Cultural Aspect

  • Financial CourseBooms and Recessions

Dimitra Kavarnou - Henley Business School, University of Reading


Attributes of the housing market ii

Attributes of the Housing Market - II

3. Political Economy

  • Plethora of laws/ rules/ regulation

  • Tax Regime continuously changing – Unstable

  • New Laws and additional taxation established and applied from 01-01/2014

  • Taxation constitutes a Disincentive to be a homeowner – investor

    4. Transactional Costs

  • High Transaction Costs

  • Among the highest in EU

Dimitra Kavarnou - Henley Business School, University of Reading


Attributes of the housing market iii

Attributes of the Housing Market - III

  • Imperfect Information

  • Lack of an well-organised information institution

  • Insufficient National Cadastre

  • The area of the islands is not mapped

  • Competitive, unprofessional, non-accredited brokerage industry

  • Immovability

  • Any real estate/housing market is immovable

  • Increased demand for spatial development (amenities, infrastructure, employment, etc.)

  • More evident to islands which have physical boundaries

Dimitra Kavarnou - Henley Business School, University of Reading


Attributes of the housing market iv

Attributes of the Housing Market – IV

7. External Effects

Main 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 Reading


Hedonic research idea

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 Greece

  • The model controls for several structural and locational characteristics of the properties as well as economic and demographic attributes of the islands

Dimitra Kavarnou - Henley Business School, University of Reading


Methodology i

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)

    Pi,j,k = α + ∑β Xi,j,k + εi,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(Pi,j,k)= α + ∑β Xi,j,k + εi,j,k

Dimitra Kavarnou - Henley Business School, University of Reading


Methodology ii

Methodology - II

But

Τhere are also island characteristics for each island (j):

(2) log(Pi,j,k) = α + ∑βXi,j,k + ∑γZj,k + εi,j,k

Controlling the Fixed Effects for each island:

(3) log(Pi,j,k) = α + ∑βXi,j,k + δj + εi,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 Reading


Data i

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

Dimitra Kavarnou - Henley Business School, University of Reading


Data ii

Data - II

Limitations of the dataset

  • Not exact location (address/number, to many cases only local toponyms of settlements)

  • Either because of incomplete dataset from the estimators

    But

  • Mainly because the properties in the Islands do not have an address themselves but they refer to the closest village/settlement

  • With 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)

DimitraKavarnou - Henley Business School, University of Reading


Data iii

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 calculated

  • 2,000 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 Reading


Data iv

Data - IV

Spotting the properties in Google Earth (approximately)

Dimitra Kavarnou - Henley Business School, University of Reading


Data v

Data - V

Dimitra Kavarnou - Henley Business School, University of Reading


Data vi

Data - VI

Calculating time distances in Google maps

to port:to airport:

Dimitra Kavarnou - Henley Business School, University of Reading


Data analysis ii

Data Analysis - II

Dimitra Kavarnou - Henley Business School, University of Reading


Data analysis iii

Data Analysis - III

  • Deflation of Assessed Housing Prices

    The Prices are deflated and expressed in December 2012 prices:

    where:

    HICPDec2012= 123.28

    HICPt = 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:

  • Flat

  • Detached House

  • Maisonette

Dimitra Kavarnou - Henley Business School, University of Reading


Data analysis iv

Data Analysis - IV

  • Dummy Variables (Zj,k) for controlling:

  • The Presence of Airport on the island

  • The Presence of Prefectural General Hospital on the island

  • The Presence of University on the island

  • Dummy 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)

DimitraKavarnou - Henley Business School, University of Reading


Descriptive statistics of the groups

Descriptive Statistics – of the Groups

Dimitra Kavarnou - Henley Business School, University of Reading


Results ols groups

Results OLS - Groups

DimitraKavarnou - Henley Business School, University of Reading


Results fixed effects groups

Results Fixed Effects- Groups

Dimitra Kavarnou - Henley Business School, University of Reading


Results i individual islands

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 space0.34-1.07% 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 area0.07-0.50% 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 Reading


Results ii

RESULTS - II

  • The property type (flats/detached houses/ maisonettes) seems to be very significant for some of the islands

    Detached housesto 14/36 islands negatively very significant (1-5%) compared to flats

    i.e. The flats are moreexpensive 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 positivelyvery 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 Reading


Results iii

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 Capital

    For 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 Reading


Results v

RESULTS – V

Time Distance to Port:

  • For the bigger islands (big distances) the time distance to the port is negativelyvery 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 regressions

    Where: 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 Reading


Results vi

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 regressions

    Where: 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 Reading


The housing market across the greek islands

Thank you

Dimitra Kavarnou - Henley Business School, University of Reading


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