Impact of HVOTL on Residential Property Value: An Australian Case StudyOverh Transmission Lines on Property Value – An Australian Residential Case of High Voltage Overhead Transmission Lines on Property Value – An Australian Residential Case Study

Peter Elliott

Overview

The background The research question Research methods Results

The antecedents of HVOTL provision The post placement impacts The effect on individuals The impact on communities The effect on homeowners

Background

Theoretical Framework

HVOTL as a technological hazard and risk Externalities Risk assessment Perceived or real threat Perceptions to the homeowner Real estate behaviour and impact on prices

What has been done before?

Overseas studies on post placement impact Overseas studies on public perceptions No published studies in Australia A lack of a comprehensive framework and

model – antecedents of HVOTL provision as well post placement impacts.

Specified facilitative models needed to assist in analysing the problem comprehensively.

The research questions

What are the causes of variation in the homeowner’s risk perceptions and reactions when electricity suppliers propose new HVOTL infrastructure?

What are the effects of HVOTL provision on the homeowner’s property values?

Methodology

Focus groups Public telephone surveys Quantitative studies of possible post

placement impacts on property value

Focus Groups

Charters Towers

Ayr

B3

B1

B2

B4

Ipswich

North Lakes

Logan

Sub Regions within Brisbane

Redlands

Redlands

Redlands

Telephone Survey Telephone numbers were taken from three stratified sets of postcodes from

a computerised White Pages (residential directory for Queensland) to ensure that sufficient numbers in the urban, peri-urban and rural sub-samples were obtained for purposes of comparison. Systematic random sampling was used, in that every nth telephone number was dialled, on a rotational basis, until the quota was achieved.  The nth number was determined by dividing the telephone numbers available by the required quota. A demographically representative cross-section of the population normally falls into place by employing this method of telephone contact.  Respondents were screened for home ownership status and then neighbourhood by asking whether where they lived could be described as:

  A built-up urban area, living close to neighbours

   Peri-urban acreage or semi-rural living

A truly rural area, as in living on a farm      

Independent Variables Extremely

Negative

Negative

Urban (ref rural)    

Rural Residential (ref rural)    

Gender (ref female)    

Professional Occupation (ref

not employed)

   

Non-Professional Occupation

(ref not employed)

   

Intervening Variables    

Concern about health risks    

Concern about visual/noise

impacts

   

Concern about safety risks    

Concern about environmental

impacts

   

Concern about property

interference

   

Summary of Significant Predictors of Negative/ Extremely Negative Attitude to HVOTL Placement × Significant predictors at p < 0.05;

Homeowners and Professional Stakeholders showing ‘Very High’ Concern for HVOTL Risks

0

5

10

15

20

25

30

35

40

45

Wire & Tower100M

Wire 100M Wire & Tower500M

Wire 500M

Home Owner (TelephoneSurvey)

Home Owner (Focus Groups)2

Property Valuer

Real Estate Agent

Developer

Percentage Reduction in Value

Figure 6

Homeowners and Professional Stakeholders showing Perceived Impacts on Property Value

House location Altitude Latitude?  Longitude   House sale date 1st Sales Date  2nd Sales Data  3rd Sales Date  4th Sales Data   House sale prices 1st Sales Price  2nd Sales Price  3rd Sales Price  4th Sales Price   Number of Bedrooms Continuous

 Number of Toilets ContinuousNumber of Garage Continuous

 Land size Per sq metre

 Building Age Year of Built

 HVOTL variables

Proximity to HVOTL Metre   Visibility High

  Moderate

  Low

Invisible

Selected housing attributes and HVOTL externalities

Sold houses in Eight Mile Plains by distance buffers 2001 to 2010

Selected property sample for visual assessment

 P(price of house) = f (housing characteristics, h1, h2…,hk, HVOTL externalities e1, e2…ek, other factors r1, r2…rk).

Hedonic Regression Equation

Property price estimates using the proximity of HVOTL and degree of visual encumbrance.degree of visual encumbrance.

 

Scheme 1   Scheme 2 Scheme 3B Std. Beta

B Std. BetaB Std. Beta

(Constant) 5832.389   -24759.165*   -83910.924*

Bedrooms 63907.084*** 0.356 62557.489*** 0.34960389.708*** 0.337

Baths 21383.383*** 0.172 20611.734*** 0.166 20403.040*** 0.164

Garages 28334.699** 0.113 28044.342** 0.111 28651.166** 0.114

Land size 153.639*** 0.186 171.164*** 0.208 185.899*** 0.225

Distance to HVOTL

    60.174** 0.112

Visual Prevalence

 

  31304.899*** 0.152

R20.559

 0.325 0.334

Adjusted R20.306

 0.317 0.326

F-value 46.097 

38.901 40.572

Significance of F-value

0.001

 

0.001 0.001

N (obs) 409 

409   409  

*** P < 0.001 ** P < 0.01 *P < 0.05

Table 11.4: Property price estimates using the proximity of HVOTL anddegree of visual encumbrance.

• The property sale prices within 50m distance from the HVTOL (Red marked) are 20% less than the mean house price within Eight Mile Plains.

• The distance between 50 and 100m shows approximately 15% lower than the mean price.

• The mean property price between 100 and 200m is $370,000, around 7% lower than the mean sale price.

• However, it seems that there is little impact on the property prices if distances over 200m

Descriptive Statistics

250

275

300

325

350

375

400

425

450

475

500

300m 200m 100m 50m

Distance

Local mean price

Suburb mean price