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Impact of HVOTL on Residential Property Value: An Australian Case Study Overh Transmission Lines on Property Value – An Australian Residential Case of.

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Presentation on theme: "Impact of HVOTL on Residential Property Value: An Australian Case Study Overh Transmission Lines on Property Value – An Australian Residential Case of."— Presentation transcript:

1 Impact of HVOTL on Residential Property Value: An Australian Case Study Overh 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

2 Overview The background The research question Research methods Results

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

4 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

5 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.

6 The research questions What are the causes of variation in the homeowners risk perceptions and reactions when electricity suppliers propose new HVOTL infrastructure? What are the effects of HVOTL provision on the homeowners property values?

7 Methodology Focus groups Public telephone surveys Quantitative studies of possible post placement impacts on property value

8 Focus Groups

9 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 n th telephone number was dialled, on a rotational basis, until the quota was achieved. The n th 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

10 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;

11 Homeowners and Professional Stakeholders showing Very High Concern for HVOTL Risks

12 Percentage Reduction in Value Figure 6 Homeowners and Professional Stakeholders showing Perceived Impacts on Property Value

13 House location Altitude Latitude? Longitude House sale date 1 st Sales Date 2 nd Sales Data 3 rd Sales Date 4 th Sales Data House sale prices 1 st Sales Price 2 nd Sales Price 3 rd Sales Price 4 th Sales Price Number of Bedrooms Continuous Number of Toilets Continuous Number of Garage Continuous Land size Per sq metre Building Age Year of Built HVOTL variables Proximity to HVOTL Metre VisibilityHigh Moderate Low Invisible Selected housing attributes and HVOTL externalities

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

15 Selected property sample for visual assessment

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

17 Property price estimates using the proximity of HVOTL and degree of visual encumbrance. degree of visual encumbrance. Scheme 1 Scheme 2 Scheme 3 BStd. Beta B B (Constant) * * Bedrooms *** *** ***0.337 Baths *** *** ***0.164 Garages ** ** **0.114 Land size *** *** ***0.225 Distance to HVOTL **0.112 Visual Prevalence ***0.152 R2R Adjusted R F-value Significance of F-value N (obs) 409 *** P < ** P < 0.01 *P < 0.05 Table 11.4: Property price estimates using the proximity of HVOTL and degree of visual encumbrance.

18 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

19 m200m100m50m Distance Local mean price Suburb mean price


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