the distribution of domestic energy-tech in great britain: 2008 – 2011

The Distribution of Domestic Energy-Techin Great Britain: 2008 – 2011

Dr Ben Anderson

Research & Policy Workshop I17th December 2013

@dataknut

2

@dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011

Contents

Why bother?

Meet the data

Distributions

Factors predicting adoption

Summary

3


Contents

Why bother?

Meet the data

Distributions


Summary

4


Why bother?

Equity:– Uneven distribution of benefits

Regressive:– Benefits may accrue to the well off

Uptake may asymptote– To something…

5


Contents

Why bother?

Meet the Data

Distributions (over time)


Summary

6


Meet the Data

British Household Panel Survey– Wave 18 (2008-9)– N households = 6,500

Understanding Society– Waves 1-4 (2009-2013)

· Data for waves 1-3 available now

– N households = 30,000

2008 2009 2010 2011 2012 2013

We are here!

✔✔

✔✔

Eco-Tech & Behaviours/Attitudes

7


Meet the Data2008 2009 2010 2011 2012 2013

We are here!

✔✔

✔

2008_09

2008_10

2008_11

2008_12

2009_01

2009_02

2009_03

2009_04

2009_05

2009_06

2009_07

2009_08

2009_09

2009_10

2009_11

2009_12

2010_01

2010_02

2010_03

2010_04

2010_05

2010_06

2010_07

2010_08

2010_09

2010_10

2010_11

2010_12

2011_01

2011_02

2011_03

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

BHPS Wave 18 USOC Wave 1

N h

ouse

hold

s

✔

8


What Energy-Tech?

Energy ‘production’– Solar PV (electricity)– Wind Turbines (electricity)– Solar Thermal (hot water)

Key questions:– Who is adopting?– What factors predict this?– What difference does it make?

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Key variables:

Energy Tech uptake

Solar PV Solar Thermal Wind Turbine

Yes 0.53% 0.58% 0.04%

180 198 13

Considering 5.05% 4.33% 2.44%

1716 1471 828

No 88.51% 90.51% 94.86%

30095 30775 32254

Considered & rejected 5.91% 4.58% 2.66%

2011 1558 905

Solar PV only35%

Solar Thermal

only35%

Both30%

10


Key variables

Energy Tech uptake

‘Environmentally friendly’– Mean individual level actions + household level behaviours

Socio-economic– Tenure, Occupancy, Income, education levels, energy

consumption

Solar PV Solar Thermal Wind Turbine

Yes 0.53% 0.58% 0.04%

180 198 13

Considering 5.05% 4.33% 2.44%

1716 1471 828

No 88.51% 90.51% 94.86%

30095 30775 32254

Considered & rejected 5.91% 4.58% 2.66%

2011 1558 905

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Contents

Why bother?

Meet the data

Distributions


Summary

12


Distributions

Over time…

Source: Own calculations of pooled BHPS (W18) & USOC (W1) GB sub-sample Weighted for non response and correcting for survey design

Error bars = 95% Confidence intervals

2008 2009 20100.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

N households Have installed energy-techConsidering installing energy-tech Have thought about it & decided not to

13


Distributions

Over equivalised income quartiles

Source: Own calculations of pooled BHPS (W18) & USOC (W1) GB sub-sample weighted for non response and correcting for survey designError bars = 95% Confidence intervals

2008 2009 20100.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

Has energy tech

Equivalised income Q4 (highest)Q3Q2Equivalised income Q1 (lowest)

2008 2009 20100.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

Considering energy tech

Equivalised income Q4 (highest)Q3Q2Equivalised income Q1 (lowest)

Equivalised income: controls for household size (persons, OECD approach)

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Distributions

Over accommodation type


Equivalised income: controls for household size (persons, OECD approach)

2008 2009 20100.00%

0.50%

1.00%

1.50%

2.00%

2.50%

Has energy tech

DetachedSemi-detachedTerraceOther

2008 2009 20100.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

14.00%


DetachedSemi-detachedTerraceOther

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Distributions

Over tenure


Confirms: DECC (2012) Identifying trends in the deployment of domestic solar PV under the Feed-in Tariff scheme

2008 2009 20100.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

Has energy tech

OwnSocial rentOther/private rent

2008 2009 20100.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

9.00%

10.00%


OwnSocial rentOther/private rent

https://www.gov.uk/government/publications/identifying-trends-in-the-deployment-of-domestic-solar-pv-under-the-feed-in-tariff-scheme


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Distributions

Over energy consumption quartiles



2008 2009 20100.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

Has energy tech

Energy spend Q4 (highest)Q3Q2Energy spend Q1 (lowest)

2008 2009 20100.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%


Energy spend Q4 (highest)Q3Q2Energy spend Q1 (lowest)



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Distributions

Over ‘Environmentally friendly’ quartiles

Index: Mean of individual level scores + recycling + green electricity tariffSource: Own calculations of pooled BHPS (W18) & USOC (W1) GB sub-sample weighted for non response and correcting for

survey designError bars = 95% Confidence intervals

2008 2009 20100.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

Has energy tech

Enviro Friendly HH Q4 (highest)Q3Q2Enviro Friendly HH Q1 (lowest)

2008 2009 20100.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%


Enviro Friendly HH Q4 (highest)Q3Q2Enviro Friendly HH Q1 (lowest)

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Distributions

Urban vs rural

Source: Own calculations of USOC (W1) GB sub-sample weighted for non response and correcting for survey designError bars = 95% Confidence intervals

2008 2009 20100.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%

1.80%

2.00%

Has energy tech

UrbanRural

2008 2009 20100.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%Considering energy tech

UrbanRural




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Contents

Why bother?

Meet the data

Distributions


Summary

20


Adopted Energy Tech

Source: Logistic regression of BHPS (W18), USOC (W1) GB sub-sample. Error bars = 95% Confidence Intervals for coefficients

But: low explanatory power => Lots of unexplained variance

Other effects: rural (positive)

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‘Seriously Considering’ Energy Tech


Other effects: rural (positive)


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‘Rejected’ all Energy Tech


Other effects: rural (negative)


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Adopted Solar PV/Solar Thermal

High explanatory power => but much captured by intercept (not shown)And small n for adoption groups

Other effects: rural (positive) for Solar Thermal but not Solar PV


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Contents

Why bother?

Meet the data

Distributions


Summary

25


Summary

Adopters generally:– home-owning, (large) detached & rural– higher reported ‘enviro friendly’ views/actions

Those seriously considering generally:– As above– Already have some form of energy tech– Highest energy spenders

Rejecters generally:– Urban renters, not detached– Lower reported ‘enviro friendly’ views/actions– Lower energy spend

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Contrasts:

Solar PV & Solar Thermal Adopters:– Different housing type ‘effects’?– Different income ‘effects’?– Different ‘attitudinal’ effects

Overall:– Emphasis on constraints over choice– Equity issues are clear…Causa

lity

?

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Thank you

Questions?– [email protected]– @dataknut

http://www.energy.soton.ac.uk/esrc-sdai-attitudes

mailto:[email protected]




the distribution of domestic energy-tech in great britain: 2008 – 2011

Education

energy tech12

great britain

energy tech14

energy consumption

data distributions factors

equivalised income quartiles

equivalised income q4

equivalised income q4