Control variables

All specifications include a number of socio-economic, demographic and housing variables, which have been previously highlighted in the literature as important determinants of household investment in energy efficient technologies, to address potential omitted variable bias related to the households’ utilisation, taste and experience of energy efficiency. The variables sample statistics are recorded in Table 6 and the definitions and respective labels are reported in Table 7.

Most importantly income and energy use is controlled for. In an analysis of the determinants of energy efficient uptake, Ameli and Brandt (2014) and Caird et al. (2008) suggest that income plays a key role in the investment decision. Heat demand has also been highlighted as an important determinant of investment (Michelsen and Madlener, 2012). Acknowledging the importance of both income and fuel expenditure

a low-income-high-cost indicator is created28 _{to control for the relative impact of}

poverty and affordability on the investment decision (Hills, 2012). One anticipates that the Low-Income-Low-Cost (LILC) group to be the least likely to participate due to financial constraints, followed by Low-Income-High-Cost (LIHC) as the relative burden of higher bills may motivate households to find alternative sources of energy. Following the same reasoning, the High-Income-Low-Cost (HILC) group is expected to be more likely to connect than LIHC though less likely than the High-Income- High-Cost (HIHC) group.

28 _{Low-income is defined as annual income falling below 60% of the median before deducting housing}

The variables expected to have a positive influence on technology adoption include: homeownership (Gillingham et al., 2012) and education (Michelsen and Madlener, 2012). Additionally, gender has been previously noted as having limited influence (Ameli and Brandt, 2015); the present analysis consistently finds an insignificant gender effect on the participation in a district heating scheme and therefore this

variable is excluded from the final model29_.

In contrast, variables expected to exert a negative influence include age, particularly over 60 years (Ameli and Brandt, 2014; Mills and Schleich, 2012), marital status, structural imperfections in the property, and economic inactivity (Davis, 2010). Regional effects could be positive or negative depending on the local socio-economic conditions (Davis, 2010; Michelsen and Madlener, 2012; Mills and Schleich, 2012). It is important to note that limited evidence is found to support the hypothesis of postcode or (aggregated) parliamentary constituency effects in the main analysis, nonetheless the regional impact is further explored in the robustness checks that

follow30.

Finally, an indicator variable is included to control for the use of prior knowledge about the energy efficient technology in the investment decision (Mills and Schleich, 2012). The variable is set equal to 1 for ‘at least average’ knowledge of DH and 0 otherwise. Further, the effect on adoption could be positive or negative depending on the general public perception of district heating technology. The DH knowledge

29 _{The null hypothesis of an insignificant gender effect cannot be rejected in the full-specification (p-}

value=0.32).

30 _{For example, the individual constituency effects are all insignificant (at the 10% level) in the full-}

indicator was interacted with the installation costs of district heating to capture the effect of the perception of the upfront costs on participation between those who have above average knowledge of district-heating schemes as compared with below average knowledge.

Table 6: Income and socio-economic variables Sample

Variable N Mean S.D. Median Min Max

Income variables

Annual income 645 22994 18396 18462 2830 201460

Annual energy costs

Annual gas bill 683 711.79 431.25 611.56 0 3577.82 Maintenance costs 558 224.01 893.44 50 0 15000 Low-income-high-cost indicator LILC 784 0.12 0.33 0 0 1 LIHC 784 0.11 0.31 0 0 1 HILC 784 0.23 0.42 0 0 1 HIHC 784 0.22 0.41 0 0 1 UNSURE BILLS/INCOME 784 0.33 0.47 0 0 1 Demographic variables NON-OWNER 784 0.65 0.48 0 0 1 DEGREE 784 0.30 0.46 0 0 1 ELDERLY 784 0.35 0.48 0 0 1 SINGLE 784 0.21 0.41 0 0 1 INACTIVE 784 0.36 0.48 0 0 1 DAMP 784 0.67 0.47 1 0 1 KNOWS DH 784 0.15 0.36 0 0 1

Table 7: Variable definitions and labels

Variable name Specification Definition

Vignette variables

DH BILL [550, 750, 800] Annual district heating bill allocated to household (£100s).

INTERFACE [1500, 1750, 2000] Upfront cost of district heating heat interface unit allocated to household (£100s).

Heuristic Variables

Log (payback period)

PBK-LM 1 = Yes

0 = No

Low-mid (2nd_{) quartile of payback}

period.

PBK-MH 1 = Yes

0 = No

High-mid (3rd_{) quartile of payback}

period.

PBK-H 1 = Yes

0 = No High (4

th_{) quartile of payback period.}

NEG SAVINGS 1 = Yes

0 = No Current annual bill < district heating bill. DK-ANNUAL COSTS 1 = Yes

0 = No Household is unsure/does not know energy or maintenance costs.

Inattention variables

POST 1 = Yes

0 = No

Household prefers information to be sent by post.

INDIRECT 1 = Yes

0 = No

Household prefers indirect information delivery.

INATTENTIVE A 1 = Yes 0 = No

Household prefers to remain inattentive.

HIGH UNOBSERVED COSTS

1 = Yes 0 = No

Household requires at least £300 reduction in annual energy bill to join a DH scheme (given upfront costs are zero).

INATTENTIVE B 1 = Yes 0 = No

Household unsure/does not know reduction in annual energy bill required to join DH scheme (given upfront costs are zero).

Low-Income-High Cost Indicator

LIHC 1 = Yes

0 = No

Annual income falls below 60% of median income and annual energy expenditure is above the median.

LILC 1 = Yes

0 = No Annual income falls below 60% of median income and annual energy expenditure is below the median.

HIHC 1 = Yes

0 = No Annual income above 60% of median income and annual energy expenditure is above the median.

HILC 1 = Yes

0 = No

Annual income above 60% of median income and annual energy expenditure is below the median.

UNSURE BILLS/INCOME 1 = Yes 0 = No

Household representative is unsure of annual energy bills and/or prefers not to say annual income.

Demographic and housing variables

INACTIVE 1 = Yes

0 = No All residents in the household are unemployed and have not sought work in the last 2 weeks and/or unavailable to work in the following 4 weeks.

SINGLE 1 = Yes

0 = No Household representative’s marital status is single.

ELDERLY 1 = Yes

0 = No

Household representative is aged over 60.

DEGREE 1 = Yes

0 = No Highest educational attainment of the household is at least a degree qualification.

NON-OWNER 1 = Yes

0 = No

Household does not own their property.

DAMP 1 = Yes

0 = No At least one structural problem in the home e.g. damp, rot or leaky roof.

KNOWS DH 1 = Yes

0 = No

Household representative has at least an ‘average’ understanding of district heating schemes.