Willingness-to-Pay for Energy Conservation and Free-Ridership on Subsidization – Evidence from Germany



Table 1: Mean Investment Cost and Mean Energy Savings

Number of
households chosen

Cost
in 1000
e

Q

in MWh

Error Comp.

1

2

No renovation

904

J

Roof

82

11.9

6.7

J

Window

116

6.3

2.8

Facade

26

10.5

7.2

J

Heating

313

2.3

3.3

Roof, Window

102

18.1

9.5

J

Roof, Facade

17

20.1

13.9

J

Roof, Heating

90

14.2

9.3

J

Window, Facade

31

16.7

10.1

J

Window, Heating

244

8.5

5.8

Facade, Heating

23

12.7

9.8

J

Roof, Window, Facade

56

26.3

16.8

J

Roof, Window, Heating

226

20.4

11.8

J

Roof, Facade, Heating

22

22.3

15.7

J

Window, Facade, Heating

70

19.0

12.3

J

Roof, Window, Facade, Heating

208

28.6

18.3

J

example, if ui1 = ui2 = 0 for all households i, and σψ2 1 = σψ22 = 0, then Equation
(8) collapses to the conditional logit specification.

In specifying the error components ψh , the aim was to capture latent effects
specific to an outcome or a set of outcomes. We explored several alternatives,
guided by the considerations noted above concerning both the hidden costs and
benefits of, respectively, grime and prestige associated with particular retrofit
options. The presented specification follows closely Cameron’s (1985) nested logit
analysis by incorporating two error components, the first of which distinguishes
the binary decision concerning whether to retrofit, and the second of which groups
13 of the remaining retrofit combinations that tend to produce annoying levels
of dirt and disarray (indicated in the final column of Table 1). We also explored
models with additional error components for alternatives conferring prestige, but

13



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