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



Table 2:

Estimation Results of Logit Models

CLogit

RP. Logit

×10-2

CLogit

RP. Logit

with EC.

with EC.

Cost (Cij)

-12.667**

-12.873**

-18.469**

-18.410**

Energy Savings (∆Qij)

22.700**

23.296**

32.806**

32.843**

Interaction of Cost with

Energy Consumption

0.101 **

0.102**

0.157**

0.157**

Income

-0.124*

-0.129*

-0.177**

-0.182**

Information Access

0.116

0.121

0.157*

0.157*

East

4.783**

4.946**

7.723**

7.724**

Interaction of Energy Savings with

Energy Consumption

-0.162**

-0.167**

-0.239**

-0.241**

Income

0.100

0.105

0.152*

0.158*

Information Access

-0.020

-0.022

-0.020

-0.020

East

-0.980

-1.073

-2.817

-2.770

Standard deviation for random parameters distribution

Cost

4.732

0.110

Energy Savings

1.289

0.318

Standard deviation for error components

No renovation

0.365

0.501

Annoying renovation

210.741**

211.819**

Log-Likelihood

-5054

-5054

-5035

-5034

**significant at the 1% level,

* significant at the 5% level. Alternative specific constants not presented.

3 Results

In this section we present the results of the discrete choice models. The section
begins with a cataloging of the coefficient estimates followed by a comparison of
model fit. Thereafter we derive the marginal WTP and present its distribution
over households. The section closes with a discussion of free-ridership and policy
implications.

3.1 Coefficient Estimates and Model Fit

Table 2 presents the results of a conditional-, random parameters-, error com-
ponents, and error components with random parameters logit model. All four
models tell a consistent story. The signs of the significant coefficients are the

15



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