Willingness-to-Pay for Energy Conservation and Free-Ridership on Subsidization

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

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

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