The University of Tennessee
Natural Resource Policy Center
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Consumer Labeling and Motivation Crowding-Out

NRPC Lead:
Christopher Clark

Outside Researchers: Kimberly Jensen, Steven Yen, W. Michael Hanemann, Clifford S. Russell

Research Assistants: Pamela Ellis

Funding Source: US Environmental Protection Agency STAR Grant

Project Description
This project will explore individual responses to environmental product labels. The focus of the project will be on: (i) measuring the effect of environmental labels on consumer willingness-to-pay for a market good and (ii) determining whether the effect is greater or less for an environmental attribute with both public and private benefits than an attribute with purely public benefits. A well-developed body of research suggests that the inclusion of relatively small extrinsic rewards (such as cost savings from an energy-efficient appliance) can actually decrease the effect of existing intrinsic rewards (such as the internal motivation for consuming an environmentally friendly product). This effect, commonly referred to as motivation crowding out, has important implications for the selection, design and marketing of environmental labels.

The exploration of consumer responses will involve the use of conjoint analysis (contingent choice) surveys in which sub-samples of respondents reveal their preferences in a series of comparisons between varieties of an energy-using home appliance. The appliance varieties will be distinguished by different levels of privately relevant attributes, including price, and by whether or not they have obtained an environmental seal-of-approval. The benefits associated with the seal will vary across sub-samples. In two sub-samples, both private and public benefits (e.g., energy cost savings and emissions reductions) will be associated with the seal, while only public benefits will feature in the other two. The magnitude of the benefits will vary between a low and a high value, for a total of four separate sub-samples. Responses will be analyzed using multinomial logit methods. To allow for heterogeneity of respondents, models in which logit coefficients vary across individuals, either continuously using random coefficient methods, or over a finite number of “classes,” using finite mixture methods, will be used.

Project Links

Christopher Clark

University of Tennessee
Agricultural Economics

Kimberly Jensen
University of Tennessee
Agricultural Economics

Steven Yen

W. Michael Hanemann
University of  California
Agricultural & Resource Economics

Clifford S. Russell
Vanderbilt University
Department of Economics

Pamela Ellis
University of Tennessee
Agricultural Economics

U.S. Environmental
Protection Agency STAR

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~To enhance policy making relative to the sustainable management
of natural resources in Tennessee and the Southeastern Region~
The University of Tennessee