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Solid waste pollution concern in economic value assessment: Is it uni-dimensional or multi-dimensional?
•Solid waste pollution concern in a multi-dimensional variable.•Dual and tripartite factor models are appropriate for solid waste pollution concern.•The more exploratory factor model supports the dual factor model.•The less exploratory factor model supports the tripartite factor model. Pollution con...
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Published in: | Resources, conservation and recycling conservation and recycling, 2015-11, Vol.104, p.49-60 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Solid waste pollution concern in a multi-dimensional variable.•Dual and tripartite factor models are appropriate for solid waste pollution concern.•The more exploratory factor model supports the dual factor model.•The less exploratory factor model supports the tripartite factor model.
Pollution concern has been established as an important predictor of economic value ascription related to solid waste service improvement, such as recycling. However, the variable is not directly observable and as such, its influence is captured by existing applied economics papers via “yes” or “no” discrete-nominal measure. Such measure assumes the variable has one dimension. This leads to loss of information, considering its multi-dimensional structure in theory. It thus implies that, if a respondent in an economic valuation study indicates a support for an improvement signified by a “yes” response to valuation question, a uni-dimensional dummy variable cannot tell what dimension of concern the respondent subscribes to. Despite this importance of understanding the variable's dimension, it has rarely been explored. This study investigates such dimensions and our findings support the existence of both the theoretically espoused dual and tripartite factor models. This implies a possible misspecification in existing solid waste related studies that have most often captured the variables via uni-dimensional nominal-discrete measure. |
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ISSN: | 0921-3449 1879-0658 |
DOI: | 10.1016/j.resconrec.2015.02.007 |