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Attribute non-attendance is an estimation problem that biases welfare estimates in the economic valuation of environmental goods when choice experiment (CE) is used. The potential for observing the problem is increased when segmented markets with dissimilar preferences exist for environmental goods but not captured in the experimental design for CE. The current procedure for avoiding this problem relies on qualitative techniques, which limits applications to large samples and thus prone to bias. To reduce such bias, this study used an alternative technique based on the design-attribute relative importance index (DARII) to determine respondents’ prioritization of attributes within and across markets. Our results in solid waste management services demonstrate that all selected attributes were highly ranked across markets. While such finding conforms to expectations based on the interview, we found a statistically significant difference in attributes prioritization across markets. We thus conclude that assuming equal priority for attributes in different market segments may be improper but possibly tangled when the qualitative method is used. As such, the study recommends CE studies to use DARII before the experimental design stage.

Attribute non-attendance is an estimation problem that biases welfare estimates in the economic valuation of environmental goods when choice experiment (CE) is used. The potential for observing the problem is increased when segmented markets with dissimilar preferences exist for environmental goods but not captured in the experimental design for CE. The current procedure for avoiding this problem relies on qualitative techniques, which limits applications to large samples and thus prone to bias. To reduce such bias, this study used an alternative technique based on the design-attribute relative importance index (DARII) to determine respondents’ prioritization of attributes within and across markets. Our results in solid waste management services demonstrate that all selected attributes were highly ranked across markets. While such finding conforms to expectations based on the interview, we found a statistically significant difference in attributes prioritization across markets. We thus conclude that assuming equal priority for attributes in different market segments may be improper but possibly tangled when the qualitative method is used. As such, the study recommends CE studies to use DARII before the experimental design stage.

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.

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.