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Valuing Environmental Goods and Services: An Economic Perspective Read chapter Read first chapter

2017 | OriginalPaper | Chapter

3. Collecting Nonmarket Valuation Data

Author : Patricia A. Champ

Published in: A Primer on Nonmarket Valuation

Publisher: Springer Netherlands

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Abstract

This chapter describes how to collect primary and secondary data for nonmarket valuation studies. The bulk of this chapter offers guidance on how to design and implement a high-quality nonmarket valuation survey. Understanding the full data collection process will also help in evaluating the quality of data that someone else collected (i.e., secondary data). As there are not standard operating procedures for collecting nonmarket valuation, this chapter highlights the issues that should be considered in each step of the data collection process from sampling to questionnaire design to administering the questionnaire. While high-quality data that reflect individual preferences will not ensure the reliability or validity of estimated nonmarket values, quality data are a prerequisite for reliable and valid nonmarket measures.

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previous chapter Conceptual Framework for Nonmarket Valuation
next chapter Contingent Valuation in Practice
Footnotes
1
Post hoc adjustments are weights applied to the data so that the sample has a distribution on key variables (usually demographic variables) that is similar to the population of interest. Groves et al. (2009) described approaches for weighting data. Post hoc adjustments are also made to data collected using probability sampling to correct for nonresponse error.
 
2
The study was a split sample test of different decision rules in a contingent-valuation question. Because we did not need to draw inference to a larger population about the magnitude of the estimated contingent values, a nonprobability sample was used.
 
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Metadata
Title
Collecting Nonmarket Valuation Data
Author
Patricia A. Champ
Copyright Year
2017
Publisher
Springer Netherlands
Book
A Primer on Nonmarket Valuation

Print ISBN: 978-94-007-7103-1

Electronic ISBN: 978-94-007-7104-8

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-94-007-7104-8_3