TY - JOUR

T1 - Correcting for non-response bias in contingent valuation surveys concerning environmental non-market goods

T2 - an empirical investigation using an online panel

AU - Bonnichsen, Ole

AU - Olsen, Søren Bøye

PY - 2016

Y1 - 2016

N2 - Data collection for economic valuation by using Internet surveys and pre-recruited Internet panels can be associated with severe disadvantages. Problems concerning sample coverage and sample representativeness can be expected. Representation errors may occur since people can choose whether to be part of an Internet panel and subsequently whether they wish to participate in the survey, thereby introducing two elements of potential self-selection. These elements may be correlated with preferences, thus making the respondents a non-random and non-representative sample, ultimately biasing results. This paper analyses a sample used for an Internet contingent valuation method survey eliciting preferences for improvements in water quality of a river. We find that some variables that affect the survey participation decision also affect willingness-to-pay, consequently biasing our welfare estimates. We show how adjusting willingness-to-pay for this bias can be accomplished by using a grouped data model incorporating a correlation parameter to account for selection.

AB - Data collection for economic valuation by using Internet surveys and pre-recruited Internet panels can be associated with severe disadvantages. Problems concerning sample coverage and sample representativeness can be expected. Representation errors may occur since people can choose whether to be part of an Internet panel and subsequently whether they wish to participate in the survey, thereby introducing two elements of potential self-selection. These elements may be correlated with preferences, thus making the respondents a non-random and non-representative sample, ultimately biasing results. This paper analyses a sample used for an Internet contingent valuation method survey eliciting preferences for improvements in water quality of a river. We find that some variables that affect the survey participation decision also affect willingness-to-pay, consequently biasing our welfare estimates. We show how adjusting willingness-to-pay for this bias can be accomplished by using a grouped data model incorporating a correlation parameter to account for selection.

KW - contingent valuation

KW - Internet panel

KW - sampling bias

KW - selection bias

KW - stated preferences

U2 - 10.1080/09640568.2015.1008626

DO - 10.1080/09640568.2015.1008626

M3 - Journal article

AN - SCOPUS:84949624715

VL - 59

SP - 245

EP - 262

JO - Journal of Environmental Planning and Management

JF - Journal of Environmental Planning and Management

SN - 0964-0568

IS - 2

ER -