5. Public perception of shallow groundwater pollution: methodology and results of the
5.5 Lessons from the contingent valuation survey
5.5 Lessons from the contingent valuation survey
The contingent valuation survey has produced first results in terms of people’s willingness to pay for groundwater improvement programmes for the Krska kotlina aquifer . Overall, 63% of the total sample is willing to pay for groundwater improvement programmes aimed at stabilising groundwater quality below drinking water threshold values with an average value of 1 350 SIT per household per month. But only 40% of the total sample is willing to pay for more ambitious improvement programmes aimed at bringing groundwater quality close to natural concentrations and thus eliminating any possible risk to connected ecosystems. The additional contribution for this second programme is equal to 1 150 SIT per household per month on average. These values are around 15% to 20% of household’s average monthly water bill.
The main lesson from the regression analyses is that location has an important impact on people’s willingness to pay and on the contribution to groundwater improvement programmes. The total mean value for households living on top of the aquifer is 2 591 SIT while other households state an amount of 1 688 SIT on average. Trust in the programme is also a key factor influencing people’s willingness to pay. Belonging to an environmental organization or citing the preservation of the patrimony as the main motivation to pay show interest for environmental matters. This interest is expressed through higher contributions to groundwater improvement programmes. However, contribution is not only a matter of interest, location and trust. It also depends on people’s incomes. Low income groups will contribute with smaller amounts to the first groundwater improvement scenario and will be less willing to pay for both scenarios.
Different models were developed to explain respondents’ willingness to pay and the values they cite. Table 14 summarises the results of the regressions for comparison.
• Low income is significant at least at the 5% level and has a negative sign in all models.
• Households with an income below 200 000 SIT per month would be less willing to pay for protecting the aquifer and improving its quality.
• Living on top of the aquifer has positive coefficients that are statistically significant for most of the models. Among respondents willing to pay (see ols model), living above the aquifer increases respondents’ willingness to pay by 18%, indicating that respondents attach a higher value to the aquifer partly due to the use value they might attach today or in the future. Living at more than 5 km of the aquifer has an negative significant impact on willingness to pay since it makes people pay 48% less.
Table 14. Summary of regression results
Scenario 1 for groundwater improvement (drinking water) Scenario 2 for groundwater improvement (natural
Number of observations 354 230 199 (including
• Low income and living above the aquifer are the two variables that appear in regression on decision to pay (logistic) and regression on willingness-to-pay amounts
14 Excluding protest answers
15 Excluding true zero bidders
- for positive bidders (ols) and for all respondents (Tobit). Their sign and level of significance are robust across all models.
• Among respondents who are willing to pay (ols), the elasticity with regards to the water bill is 0.33. This implies that an increase by 10% of the water bill leads to an increase in willingness to pay values by 3.3%.
• Coefficients are much more important in the Tobit regression. Due to the inclusion of zeros in the regression, elasticities are also larger. But the relative importance of coefficients between variables remains the same and is consistent for the different models tested. For example, drinking tap water remains the variable with the highest coefficient similar to the ols regression.
• In the Heckman regression, two regressions are estimated at the same time: the first regression explains why respondents do not reveal their willingness to pay as a sign of protest while the second regression explains the amount. This model takes selection into account: some variables are censored because respondents do not want to say how much they would be willing to pay as a means of protest. In this special case, equations are considered as independent.
Overall, results are in line with other contingent valuation studies16. One noticeable difference relates to gender. According to past studies in European countries, males are expected to be willing to pay more than female. This gender-based difference is however not found in the Krsko kotlina aquifer area.
The relatively low explanatory power of models is also in line with what is found in other contingent valuation studies. R2 are small, be it in the Slovenian contingent valuation or in other contingent valuation studies – if this information is provided at all in other studies (which is not always the case). For example, Park and Al. (2002) undertake a Tobit regression aiming at explaining the willingness to pay to preserve health of coastal coral reefs and current water quality. But they do not give information about goodness of fit. In the same way, Bateman and Al. (2005) do not provide pseudo-R2 in their random effects Tobit regression17. For studies mentioning this kind of statistics, one can quote Frew and Al.
(2001) who obtained adjusted R-square of 0.034 and 0.04518 when working on logistic regressions predicting willingness to pay of zero for colorectal cancer screening. For linear regression on positive willingness to pay values, adjusted R-square are equal to 0.075 and 0.126. Cho (Cho and Al., 2005) also obtains quite low values for Heckman estimates and did not provide values for Tobit regressions. One exception is the analysis by Rozan and Al.
(1997) who investigated inhabitants’ willingness to pay for improvement in groundwater quality. R2 for the ols method provided in this study on data for all inhabitants or separated between users and non-users are rather small, ranging from 0.13 to 0.2. Concerning the decision to pay, the Mac Fadden R219 was equal to 0.73 for users, admittedly, but equal to 0.024 for non users and 0.084 for both users and non users considered together.
It is also important to stress that the total number of variables significant in regressions found significant in our Slovenian models is very similar to what is found in other similar studies (see for example Cho and Al., 2005)
16 See for example Willinger and Stenger “Preservation Value for groundwater quality in a large aquifer : a contingent valuation study of the Alsatian aquifer” in Journal of Environmental Economics (1998), 53 177-193.
17 The purpose of the article is to compare the contingent valuation method and the contingent ranking method on the valuation of improvements to the water quality of an urban river.
18 WTP has been explained for both type of screening for colorectal cancer .
19 Mac Fadden R2 is a pseudo R2