Birr-Pedersen K. 2008. PhD thesis. Measurement and benefit transfer of amenity values from afforestation projects – A spatial economic valuation approach using GIS technologi. Environmental Economics and Rural Development Division, Institute of Food and Resource Economics, Faculty of Life Sciences, University of Copenhagen and Department of Policy Analysis, NERI. National Environmental Research Institute, Denmark. 197 pp.
Summary
Urban forests provide substantial non-market benefits to residents and out-of-town visitors in the form of amenity and recreational values. Newly planted forest areas can create amenity values to people living close to them less than 10 years after planting started. This has been confirmed by a number of non-market valuation studies in Denmark, Sweden and other European countries. Estimates of these values in monetary terms are an invaluable input in cost-effectiveness and cost –benefit analyses, both as primary benefits of the creation of new forest areas but also as secondary benefits in determining the net-costs of environmental protection measures that involve afforestation measures.
This kind of benefit transfer, i.e. the transfer of monetary estimates for environmental goods from a study site to a policy site, is a cost and time saving solution compared to conducting an original study. How uncertain such benefit transfers can be has been shown in several studies testing for accuracy of benefit transfer. Most of these benefit transfer testing studies are based on contingent valuation and travel cost models, only one is based on the hedonic pricing method, although this method is heavily applied in non-market valuation exercises.
In this Ph.D. thesis benefit transfer has been applied in three cases including one based on original empirical research. The results are presented in four articles included in the appendix of this report. In the first case of benefit transfer the implications for policy decisions of including monetary values for secondary effects have been demonstrated while the second benefit transfer application used values from Danish and Swedish forest valuation studies to determine the amenity and recreational values of forest in the urban fringe areas in Scania, South-western Sweden. In both cases results indicate substantial values for forest areas close to residential areas, but illustrate also the substantial uncertainty attached to this valuation methodology.
As an original empirical contribution this Ph.D. study has analysed three afforestation areas in Denmark using the hedonic pricing method in combination with Geographical Information Systems (GIS). Results confirm the positive effect of proximity to forested areas on housing prices found in earlier studies in Denmark. However, housing values are also impacted by other location-related attributes, natural or man-made, and their omission in estimating the hedonic price function can lead to omitted variable bias in determining the parameter for distance to afforestation areas and thus the marginal price for forest proximity.
For each case study area two different types of models were constructed, a “simple” model that only contained structural variables of the house and the “distance to the new forest” measure as explanatory variables and an “advanced” model that in addition to the variables of the simple model did include a range of other location-related variables, typical for Danish housing markets. Results show a mixed evidence of the importance of including other location-related characteristics in model estimation. For three models including other spatial variables resulted in substantial changes in the parameter estimated for the distance to new forest variable, changing the significance level of this coefficient from insignificant to significant and vice versa. Other models were relatively robust to the inclusion of other spatial variables.
This analysis shows the uncertainty involved in applying the hedonic pricing method to value non-market goods. Although based on real money transactions, i.e. the purchase of a house with certain characteristics, the likelihood of missing out on relevant variables is high, either because these are not easily accessible or too expensive to obtain. This can lead to omitted variable bias in the estimation of the parameter of interest and thus misleading information about marginal and non-marginal benefits to policy makers.
Based on the empirical results this Ph.D. study did test for accuracy of benefit transfer of amenity values from afforestation projects in Denmark using both the classical test of assuming equality and equivalence testing, where inequality is assumed in the null hypothesis. Amenity values were estimated by applying the first stage of the hedonic pricing method and then calculating the percent differences in housing prices for different distance intervals. While tests for statistical equality of WTP estimates could not reject the null hypothesis of equality between WTP estimates for different distances in the majority of cases it would be inadequate to interpret these results in favour of validity of benefit transfer. Transfer errors can be substantial also for those transfers where equality of WTP estimates could not be rejected.
A cautious approach to benefit transfer is also warranted given the results from the equivalence tests. For none of the transfers the null hypothesis of inequality could be rejected with error margins of 50 %. Only for transfers between two areas with rather similar WTP results, the majority of transferred values are accepted to be equivalent within error ranges of 75 %.
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