The current empirical analysis is set in the Seoul metropolitan area and attempted to analyze the Korean population’s behavior vis-à-vis to open space and other factors that determine housing prices. Using the comprehensive real transaction price data and other geocoded socio-economic data, the analysis reveals that marginal implicit prices can be monetized by using estimates from the revealed preference method of hedonic price analysis and shows the SMA residents are willing to pay higher premiums for green and open spaces and other favorable unit and location characteristics. For example, the present analysis shows that homes decrease in value at rates of 14,614 KRW and 9,958 KRW per meter of distance: homes located closer to these amenities are worth more than those located at a distance. It implies that the government needs to pay a great deal of attention in a location decision of green and open spaces since new investment in green and open spaces would be likely to entail positive externalities or pitfalls in general.
The present analysis also suggests that, having marginal implicit prices in hand, a global demand curve can be derived – which can be then used as an important tool to estimate economic benefits of both environmental and non-environmental attributes of the project of our interests. It is important that economic benefits of environmental projects – public goods for which there is no entrance fee and therefore economic benefits cannot be estimated with a conventional economic analysis - can be estimated with revealed preference methods (i.e. hedonic price model) which are considered theoretically and empirically more sound than stated preference methods such as contingent valuation method because revealed preference methods analyze the behavior of actual market participants with advanced statistical methods.
Nevertheless, we should be cautious when applying hedonic price models to estimate economic benefits of environmental projects when the size and scale of the investment projects are large. This is because the scale and size of public goods investment projects that PIMAC analyzes are often so large that the spatially influenced area is also often large, which implies that it is likely that non-use values – which revealed preference methods cannot capture by nature - are in play. A vast size of area set in the present analysis helps to estimate economic benefits of large-scale projects. If non-use values are in play, however, socio-economic benefits will be, in theory, smaller than benefits predicted by contingent valuation methods. In such cases, we need to be cautious for applying revealed preference methods. Nevertheless, contingent valuation methods are subject to various types of biases arisen from diverse sources inherent in surveys and the well-known fact that free riders consuming public goods are less likely to state their WTP accurately. This often entails political conflicts in an investment decision making, which gives lights to consideration of revealed preference methods such as hedonic price models given that a more robust structural model is developed by the research followed.