To economically justify the need for better SWM services in the developing countries, good valuation studies on the potential benefits of such services are necessary. Several techniques for assigning economic values to SWM services have been used in the literature, including travel cost (Anex, 1995), hedonic housing price (Arimah, 1996), choice modeling or experiments (Huhtala, 1999; Othman, 2002; Naz and Nazm 2005 and Boyer, 2006 and Jin et al. 2006). But the method that is used the most is the method of contingent valuation or ranking; a non-exhaustive research in the literature gives a list of 19 contingent valuation studies in this area<sup>4</sup> . Evidence from the existing research suggests that the estimates of environmental and public good benefits from well-designed and properly executed contingent valuation surveys appear to be at least as good as estimates obtained with other valuation techniques (OECD, 1994, Mitchell and Carson 1989, Whittington et al., 1990).

Two advantages can further explain the widespread use of the contingent valuation method in environment-related public service valuations. The first is its flexibility. Based on hypothetical markets that can be flexibly defined by researchers according to the specific characteristics of the public services in question, the respondents of valuation surveys are invited to directly state their preferences and to reveal their willingness-to-pay for the specified qualities or quantities of improvement. This is very different from the hedonic price method, whose applicability to a public service valuation depends closely on the existence of compatible real-market data. The second advantage is the capacity of contingent valuation method to measure not only the use value but also other intangible values from the improved public service, such as the non-use value and especially the existence value (Krutilla, 1967). This is very different from the market-based valuation methods, such as the travel cost method, which can only measure (partial) use values of a public service.

Though the contingent valuation method can be a feasible and valid technique to measure the levels of payment for SWM services (Altaf et al. 1994; Altaf and Deshazo, 1996; Whittington et al., 1991), contingent valuation studies for SWM projects in the developing countries have mostly been conducted after 2000<sup>5</sup> . Few such studies have been conducted in China, especially on SWM services in small towns.

This paper reports on a contingent valuation study we conducted in Yunnan, China, on municipal solid waste management based on a real investment project which was intended to improve the solid waste collection and disposal system in county-level and township-level small towns.<sup>6</sup> The project was to be located in Eryuan County of Yunnan Province, and the survey was conducted there in the summer of 2007. Because the survey was conducted for the benefit-cost analysis of a real investment project proposal, the hypothetical nature of a contingent valuation study, which is the single most important criticism of the method for potential biases, can be ameliorated, and therefore the results can be more reliable.

> 4 Altaf and Deshazo, 1996; Lake et al., 1996; Tiller et al., 1997; Adaland and Caplan, 1999; Huhtala, 1999; Sterner and Bartelings, 1999; Caplan et al. 2002; Othman, 2002; Bluffstone and DeShazo, 2003; Huang and Ho, 2005; Palatnik et al. 2005, 2008; Basili et al. 2006; Jin et al. 2006; Lal and Takau, 2006; Fonta et al. 2007; Osumanu, 2007; Afroz et al. 2009, and Ichoko et al. 2009.

> 5 Examples include Othman (2002) on Malaysia, Bluffstone and Deshazo (2003) on Lithuania, Huang and Ho (2005) on Taiwan, China, Naz and Naz (2005) on Philippines, Jin et al. (2006) on Macao, Lal and Takau (2006) on Kingdom of Tonga, Fonta et al. (2007) and Ichoku et al (2009) on Nigeria, Osumanu (2007) on Ghana, and Afroz et al. (2009) on Bangladesh.

> 6 The administrative system in China is composed of 5 levels: nation, province, prefecture/municipality, county, township/xiang,  from the highest to the lowest respectively.

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