Stated preference approaches use hypothetical data to estimate the ex ante willingness to pay for various commodities. For example, the contingent valuation method can be used to estimate economic values of environmental resources, including nonuse values – those environmental values that are enjoyed by consumers who do not use the environmental resource on-site. Most economists, however, are firmly rooted in the revealed preference paradigm to estimate the use values of environmental resources. Revealed preference approaches are based on actual choices and actual choices based on real costs and benefits better reflect environmental values. During the decade of the 1990s the “contingent valuation debate” dominated the environmental valuation literature. Economists developed competing damage estimates associated with the Exxon Valdez oil spill, argued about whether nonuse values exist and whether the contingent valuation method is able to accurately measure them. Critics of the contingent valuation method argued that hypothetical behavior is too inaccurate to use for policy analysis. Proponents argued that contingent valuation generated value estimates that are no less accurate than those developed with revealed preference nonmarket valuation approaches. Economists tend to consider revealed and stated preference approaches as substitutes when choosing valuation methods. There are problems with this attitude. Since the revealed preference approaches rely on historical data, evaluation of new policies is often limited. Oftentimes, stated preference methods are the only way to gain policy relevant information. But, stated preference approaches are based on hypothetical survey data and respondents can be placed in unfamiliar situations. Revealed preference data is firmly planted in reality. Since the strengths of the revealed preference approaches are also the weaknesses of the stated preference approaches and vice versa, revealed and stated preference methods should be considered complements. The combination and joint estimation of revealed and stated preference data seeks to exploit the contrasting strengths of the revealed and stated approaches while minimizing their weaknesses (Cameron 1992; Adamowicz et al. 1994). Joint estimation has addressed a wide range of important issues in nonmarket environmentalvalu ation, including the hypothetical bias of contingent valuation and behavior data, the valuation of quality change that extends beyond the range of historical experience, and the development of new econometric and survey methods that specifically address data combination (Whitehead et al. 2008). Data combination can be used to mitigate a large number of problems. First, some revealed preference data are limited to analyzing a range of behavior in response to a limited range of market or environmental change. Stated preference surveys can be designed to collect data on hypothetical behavior, which allows estimation of behavior beyond the range of historical experience. Second, general population surveys can be used to survey users and nonusers of an environmental resource and analyze the decision to participate in the market. But these data are limited when trying to understand changes in participation. Combining revealed preference data with stated preference data from surveys of the general population can be used to understand changes in participation and the market size with new products or environmental changes. Third, there is often high correlation between independent variables in revealed preference data. Multicollinearity among characteristics leads …