chapter  21
3 Pages

Conclusions and future research: John C. Whitehead, Timothy C. Haab, and Ju-Chin Huang

ByJOHN C . WHITEHEAD , TIMOTHY C . HAAB AND

One of the major contributions of environmental economists to economic knowledge is the estimation of the benefits and costs of environmental policy. If you want an estimate of the environmental cost of the BP oil spill to Gulf of Mexico anglers or an environmentalist far from the blowout, an environmental economist can give you a hard, cold monetary answer. This often leads to disagreements with those on the right and left of the environmental spectrum and, even, other economists. Not surprisingly, business people don’t like so much attention paid to the benefits of environmental policy because it might cost them money. So, they tend to hire non-environmental economists, who are already queasy about “nonmarket valuation” methods, to discredit the methods of environmental economists (e.g. the “contingent valuation debate”). Measuring the benefits of environmental policy is also often questioned by environmentalists who either say it is immoral or crass to put dollar values on intangible benefits or that these benefits are infinitely valued. One response is that people through their behavior put finite values on the environment every day. Environmental economists simply report this behavior. To some economists certain methods of nonmarket valuation may seem like pseudo-science since we consider behavior that is generally outside the market (where there are no obvious demand or supply curves). For example, we might consider the importance of the response of recreation travel to environmental quality or trust willingness-to-pay statements about environmental quality to infer benefits about environment policy. Within this broader context, this book demonstrates, in a number of ways, that the nonmarket valuation methods of environmental economists are of great use in the debates and analysis of environmental policy. The combination of revealed preference (RP) and stated preference (SP) data can exploit the advantages of each data source while mitigating the problems associated with their weaknesses. The gaps in this book suggest several directions for future research. In this chapter we briefly summarize four of these: econometric advances, new study designs, new types of data combination and new applications. While there has been some headway made in each of areas, significant growth is needed.