This paper proposes an alternative approach to addressing the complex problems of climate change caused by greenhouse gas emissions. The author, who won the 2009 Nobel Prize in Economic Sciences, argues that single policies adopted only at a global scale are unlikely to generate sufficient trust among citizens and firms so that collective action can take place in a comprehensive and transparent manner that will effectively reduce global warming. Furthermore, simply recommending a single governmental unit to solve global collective action problems is inherently weak because of free-rider problems. For example, the Carbon Development Mechanism (CDM) can be 'gamed' in ways that hike up prices of natural resources and in some cases can lead to further natural resource exploitation. Some flaws are also noticeable in the Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD) program. Both the CDM and REDD are vulnerable to the free-rider problem. As an alternative, the paper proposes a polycentric approach at various levels with active oversight of local, regional, and national stakeholders. Efforts to reduce global greenhouse gas emissions are a classic collective action problem that is best addressed at multiple scales and levels. Given the slowness and conflict involved in achieving a global solution to climate change, recognizing the potential for building a more effective way of reducing green house gas emissions at multiple levels is an important step forward. A polycentric approach has the main advantage of encouraging experimental efforts at multiple levels, leading to the development of methods for assessing the benefits and costs of particular strategies adopted in one type of ecosystem and compared to results obtained in other ecosystems. Building a strong commitment to find ways of reducing individual emissions is an important element for coping with this problem, and having others also take responsibility can be more effectively undertaken in small- to medium-scale governance units that are linked together through information networks and monitoring at all levels.