Projects Funded for Dalia Ghanem


The Effectiveness of Reforestation: The Tradeoff between Climate Change Mitigation and Adaptation

Dalia Ghanem and Daria (Dasha) Ageikina


Specific Objectives of the Project:

The initial goal of the project was to assess the optimality of public reforestation projects in the context of both climate change mitigation and adaptation efforts in California and the U.S. We aimed to analyze the tradeoff between the climate mitigation value of afforestation and its cost in terms of wildfire risks. During the project, the objective became more specific. The focus shifted to the CARB’s Compliance Offset Program U.S. Forest Projects. The main final objective of the paper was to investigate whether the program’s design suffers from adverse selection that could lead to the program’s inefficiency.

Summary of Results:

In the program under consideration, an individual or an organization can get carbon offsets for engaging in one of the three activities: reforestation, improved forest management, or avoided conversion of forested land to other uses (such as residential areas or agricultural land). The main aim for each of them is to achieve a sustainable long-term growth of forests and maintain the stocking of trees at the project's designated land at a high level. The Compliance Offset Program does consider that wildfires might affect the forest projects and hence reverse the carbon sequestration. It treats the wildfire risk just like any other risk that can interrupt the project. To insure against such risks, the Air Resources Board maintains a Forest Buffer Account. Each project operator must contribute a part of their awarded carbon offsets to the Account. If an unexpected wildfire burns down the trees in the project area, the project operator will not lose the already awarded credits. The Account is insurance against such cases for both project operators and for the Program itself.

Our concern about this insurance-like buffer account was the potential adverse selection due to the essentially flat wildfire risk suggested by the program. We created a simple economic model of risk-neutral agents deciding whether to participate in the program. The model predicts that the potential forest projects with higher wildfire risks might be more likely to opt into the program because it provides partial insurance against wildfires. This adverse selection of the projects would make the Compliance Offset Program inefficient. First, the expected carbon sequestered, or the number of offsets supplied to the Cap-and-Trade market might not be optimal. For instance, fewer projects might participate, making carbon sequestration too low. In health insurance, it would correspond to a case when the equilibrium premium is too high, resulting in the lack of low-risk buyers. Second, the overall program will not be cost-effective because it could use more low-risk projects to sequester the same amount of carbon. Third, if high-risk projects increase the wildfire risks of the areas around them even more, it might put communities in danger and create other welfare effects.

To see empirically whether adverse selection is present in the program, we used open access data on the U.S. Offset projects, available on the ARB's website. At the time of the empirical analysis, 147 projects participated, but the program is ongoing, and more projects join each year. In our analysis, we used 79 projects because of the access to the GIS data for the other 68 of them. We compared the estimated fire risks of the projects' locations to the fire risks in the comparison group of other eligible lands. The data on fire risks comes from the USDA Forest Service.

We could not find any statistically significant adverse selection as of now. However, we did not fully finish the analysis yet, and the project is still in progress. Possibly, we did not detect adverse selection due to a small sample of the projects. We still need to estimate the locations of the remaining 68 projects. The total acreage of all 147 projects should be around 10 million acres. The second factor might be a comparison group of eligible lands. We are yet to refine the comparison group and exclude all potential lands that have a low chance of participation regardless of the fire risk of the project.


The Effect of Climate Change on Agriculture: Testing Nonparametric Identification in the Panel Data Context

Dalia Ghanem and Xiaomeng Cui


Measuring the Effects of Climate Change and Ground-level Ozone on Agricultural Yields in China

Colin Carter and Dalia Ghanem