Policy design is crucial to improving environmental quality, particularly in industries with living natural resources. Given that trees remove atmospheric CO2, shellfish mitigate eutrophication, and cows emit methane, among others, it is unsurprising that a number of policies and programs have emerged in recent years to maximize the environmental benefits (or minimize damages) from stocks of natural resources. Existing policies include Payments for Ecosystem Services (PES), such as REDD+ and the USDA Conservation Reserve Program, Nutrient Credit Trading in the Chesapeake Bay, and Denmark’s recently passed Livestock Tax. Each differ in institutional context, heterogeneity of firm behavior, and program structure, such as incentive targets. Addressing each dimension can play a crucial role in reducing damages to the environment.
Incentive targets
The target of environmental incentives is one of the most important dimensions on which policy effectiveness is determined. I propose a theoretical model of renewable natural resource extraction to understand how different second-best incentive targets affect environmental quality when a stock of privately-owned natural capital can jointly produce a public good (or bad) (Chuang 2025). Drawing from the seminal work of Dasgupta and Heal (1978) and Beltratti et al. (1993), I evaluate how incentives targeting either stocks of natural capital or flows of output affect the total stock of the natural resource held by the firm and, therefore, environmental quality, when the firm relies on natural growth of the stock for its operations. I find that incentives that target the source of the externality more directly, the stock of natural capital, can lead to the socially-optimal level of environmental quality. However, incentives on flows of production perform no better than no policy. The driving factor is the degrees of freedom under which the firm can adjust its production behavior. Under a stock incentive, the firm obtains two sources of revenue and can therefore adjust firm activity away from extraction. Behavior then becomes analogous to a multi-product firm, offering both a private good and an ecosystem service. Under a flow incentive, the firm cannot adjust productive activity away from extraction. Under this setting, the firm is only able to maximize profits using the same channel as no policy, which leads to the same level of the natural resource stock and, therefore, environmental quality as if no policy existed.
The model provides a benchmark theoretical model for environmental incentive evaluation and targeting, and therefore makes a number of strong assumptions. Included among these is homogeneity of extraction across geographies and the presence of strong legal and financial institutions. Unfortunately, the real world is not so straightforward. Therefore, other policy design strategies are needed, as recent work has highlighted.
Extraction Intensity and Differential Enforcement
Targeting policy efforts towards areas with higher extraction activity can lead to greater reductions in environmental damages, particularly in settings that are institutionally constrained. Assunção et al. (2023) estimate the impacts of differential monitoring and enforcement of (primarily) illegal clearing of the Amazon Rainforest in Brazil. In 2008, the Brazilian government issued a “priority list” of municipalities that were subject to increased monitoring and enforcement efforts based on multiple measures of the total amount of forested area cleared. The authors state that the government likely assumed that high deforestation in the listed municipalities would persist in absence of the policy. Therefore, using a changes-in-changes (CIC) approach, the authors found that this geographically heterogeneous policy led to a 43% reduction in deforestation in the following year, which contributed to a total reduction in carbon emissions by approximately 50 million tons.
The authors also emphasize that the choice of municipalities in the list was not necessarily optimal. They then present a model of an optimal “blacklist” that minimizes total deforestation (or total carbon emissions) subject to realistic administrative constraints, such as restrictions on the total area that can be monitored. Assuming the policymaker chooses blacklist municipalities under ambiguity using the minimax criterion, the authors find a further reduction in carbon emissions by 10% relative to the existing policy, amounting to avoided damages valued at approximately $1.2 billion.
Access to Financial Institutions
Many PES programs are intended to increase environmental quality, but lack of access to financial institutions can play a role in efficacy. Fenichel et al. (2019) provide a model of firm-level provision of ecosystem services to capture both extensive and intensive margin effects with respect to land use for tree cultivation in the Panama Canal Watershed. Using a Faustmann model framework under different PES structures and financial instruments, their results suggest that the presence of well-functioning financial institutions can lead to PESs that are generally less costly to environmental program funders and with the largest areas of land containing the oldest-growth trees. In particular, flat PES payments per unit of land allocated to timber, subsidized loans, and the availability of savings accounts encourage the largest land-use change towards industries that provide more ecosystem services. These incentives and financial instruments increase ability for a landholder to smooth consumption, but switching behavior is highest among the wealthiest landholders. The later result contradicts a secondary objective of PES programs, which is poverty reduction. The authors highlight that absence of non-forest financial instruments may induce higher costs of PES program implementation as well as shorter rotation periods, which can reduce overall ecosystem services provision.