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Credible empirical estimation of the economic impacts of climate change is dependent on data structure (e.g., cross sectional, panel) and the functional relationship between weather data and behavioral outcomes. We show here how these modeling decisions lead to significantly different results when estimating the effects of weather and simulating the potential welfare impacts of climate change on outdoor recreation. Using participation data from 1.6 million households in the United States from 2004 to 2009, we estimate the impact of temperature and precipitation on participation decisions for marine shoreline recreational fishing. Results from linear models suggest temperature positively impacts participation and, by implication, climate change is likely to improve welfare associated with outdoor recreation in all regions of our study area. Conversely, nonlinear specifications suggest more days with extreme heat reduce participation and lead to significant declines in welfare under future climate scenarios. Differences in the treatment of how weather enters recreation participation decisions change both the sign and magnitude of welfare effects by nearly $1 billion annually. Differences in data structure, however, only affect the magnitude of welfare impacts but not the sign. Disaggregation of welfare estimates suggests warmer baseline climates are more susceptible to these choices. Our results demonstrate the critical nature of modeling decisions about data structure and the use of weather data to assess the future impacts of climate change, especially with nonmarket goods where value is related to environmental quality such as outdoor recreation.

Outdoor recreation is one of the most popular leisure activities in the United States, yet the potential impacts of climate change on the nonmarket aspects of this activity are largely unkn...

Recent warnings from scientists suggest there is limited time to enact policies to avert wide‐ranging ecological and social damage from climate change. In the United States, discussions about comprehensive national policies to avert climate change have begun, with “Green New Deal” proposals and climate plans put forth by members of Congress and presidential candidates. Oceans are largely absent or separate from these nascent policy proposals. Here, we highlight a policy framework to develop terrestrial and ocean‐integrated policies that can complement and enhance terrestrial‐focused initiatives focused on four specific sectors: 1) energy; 2) transportation; 3) food security; and 4) habitat restoration. Given political friction and constrained budgets, an integrated policy framework offers greater potential to achieve a portfolio of mitigation and adaptation goals in a cost‐effective manner, beyond what could be realized with marine or terrestrial policy solutions alone.

This paper empirically estimates the economic impacts of a large-scale public investment in natural infrastructure aimed at adapting to climate change and increasing coastal resilience. I utilize temporal and spatial variation in investment in dunes to provide a hedonic property value estimate of the economic benefits. I identify the net effect of treatment utilizing the doubly robust Oaxaca-Blinder estimator and show that coastal housing price increases attributable to constructed dunes are approximately 3.6%. A decomposition of the average impact suggests that the policy intervention generates ancillary costs related to impaired ocean views and privacy concerns that partially offset large protection benefits.

A primary conduit for coastal adaptation to climate change on private land is the hardening, or armoring, of the shoreline to mitigate the effects of erosion and sea-level rise (SLR). When such decisions are made at the parcel-level, there is potential for spatial spillovers, including externalities due to deflected wave action and peer effects. We estimate a discrete choice model of landowner armoring choices from 1990 to 2015 in the U.S. state of Oregon that suggests the impacts of spatial spillovers are highly influential determinants in these private adaptation decisions. Our landscape simulations excluding spatial spillovers may under-predict future armoring by 37–97 percent. From scenario-based simulations, we then demonstrate the primacy of policy, as a removal of a current land-use regulation that limits armoring has potential to significantly increase future armoring by 69 percent. Furthermore, inclusion of SLR projections suggests armoring would increase an additional 5.4 percent within four decades.

Efficient adaptation to climate change in coastal areas is likely to require public policy interventions. New policies or expectations of policy changes that impact private assets, such as housing, may generate economic incentives that result in unintended consequences. We examine the effect on new housing development resulting from a scientific report by a regulatory agency mandating coastal communities in North Carolina (NC) consider sea-level rise when developing new land-use policies. Estimates from our preferred triple-differences model suggest the policy announcement increased building permits by 32% in coastal NC counties until permitting returned to pre-policy levels after a moratorium on new regulations was passed by the state legislature. Our results are supported by numerous robustness checks, including alternative controls, placebo tests and a parcel-level model in Dare County, NC. This green paradox in coastal climate adaptation implies that hundreds of millions of dollars in additional unregulated housing was constructed in NC locations vulnerable to sea-level rise likely due to perverse incentives generated by a policy signal.

Empirical studies and on-the-ground policies assessing optimal selection of projects in the context of payments for environmental services programs rarely consider spatial proximity of one project to other projects. This occurs despite evidence from theoretical and ecological studies that benefits are often spatially interdependent. This paper develops a flexible construct of “spatial synergy benefits” using the principles of Newtonian gravity similar to efforts in other application areas. This approach is novel to the literature on environmental preservation and, as a systematic method, can account for a wide variety of spatial interdependencies. The empirical setting for the application is farm and forest preservation in Delaware, with a quadratic knapsack algorithm used to select the optimal set of parcels. Application results show that the specific level of the spatial synergy benefit measure does not significantly alter the number of parcels and acreage preserved, but that the composition of the optimal set changes as agglomeration preferences increase. These changes in the optimal targeted set indicate a potential bias in past research on PES selection. Policy makers informed by methods that do not explicitly account for spatial agglomeration preferences often make incorrect investment choices from a cost-effectiveness perspective.

This article provides a practical, applied analysis of optimal targeting in agricultural land preservation, comparing the performance of four alternative targeting strategies. Nonmarket benefit data and hedonic cost estimates are used for parcels in Sussex County, Delaware. The results show that branch-and-bound optimization (OPT) does not significantly outperform the much simpler benefit–cost ratio targeting (BCRT). However, significant losses of potential net benefits occur when applied methods overlook either benefits or costs. In this application, benefit targeting (BT) and cost targeting (CT) significantly underperform both OPT and BCRT, with BT underperforming all other methods.

Log export bans (LEBs) are a popular development tool utilised by developing nations with sizable endowments of timber; however, the actual impact of these policies is debatable. British Columbia has a developed forestry sector and still maintains a LEB. This trade restriction continually creates conflicts with Canada's international trade partners, including the United States. This paper examines the efficiency implications of a hypothetical removal of roundwood export restrictions in British Columbia using roundwood price and quantity data from 1995 to 2008. A time-series econometric approach is utilised to determine supply and demand elasticities for British Columbia's roundwood. Empirical results from a vector error correction model suggest that a removal of export restrictions will generate an overall increase of approximately $347.91 million US dollars per year to British Columbia's forest economy.

Economists advocate that the billions of public dollars spent on conservation be allocated to achieve the largest possible social benefit. This is “cost-effective conservation”—a process that incorporates both monetized benefits and costs. Though controversial, cost-effective conservation is poorly understood and rarely implemented by planners. Drawing from the largest publicly financed conservation programs in the United States, this paper seeks to improve the communication from economists to planners and to overcome resistance to cost-effective conservation. Fifteen practical lessons are distilled, including the negative implications of limiting selection with political constraints, using nonmonetized benefit measures or benefit indices, ignoring development risk, using incomplete cost measures, employing cost measures sequentially, and using benefit indices to capture costs. The paper highlights interrelationships between benefits and complications such as capitalization and intertemporal planning. The paper concludes by identifying the challenges at the research frontier, including incentive problems associated with adverse selection, additionality, and slippage.

Economists advocate that the billions of public dollars spent on conservation should be allocated to achieve the largest possible social benefit. This is what we term “cost-effective conservation”-- a process that incorporates both benefits and costs that are measured with money. This controversial proposition has been poorly understood and not implemented by conservation planners. Drawing from evidence from the largest conservation programs in the United States, this paper seeks to improve the communication between economists and planners and overcome resistance to cost-effective conservation by addressing the open questions that likely drive skepticism among non-economists and by identifying best practices for project selection. We first delineate project-selection strategies and compare them to optimization. Then we synthesize the body of established research findings from economics into 20 practical lessons. Based on theory, policy considerations, and empirical evidence, these lessons illustrate the potential gains from improving practices related to cost-effective selection and also address how to overcome landowner-incentive challenges that face programs.