Journal of Development Economics 97 (2012) 427–436
We estimate neighbor interactions in deforestation in Costa Rica. To address simultaneity and the presence of spatially correlated unobservables, we measure for neighbors’ deforestation using the slopes of neighbors’ and neighbors’ neighbors’ parcels. We find that neighboring deforestation significantly raises the probability of deforestation. Policies for agricultural development or forest conservation in one area will affect deforestation rates in non-targeted neighboring areas. Correct estimation of the interaction reverses the naive estimate’s prediction of multiple equilibria.
B. Rapidel, F. DeClerk, J. LeCoq and J. Beer Eds. “Ecosystem services from Agriculture and Agroforestry: Measurement and Payment”. Chapter 14. Earthscan Press.
in Costa Rica. The first years of implementation set the basis for what the programme has become. Important changes have been made since the beginning, such as the institution in charge of implementing the programme, parcels selection criteria, and new offices that were opened in different areas of the country with the objective of reducing application costs. Using 2003 as the starting point of when these changes took place, we discuss if they had a programme efficiency effect on reducing deforestation. We focus on forest conservation contracts because it is the most important category of the programme in terms of budget and amount of land enrolled. We use matching techniques, geographic information systems (GIS), characterize the areas where payments were implemented in each of the time periods using a long list of variables, and look for similar areas that did not receive payments. We find that, as other studies have found for this period (Robalino et al, 2008; Arriagada, 2008), the impacts are low but significant. While it seems that, overall, institutional changes have not had a significant effect on impact, we also look at the impacts of forest conservation contracts per office. We find that those offices located in areas with high deforestation tend to have higher impacts.
Alexander Pfaff, Erin O. Sills, Gregory S. Amacher, Michael J. Coren, Kathleen Lawlor, Charlotte Streck
Report from the Nicholas Institute for Environmental Policy Solutions, Duke University (with the support of the Packard Foundation)
National and international efforts within the last few decades to reduce forest loss, while having some impact, have failed to substantially slow the loss of the world’s forests. Forest loss, i.e., deforestation and forest degradation, is widespread and accounts for 12%–17% of the world’s greenhouse gas (GHG) emissions. Global concern about climate change and the realization that reduced emissions from deforestation and degradation (REDD) can play a role in climate change mitigation make it critical to learn from our past experiences with policies to reduce forest loss. Within the UN Framework Convention on Climate Change (UNFCCC), negotiators are actively considering ways to include incentives for REDD and other forest carbon activities in any post-2012 treaty. In parallel, the U.S. Congress is developing proposals for a long-term climate policy that includes incentives for REDD, and possibly other international forest carbon activities. Such policies may mobilize new funds for forest conservation, including for addressing drivers of deforestation and forest degradation in developing countries. Climate-related incentives for REDD are likely to be performance-based, i.e., to emphasize the measurement, reporting, and verification of all results. The implementation of this emphasis, alongside the introduction of new financial incentives, could increase such policies’ impacts on forest loss relative to the past. Policy effectiveness, efficiency, and equity can increase if we learn lessons from the past about what drives and what inhibits deforestation and degradation. It is in the interest of any REDD program to understand what has worked in reducing deforestation and degradation and what has not, as well as the reasons for observed differences in outcomes. Investments and policies can then more effectively embrace and extend success while reducing risks of further failures. This report aims to provide lessons to inform U.S. and international policymakers by analyzing dominant influences on deforestation and degradation. We study not only forest-focused policies, but also other policies that directly or indirectly influence forest loss, all in light of relevant nonpolicy factors such as trends in commodity prices. We provide examples of previous policies to draw lessons from successes and failures, then link those observations about the past to the decisions current policymakers must soon make within ongoing climate policy deliberations.
Proceedings of the Royal Society B 2010 doi:10.1098/rspb.2010.1713
Protected areas (PAs) dominate conservation efforts. They will probably play a role in future climate policies too, as global payments may reward local reductions of loss of natural land cover. We estimate the impact of PAs on natural land cover within each of 147 countries by comparing outcomes inside PAs with outcomes outside. We use ‘matching’ (or ‘apples to apples’) for land characteristics to control for the fact that PAs very often are non-randomly distributed across their national landscapes. Protection tends towards land that, if unprotected, is less likely than average to be cleared. For 75 per cent of countries, we find protection does reduce conversion of natural land cover. However, for approximately 80 per cent of countries, our global results also confirm (following smaller-scale studies) that controlling for land characteristics reduces estimated impact by half or more. This shows the importance of controlling for at least a few key land characteristics. Further, we show that impacts vary considerably within a country (i.e. across a landscape): protection achieves less on lands far from roads, far from cities and on steeper slopes. Thus, while planners are, of course, constrained by other conservation priorities and costs, they could target higher impacts to earn more global payments for reduced deforestation.
Using case studies and concepts we suggest that constraints upon aggregate or global forest transition are significantly more severe than those upon local forest reversals. The basic reason is that one region’s reversal can be facilitated by other regions that supply resources and goods, reducing the demands upon the region where forests rise. Many past forest reversals involve such interdependence. For ‘facilitating regions’ also to rise in forest requires other changes, since they will not be receiving such help. We start by discussing forest-transitions analysis within the context of Environmental Kuznets Curves (EKCs), for a useful typology of possible shifts underlying transitions. We then consider the historical Northeast US where a regional reversal was dramatic and impressive. Yet this depended upon agricultural price shocks, due to the Midwest US supplying food, and also upon the availability of timber from other US regions. Next we consider deforestation in Amazônia, whose history (like the Northeast US) suggests a potential local role for urbanization, i.e. spatial concentration of population. Yet inter-regional issues again are crucial. For cattle and soy, expansion of global demands may give to Amazonia a role more like the Midwest than the Northeast US. In addition, across-region interdependencies will help determine where reversal and facilitation occur. Finally we discuss the constraints upon very broad forest transition.
Taylor H. Ricketts, Britaldo Soares-Filho, Gustavo A.B. da Fonseca, Daniel Nepstad, Alexander Pfaff, Annie Petsonk, Anthony Anderson, Doug Boucher, Andrea Cattaneo, Marc Conte, Ken Creighton, Lawrence Linden, Claudio Maretti, Paulo Moutinho, Roger Ullman, Ray Victurine
Forest clearing and degradation account for roughly 15% of global greenhouse gas emissions, more than all the cars, trains, planes, ships, and trucks on earth. This is simply too big a piece of the problem to ignore; fail to reduce it and we will fail to stabilize our climate. Although the recent climate summit in Copenhagen failed to produce a legally binding treaty, the importance of forest conservation in mitigating climate change was a rare point of agreement between developed and developing countries and is emphasized in the resulting Copenhagen Accord. Language from the meeting calls for developing countries to reduce emissions from deforestation and degradation (nicknamed REDD), and for wealthy nations to compensate them for doing so. For REDD to succeed, forest nations must develop policies and institutions to reduce and eventually eliminate forest clearing and degradation. One of the most straightforward components of such a program is also one of the oldest and most reliable tricks in the conservation book: protected areas. Indigenous lands and other protected areas (hereafter ILPAs)— created to safeguard land rights, indigenous livelihoods, biodiversity, and other values— contain more than 312 billion tons of carbon (GtC). Crucially, and paradoxically, this ‘‘protected carbon’’ is not entirely protected. While ILPAs typically reduce rates of deforestation compared to surrounding areas, deforestation (with resulting greenhouse gas [GHG] emissions) often continues within them, especially inside those that lack sufficient funding, management capacity, or political backing. These facts suggest an attractive but overlooked opportunity to reduce GHG emissions: creating new ILPAs and strengthening existing ones. Here, we evaluate the case for this potential REDD strategy. We focus on the Amazon basin given its importance for global biodiversity, its enormous carbon stocks, and its advanced network of indigenous lands and other protected areas.
We estimate neighbor interactions in deforestation in Costa Rica. To address simultaneity and the presence of spatially correlated unobservables, we measure for neighbors’ deforestation using the slopes of neighbors’ and neighbors’ neighbors’ parcels. We find that neighboring deforestation significantly raises the probability of deforestation. Policies for agricultural development or forest conservation in one area will affect deforestation rates in non-targeted neighboring areas. Correct estimation of the interaction reverses the naive estimate’s prediction of multiple equilibria.