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Governments are catching up with economic theory and practice by increasingly integrating ecosystem service values into national planning processes, including benefit-cost analyses of public policies. Such analyses require information not only about today’s benefits from ecosystem services but also on how benefits change over time. We address a key limitation of existing policy guidance, which assumes that benefits from ecosystem services remain unchanged. We provide a practical rule that is grounded in economic theory and evidence-based as a guideline for how benefits change over time: They rise as societies get richer and even more so when ecosystem services are declining. Our proposal will correct a substantial downward bias in currently used estimates of future ecosystem service values. This will help governments to reflect the importance of ecosystems more accurately in benefit-cost analyses and policy decisions they inform.

info:eu-repo/semantics/published

Data for reproducing Figures of the manuscript Trends in tropical forest loss and the social value of emission reductions by Thomas Knoke et al. Full data sets and spreadsheets are available via 10.5281/zenodo.8016364, Data for reproducing Figures of the manuscript Trends in tropical forest loss and the social value of emission reductions by Thomas Knoke et al. Full data sets and spreadsheets are available via 10.5281/zenodo.8016364

Reducing global forest losses is essential to mitigate climate change and its associated social costs. Multiple market and non-market factors can enhance or reduce forest loss. Here, to understand the role of non-market factors (for example, policies, climate anomalies or conflicts), we can compare observed trends to a reference (expected) scenario that excludes non-market factors. We define an expected scenario by simulating land-use decisions solely driven by market prices, productivities and presumably plausible decision-making. The land-use allocation model considers economic profits and uncertainties as incentives for forest conversion. We compare reference forest losses in Brazil, the Democratic Republic of Congo and Indonesia (2000–2019) with observed forest losses and assign differences from non-market factors. Our results suggest that non-market factors temporarily lead to lower-than-expected forest losses summing to 11.1 million hectares, but also to phases with higher-than-expected forest losses of 11.3 million hectares. Phases with lower-than-expected forest losses occurred earlier than those with higher-than-expected forest losses. The damages avoided by delaying emissions that would otherwise have occurred represent a social value of US$61.6 billion (as of the year 2000). This result shows the economic importance of forest conservation efforts in the tropics, even if reduced forest loss might be temporary and reverse over time.

Lemoine and Rudik (2017) argues that it is efficient to delay reducing carbon emissions, due to supposed inertia in the climate system's response to emissions. This conclusion rests upon misunderstanding the relevant earth system modeling: there is no substantial lag between CO2 emissions and warming. Applying a representation of the earth system that captures the range of responses seen in complex earth system models invalidates the original article's implications for climate policy. The least-cost policy path that limits warming to 2°C implies that the carbon price starts high and increases at the interest rate. It cannot rely on climate inertia to delay reducing and allow greater cumulative emissions.

Having its roots in the financial system, the world economic downturn at stake since 2008 has revealed the importance of capital requirements for banks. Reinhart and Rogoff (2009) have shown that financial crises have substantial economic impact, reducing the GDP of 10% or more, with a non- neglecting part being permanent. This highlights the importance of a stable financial market for the entire economy. As a consequence, the new Basel III agreements have substantially increased capital requirement, which has generated important debates on the cost of raising capital for banks. In particular, banking associations have argued that this new regulation would increase funding costs for banks and therefore increase the cost of bank-credits. However these arguments generally focus on short-term feedbacks, whereas in order to define an adequate legislation and prevent new crises, a long-term perspective is essential. Using a large worldwide database of 98 banks over a period of 25 years, we have tested the Modigliani and Miller theorem, which states the neutrality of capital structure on the value of the bank - and hence on the weighted average cost of capital.1 Our main results reveal that financial market tends to underprice leverage risk compared to M&M predictions. Leveraging increases market value of banks making rational the shareholders’ decision of opting for very high leverage.2 We also show that the gain of leverage is much higher during the crisis period (after 2007) than during the preceding more stable period (1990-2006). This gain is also higher for systemically important banks, which are very likely to be bailed out by the government in case of distress. We argue that the underpriced transfer of risk from banks’ shareholders to governments is the most convincing theoretical argument explaining this departure from M&M theorem. The three other possible explanations - tax advantages, agency costs between managers and shareholders, and role of completing financ

Integrated assessment models (IAMs) provide key inputs to decision-makers on economically efficient climate policies, and technical change is one of the key assumptions in any IAM that estimates mitigation costs. We conduct a systematic survey of how technical change is currently represented in the main IAMs and find that a diversity of approaches continues to exist. This makes it important to conduct an up-to-date assessment of what difference technical change makes to IAM results. Here we attempt such an assessment, using an analytical IAM with a reduced-form representation of technical change, which we can calibrate on the relationship between abatement costs and the timing of abatement in 109 IAM scenarios from two major databases. We first show in theory how a range of technical-change mechanisms can be adequately captured in a reduced-form model, in which the key difference is whether technical change is a function of time, i.e., exogenous, or cumulative past emissions abatement, i.e., endogenous. We then derive analytical and quantitative results on the effect of technical change on optimal climate policy, for both cost-benefit and cost-effectiveness policy problems. Under cost-benefit analysis, technical change has a quantitatively large, negative effect on long-run emissions and temperatures. The effect on carbon prices differs markedly depending on whether technical change is exogenous or endogenous, and whether clean technology deployment is incentivised by carbon prices or a dedicated deployment subsidy. Under cost-effectiveness analysis, technical change has a small effect on transient emissions and temperatures, but it has a large, negative effect on carbon prices almost irrespective of the policy instruments available. We make several practical recommendations for how IAMs can better incorporate TC, particularly when facing computational constraints.

Carbon markets have emerged in recent decades as one of the most important tools for curbing industrial greenhouse gas emissions, but they present a number of novel enforcement challenges as compared to more conventional pollution regulations—new regulators with narrow authority, lack of legal precedent, and more. To shed light on the practical issues involved in policing carbon markets, we present the first comprehensive analysis of the EU Emissions Trading System, a single program that was policed by 31 different national regulators. We find generally high rates of compliance coupled with low rates of enforcement, a pattern that is known in the literature as ‘Harrington’s paradox.’ Variation in the probability and severity of fines explain just one tenth of the variation in compliance rates. Meanwhile, other enforcement strategies that have been pointed to as resolutions to Harrington’s paradox in other applications, such as ‘naming and shaming,’ appear to have had little discernible effect.

Two approaches are predominant in climate models: cost-benefit and cost-effectiveness analysis. On the one hand, cost-benefit analysis maximises welfare, finding a trade-off between climate damages and emission abatement costs. On the other hand, cost-effectiveness analysis minimises abatement costs, omits damages but adds a climate constraint, such as a radiative forcing constraint, a temperature constraint or a cumulative emissions constraint. These constraints can be applied from today onwards or only from 2100 onwards, allowing to overshoot the target before 2100. We analyse the impacts of these different constraints on optimal carbon prices, emissions and welfare. To do so, we fit a model with abatement costs, capital repurposing costs (stranded assets) and technological change on IPCC and NGFS scenarios. The welfare-maximizing scenario reaching 1.5°C in 2100 has almost no net negative emissions at the end of the century (-2GtCO2/y). A constraint on cumulative emissions has the best welfare properties, followed by a temperature constraint with overshoot. A forcing constraint with overshoot has insufficient early abatement, leading to a substantial welfare loss of $29 Trillion, spread out over the century. As to the paths reaching 2°C, all cost-effectiveness analysis abate too late, but the welfare impact of this dynamic inefficiency is milder. Again, a forcing constraint with overshoot scores worst.

Reducing global forest losses is essential to mitigate climate change and its associated social costs. Multiple market and non-market factors can enhance or reduce forest loss. Here, to understand the role of non-market factors (for example, policies, climate anomalies or conflicts), we can compare observed trends to a reference (expected) scenario that excludes non-market factors. We define an expected scenario by simulating land-use decisions solely driven by market prices, productivities and presumably plausible decision-making. The land-use allocation model considers economic profits and uncertainties as incentives for forest conversion. We compare reference forest losses in Brazil, the Democratic Republic of Congo and Indonesia (2000–2019) with observed forest losses and assign differences from non-market factors. Our results suggest that non-market factors temporarily lead to lower-than-expected forest losses summing to 11.1 million hectares, but also to phases with higher-than-expected forest losses of 11.3 million hectares. Phases with lower-than-expected forest losses occurred earlier than those with higher-than-expected forest losses. The damages avoided by delaying emissions that would otherwise have occurred represent a social value of US$61.6 billion (as of the year 2000). This result shows the economic importance of forest conservation efforts in the tropics, even if reduced forest loss might be temporary and reverse over time.

Societal Impact Statement Humankind is facing both climate and biodiversity crises. This article proposes the foundations of a scheme that offers tradable credits for combined aboveground and soil carbon and biodiversity. Multidiversity—as estimated based on high-throughput molecular identification of soil meiofauna, fungi, bacteria, protists, plants and other organisms shedding DNA into soil, complemented by acoustic and video analyses of aboveground macrobiota—offers a cost-effective method that captures much of the terrestrial biodiversity. Such a voluntary crediting system would increase the quality of carbon projects and contribute funding for delivering the Kunming-Montreal Global Biodiversity Framework. Summary Carbon crediting and land offsets for biodiversity protection have been developed to tackle the challenges of increasing greenhouse gas emissions and the loss of global biodiversity. Unfortunately, these two mechanisms are not optimal when considered separately. Focusing solely on carbon capture—the primary goal of most carbon-focused crediting and offsetting commitments—often results in the establishment of non-native, fast-growing monocultures that negatively affect biodiversity and soil-related ecosystem services. Soil contributes a vast proportion of global biodiversity and contains traces of aboveground organisms. Here, we outline a carbon and biodiversity co-crediting scheme based on the multi-kingdom molecular and carbon analyses of soil samples, along with remote sensing estimation of aboveground carbon as well as video and acoustic analyses-based monitoring of aboveground macroorganisms. Combined, such a co-crediting scheme could help halt biodiversity loss by incentivising industry and governments to account for biodiversity in carbon sequestration projects more rigorously, explicitly and equitably than they currently do. In most cases, this would help prioritise protection before restoration and help promote more socially and environmentally

This article examines the relationship between capital ratios and returns on US bank stocks between 1973 and 2019. Banks with low capital ratios do not have higher, but rather lower returns than banks with intermediate levels of capital. This is not explained by standard risk factors. As a result, risk-adjusted returns (alphas) of lowcapital banks are negative. Moreover, the stock returns exhibit a delayed reaction to changes in capital ratios. Low-capital banks that further increase their debt have high abnormal returns on the day of announcement, but tend to have low risk-adjusted returns in the 9 months that follow. The paper uncovers several explanations for this leverage anomaly: under-priced default risk, under-priced systematic risk and sensitivity to idiosyncratic volatility.

Communities and individuals are increasingly turning to courts to hold governments and high emitting corporations to account for the adverse consequences of climate change and are starting to find success. For defending corporations, rising climate litigation risk may exacerbate well-known physical and transition risks associated with climate change. Yet, little is known about the impacts of climate litigation against corporations. Here we provide the first robust evidence. We construct a comprehensive database of filings and decisions relating to 108 climate change lawsuits worldwide against US and European-listed corporations between 2005–2021. Our causal analysis estimates that a filing or an unfavourable court decision in a climate case reduced firm value by -0.41% on average, relative to expected values. The largest stock market responses were found for cases filed against Carbon Majors, reducing firm value by -0.57% following case filings and by -1.50% following unfavourable judgements. Larger market reactions are observed in “novel” cases involving a new form of legal argument or in a new jurisdiction. No statistically significant effect on firm value was found in filings against non-Carbon Majors. We conclude that lenders, financial regulators, and governments should consider climate litigation risk as a relevant financial risk in a warmer future.

Communities and individuals are increasingly turning to courts to hold governments and high emitting corporations to account for the adverse consequences of climate change and are starting to find success. For defending corporations, rising climate litigation risk may exacerbate well-known physical and transition risks associated with climate change. Yet, little is known about the impacts of climate litigation against corporations. Here we provide the first robust evidence. We construct a comprehensive database of filings and decisions relating to 108 climate change lawsuits worldwide against US and European-listed corporations between 2005–2021. Our causal analysis estimates that a filing or an unfavourable court decision in a climate case reduced firm value by -0.41% on average, relative to expected values. The largest stock market responses were found for cases filed against Carbon Majors, reducing firm value by -0.57% following case filings and by -1.50% following unfavourable judgements. Larger market reactions are observed in “novel” cases involving a new form of legal argument or in a new jurisdiction. No statistically significant effect on firm value was found in filings against non-Carbon Majors. We conclude that lenders, financial regulators, and governments should consider climate litigation risk as a relevant financial risk in a warmer future.

The optimal transition to a low-carbon economy must account for adjustment costs in switching from dirty to clean capital, technological progress, and economic and climatic shocks. We study the low-carbon transition using a dynamic stochastic general equilibrium model with emissions abatement costs calibrated on a large energy modelling database, solved with recursive methods. We show how capital inertia puts upward pressure on emissions and temperatures in the short run, but that nonetheless it is optimal to actively disinvest from – to ‘strand’ – a significant share of the dirty capital stock. Conversely, clean technological progress, as well as uncertainty about climatic and economic factors, lead to lower emissions and temperatures in the long run. Putting these factors together, we estimate a net premium of 33% on the optimal carbon price today relative to a ‘straw man’ model with perfect capital mobility, fixed abatement costs and no uncertainty.

The optimal transition to a low-carbon economy must account for adjustment costs in switching from dirty to clean capital, technological progress, and economic and climatic shocks. We study the low-carbon transition using a dynamic stochastic general equilibrium model with emissions abatement costs calibrated on a large energy modelling database, solved with recursive methods. We show how capital inertia puts upward pressure on emissions and temperatures in the short run, but that nonetheless it is optimal to actively disinvest from – to ‘strand’ – a significant share of the dirty capital stock. Conversely, clean technological progress, as well as uncertainty about climatic and economic factors, lead to lower emissions and temperatures in the long run. Putting these factors together, we estimate a net premium of 33% on the optimal carbon price today relative to a ‘straw man’ model with perfect capital mobility, fixed abatement costs and no uncertainty.

This paper investigates the joint impact of the European Union Emissions Trading System (EU ETS), Europe’s main climate change policy, on carbon emissions and economic performance of regulated companies. The impact on emissions is analysed using installation-level carbon emissions from national Polluting Emissions Registries from France, Netherlands, Norway and the United Kingdom complemented with data from the European Pollutant Release and Transfer Register (E-PRTR). The impact on firm performance is analysed using firm-level data for all countries covered by the EU ETS. A matching methodology exploiting installation-level inclusion criteria combined with difference-in-differences is used to estimate the policy’s causal impact on installations’ emissions and on firms’ revenue, assets, profits and employment. We find that the EU ETS has induced carbon emission reductions in the order of -10% between 2005 and 2012, but had no negative impact on the economic performance of regulated firms. These results demonstrate that concerns that the EU ETS would come at a cost in terms of competitiveness have been vastly overplayed. In fact, we even find that the EU ETS led to an increase in regulated firms’ revenues and fixed assets. We explore various explanations for these findings.

How high should we build a dyke today, knowing that it will serve for more than 50 years? This depends on the unconditional probability distribution of future temperatures. We review the literature on estimates of future emissions for current policy scenarios and current pledge scenarios. Reviewing expert elicitations, abatement costs of scenarios, learning rates of technologies, fossil fuel supply side dynamics and geoengineering, we argue that scenarios with emissions largely beyond current policy scenarios and largely below current pledge scenarios are relatively unlikely. Based on this, we develop a transparent method to estimate unconditional probability distributions of future temperatures and temperature exceedance probabilities for use in Value at Risk stress tests in 2030, 2050 and 2100.

How high should we build a dyke today, knowing that it will serve for more than 50 years? This depends on the unconditional probability distribution of future temperatures. We review the literature on estimates of future emissions for current policy scenarios and current pledge scenarios. Reviewing expert elicitations, abatement costs of scenarios, learning rates of technologies, fossil fuel supply side dynamics and geoengineering, we argue that scenarios with emissions largely beyond current policy scenarios and largely below current pledge scenarios are relatively unlikely. Based on this, we develop a transparent method to estimate unconditional probability distributions of future temperatures and temperature exceedance probabilities for use in Value at Risk stress tests in 2030, 2050 and 2100.

Measures of inequality aversion are elicited using hypothetical decision tasks. The tasks require an assessment of projects in the presence of environmental inequalities across space and time. We also test the effect of different environmental domains (air pollution, recreational forest and soil fertility) and contextual framings (gain/loss, within/between regions and present–future/past–present inter-temporal trade-offs). Estimated mean inequality aversion is higher in the intra-temporal framing (an elasticity of 2.9), than in the inter-temporal framing with either negative (2.0) or positive (1.4) growth in environmental quality. Differences across environmental domains exist but are less pronounced. Similar results hold for pure time preference. Losses are associated with a lower pure rate of time preference but higher inequality aversion compared to gains. The results indicate how domain-specific ‘dual’ discount rates or rather changing relative shadow prices for the environment might be calibrated. Yet, seen as an exercise in empirical social choice, the context dependent results reject the classical Utilitarian formulation of a single Ramsey Rule.

We show that economic models of climate change produce climate dynamics inconsistent with current climate science models: (i) the delay between CO 2 emissions and warming is much too long and (ii) positive carbon cycle feedbacks are mostly absent. These inconsistencies lead to biased economic policy advice. Controlling for how the economy is represented, different climate models result in significantly different optimal CO 2 emissions. A long delay between emissions and warming leads to optimal carbon prices that are too low and attaches too much importance to the discount rate. Similarly we find that omitting positive carbon cycle feedbacks leads to optimal carbon prices that are too low. We conclude that it is important for policy purposes to bring economic models in line with the state of the art in climate science, and we make practical suggestions for how to do so.

We exploit recent advances in climate science to develop a physically consistent, yet surprisingly simple, model of climate policy. It seems that key economic models have greatly overestimated the delay between carbon emissions and warming, and ignored the saturation of carbon sinks that takes place when the atmospheric concentration of carbon dioxide rises. This has important implications for climate policy. If carbon emissions are abated, damages are avoided almost immediately. Therefore it is optimal to reduce emissions significantly in the near term and bring about a slow transition to optimal peak warming, even if optimal steady-state/peak warming is high. The optimal carbon price should start relatively high and grow relatively fast.

There is a considerable body of evidence showing that our preferences exhibit both reference dependence and loss aversion, a.k.a. the endowment effect. In this paper, we consider the implications of the endowment effect for discounting, with a special focus on discounting future improvements in the environment. We show that the endowment effect modifies the discount rate via (i) an instantaneous endowment effect and (ii) a reference-updating effect. Moreover we show that these two effects often combine to dampen the preference to smooth consumption over time. What this implies for discounting future environmental benefits may then depend critically on whether environmental quality is merely a factor of production of material consumption, or whether it is an amenity. On an increasing path of material consumption, dampened consumption smoothing implies a lower discount rate. But on a declining path of environmental quality and where we derive utility directly from environmental quality, it implies a higher discount rate. On non-monotonic paths, loss aversion specifically can give rise to substantial discontinuities in the discount rate.

Governments are catching up with economic theory and practice by increasingly integrating ecosystem service values into national planning processes, including benefitcost analyses of public policies. Such analyses require information not only about today’s benefits from ecosystem services but also on how benefits change over time. We address a key limitation of existing policy guidance, which assumes that benefits from ecosystem services remain unchanged. We provide a practical rule that is grounded in economic theory and evidence-based as a guideline for how benefits change over time: They rise as societies get richer and even more so when ecosystem services are declining. Our proposal will correct a substantial downward bias in currently used estimates of future ecosystem service values. This will help governments to reflect the importance of ecosystems more accurately in benefit-cost analyses and policy decisions they inform.

How high should we build a dyke today, knowing that it will serve for more than 50 years? This depends on the probability distribution of future temperatures. We review the literature on estimates of future emissions for current/stated policy scenarios and current pledge scenarios. Reviewing expert elicitations, abatement costs of scenarios, learning rates of technologies, fossil fuel supply side dynamics and geoengineering, we argue that scenarios with emissions largely beyond current/stated policy scenarios and largely below current pledge scenarios are relatively unlikely. Based on this, we develop a literature-informed evaluation of the likelihoods of future temperature for use in Value at Risk stress tests in 2030, 2050 and 2100.

Efforts to avert dangerous climate change by conserving and restoring natural habitats are hampered by concerns over the credibility of methods used to quantify their long-term impacts. Here we develop a flexible framework for estimating the net social benefit of impermanent nature-based interventions that integrates three substantial advances: (1) conceptualizing the permanence of a project’s impact as its additionality over time; (2) risk-averse estimation of the social cost of future reversals of carbon gains; and (3) post-credit monitoring to correct errors in deliberately pessimistic release forecasts. Our framework generates incentives for safeguarding already credited carbon while enabling would-be investors to make like-for-like comparisons of diverse carbon projects. Preliminary analyses suggest nature-derived credits may be competitively priced even after adjusting for impermanence.

It is unclear how much carbon should be stored in temporary and risky offsets to compensate one ton of CO2 emissions. Here we cast the social value of an offset (SVO), measured in terms of economic damages avoided, as a well-defined fraction of the social cost of carbon reflecting offset duration, and risks of non-additionality and failure. The SVO reflects the value of temporary storage, and overcomes shortcomings in the climate science and economics of previous contributions1,2,3,4. The SVO is policy relevant. An efficient net-zero policy will consist of offsets if their SVO/cost ratio exceeds the benefit/cost ratio of alternatives. The SVO yields an indicator of the equivalence of offsets to permanent carbon storage measured by the ratio of the SVO to the social cost of carbon. We provide a matrix of equivalence factors for different risks, permanence and climate scenarios. Estimation yields a rule of thumb: one offset sequestering one ton for 50 years is equivalent to between 0.33 and 0.5 tons permanently locked away. Equivalence offers a means of replacing perpetual offset contracts by simpler, easy to monitor short-term contracts, has applications to carbon life cycle analysis5 and the valuation of carbon debts6, and can be the basis of comparing offsets of different qualities in the voluntary and compliance markets.