No abstract

Rising inequalities and accelerating global environmental change pose two of the most pressing challenges of the twenty-first century. To explore how these phenomena are linked, we apply a social-ecological systems perspective and review the literature to identify six different types of interactions (or “pathways”) between inequality and the biosphere. We find that most of the research so far has only considered one-directional effects of inequality on the biosphere, or vice versa. However, given the potential for complex dynamics between socioeconomic and environmental factors within social-ecological systems, we highlight examples from the literature that illustrate the importance of cross-scale interactions and feedback loops between inequality and the biosphere. This review draws on diverse disciplines to advance a systemic understanding of the linkages between inequality and the biosphere, specifically recognizing cross-scale feedbacks and the multidimensional nature of inequality.

The social cost of carbon (SCC), commonly referred to as the carbon price, is the monetized damage from emitting one unit of CO 2 to the atmosphere. The SCC is typically obtained from large-scale computational Integrated Assessment Models (IAMs) that consolidate interdisciplinary climate research inputs to obtain a carbon price estimate relevant for policy-making (1). However, the climateeconomy interactions of IAMs remain inaccessible to scientists in general. Here we develop a simple closed-form formula that captures the key physical and economic determinants of the SCC in the IAMs. For a mainstream IAM, it explains over 99 percent of the within-model variation originating from structural uncertainties; in an inter-model comparison, the structural variation captured by the formula matches closely a SCC distribution of previous SCC estimates (2). The precise replication of the SCC estimates is strikingly free of details such as those on future policy and technology options, or even carbon concentration levels; the size of the current economy and the emissions-temperature-damage response are the dominant SCC determinants in the IAMs. The structural interpretation given allows decision-makers to disentangle the subjective and structural determinants of the carbon price. Structural uncertainties alone lead to a strongly right-skewed density with median 15 €/tCO 2 , mean 31 €/tCO 2 , and more than 5 percent probability for higher than 100 €/tCO 2 for year 2015.3

The social cost of carbon (SCC), commonly referred to as the carbon price, is the monetized damage from emitting one unit of CO 2 to the atmosphere. The SCC is typically obtained from large-scale computational Integrated Assessment Models (IAMs) that consolidate interdisciplinary climate research inputs to obtain a carbon price estimate relevant for policy-making (1). However, the climateeconomy interactions of IAMs remain inaccessible to scientists in general. Here we develop a simple closed-form formula that captures the key physical and economic determinants of the SCC in the IAMs. For a mainstream IAM, it explains over 99 percent of the within-model variation originating from structural uncertainties; in an inter-model comparison, the structural variation captured by the formula matches closely a SCC distribution of previous SCC estimates (2). The precise replication of the SCC estimates is strikingly free of details such as those on future policy and technology options, or even carbon concentration levels; the size of the current economy and the emissions-temperature-damage response are the dominant SCC determinants in the IAMs. The structural interpretation given allows decision-makers to disentangle the subjective and structural determinants of the carbon price. Structural uncertainties alone lead to a strongly right-skewed density with median 15 €/tCO 2 , mean 31 €/tCO 2 , and more than 5 percent probability for higher than 100 €/tCO 2 for year 2015.3

To what extent have national fiscal policies contributed to the decarbonisation of newly sold passenger cars? We construct a simple model that generates predictions regarding the effect of fiscal policies on average CO 2 emissions of new cars, and then test the model empirically. Our empirical strategy combines a diverse series of data. First, we use a large database of vehicle-specific taxes in 15 EU countries over 2001-2010 to construct a measure for the vehicle registration and annual road tax levels, and separately, for the CO 2 sensitivity of these taxes. We find that for many countries the fiscal policies have become more sensitive to CO 2 emissions of new cars. We then use these constructed measures to estimate the effect of fiscal policies on the CO 2 emissions of the new car fleet. The increased CO 2 -sensitivity of registration taxes have reduced the CO 2 emission intensity of the average new car by 1.3 %, partly through an induced increase of the share of diesel-fuelled cars by 6.5 percentage points. Higher fuel taxes lead to the purchase of more fuel efficient cars, but higher diesel fuel taxes also decrease the share of (more fuel efficient) diesel cars; higher annual road taxes have no or an adverse effect.Keywords Vehicle registration taxes · Fuel taxes · CO 2 emissions JEL Classification H30 · L62 · Q48 · Q54 · Q58 · R48 B Reyer Gerlagh r.gerlagh@uvt.nl