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Process-based integrated assessment models (IAMs) project long-term transformation pathways in energy and land-use systems under what-if assumptions. IAM evaluation is necessary to improve the models’ usefulness as scientific tools applicable in the complex and contested domain of climate change mitigation. We contribute the first comprehensive synthesis of process-based IAM evaluation research, drawing on a wide range of examples across six different evaluation methods including historical simulations, stylised facts, and model diagnostics. For each evaluation method, we identify progress and milestones to date, and draw out lessons learnt as well as challenges remaining. We find that each evaluation method has distinctive strengths, as well as constraints on its application. We use these insights to propose a systematic evaluation framework combining multiple methods to establish the appropriateness, interpretability, credibility, and relevance of process-based IAMs as useful scientific tools for informing climate policy. We also set out a programme of evaluation research to be mainstreamed both within and outside the IAM community.
Climate science provides strong evidence of the necessity of limiting global warming to 1.5 °C, in line with the Paris Climate Agreement. The IPCC 1.5 °C special report (SR1.5) presents 414 emissions scenarios modelled for the report, of which around 50 are classified as '1.5 °C scenarios', with no or low temperature overshoot. These emission scenarios differ in their reliance on individual mitigation levers, including reduction of global energy demand, decarbonisation of energy production, development of land-management systems, and the pace and scale of deploying carbon dioxide removal (CDR) technologies. The reliance of 1.5 °C scenarios on these levers needs to be critically assessed in light of the potentials of the relevant technologies and roll-out plans. We use a set of five parameters to bundle and characterise the mitigation levers employed in the SR1.5 1.5 °C scenarios. For each of these levers, we draw on the literature to define 'medium' and 'high' upper bounds that delineate between their 'reasonable', 'challenging' and 'speculative' use by mid century. We do not find any 1.5 °C scenarios that stay within all medium upper bounds on the five mitigation levers. Scenarios most frequently 'over use' CDR with geological storage as a mitigation lever, whilst reductions of energy demand and carbon intensity of energy production are 'over used' less frequently. If we allow mitigation levers to be employed up to our high upper bounds, we are left with 22 of the SR1.5 1.5 °C scenarios with no or low overshoot. The scenarios that fulfil these criteria are characterised by greater coverage of the available mitigation levers than those scenarios that exceed at least one of the high upper bounds. When excluding the two scenarios that exceed the SR1.5 carbon budget for limiting global warming to 1.5 °C, this subset of 1.5 °C scenarios shows a range of 15–22 Gt CO2 (16–22 Gt CO2 interquartile range) for emissions in 2030. For the year of reaching net zero CO2 emissions the range is 2039–2061 (2049–2057 interquartile range).
Closing the emissions gap between Nationally Determined Contributions (NDCs) and the global emissions levels needed to achieve the Paris Agreement’s climate goals will require a comprehensive package of policy measures. National and sectoral policies can help fill the gap, but success stories in one country cannot be automatically replicated in other countries. They need to be adapted to the local context. Here, we develop a new Bridge scenario based on nationally relevant, short-term measures informed by interactions with country experts. These good practice policies are rolled out globally between now and 2030 and combined with carbon pricing thereafter. We implement this scenario with an ensemble of global integrated assessment models. We show that the Bridge scenario closes two-thirds of the emissions gap between NDC and 2 °C scenarios by 2030 and enables a pathway in line with the 2 °C goal when combined with the necessary long-term changes, i.e. more comprehensive pricing measures after 2030. The Bridge scenario leads to a scale-up of renewable energy (reaching 52%–88% of global electricity supply by 2050), electrification of end-uses, efficiency improvements in energy demand sectors, and enhanced afforestation and reforestation. Our analysis suggests that early action via good-practice policies is less costly than a delay in global climate cooperation.
The large majority of climate change mitigation scenarios that hold warming below 2 °C show high deployment of carbon dioxide removal (CDR), resulting in a peak-and-decline behavior in global temperature. This is driven by the assumption of an exponentially increasing carbon price trajectory which is perceived to be economically optimal for meeting a carbon budget. However, this optimality relies on the assumption that a finite carbon budget associated with a temperature target is filled up steadily over time. The availability of net carbon removals invalidates this assumption and therefore a different carbon price trajectory should be chosen. We show how the optimal carbon price path for remaining well below 2 °C limits CDR demand and analyze requirements for constructing alternatives, which may be easier to implement in reality. We show that warming can be held at well below 2 °C at much lower long-term economic effort and lower CDR deployment and therefore lower risks if carbon prices are high enough in the beginning to ensure target compliance, but increase at a lower rate after carbon neutrality has been reached.
Charities typically ask potential donors repeatedly for a donation. These repeated requests might trigger avoidance behavior. Considering that, this paper analyzes the impact of offering an ask avoidance option on charitable giving. In a proposed utility framework, the avoidance option decreases the social pressure to donate. At the same time, it induces feelings of gratitude toward the fundraiser, which may lead to a reciprocal increase in donations. The results of a lab experiment designed to disentangle the two channels show no negative impact of the option to avoid repeated asking on donations. Instead, the full model indicates a positive impact of the reciprocity channel. This finding suggests that it might be beneficial for charities to introduce an ask avoidance option during high-frequency fundraising campaigns.
Beyond good faith
(2021)
The ambitious climate targets set by industrialized nations worldwide cannot be met without decarbonizing the building stock. Using Germany as a case study, this paper takes stock of the extensive set of energy efficiency policies that are already in place and clarifies that they have been designed “in good faith” but lack in overall effectiveness as well as cost-efficiency in achieving these climate targets. We map out the market failures and behavioural considerations that are potential reasons for why realized energy savings fall below expectations and why the household adoption of energy-efficient and low-carbon technologies has remained low. We highlight the pressing need for data and modern empirical research to develop targeted and cost-effective policies seeking to correct these market failures. To this end, we identify some key research questions and identify gaps in the data required for evidence-based policy.
Pathways toward limiting global warming to well below 2 ∘C, as used by the IPCC in the Fifth Assessment Report, do not consider the climate impacts already occurring below 2 ∘C. Here we show that accounting for such damages significantly increases the near-term ambition of transformation pathways. We use econometric estimates of climate damages on GDP growth and explicitly model the uncertainty in the persistence time of damages. The Integrated Assessment Model we use includes the climate system and mitigation technology detail required to derive near-term policies. We find an optimal carbon price of $115 per tonne of CO2 in 2030. The long-term persistence of damages, while highly uncertain, is a main driver of the near-term carbon price. Accounting for damages on economic growth increases the gap between the currently pledged nationally determined contributions and the welfare-optimal 2030 emissions by two thirds, compared to pathways considering the 2 ∘C limit only.
Global emissions scenarios play a critical role in the assessment of strategies to mitigate climate change. The current scenarios, however, are criticized because they feature strategies with pronounced overshoot of the global temperature goal, requiring a long-term repair phase to draw temperatures down again through net-negative emissions. Some impacts might not be reversible. Hence, we explore a new set of net-zero CO2 emissions scenarios with limited overshoot. We show that upfront investments are needed in the near term for limiting temperature overshoot but that these would bring long-term economic gains. Our study further identifies alternative configurations of net-zero CO2 emissions systems and the roles of different sectors and regions for balancing sources and sinks. Even without net-negative emissions, CO2 removal is important for accelerating near-term reductions and for providing an anthropogenic sink that can offset the residual emissions in sectors that are hard to abate.
Does loss aversion apply to social image concerns? In a laboratory experiment, we first induce social image in a relevant domain, intelligence, through public ranking. In a second stage, subjects experience a change in rank and are offered scope for lying to improve their final, also publicly reported rank. Subjects who care about social image and experience a decline in rank lie more than those experiencing gains. Moreover, we document a discontinuity in lying behavior when moving from rank losses to gains. Our results are in line with loss aversion in social image concerns.
In the past years, work-time in many industries has become more flexible, opening up a new channel for intertemporal substitution: workers might, instead of saving, adjust their work-time to smooth consumption. To study this channel, we set up a two-period consumption/saving model with wage uncertainty. This extends the standard saving model by also allowing a worker to allocate a fixed time budget between two work-shifts. To test the comparative statics implied by these two different channels, we conduct a laboratory experiment. A novel feature of our experiments is that we tie income to a real-effort style task. In four treatments, we turn on and off the two channels for consumption smoothing: saving and time allocation. Our main finding is that savings are strictly positive for at least 85 percent of subjects. We find that a majority of subjects also uses time allocation to smooth consumption and use saving and time shifting as substitutes, though not perfect substitutes. Part of the observed heterogeneity of precautionary behavior can be explained by risk preferences and motivations different from expected utility maximization. (c) 2021 Elsevier B.V. All rights reserved.
Using data from the German Socio-Economic Panel and exploiting the staggered implementation of a compulsory schooling reform in West Germany, this article finds that an additional year of schooling lowers the probability of being very concerned about immigration to Germany by around six percentage points (20 percent). Furthermore, our findings imply significant spillovers from maternal education to immigration attitudes of her offspring. While we find no evidence for returns to education within a range of labor market outcomes, higher social trust appears to be an important mechanism behind our findings.
Starting in 2009, the German state of Saxony distributed sports club membership vouchers among all 33,000 third graders in the state. The policy’s objective was to encourage them to develop a long-term habit of exercising. In 2018, we carried out a large register-based survey among several cohorts in Saxony and two neighboring states. Our difference-in-differences estimations show that, even after a decade, awareness of the voucher program was significantly higher in the treatment group. We also find that youth received and redeemed the vouchers. However, we do not find significant short- or long-term effects on sports club membership, physical activity, overweightness, or motor skills.
The employment implications of decarbonizing the energy sector have received far less attention than the technology dimension of the transition, although being of critical importance to policymakers. In this work, we adapt a methodology based on employment factors to project future changes in quantity and composition of direct energy supply jobs for two scenarios - (1) relatively weak emissions reductions as pledged in the nationally determined contributions (NDC) and (2) stringent reductions compatible with the 1.5 °C target. We find that in the near-term the 1.5°C-compatible scenario results in a net increase in jobs through gains in solar and wind jobs in construction, installation, and manufacturing, despite significant losses in coal fuel supply; eventually leading to a peak in total direct energy jobs in 2025. In the long run, improvements in labour productivity lead to a decrease of total direct energy employment compared to today, however, total jobs are still higher in a 1.5 °C than in an NDC scenario. Operation and maintenance jobs dominate future jobs, replacing fuel supply jobs. The results point to the need for active policies aimed at retraining, both inside and outside the renewable energy sector, to complement climate policies within the concept of a “just transition”.
Cost degression in photovoltaics, wind-power and battery storage has been faster than previously anticipated. In the future, climate policy to limit global warming to 1.5–2 °C will make carbon-based fuels increasingly scarce and expensive. Here we show that further progress in solar- and wind-power technology along with carbon pricing to reach the Paris Climate targets could make electricity cheaper than carbon-based fuels. In combination with demand-side innovation, for instance in e-mobility and heat pumps, this is likely to induce a fundamental transformation of energy systems towards a dominance of electricity-based end uses. In a 1.5 °C scenario with limited availability of bioenergy and carbon dioxide removal, electricity could account for 66% of final energy by mid-century, three times the current levels and substantially higher than in previous climate policy scenarios assessed by the Intergovernmental Panel on Climate Change. The lower production of bioenergy in our high-electrification scenarios markedly reduces energy-related land and water requirements.
In Germany, the productivity of professional services, a sector dominated by micro and small firms, declined by 40 percent between 1995 and 2014. This productivity decline also holds true for professional services in other European countries. Using a German firm-level dataset of 700,000 observations between 2003 and 2017, we analyze this largely uncovered phenomenon among professional services, the 4th largest sector in the EU15 business economy, which provide important intermediate services for the rest of the economy. We show that changes in the value chain explain about half of the decline and the increase in part-time employment is a further minor part of the decline. In contrast to expectations, the entry of micro and small firms, despite their lower productivity levels, is not responsible for the decline. We also cannot confirm the conjecture that weakening competition allows unproductive firms to remain in the market.
Elevated annual average temperature has been found to impact macro-economic growth. However, various fundamental elements of the economy are affected by deviations of daily temperature from seasonal expectations which are not well reflected in annual averages. Here we show that increases in seasonally adjusted day-to-day temperature variability reduce macro-economic growth independent of and in addition to changes in annual average temperature. Combining observed day-to-day temperature variability with subnational economic data for 1,537 regions worldwide over 40 years in fixed-effects panel models, we find that an extra degree of variability results in a five percentage-point reduction in regional growth rates on average. The impact of day-to-day variability is modulated by seasonal temperature difference and income, resulting in highest vulnerability in low-latitude, low-income regions (12 percentage-point reduction). These findings illuminate a new, global-impact channel in the climate–economy relationship that demands a more comprehensive assessment in both climate and integrated assessment models.
We develop a model of optimal carbon taxation and redistribution taking into account horizontal equity concerns by considering heterogeneous energy efficiencies. By deriving first- and second-best rules for policy instruments including carbon taxes, transfers and energy subsidies, we then investigate analytically how horizontal equity is considered in the social welfare maximizing tax structure. We calibrate the model to German household data and a 30 percent emission reduction goal. Our results show that energy-intensive households should receive more redistributive resources than energy-efficient households if and only if social inequality aversion is sufficiently high. We further find that redistribution of carbon tax revenue via household-specific transfers is the first-best policy. Equal per-capita transfers do not suffer from informational problems, but increase mitigation costs by around 15 percent compared to the first- best for unity inequality aversion. Adding renewable energy subsidies or non-linear energy subsidies, reduces mitigation costs further without relying on observability of households’ energy efficiency.
We study the role and drivers of persistence in the extensive margin of bilateral trade. Motivated by a stylized heterogeneous firms model of international trade with market entry costs, we consider dynamic three-way fixed effects binary choice models and study the corresponding incidental parameter problem. The standard maximum likelihood estimator is consistent under asymptotics where all panel dimensions grow at a constant rate, but it has an asymptotic bias in its limiting distribution, invalidating inference even in situations where the bias appears to be small. Thus, we propose two different bias-corrected estimators. Monte Carlo simulations confirm their desirable statistical properties. We apply these estimators in a reassessment of the most commonly studied determinants of the extensive margin of trade. Both true state dependence and unobserved heterogeneity contribute considerably to trade persistence and taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin.
Integrated assessment models (IAMs) form a prime tool in informing about climate mitigation strategies. Diagnostic indicators that allow comparison across these models can help describe and explain differences in model projections. This increases transparency and comparability. Earlier, the IAM community has developed an approach to diagnose models (Kriegler (2015 Technol. Forecast. Soc. Change 90 45–61)). Here we build on this, by proposing a selected set of well-defined indicators as a community standard, to systematically and routinely assess IAM behaviour, similar to metrics used for other modeling communities such as climate models. These indicators are the relative abatement index, emission reduction type index, inertia timescale, fossil fuel reduction, transformation index and cost per abatement value. We apply the approach to 17 IAMs, assessing both older as well as their latest versions, as applied in the IPCC 6th Assessment Report. The study shows that the approach can be easily applied and used to indentify key differences between models and model versions. Moreover, we demonstrate that this comparison helps to link model behavior to model characteristics and assumptions. We show that together, the set of six indicators can provide useful indication of the main traits of the model and can roughly indicate the general model behavior. The results also show that there is often a considerable spread across the models. Interestingly, the diagnostic values often change for different model versions, but there does not seem to be a distinct trend.
We investigate how the economic consequences of the pandemic, and of the government-mandated measures to contain its spread, affect the self-employed – particularly women – in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are 35% more likely to experience income losses than their male counterparts. Conversely, we do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, i.e. the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.