No time to tax! Can a gradually increasing carbon tax really provide a cost-efficient green transition?

Author(s):  
Claudia Wieners ◽  
Francesco Lamperti ◽  
Andrea Roventini ◽  
Roberto Buizza

<p>It is widely assumed in climate economics that a uniform, gradually increasing carbon tax mirroring the “social cost of carbon” (SCC) leads to cost-optimal emission reduction. The underlying idea is that emitters switch to carbon-saving technologies as soon as the tax becomes so high that this switch saves money. If we let the tax equal the SCC, i.e. the extra damage caused by emitting one extra ton of CO2, then everybody who can save carbon at a lower price than the damage caused by this emission will do so, whereas those for whom the emission-saving costs more than the associated damage will not. Models like Nordhaus’ famous DICE model find a roughly exponentially increasing SCC, corresponding to an exponentially increasing carbon tax.</p><p>We implemented such an exponentially increasing carbon tax in a simple agent-based model, the Dystopian Schumpeter-Keynes (DSK) model. Agent-based models dispense with restrictive perfect rationality and market equilibrium assumptions and are able to describe non-equilibrium dynamics and tipping as emergent properties of collective behaviour. They are not yet widely used in climate economics.</p><p>The DSK model contains two types of firms which manufacture machines or a consumption good, respectively, using labour and energy (electricity and/or fuel). Electricity is provided by a monopolist using green (carbon neutral) or brown (fuel-based) plants.</p><p>In DSK, the DICE-based carbon tax is far from satisfying as climate policy. In the first ≈30 years, the tax is too low to trigger a green transition in the electricity sector. When green plants finally do become competitive, it still takes decades until the transition is completed, because power plants have a long lifetime and are replaced only gradually. Higher taxes can speed up the process somewhat, but even modest increases in the transition rate require big increases in the tax (and hence considerable side effects on the economy, including unemployment). The exponentially increasing carbon tax is thus low at the beginning of the transition, where higher taxes would be most needed, but becomes high (with associated side effects) at later stages, when the transition is already gaining momentum by positive feedbacks, most notably innovation reducing the price of green plants. It would be preferable to implement a constant (or even slightly decreasing) tax which is sufficiently high from the beginning.</p><p>Apart from green electricity, decarbonisation also requires fuel-using firms to switch to electricity. However, the carbon tax does not incentivise this switch initially, as the tax increases not only fuel price, but also electricity price. Again, the switch takes time, while rapid decarbonisation requires a swift start of electrification. One way around it is to levy a higher carbon tax on manufacturing firms than on the electricity sector (to make electricity use more attractive); alternatively, one could simply impose regulations.</p><p>Our results suggest that a carbon tax should not be gradually increasing and uniform, but high from the beginning and sector-dependent. We also find that tax-free policies, such as green subsidies or regulations, can bring about a green transition with possibly less side effects.</p>

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2150 ◽  
Author(s):  
Steve Dahlke

This paper presents estimates of short run impacts of a carbon price on the electricity industry using a cost-minimizing mathematical model of the U.S. market. Prices of $25 and $50 per ton of carbon dioxide equivalent emissions cause electricity emissions reductions of 17% and 22% from present levels, respectively. This suggests significant electricity sector emissions reductions can be achieved quickly from a modest carbon tax, and diminishing reductions occur when increasing from $25 to $50. The model captures short run effects via operational changes at existing U.S. power plants, mostly by switching production from coal to natural gas. A state-level analysis yields the following conclusions: (1) states which reduce the most emissions are high coal-consumers in the Mid-Atlantic and Midwest regions, (2) 15 states increase emissions after carbon policy because they increase natural gas consumption to offset coal consumption decreases in neighboring states, and (3) a flat per-capita rebate of tax revenue leads to wealth transfers across states.


2019 ◽  
Author(s):  
Steven Dahlke

This paper presents estimates of short run impacts of a carbon price on the electricity industry using a cost-minimizing mathematical model of the U.S. market. Prices of 25 and 50 dollars per ton of carbon dioxide equivalent emissions cause electricity emissions reductions of 17% and 22% from present levels, respectively. This suggests significant electricity sector emissions reductions can be achieved quickly from a modest carbon tax. Short run effects refer to operational changes at existing U.S. power plants, mostly by switching production from coal plants to natural gas plants. The results do not include long run emissions reductions related to 1) new investments and retirements of electricity production assets, and 2) demand response as regulated electricity suppliers pass cost changes to retail customers. A state-level analysis of the results leads to the following conclusions: 1) most emissions reductions come from high coal-consuming states in the Mid-Atlantic and Midwest regions, 2) fifteen states increase emissions because their natural gas consumption offsets coal consumption in neighboring states, and 3) a flat per-capita rebate of tax revenue leads to wealth transfers across states.


Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 84
Author(s):  
Jinxi Yang ◽  
Christian Azar ◽  
Kristian Lindgren

To achieve the climate goals of the Paris Agreement, greenhouse gas emissions from the electricity sector must be substantially reduced. We develop an agent-based model of the electricity system with heterogeneous agents who invest in power generating capacity under uncertainty. The heterogeneity is characterised by the hurdle rates the agents employ (to manage risk) and by their expectations of the future carbon prices. We analyse the impact of the heterogeneity on the transition to a low carbon electricity system. Results show that under an increasing CO2 tax scenario, the agents start investing heavily in wind, followed by nuclear and to some extent in natural gas fired power plants both with and without carbon capture and storage as well as biogas fired power plants. However, the degree to which different technologies are used depend strongly on the carbon tax expectations and the hurdle rate employed by the agents. Comparing to the case with homogeneous agents, the introduction of heterogeneity among the agents leads to a faster CO2 reduction. We also estimate the so called “cannibalisation effect” for wind and find that the absolute value of wind does not drop in response to higher deployment levels, but the relative value does decline.


Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3860
Author(s):  
Priyanka Shinde ◽  
Ioannis Boukas ◽  
David Radu ◽  
Miguel Manuel de Manuel de Villena ◽  
Mikael Amelin

In recent years, the vast penetration of renewable energy sources has introduced a large degree of uncertainty into the power system, thus leading to increased trading activity in the continuous intra-day electricity market. In this paper, we propose an agent-based modeling framework to analyze the behavior and the interactions between renewable energy sources, consumers and thermal power plants in the European Continuous Intra-day (CID) market. Additionally, we propose a novel adaptive trading strategy that can be used by the agents that participate in CID market. The agents learn how to adapt their behavior according to the arrival of new information and how to react to changing market conditions by updating their willingness to trade. A comparative analysis was performed to study the behavior of agents when they adopt the proposed strategy as opposed to other benchmark strategies. The effects of unexpected outages and information asymmetry on the market evolution and the market liquidity were also investigated.


mSphere ◽  
2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Emily G. Sweeney ◽  
Andrew Nishida ◽  
Alexandra Weston ◽  
Maria S. Bañuelos ◽  
Kristin Potter ◽  
...  

ABSTRACTBacteria are often found living in aggregated multicellular communities known as biofilms. Biofilms are three-dimensional structures that confer distinct physical and biological properties to the collective of cells living within them. We used agent-based modeling to explore whether local cellular interactions were sufficient to give rise to global structural features of biofilms. Specifically, we asked whether chemorepulsion from a self-produced quorum-sensing molecule, autoinducer-2 (AI-2), was sufficient to recapitulate biofilm growth and cellular organization observed for biofilms ofHelicobacter pylori, a common bacterial resident of human stomachs. To carry out this modeling, we modified an existing platform, Individual-based Dynamics of Microbial Communities Simulator (iDynoMiCS), to incorporate three-dimensional chemotaxis, planktonic cells that could join or leave the biofilm structure, and cellular production of AI-2. We simulated biofilm growth of previously characterizedH. pyloristrains with various AI-2 production and sensing capacities. Using biologically plausible parameters, we were able to recapitulate both the variation in biofilm mass and cellular distributions observed with these strains. Specifically, the strains that were competent to chemotax away from AI-2 produced smaller and more heterogeneously spaced biofilms, whereas the AI-2 chemotaxis-defective strains produced larger and more homogeneously spaced biofilms. The model also provided new insights into the cellular demographics contributing to the biofilm patterning of each strain. Our analysis supports the idea that cellular interactions at small spatial and temporal scales are sufficient to give rise to larger-scale emergent properties of biofilms.IMPORTANCEMost bacteria exist in aggregated, three-dimensional structures called biofilms. Although biofilms play important ecological roles in natural and engineered settings, they can also pose societal problems, for example, when they grow in plumbing systems or on medical implants. Understanding the processes that promote the growth and disassembly of biofilms could lead to better strategies to manage these structures. We had previously shown thatHelicobacter pyloribacteria are repulsed by high concentrations of a self-produced molecule, AI-2, and thatH. pylorimutants deficient in AI-2 sensing form larger and more homogeneously spaced biofilms. Here, we used computer simulations of biofilm formation to show that localH. pyloribehavior of repulsion from high AI-2 could explain the overall architecture ofH. pyloribiofilms. Our findings demonstrate that it is possible to change global biofilm organization by manipulating local cell behaviors, which suggests that simple strategies targeting cells at local scales could be useful for controlling biofilms in industrial and medical settings.


Author(s):  
Seyedeh Asra Ahmadi ◽  
Seyed Mojtaba Mirlohi ◽  
Mohammad Hossein Ahmadi ◽  
Majid Ameri

Abstract Lack of investment in the electricity sector has created a huge bottleneck in the continuous flow of energy in the market, and this will create many problems for the sustainable growth and development of modern society. The main reason for this lack of investment is the investment risk in the electricity sector. One way to reduce portfolio risk is to diversify it. This study applies the concept of portfolio optimization to demonstrate the potential for greater use of renewable energy, which reduces the risk of investing in the electricity sector. Besides, it shows that investing in renewable energies can offset the risk associated with the total input costs. These costs stem from the volatility of associated prices, including fossil fuel, capital costs, maintenance, operation and environmental costs. This case study shows that Iran can theoretically supply ~33% of its electricity demand from renewable energy sources compared to its current 15% share. This case study confirms this finding and predicts that Iran, while reducing the risk of investing in electricity supply, can achieve a renewable energy supply of ~9% with an average increase in supply costs. Sensitivity analysis further shows that with a 10% change in input cost factors, the percentage of renewable energy supply is only partially affected, but basket costs change according to the scenario of 5–32%. Finally, suggestions are made that minimize risk rather than cost, which will bring about an increase in renewable energy supply.


2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Philip J. Ball

Abstract A review of conventional, unconventional, and advanced geothermal technologies highlights just how diverse and multi-faceted the geothermal industry has become, harnessing temperatures from 7 °C to greater than 350 °C. The cost of reducing greenhouse emissions is examined in scenarios where conventional coal or combined-cycle gas turbine (CCGT) power plants are abated. In the absence of a US policy on a carbon tax, the marginal abatement cost potential of these technologies is examined within the context of the social cost of carbon (SCC). The analysis highlights that existing geothermal heat and power technologies and emerging advanced closed-loop applications could deliver substantial cost-efficient baseload energy, leading to the long-term decarbonization. When considering an SCC of $25, in a 2025 development scenario, geothermal technologies ideally need to operate with full life cycle assessment (FLCA) emissions, lower than 50 kg(CO2)/MWh, and aim to be within the cost range of $30−60/MWh. At these costs and emissions, geothermal can provide a cost-competitive low-carbon, flexible, baseload energy that could replace existing coal and CCGT providing a significant long-term reduction in greenhouse gas (GHG) emissions. This study confirms that geothermally derived heat and power would be well positioned within a diverse low-carbon energy portfolio. The analysis presented here suggests that policy and regulatory bodies should, if serious about lowering carbon emissions from the current energy infrastructure, consider increasing incentives for geothermal energy development.


Author(s):  
Sebastiaan Tieleman

AbstractAgent-based models provide a promising new tool in macroeconomic research. Questions have been raised, however, regarding the validity of such models. A methodology of macroeconomic agent-based model (MABM) validation, that provides a deeper understanding of validation practices, is required. This paper takes steps towards such a methodology by connecting three elements. First, is a foundation of model validation in general. Second is a classification of models dependent on how the model is validated. An important distinction in this classification is the difference between mechanism and target validation. Third, is a framework that revolves around the relationship between the structure of models of complex systems with emergent properties and validation in practice. Important in this framework is to consider MABMs as modelling multiple non-trivial levels. Connecting these three elements provides us with a methodology of the validation of MABMs and allows us to come to the following conclusions regarding MABM validation. First, in MABMs, mechanisms at a lower level are distinct from, but provide input to higher levels of mechanisms. Since mechanisms at different levels are validated in different ways we can come to a specific characterization of MABMs within the model classification framework. Second, because the mechanisms of MABMs are validated in a direct way at the level of the agent, MABMs can be seen as a move towards a more realist approach to modelling compared to DSGE.


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