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Who gains from technological advancement? The role of policy design when cost development for key abatement technologies is uncertain

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Abstract

A simple model is used to illustrate the effects of a reduction in (marginal) abatement cost in a two-country setting. It can be shown that a country experiencing a cost reduction can actually be worse off. This holds true for a variety of quantity and price-based emission policies. Under price-based policies, a country with lower abatement costs might engage in additional abatement effort for which it is not compensated. Under a quantity-based policy with a given allocation, a seller of permits can also be negatively affected by a lower carbon price. We also argue that abatement cost shocks to renewable energy and carbon capture and storage (CCS) are different in terms of their effects on international energy markets. A shock to renewable energy benefits energy importers because the value of fossil fuels is reduced. The opposite holds for a shock to CCS which benefits energy exporters. The channels identified in the theoretical model can be confirmed in a more complex global computable general equilibrium model. Some regions are indeed worse off from a shock that lowers their abatement costs.

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Notes

  1. The result from this overlapping regulation is a decline in emission prices and a thus a reduction in the cost of emission abatement within the emission trading scheme (ETS). The total welfare cost increases because renewable energy requirements constitute an additional constraint in the cost minimizing problem.

  2. In this section we only analyze the impacts of a shock that leads to lower abatement costs in an abatement technology. The results, however, can easily be carried over to the case when costs of abatement technologies are higher than expected.

  3. Note that this model does not explicitly include marginal damages and we assume here an exogenous target for emissions. A comparison of marginal damages and marginal abatement cost would, however, be required to find the optimal policy instrument under uncertainty (Weitzman 1974). The aim of the paper is not to determine an optimal policy, but rather to stress the characteristics of policy instruments under abatement cost uncertainty.

  4. More specifically, the tax is paid by atomistic producers in the country and refunded lump sum to a representative household of the country. Further assuming that the representative household owns the productive capital in the country, there are zero international net payments and tax payments and receipts offset each other from the perspective of the entire country. The country could improve its welfare by adjusting the tax rate in response to the tax, but the second best setting with a locked in tax rate \(\bar{\lambda }\) prevents the country from doing so.

  5. Plugging the expression for \(a_1\) from Eq. (7) into Eq. (6) and differentiating with respect to \(\phi\) yields \(\frac{1}{6}\frac{\bar{\lambda }^\frac{3}{2}}{\sqrt{\beta \phi }}\) which is larger than zero, indicating rising costs for the quadratic case. For other convex functions it is a priori not clear which of the two effect dominates.

  6. The setup of the figures in this section is similar to Anger (2008) who uses this method to show distributional consequences of linking emission trading systems.

  7. This result is comparable to Peterson and Klepper (2007), who state that under a globally harmonized carbon tax countries with lower marginal abatement costs will face higher total abatement costs.

  8. This setting would be equivalent to an auctioning of permits by a global agency which then redistributed revenues lump sum to those countries which have bought the permits.

  9. There are of also cases where country 1 could switch from a buyer to a seller. This is not visible in Eq. (15) as this is only the marginal effect, but could be easily shown in a variation for Fig. 3.

  10. In this case it will gain unambiguously because also the cost for the remaining permits it needs to buy declines.

  11. For the interval between \(a_2\) and \(a_2'\) country 2 now prefers to buy additional permits, which is cheaper than own abatement.

  12. Shocks to cost of key abatement technologies are likely to be positively correlated so that all countries will enjoy a cost reduction. However, the benefit will be higher in countries that can make better use of the technology, e.g., because of geographical features.

  13. We assume that the price increases with further demand for fossil fuel (\(\frac{\partial p}{\partial \sum _i f_i} > 0\)) and decreases with additional supply for renewable energy (\(\frac{\partial p}{\partial \sum _i r_i} < 0\)) and renewable energy is not traded.

  14. Here we consider only one type of fossil fuel. In the CGE model in Sect. 3, different kinds of fossil fuels (coal, oil, and gas) with different carbon contents are explicitly modeled.

  15. An alternative interpretation would be that the technology shock improves the capture rate, i.e., the share of CO\(_2\) that is captured and not released into the atmosphere.

  16. This would mean that \(|\frac{\partial (1-\theta _1)f_1}{\partial \phi } |> |\frac{\partial \theta _1 f_2}{\partial \phi } |\), making use of net exports being re-written as \((1-\theta _1)f_1-\theta _1 f_2\).

  17. This follows from \(f_1\) and \(f_2\) changing in the same proportion and the fact that production shares are held constant at \(\theta _1\) and \(\theta _2\).

  18. The scenario is not designed to find an optimal policy to exploit learning-by-doing. We are rather interested in the changes of cost induced by a certain shock.

  19. The cost penalties reported here are simple unweighted averages of the model regions.

  20. The LES demand system differentiates between basic demand which is not generating utility and other consumption. The consumption level here only refers to the latter.

  21. All variables referring to levels are in per cent and variables referring to changes are expressed in percentage points, see also Appendix 3 for more details on the variables.

  22. While the coefficient for within region energy trade has a positive sign and thus an opposing effect, most of the variation is between regions. The between region channel thus dominates here, see also Fig. 7.

  23. Both in the case of Tax and Tax*, revenues are returned domestically lump sum, while in the case of a fixed allocation there is a transfer to other countries.

  24. Under Tax* and ntr schemes, Japan, Canada, Europe (WEU and EEU), and Pacific Asia are worse off. Under CDC, only India and Japan are worse off while in the tax scenario all countries, but India, Russia (FSU), Australia (ANZ) and Latin America are worse off.

  25. If payment of taxes and revenue allocation were decoupled, then this effect would no longer hold. This would, however, require an international mechanism for distribution of revenues and would create international transfers. Proponents of a regime with a coordinated tax rate claim that the very absence of international transfers increases the chances for implementation.

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Acknowledgments

I am grateful to Sonja Peterson for very helpful comments. I would like to thank Till Requate for fruitful discussions and Michael Rose for research assistance. Anonymous reviewers provided helpful suggestions that improved the manuscript. Funding was provided by the German Federal Ministry of Education and Research (reference 01LA1127C).

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Correspondence to Matthias Weitzel.

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Appendices

Appendix 1: Derivation of some equations

Making use of Eqs. (6) and (8), it follows that

$$\begin{aligned} \eta _{C_{1}\phi }= & \frac{\partial C_1}{\partial \phi } \frac{\phi }{C_1} \nonumber \\= & \left( - \frac{1}{3} \frac{\beta }{\phi } a_1^3 + \frac{1}{3} \frac{\partial a_1^3}{\phi } \right) \frac{\phi }{\frac{1}{3} \frac{\beta }{\phi } a_1^3} \nonumber \\= \,& \eta _{a_1^3 \phi } -1 \end{aligned}$$
(20)

with

$$\begin{aligned} \eta _{a_1^3 \phi } = \frac{\partial a_1^3}{\partial \phi } \frac{\phi }{a_1^3}. \end{aligned}$$
(21)

This leads to

$$\begin{aligned} \frac{\partial C_1}{\partial \phi } = \frac{C_1}{\phi }\eta _{C_{1}\phi } = \frac{C_1}{\phi }\left( \eta _{a_1^3 \phi } -1 \right) \end{aligned}$$
(22)

and thus to condition (9).

Analogously, for globally constant emissions equation (11) can be re-written as

$$\begin{aligned} \eta _{C_{1}\phi }&= \frac{\partial C_1}{\partial \phi } \frac{\phi }{C_1} \nonumber \\&= \left( - \frac{1}{3} \frac{\partial \lambda }{\partial \phi } a_1 + \frac{1}{3} \lambda \frac{\partial a_1}{\phi } \right) \frac{\phi }{\frac{1}{3} \frac{\beta }{\phi } a_1^3} \nonumber \\&= \frac{\partial \lambda }{\partial \phi } \frac{\phi }{\lambda } + \frac{\partial a_1}{\partial \phi } \frac{\phi }{a_1} \nonumber \\&= \eta _{\lambda \phi } + \eta _{a_1 \phi } \end{aligned}$$
(23)

which leads to condition (12).

For the emission trading system, the elasticity of cost \(C_i\) for \(\phi\) can be calculated from Eqs. (14) and (15)

$$\begin{aligned} \eta _{C_{i}\phi }= & \frac{\partial C_i}{\partial \phi } \frac{\phi }{C_i} \nonumber \\= & \left[ \frac{1}{3}\frac{\partial \lambda }{\partial \phi } a_i + \frac{1}{3}\lambda \frac{\partial a_i}{\partial \phi } + \frac{\partial \lambda }{\partial \phi } \left( \hat{a}_i - a_i \right) - \lambda \frac{\partial a_i}{\partial \phi } \right] \frac{\phi }{\frac{1}{3}\lambda a_i + \lambda \left( \hat{a}_i - a_i \right) } \nonumber \\= & {} \left[ \left( \frac{1}{3} a_i + \left( \hat{a}_i - a_i \right) \right) \frac{\partial \lambda }{\partial \phi } + \left( \frac{1}{3} \lambda -\lambda \right) \frac{\partial a_i}{\partial \phi } \right] \frac{\phi }{\frac{1}{3}\lambda a_i + \lambda \left( \hat{a}_i - a_i \right) } \nonumber \\= & \frac{\frac{1}{3} a_i + \left( \hat{a}_i - a_i \right) }{\frac{1}{3} a_i + \left( \hat{a}_i - a_i \right) } \frac{\partial \lambda }{\partial \phi } \frac{\phi }{\lambda } + \frac{\left( \frac{1}{3} \lambda -\lambda \right) }{ \frac{1}{3} \lambda + \frac{\lambda \hat{a}_i}{a_i} - \lambda } \frac{\partial a_i}{\partial \phi } \frac{\phi }{a_i} \nonumber \\= & \eta _{C_i\lambda } \eta _{\lambda \phi } + \eta _{C_i a_i} \eta _{a_i \phi } \end{aligned}$$
(24)

with

$$\begin{aligned} \eta _{C_i\lambda } = 1 \end{aligned}$$
(25)

and

$$\begin{aligned} \eta _{C_i a_i} = \frac{ \frac{1}{3}\lambda a_i - \lambda a_i }{ \frac{1}{3}\lambda a_i + \lambda \left( \hat{a}_i - a_i \right) } \end{aligned}$$
(26)

which leads to condition (16).

Appendix 2: Regions and sectors in the DART model

Countries and regions

WEU

Western Europe

CPA

China, Hong-Kong

EEU

Eastern Europe

IND

India

USA

United States of America

LAM

Latin America

JPN

Japan

PAS

Pacific Asia

CAN

Canada

MEA

Middle East and Norther Africa

ANZ

Australia, New Zealand

AFR

Sub-Saharan Africa

FSU

Former Soviet Union

  

Production sectors/commodities

Energy sectors

Non-energy sectors

COL

Coal

AGR

Agricultural production

CRU

Crude oil

ETS

Energy intensive production

GAS

Natural gas

OTH

Other manufactures and services

OIL

Refined oil products

CRP

Chemical products

ELY

Electricity

MOB

Mobility

  

OLI

Other light industries

  

OHI

Other heavy industries

  

SVCS

Services

Renewable and advanced electricity technologies

WIN

Wind

SOL

Solar

HYD

Hydro

SBIO

Solid biomass

GASCCS

Advanced gas with CCS

COLCCS

Advanced coal with CCS

Appendix 3: Variables used in regression analysis

Variable name

Description

Change in renewables

Change in the share of solar and wind in the electricity mix in percentage points (relative to the scenario without a shock)

Change in CCS

Change in the share of CCS in the electricity mix in percentage points (relative to the scenario without a shock)

Pre-shock level of renewables

Share of solar and wind in the electricity mix in percent in the scenario without a shock

Pre-shock level of CCS

Share of CCS in the electricity mix in percent in the scenario without a shock

Pre-shock net fossil fuel exports

Value of net fossil fuel export without shock relative to GDP

Pre-shock net coal exports

Value of net coal export without shock relative to GDP

Pre-shock net gas exports

Value of net natural gas export without shock relative to GDP

Pre-shock net oil exports

Value of net export of crude oil and oil products without shock relative to GDP

Change in emissions

Change in emissions in percent (relative to the scenario without a shock)

Pre-shock surplus

Value of emission allowances sold on the international carbon market relative to GDP in the scenario without a shock

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Weitzel, M. Who gains from technological advancement? The role of policy design when cost development for key abatement technologies is uncertain. Environ Econ Policy Stud 19, 151–181 (2017). https://doi.org/10.1007/s10018-016-0142-9

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