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Carbon adjustment in a consumption-based emission inventory accounting: a CGE analysis and implications for a developing country

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Abstract

Because ‘border carbon adjustment (BCA)’ may violate the presently operational National Emission Inventory (NEI) accounting practised under the United Nations Framework Convention on Climate Change (UNFCCC) which is based on territorial production–based emission reduction responsibility approach, this study intends to investigate the implications of BCA imposition on the exports from a developing country under a territorial consumption-based alternative framework. With this alternative framework of accounting, the study assumes the BCA-burdened developing country to implement ‘domestic carbon adjustment (DCA)’ measures and experiments by applying a static ‘computable general equilibrium (CGE)’ modelling. The result from this study indicates that the closer the rates of BCA and the DCA, the more effective the carbon adjustment schemes are to reduce the emission intensity of energy use. The stricter carbon adjustment measures also found changing the energy consumption pattern of productive sectors by inducing the emission-intensive sectors to switch towards low-emission intensive natural gas. The study recommends the implementation of DCA measures for a developing country as stricter as compared to the foreign standards in a consumption-based framework to make the carbon adjustment initiatives more effective.

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Notes

  1. ‘Carbon leakage’ is said to happen when the mitigation efforts from the developed countries due to their stricter unilateral environmental regulations are offset by the excessive emissions generated from the non-binding developing countries due to their relative weaknesses in carbon regulation policies (Böhringer et al. 2017).

  2. The system boundary is a conceptual line that divides any system from its environment. Any system’s environment is made up of things that are not part of the system but can either affect the system or be affected by it.

  3. See this definition in Intergovernmental Panel on Climate Change (IPCC 1996).

  4. Appendix 1 explains this production structure with equations (9) to (16).

  5. The Stone-Geary utility function first represented by Roy C. Geary (1950) which introduces the element of subsistence level of consumption to the standard Cobb-Douglas utility function.

  6. Indirect taxes, as reported in the SAM, are net of subsidies and inclusive of all types of indirect taxes for domestic goods production, consumption, and foreign goods import and export.

  7. The Walrasian model assumes that if all the (n-1) number of markets are in equilibrium then the n-th market will also be in equilibrium, so the model would contain only (n-1) number of independent equations to show the equilibrium conditions for all ‘n’ markets.

  8. See Appendix 2 for the equations depicting the scenario experiments.

  9. So far there is no consensus in the literature for the choice of any particular rate on carbon price. The carbon adjustment rates in this study are based on the argument of Li and Su (2017). The carbon adjustment rates are converted into local currency equivalent based on the average exchange rate in 2007–2008 which was USD 1 = INR 41.26 (Reserve Bank of India).

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Appendices

Appendix 1. Production functions

Tier-I processing: coal and oil composite (FUELi)

$$ {QFUEL}_c={\alpha}_c^1{\left\{{\delta}_c^1{QCOAL}_c^{-{\rho}_c^1}+\left(1-{\delta}_c^1\right){QPOIL}_c^{-{\rho}_c^1}\right\}}^{-\frac{1}{\rho_c^1}} $$
(9)

where

QFUEL :

quantity of ‘coal-oil composite’ commodity

QCOAL, :

quantities of ‘coal and coal products’

QPOIL :

quantity of ‘oil and oil products’

\( {\alpha}_c^1 \), \( {\delta}_c^1,{\rho}_c^1 \):

CES function (1) scale and share parameter and the exponent, respectively.

Tier-II processing: fossil fuel composite (FOSSILi)

$$ {QFOSSIL}_c={\alpha}_c^2{\left\{{\delta}_c^2{QFUEL}_c^{-{\rho}_c^2}+\left(1-{\delta}_c^2\right){QNGAS}_c^{-{\rho}_c^2}\right\}}^{-\frac{1}{\rho_c^2}} $$
(10)

where

QFOSSIL :

quantity of ‘fossil fuel aggregate’ commodity

QNGAS :

quantities of natural gas.

\( {\alpha}_c^2 \), \( {\delta}_c^2,{\rho}_c^2 \):

CES function (2) scale and share parameter and the exponent, respectively.

Tier-III processing: energy composite (ENERGYi)

$$ {QENERGY}_c={\alpha}_c^3{\left\{{\delta}_c^3{QFOSSIL}_c^{-{\rho}_c^3}+\left(1-{\delta}_c^3\right).{\left({\lambda}_{ELEC}{QELEC}_c\right)}^{-{\rho}_c^3}\right\}}^{-\frac{1}{\rho_c^3}} $$
(11)

where

QENERGY :

quantity of ‘energy composite’ commodity

QELEC :

quantities of ‘electricity’

\( {\alpha}_c^3 \), \( {\delta}_c^3,{\rho}_c^3 \):

CES function (3) scale and share parameter and the exponent, respectively.

Tier-IV processing: value-added composite (VAi)

$$ {QVA}_c={\alpha}_c^4{\left\{{\delta}_c^4{LD}_c^{-{\rho}_c^4}+\left(1-{\delta}_c^4\right){KD}_c^{-{\rho}_c^4}\right\}}^{-\frac{1}{\rho_c^4}} $$
(12)

where

QVA :

production of ‘value added composite’ commodity

LD, KD :

input demands for ‘labour’ and ‘capital’, respectively

\( {\alpha}_c^4 \), \( {\delta}_c^4,{\rho}_c^4 \):

CES function (4) scale and share parameter and the exponent, respectively.

Tier-V processing: value-added and energy composite (QVAENi)

$$ { QVA EN}_c={\alpha}_c^5{\left\{{\delta}_c^5{\left({QVA}_C\right)}^{-{\rho}_c^5}+\left(1-{\delta}_c^5\right){QENERGY}_c^{-{\rho}_c^5}\right\}}^{-\frac{1}{\rho_c^5}} $$
(13)

where

QVAEN :

quantity of ‘value-added energy composite’ commodity

\( {\alpha}_c^5 \), \( {\delta}_c^5,{\rho}_c^5 \):

CES function (5) scale and share parameter and the exponent, respectively.

Tier-VI processing: intermediate input aggregate (INTi)

Input demand functions

$$ {QINT}_{CINT}^c={\mathit{\operatorname{int}}}_{CINT}^c{ QINT A}_C $$
(14)

where

QINTA :

quantity of intermediate aggregate

QINT:

quantity of intermediate inputs

\( {\mathit{\operatorname{int}}}_{CINT}^c \) :

Leontief coefficients (input CINT per unit of aggregate intermediate)

Tier-VII processing: final output (Xi)

Input demand functions

$$ {QVAEN}_c={ivaen}_c{QX}_C $$
(15)
$$ {QINTA}_c={inta}_c{QX}_c $$
(16)

where

QX :

quantity of final output

ivaen :

Leontief coefficients for the QVAEN in the final output production

inta:

Leontief coefficients for the QINTA in the final output production

Appendix 2. Simulations

Foreign countries imposing the BCA on Indian export. With BCA imposition Indian exporters receiving lower prices for their commodities.

$$ {PEX}_c\left(1+\frac{\left({bca}_c{EMINT}_c\right)}{PX_c}\right)={\overline{PWEX}}_c. EXR $$
(17)

where

PEX :

supply price of Indian export

\( \overline{PWEX} \) :

exogenous world price of Indian export

EXR :

exchange rate

bca :

border carbon adjustment

India imposing the RBCA on its import. With RBCA imposition the tax burden is shared between Indian consumers and the foreign importers.

$$ {PIM}_c\left(1-\frac{\left({rbca}_c{emm}_c\right)}{PWIM_c}\right)={PWIM}_c. EXR $$
(18)

where

PIM :

domestic price of Indian import

PWIM:

endogenous world price of Indian import

rbca :

retaliatory border carbon adjustment

Under DCA measure, India imposing a PCA on Indian production of final output. With PCA imposition the cost function for the final output processing will change.

$$ {PX}_c\left(1-\frac{\left({pca}_c{EMINT}_c\right)}{PX_c}\right)=\frac{QVAEN_c{PVAEN}_c+{QINTA}_c{PINTA}_c}{QX_c} $$
(19)

where

QX, PX :

quantity and price of final output

QVAEN:

quantity of ‘value-added and energy composite’ commodity

PVAEN:

price of ‘value-added and energy composite’ commodity

QINTA :

quantity of intermediate aggregate

PINTA :

price of intermediate input aggregate

pca :

production carbon adjustment

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Banerjee, S. Carbon adjustment in a consumption-based emission inventory accounting: a CGE analysis and implications for a developing country. Environ Sci Pollut Res 28, 19984–20001 (2021). https://doi.org/10.1007/s11356-020-11771-3

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