## wpiea2021207-print-pdf

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---

### Motivation and scope
- Unilateral climate policies can lead to carbon leakage, "whereby domestic emission reductions are offset by increases in other countries."
- Carbon leakage is relevant because it:
  - "undermines the effectiveness of unilateral environmental policies."
  - "can reflect a loss of domestic economic competitiveness and global market share if production costs increase."
  - "provides the rationale for border carbon adjustment mechanisms."
- Objective: to "revisit carbon leakage econometrically."

### Literature and open questions
- Theoretical literature: no consensus on magnitude or sign of carbon leakage; earlier papers find positive leakage rates of widely differing magnitudes; some recent models identify channels for negative leakage.
- Empirical literature: smaller than theoretical literature and "mostly imply that carbon leakage is limited"; many studies face "data-related and methodological limitations" including limited historical variation in carbon pricing and measurement issues.
- Noted empirical controversies and issues:
  - "Green paradox" / intertemporal leakage (Sinn (2012); Jensen et al., 2015).
  - Critiques on Kyoto-channel for leakage and sectoral variation complicating causal identification (Naegele and Zaklan (2019); Branger and Quirion (2014); Sato and Dechezleprêtre (2015)).

### Methodological innovations
- Two main innovations:
  - Use policy-induced changes in country-sector-specific energy prices as plausibly exogenous variation in carbon emissions and flows (data from Sato et al. (2019)); combine with country-sector carbon embodied in final demand and trade flows (Wiebe and Yamano (2016)).
    - Rationale: energy prices vary more than historical carbon prices and cover more countries and sectors, allowing richer controls and reduced omitted variable bias.
  - Develop a simple accounting framework for emissions to calculate carbon leakage rates from estimated energy-price elasticities of cross-border carbon flows and domestic emissions; yields "an expression for carbon leakage that is akin to the theoretical modeling literature."

### Data and coverage
- Carbon embodied data: OECD’s Trade in Embodied CO2 Database (TECO2) compiled by Wiebe and Yamano (2016).
- Sectoral energy prices: Sato et al. (2019), covering 21 production sectors in 48 countries for 1995–2015; prices are weighted averages of tax-inclusive fuel-specific prices.
- Missing data complemented with national sources for Russia, China and India; average user-price for electricity and natural gas used as an additional sector.
- Merged dataset: unbalanced panel covering 38 countries and 21 sectors over the 2005–15 period.
- Combined emissions in estimation: sectors account for 75 percent of all production-related domestic emissions on average across covered countries (60 percent coverage of global emissions from production); note ~15 percent of global carbon emissions are from households’ electricity and fuel consumption (not included).

### Empirical specification
- Log-log elasticity regressions with country-sector, country-year and sector-year fixed effects.
- Dependent variables:
  - carbon embodied in exports from sector s in country i to rest of world;
  - carbon embodied in imports of country i originating from sector s in rest of world;
  - carbon embodied in domestic final demand of country i originating from sector s;
  - domestic carbon emissions of sector s and country i.
- Standard errors clustered at the country-sector level.

### Main regression estimates (Table 1)
- Impact of sectoral energy price on carbon flows (coefficients; standard errors in parentheses):
  - Imports: 0.0158 (0.0491)
  - Exports: -0.321** (0.155)
  - Emissions: -0.523*** (0.151)
  - Consumption: -0.198* (0.103)
- Observations:
  - Imports: 8,247
  - Exports: 8,124
  - Emissions: 8,168
  - Consumption: 8,235
- R-squared:
  - Imports: 0.997
  - Exports: 0.983
  - Emissions: 0.986
  - Consumption: 0.993
- Key interpretations:
  - Higher energy prices significantly reduce carbon embodied in exports (elasticity -0.321**) and domestic emissions (coefficient -0.523***).
  - Reduction in carbon consumption is significant but smaller (-0.198*), consistent with imports contributing to domestic demand.
  - No significant effect on carbon embodied in imports (0.0158, not statistically significant).
- Illustrative comparison:
  - Sweden average energy price level in 2015: 677 USD per ton of oil equivalent (toe) (in real 2010 USD).
  - United States average energy price in 2015: 275 USD per toe (in real 2010 USD).
  - Using the exports elasticity (-0.321), if the US implemented Sweden’s energy pricing, exports of carbon would decline by more than 30 percent.

### Heterogeneity across countries (Table 2)
- Baseline sectoral energy price and interaction with EU14+UK:
  - Sectoral energy price (baseline):
    - Imports: -0.0394 (0.0598)
    - Exports: -0.260 (0.183)
    - Emissions: -0.451** (0.182)
    - Consumption: -0.250** (0.126)
  - Sectoral energy price × EU14+UK:
    - Imports: 0.168* (0.0954)
    - Exports: -0.187 (0.311)
    - Emissions: -0.222 (0.297)
    - Consumption: 0.157 (0.181)
- Observations and R-squared: same counts and fits as Table 1.
- Interpretation:
  - Interaction terms mostly insignificant, suggesting no statistically significant differences between EU14+UK and non-EU14+UK countries, except imports increase in EU15 following energy price increases (interaction on imports 0.168*).

### Heterogeneity across EITE industries (Table 3)
- EITE sectors: Mining energy, Mining non-energy, Paper products, Refined oil products, Chemicals, Basic metals, Electricity and gas.
- Coefficients:
  - Sectoral energy price:
    - Imports: 0.001 -0.054 (formatting in source ambiguous)
    - Exports: -0.356** (0.168)
    - Emissions: -0.611*** (0.167)
    - Consumption: -0.203* (0.104)
  - Sectoral energy price × EITE:
    - Imports: 0.0432 -0.043 (formatting in source ambiguous)
    - Exports: 0.099 (0.141)
    - Emissions: 0.247* (0.141)
    - Consumption: 0.013 (0.131)
- Observations and R-squared: same as Table 1.
- Interpretation:
  - Interaction terms largely insignificant except domestic emissions (interaction 0.247*), indicating domestic emissions in EITE sectors are more inelastic to energy price changes.

### Other effects of energy price changes (Table 4 & Table 5)
- Energy usage, CO2 intensity, energy mix (Table 4):
  - Sectoral energy price effects:
    - Energy use (log KTOE): -0.347*** (0.0600)
    - CO2 intensity (ratio of CO2 to value added): -2.246* (1.266)
    - Share biofuel: 0.0261*** (0.00655)
  - Observations:
    - Energy use: 8,024
    - CO2 intensity: 8,246
    - Share biofuel: 7,848
  - R-squared:
    - Energy use: 0.993
    - CO2 intensity: 0.676
    - Share biofuel: 0.974
  - Interpretation:
    - Higher energy prices lower energy use and CO2 intensity and raise biofuel share, implying firm-level adjustments in usage and mix that would mitigate leakage.
- Competitiveness indicators (Table 5):
  - Sectoral energy price effects:
    - Value added: -0.219 (0.176)
    - Wages: -0.198* (0.113)
    - Employment: -0.154 (0.140)
  - Observations: 8,247 for all three
  - R-squared: 0.975, 0.988, 0.990
  - Interpretation:
    - Negative signs as expected; value added and employment coefficients lack statistical significance in this sample (but become significant when panel extended to 1995).

### Carbon leakage: conceptual framework and accounting
- Emissions identity for country i:
  - D_i + X_i,RW = Y_i + M_i,RW
    - D_i: carbon embodied in final domestic demand of country i
    - X_i,RW: carbon embodied in exports from i to rest of world
    - M_i,RW: carbon embodied in imports to i from rest of world
    - Y_i: carbon emissions of country i
- Small unilateral domestic carbon price change p̂_i yields:
  - ∂D_i/∂p_i p̂_i + ∂X_i,RW/∂p_i p̂_i = ∂Y_i/∂p_i p̂_i + ∂M_i,RW/∂p_i p̂_i
  - ∂D_RW/∂p_i p̂_i + ∂X_RW,i/∂p_i p̂_i = ∂Y_RW/∂p_i p̂_i + ∂M_RW,i/∂p_i p̂_i
- Leakage definition:
  - L(p̂_i) ≡ 1 − (∂Y_RW/∂p_i) / (∂Y_i/∂p_i) = − (∂Y_RW/∂p_i) / (∂Y_i/∂p_i)
  - For non-infinitesimal changes: L(p̂_i) ≡ − ΔY_RW / ΔY_i
  - Leakage = 1 when domestic reductions fully offset by foreign increases; leakage can be negative if foreign emissions fall.
- Reduced-form accounting expression (assuming ∂D_RW/∂p_i ≈ 0):
  - L(p̂_i) = (β̂_X X_X_i,RW − β̂_M M_M_i,RW) / (β̂_Y Y_Y_i)
    - β̂_X, β̂_M, β̂_Y are estimated elasticities for exports, imports and production (Table 1).

### Country-level leakage estimates and patterns
- (Unweighted) average leakage rate across sample: 0.25.
  - Interpretation: a reduction of 100 tons domestically accompanied by an increase of 25 tons abroad.
- Alternative estimate average leakage rate: 0.15.
- Correlation between two sets of estimates (excluding Switzerland): 0.83.
- Statistical significance: all countries have statistically significant leakage rates at the 90 percent confidence level, except Switzerland.
- Selected country statistics (Table 6 entries; values preserved exactly):
  - AUS: CO2 imports 100.985, CO2 exports 74.432, CO2 product 275.888, leakage est. 0.177
  - AUT: CO2 imports 33.051, CO2 exports 18.735, CO2 product 32.600, leakage est. 0.383
  - BEL: CO2 imports 39.255, CO2 exports 23.823, CO2 product 45.688, leakage est. 0.346
  - CHN: CO2 imports 488.635, CO2 exports 1775.187, CO2 product 7949.845, leakage est. 0.139
  - DEU: CO2 imports 216.854, CO2 exports 153.780, CO2 product 455.922, leakage est. 0.221
  - EU15: CO2 imports 789.657, CO2 exports 298.318, CO2 product 1384.193, leakage est. 0.149
  - JPN: CO2 imports 287.074, CO2 exports 157.272, CO2 product 839.268, leakage est. 0.125
  - USA: CO2 imports 998.644, CO2 exports 258.673, CO2 product 2766.607, leakage est. 0.068
  - ZAF: CO2 imports 34.028, CO2 exports 132.687, CO2 product 336.002, leakage est. 0.245
  - (Full table contains additional country entries and corresponding numeric values.)

### Findings, interpretation and limitations
- Findings and patterns:
  - Carbon leakage can be significant and differs across countries depending on country size and openness to trade.
  - Leakage rates are generally larger for small open economies; EU countries tend to have higher leakage rates individually but the EU14+UK aggregate leakage is relatively low owing to its size.
  - Leakage estimates assume constant marginal effects; leakage may be non-linear for large price changes.
- Caveats and limitations:
  - Reduced-form accounting is agnostic on exact channels (production, trade, consumption) through which price changes operate.
  - Framework not suited to detailed counterfactuals (sectoral carbon prices, border carbon adjustments).
  - Foreign carbon consumption responses to domestic price changes are ignored (assumed small for small countries).
  - Does not capture effects where large open economies depress world fossil fuel demand and reduce world energy prices (could bias estimates downward).
  - Endogenous technological change and energy-saving innovation could reduce leakage over longer periods (potential upward bias if unaccounted).

### Policy implications and recommendations
- Robust empirical estimates of carbon leakage are important for international climate policy debates, including carbon border adjustment mechanisms and unilateral climate policy design.
- Carbon leakage is necessary but not sufficient justification for border carbon adjustments; design complexity, legal and administrative constraints matter.
- Given relatively high leakage rates estimated for many European countries, common European climate policies can be advantageous for reducing cross-border leakage.
- Evidence suggests arguments against carbon border adjustment schemes based on limited empirical evidence could be reconsidered.

### Conclusions and directions for future research
- Carbon leakage differs across countries and can be sizeable, particularly in small open economies.
- The paper leverages policy-induced changes in energy prices (rather than limited carbon price variation) to mitigate downward bias from low carbon price coverage.
- Suggested future research:
  - Explore sectoral differences in leakage with richer models able to compute sectoral and intersectoral leakage.
  - Use structural trade models to estimate foreign consumption responses to domestic carbon price changes.
  - Investigate role of endogenous technological change and international spillovers of energy-saving innovations.

*Source: wpiea2021207-print-pdf*

### References .............................................................................................................

### I. INTRODUCTION

### Motivation and scope
- Unilateral climate policies can lead to carbon leakage, "whereby domestic emission reductions are offset by increases in other countries."
- Carbon leakage is relevant because it:
  - "undermines the effectiveness of unilateral environmental policies."
  - "can reflect a loss of domestic economic competitiveness and global market share if production costs increase."
  - "provides the rationale for border carbon adjustment mechanisms."
- The objective of the paper is to "revisit carbon leakage econometrically."

### Summary of the literature and open questions
- Theoretical literature:
  - Has "not reached consensus on the approximate magnitude or even the sign of carbon leakage."
  - Earlier papers generally find positive leakage rates of widely differing magnitudes; some recent papers identify channels for negative leakage.
- Empirical literature:
  - Smaller than theoretical literature and "mostly imply that carbon leakage is limited."
  - Many empirical studies face "data-related and methodological limitations" including limited historical variation in carbon pricing and measurement issues with loopholes or compensation mechanisms.
  - Some studies find evidence of leakage from the Kyoto Protocol; the result of Aichele and Felbermayr (2015) is "controversial."
- Footnoted issues noted in the source:
  - The "green paradox" or intertemporal leakage—announcing future policy may increase current emissions (Sinn (2012); Jensen et al., 2015).
  - Critiques that the Kyoto-channel for leakage is unclear (Naegele and Zaklan (2019)) and that lack of sectoral variation complicates causal identification (Branger and Quirion (2014); Sato and Dechezleprêtre (2015)).

### Methodological innovations of this paper
- Two main innovations aimed at overcoming limitations of prior empirical work:
  - Exploit "policy-induced changes in country-sector-specific energy prices to estimate plausibly exogenous variation in carbon emissions and flows at the country-sector level" using data by Sato et al. (2019).
    - Rationale: energy prices vary more than historical carbon prices and cover many more countries and sectors, allowing richer controls and reduced omitted variable bias.
    - Combine energy-price data with "country-sector level information on carbon embodied in final demand and trade flows" from Wiebe and Yamano (2016).
  - Calculate carbon leakage rates from estimated coefficients measuring the effects of energy prices on cross-border carbon flows and domestic emissions by developing "a simple accounting framework for emissions" that yields "an expression for carbon leakage that is akin to the theoretical modeling literature."
    - Enables retrieval of "precise estimates of country-level carbon leakage rates from our country-sector level regressions."

### Key findings and robustness
- Empirical results:
  - "We show that carbon leakage can be significant, but that there are differences across countries, depending on country size and openness to trade."
  - Results are "statistically robust and significant."
- Additional analyses:
  - Provide a plausibility test documenting "(although limited) evidence of the underlying loss in competitiveness and changes in energy usage patterns."
  - Examine heterogeneity in "energy price elasticities of emissions and carbon flows between different country and sector groupings."

### Paper organization (from source)
- Section 2 presents the data used in the empirical analysis.

*Source: wpiea2021207-print-pdf - References*

### Section 3 presents our regression estimates on the energy price elasticity of carbon trade

### Section 3 presents our regression estimates on the energy price elasticity of carbon trade flows and domestic carbon production

### Data
- Carbon embodied in goods and services trade and final demand measured using OECD’s Trade in Embodied CO2 Database (TECO2), compiled by Wiebe and Yamano (2016).
- Sectoral energy prices from Sato et al. (2019) covering 21 production sectors in 48 countries for 1995–2015; prices are weighted averages of tax-inclusive fuel-specific prices with weights derived from fuel input use by country and sector.
- Missing data in Sato et al. (2019) complemented with national sources for Russia, China and India; average user-price for electricity and natural gas used as an additional sector.
- Merged dataset: unbalanced panel covering 38 countries and 21 sectors over the 2005–15 period.
- Combined emissions from sectors included in estimation amount to 75 percent of all production-related domestic emissions on average across covered countries (this amounts to a 60 percent coverage of global emissions from production; note that around 15 percent of global carbon emissions are from households’ electricity and fuel consumption, which are not included).

### Empirical results — specification
- Estimated elasticity regression (all variables in logs) with country-sector, country-year and sector-year fixed effects:
  - Dependent variables: (i) carbon embodied in exports from sector s in country i to rest of world; (ii) carbon embodied in imports of country i originating from sector s in rest of world; (iii) carbon embodied in domestic final demand of country i originating from sector s; (iv) domestic carbon emissions of sector s and country i.
- Standard errors clustered at the country-sector level.

### Empirical results — main estimates (Table 1)
- Impact of sectoral energy price on carbon flows (coefficients; standard errors in parentheses):
  - Imports: 0.0158 (0.0491)
  - Exports: -0.321** (0.155)
  - Emissions: -0.523*** (0.151)
  - Consumption: -0.198* (0.103)
- Observations:
  - Imports: 8,247
  - Exports: 8,124
  - Emissions: 8,168
  - Consumption: 8,235
- R-squared:
  - Imports: 0.997
  - Exports: 0.983
  - Emissions: 0.986
  - Consumption: 0.993
- Interpretation highlights:
  - Higher energy prices significantly reduce carbon embodied in exports (elasticity estimate of -0.3) and domestic emissions (coefficient -0.523***).
  - Reduction in carbon consumption is significant but smaller in magnitude (-0.198*), plausibly because a portion of carbon embodied in domestic demand comes from imports.
  - No significant effect on carbon embodied in imports (point estimate 0.0158, not statistically significant).

- Illustrative comparison (as discussed):
  - Sweden average energy price level in 2015: 677 USD per ton of oil equivalent (toe) (in real 2010 USD).
  - United States average energy price in 2015: 275 USD per toe (in real 2010 USD).
  - Using the exports elasticity (-0.321), if the US implemented Sweden’s energy pricing, exports of carbon would decline by more than 30 percent.

### Heterogeneity across countries (Table 2)
- Baseline sectoral energy price coefficients and interaction with EU14+UK dummy:
  - Sectoral energy price (baseline):
    - Imports: -0.0394 (0.0598)
    - Exports: -0.260 (0.183)
    - Emissions: -0.451** (0.182)
    - Consumption: -0.250** (0.126)
  - Sectoral energy price × EU14+UK:
    - Imports: 0.168* (0.0954)
    - Exports: -0.187 (0.311)
    - Emissions: -0.222 (0.297)
    - Consumption: 0.157 (0.181)
- Observations and fit:
  - Observations: same as Table 1 (8247, 8124, 8168, 8235)
  - R-squared: 0.997, 0.983, 0.986, 0.993
- Interpretation:
  - Interaction mostly insignificant, suggesting no statistically significant differences between energy price elasticities in EU14+UK (EU15) and non-EU15 countries, except that imports increase in EU15 countries following energy price increases (interaction on imports 0.168*).

### Heterogeneity across industries (EITE) (Table 3)
- EITE definition: Mining energy, Mining non-energy, Paper products, Refined oil products, Chemicals, Basic metals, Electricity and gas.
- Baseline sectoral energy price and interaction with EITE:
  - Sectoral energy price:
    - Imports: 0.001 -0.054 (standard error placement in source is ambiguous for imports row but reported as 0.001 with trailing -0.054 in text)
    - Exports: -0.356** (0.168)
    - Emissions: -0.611*** (0.167)
    - Consumption: -0.203* (0.104)
  - Sectoral energy price × EITE:
    - Imports: 0.0432 -0.043 (similarly reported formatting)
    - Exports: 0.099 (0.141)
    - Emissions: 0.247* (0.141)
    - Consumption: 0.013 (0.131)
- Observations and fit:
  - Observations: 8,247; 8,124; 8,168; 8,235
  - R-squared: 0.997, 0.983, 0.986, 0.993
- Interpretation:
  - Interaction terms largely insignificant except for domestic emissions (interaction 0.247*), indicating domestic emissions in EITE sectors are more inelastic to energy price changes.

### Other effects of changes in energy prices
- Energy usage, CO2 intensity, and energy mix (Table 4):
  - Sectoral energy price effects:
    - Energy use (log KTOE): -0.347*** (0.0600)
    - CO2 intensity (ratio of CO2 to value added): -2.246* (1.266)
    - Share biofuel: 0.0261*** (0.00655)
  - Observations:
    - Energy use: 8,024
    - CO2 intensity: 8,246
    - Share biofuel: 7,848
  - R-squared:
    - Energy use: 0.993
    - CO2 intensity: 0.676
    - Share biofuel: 0.974
  - Interpretation:
    - Increases in energy prices lower energy use and CO2 intensity and raise biofuel share, implying firms adjust energy usage and mix which would mitigate leakage.

- Competitiveness indicators (Table 5):
  - Sectoral energy price effects:
    - Value added: -0.219 (0.176)
    - Wages: -0.198* (0.113)
    - Employment: -0.154 (0.140)
  - Observations: 8,247 for all three
  - R-squared: 0.975, 0.988, 0.990
  - Interpretation:
    - Signs negative as expected but value added and employment coefficients lack statistical significance in this sample; when panel extended to 1995, coefficients become significant (note from source).

### Carbon leakage rates — conceptual framework and accounting
- Identity linking consumption, exports, production, and imports of carbon for country i:
  - D_i + X_i,RW = Y_i + M_i,RW
    - D_i: carbon embodied in final domestic demand of country i
    - X_i,RW: carbon embodied in exports from i to rest of world
    - M_i,RW: carbon embodied in imports to i from rest of world
    - Y_i: carbon emissions of country i
- Small unilateral domestic carbon price change p̂_i induces changes satisfying:
  - ∂D_i/∂p_i p̂_i + ∂X_i,RW/∂p_i p̂_i = ∂Y_i/∂p_i p̂_i + ∂M_i,RW/∂p_i p̂_i
  - ∂D_RW/∂p_i p̂_i + ∂X_RW,i/∂p_i p̂_i = ∂Y_RW/∂p_i p̂_i + ∂M_RW,i/∂p_i p̂_i
- Definition of carbon leakage L(p̂_i):
  - L(p̂_i) ≡ 1 − (∂Y_RW/∂p_i) / (∂Y_i/∂p_i) = − (∂Y_RW/∂p_i) / (∂Y_i/∂p_i)
  - For non-infinitesimal changes: L(p̂_i) ≡ − ΔY_RW / ΔY_i
  - Leakage equals one when domestic reductions are fully offset by foreign increases (global emissions unchanged); leakage can be negative if foreign emissions fall too (e.g., technology adoption abroad).
- Reduced-form accounting expression using estimated elasticities (assuming ∂D_RW/∂p_i ≈ 0 so foreign consumption responses to domestic price ignored):
  - L(p̂_i) = (β̂_X X_X_i,RW − β̂_M M_M_i,RW) / (β̂_Y Y_Y_i)
    - where β̂_X, β̂_M, β̂_Y are the carbon exports, imports and production elasticities estimated in Table 1 (exports, imports, and emissions elasticities, respectively).

*Source: Section 3 (regression estimates) and associated sections from the provided IMF working paper content.*

### 1. The values 푋푋

### 1. The values 푋푋

### Conceptual framework and methodological notes
- 푋푋푖,푅푅푅푅, 푀푀푖,푅푅푅푅 and 푌푌푖 denote aggregate quantities of carbon exports, imports and emissions in country 푖푖.
- Leakage increases with (a) sensitivity of trade in carbon to unilateral price and policy changes and (b) openness to trading in (embedded) carbon.
- Trade effects from domestic carbon policies are necessary but not sufficient to measure carbon leakage; production responses must also be accounted for.
- If domestic emissions responses are zero, the ratio in Eq. (5) can have a confidence interval between −∞ and ∞ because the denominator could be arbitrarily close to zero.
- The study jointly estimates effects on domestic emissions, carbon imports, and exports; authors state this is the first empirical study to do so.
- The approach is reduced-form and focuses on aggregate net effects; it does not model complex cross-sectoral linkages or allow for detailed counterfactuals such as sectoral carbon prices or border carbon adjustment mechanism simulations.
- Eq. (5) ignores foreign carbon consumption responses to domestic carbon price changes (푝푝̂푖). The authors argue that for sufficiently small countries, the elasticity of carbon consumption in the rest of the world is likely small relative to elasticities of exports and imports of the focal country.

### Country-specific carbon leakage rates (estimation summary)
- The (unweighted) average leakage rate across all countries in the sample is 0.25.
  - Interpretation: A reduction of 100 tons of carbon emissions domestically would be accompanied by an increase of 25 tons abroad.
- EU14+UK aggregate leakage rate (using elasticities from Table 1 and consolidated flows) is reported; results are presented in Figure 1.
- Using alternative estimates results in an average leakage rate of 0.15.
- When excluding Switzerland, the correlation between the two sets of estimates is 0.83.
- All countries have statistically significant leakage rates at the 90 percent confidence level, except for Switzerland.

### Selected country-level statistics (Table 6: CO2 imports, CO2 exports, CO2 product leakage est.)
- AUS: CO2 imports 100.985, CO2 exports 74.432, CO2 product 275.888, leakage est. 0.177
- AUT: CO2 imports 33.051, CO2 exports 18.735, CO2 product 32.600, leakage est. 0.383
- BEL: CO2 imports 39.255, CO2 exports 23.823, CO2 product 45.688, leakage est. 0.346
- CHN: CO2 imports 488.635, CO2 exports 1775.187, CO2 product 7949.845, leakage est. 0.139
- DEU: CO2 imports 216.854, CO2 exports 153.780, CO2 product 455.922, leakage est. 0.221
- EU15: CO2 imports 789.657, CO2 exports 298.318, CO2 product 1384.193, leakage est. 0.149
- JPN: CO2 imports 287.074, CO2 exports 157.272, CO2 product 839.268, leakage est. 0.125
- USA: CO2 imports 998.644, CO2 exports 258.673, CO2 product 2766.607, leakage est. 0.068
- ZAF: CO2 imports 34.028, CO2 exports 132.687, CO2 product 336.002, leakage est. 0.245
- (Full table contains additional country entries and corresponding numeric values.)

### Findings, patterns and interpretation
- Leakage rates vary widely across countries and are generally larger for small open economies compared to larger economies.
- EU countries tend to have higher leakage rates because they are smaller and more open on average and tend to produce less carbon while relying on larger imports.
- The EU14+UK aggregate has a relatively low leakage rate owing to its size; the whole EU (larger than EU14+UK) could have an even lower leakage rate.
- Leakage estimates reflect constant marginal effects; in practice leakage may be non-linear (large price increases may trigger different responses than small changes).
- No carbon spillovers can arise in sectors with zero emissions; intersectoral substitution effects and endogenous technological change can alter leakage magnitudes.

### Caveats and limitations
- The accounting framework is agnostic on exact channels through which price changes affect domestic emissions, imports, exports, and consumption.
- The reduced-form approach is not suited for detailed policy counterfactuals (e.g., sectoral carbon prices, border carbon adjustments).
- Foreign carbon consumption responses to domestic price changes are ignored due to empirical estimation challenges without a structural trade model.
- The framework does not adequately capture that emission constraints in larger open economies may depress global fossil fuel demand and reduce world energy prices; this channel could bias estimates downward.
- Endogenous technological change and energy-saving innovation could reduce carbon leakage over longer periods, potentially biasing estimates upward if not accounted for.

### Policy implications and recommendations
- Robust estimates of carbon leakage are important to inform international climate policy debates, including discussions on carbon border adjustment mechanisms and unilateral climate policies.
- Carbon leakage is necessary but not sufficient justification for border carbon adjustment schemes; design complexity and legal, administrative, and other constraints remain important.
- Given relatively high leakage rates estimated for many European countries, common European climate policies can be advantageous for reducing cross-border leakage.
- The evidence on leakage suggests that arguments against carbon border adjustment schemes based on limited empirical evidence could be reconsidered.

### Conclusions and directions for future research
- Carbon leakage differs across countries and can be sizeable, particularly in small open economies.
- The paper exploits policy-induced changes of energy prices (rather than focusing narrowly on carbon prices) to avoid downward bias from low/limited carbon price coverage.
- Future research could:
  - Explore sectoral differences in leakage rates with richer models able to compute sectoral leakage and intersectoral leakage.
  - Use structural trade models to estimate foreign consumption responses to domestic carbon price changes.
  - Investigate the role of endogenous technological change and international spillovers of energy-saving innovations.

*Source: wpiea2021207-print-pdf - 1. The values 푋푋*

### Appendix I.  Summary of the Literature

### Appendix I. Summary of the Literature

### A. Theoretical Literature — Cross-border leakage
- Earlier theoretical literature quantifies cross-border leakage rates mostly using computable general equilibrium (CGE) frameworks and generally finds positive carbon leakage rates of widely differing magnitudes.
- Examples and ranges reported:
  - Babiker (2005): leakage rates can range from 25 percent to 130 percent where a leakage rate of above 100 percent would imply higher global emissions as a result of domestic reductions.
  - Branger and Quirion (2014b): leakage rate estimates range from 2 percent to 41 percent.
- Determinants and drivers of heterogeneity (Branger and Quirion (2014a)):
  - Scenario hypotheses: "the bigger the abating coalition, the smaller the leakage rate while the more ambitious the target, the higher the leakage rate."
  - Elasticities: fossil fuel supply and Armington elasticities drive results (fossil fuel supply elasticity reflects the extent to which a decrease in fossil fuel demand drives the reduction in the fuel price; Armington elasticity determines the substitutability between domestic and foreign products).
- Channels and findings from more recent theoretical work:
  - Multi-stage production and trade in intermediate goods complicate unilateral abatement effects; leakage rates are always positive in some models, yet a channel of negative leakage exists where less emission-intensive industries relocate to the more stringently regulated region (Schenker et al. (2018)).
  - Bogmans (2015): stricter unilateral environmental policy can reduce the net supply of intermediate goods to world markets, producing negative global supply effects and reducing emissions abroad.
  - Perino et al. (2019): within a group of countries with a carbon-pricing system, the magnitude and sign of internal carbon leakage depend on the design of the unilateral policy.
  - Ferguson and Sanctuary (2019): carbon leakage could be negative if difficulties to substitute between domestic- and foreign-sourced inputs lead domestic firms to reduce output, causing a fall in foreign sourced inputs.
  - Karp (2013): a two-sector model with three factors of production shows unilateral regulation lowers national income, reduces demand for both clean and dirty goods and shifts domestic production factors into home's dirty goods sector, undermining the need for dirty goods supply abroad and promoting negative leakage.
  - Baccianti and Schenker (2021): in a two-country model, firms in the non-regulating country may increase markups rather than output under some conditions, resulting in a fall of emissions.

### A. Theoretical Literature — Inter-sectoral leakage
- This strand analyzes leakage from one sector to another within countries as a result of partial carbon price increases, often in closed-economy settings.
- Findings and mechanisms:
  - Theoretical evidence is inconclusive.
  - Baylis et al. (2014) (two-sector closed-economy model with factor mobility): the effect of an increase in the price of carbon in one sector on economy-wide emissions is ambiguous due to two opposing effects:
    - Consumer substitution toward the untaxed sector (positive leakage).
    - Firms in the taxed sector substitute away from energy and bid up the price of the mobile factor, resulting in negative leakage (lower production and lower emissions in the untaxed sector).
  - King et al. (2019): effects on aggregate emissions of partial carbon taxation depend on:
    - the sector’s level of emissions relative to aggregate emissions,
    - the sector’s intersectoral influence on emissions via upstream and downstream linkages,
    - the aggregate demand effects of rebating the tax revenue.
    - Prediction: taxation in sectors with sufficiently high emissions will always reduce aggregate emissions; if sector emissions are low, tax rebate effects can exceed other effects and potentially increase aggregate emissions.

### B. Empirical Literature — Overview
- Empirical literature on carbon leakage is relatively small but growing (Dechezleprêtre and Sato, 2017).
- Ellis et al. (2019) review: little evidence in support of carbon leakage, echoing Branger and Quirion (2014).
- Most empirical papers do not quantify carbon leakage rates and provide indirect evidence; they differ by policy variable and by whether they examine effects on trade flows (goods, services, embodied carbon) or firm location and investment decisions.

### B. Empirical Literature — Effects of changes in sector-level prices
- Sato and Dechezleprêtre (2015): use variation in industry-level energy prices; find relatively small effects of changes in energy price differentials on bilateral goods and services imports. They do not examine trade flows of embodied carbon exports or domestic emissions.
- Tian and Yang (2020): increases in industry-level energy prices have dampened domestic emissions in China.

### B. Empirical Literature — Effects of ratifying the Kyoto Protocol
- Several papers examine ratification effects on carbon embodied in trade flows; these are among the few that find evidence supporting carbon leakage.
- Key findings:
  - Aichele and Felbermayr (2012): ratification reduced domestic emissions but not the overall carbon footprint including carbon embodied in imports.
  - Aichele and Felbermayr (2015): using bilateral sector-level flows of embodied carbon and the differential Kyoto commitment between importing and exporting countries, they show embodied carbon imports in committed countries from noncommitted ones increased significantly, suggesting leakage.
    - Combining their results with Aichele and Felbermayr (2012) domestic emissions effects, they argue their coefficient estimates would amount to a leakage rate of 40 percent.
  - Hartl (2019): expands methodologically on Aichele and Felbermayr (2015) and also finds evidence of carbon leakage via deterioration of the carbon trade balance of Kyoto ratifiers vis-à-vis non-ratifiers.
- Critiques and caveats:
  - Naegele and Zaklan (2019): suggest the channel through which Kyoto induced leakage is unclear.
  - Branger and Quirion (2014) and Sato and Dechezleprêtre (2015): absence of sectoral variation in the policy variable makes controlling for other confounding macroeconomic shocks difficult.
  - Kumar and Prabhakar (2016): similar approach using export data from a few Asian countries; do not find robust evidence of leakage from ratifying Kyoto.

### B. Empirical Literature — Effects of the EU ETS and other country-specific policies
- Surveys and reviews:
  - Verde (2020): comprehensive survey concluding no evidence so far that the EU ETS resulted in a loss of competitiveness or in carbon leakage; attributes conclusion to low carbon prices under the EU ETS during studied periods and omission of longer-term impacts in most studies.
  - Joltreau and Sommerfeld (2019): examine reasons empirical literature finds no effects of EU ETS on competitiveness.
  - Ellis et al. (2019): attribute null findings to low carbon price levels, exemptions to carbon taxes for industry, generous free allowances under ETS, or other compensation mechanisms.
- Empirical studies:
  - Naegele and Zaklan (2019): use trade and embodied carbon data to and from the EU by source country and industry; using several EU-ETS related policy variables and controlling for unobserved industry-country effects, they do not find significant effects on net imports of goods and services and embodied carbon; attribute results to barriers to leakage being greater than ETS-imposed costs during the study period.
  - Garnadt et al. (2020): gravity-type setting with a dummy for differences in adherence to EU ETS between importer and exporter; find that the CO2 footprint of final demand in a country with ETS originating from production of a country without ETS increases by around 3 percent, but do not find clear aggregate effects when examining import-related indicators.
- Additional notes:
  - Some time-series studies and simpler methods exist that find no evidence of leakage but often lack controls for unobserved effects (examples: Sartor (2013), Branger et al. (2016)).
  - Bolscher et al. (2013): argue ETS-related costs constitute a small share of overall input costs in various industries, making leakage implausible.
  - Cludius et al. (2020): find significant pass-through of ETS-related costs to product prices, which could be interpreted as evidence that carbon leakage was limited subject to caveats.
- Aggregate assessment:
  - Zachmann and McWilliams (2020) and Felbermayr and Peterson (2020): review ex-ante simulation studies and econometric ex-post studies; document evidence in support of carbon leakage in some industries but overall mixed evidence at the aggregate level.
  - Ferguson and Sanctuary (2019): empirically show imports of intermediate inputs by Swedish manufacturers rise in response to a sudden and unexpected increase in electricity prices, suggesting negative carbon leakage attributed to reduced firm output and demand for inputs.
  - Levinson (2009): decomposition analysis finds U.S. manufacturing pollution reduction largely attributable to improvements in production technology rather than relocation abroad, suggesting small carbon leakage.

### B. Empirical Literature — Effects of carbon prices on firm-level investment and location decisions
- Evidence on relocation and investment responses is mixed and often heterogeneous across sectors and firms:
  - Dechezleprêtre et al. (2019): survey data show no evidence of relocation within multinational firms in response to the EU ETS.
  - Koch and Basse Mama (2019): administrative data find evidence supporting carbon leakage via increased outward foreign direct investment (FDI) of German multinational firms due to the EU ETS.
  - Martin et al. (2014): firm-level survey data in manufacturing find propensity to downsize or relocate in response to higher carbon prices is relatively small but heterogeneous across sectors and firms.
  - Calel and Dechezleprêtre (2016): EU ETS has significantly increased low-carbon innovation among regulated firms.

### Stylized Facts at the Sector Level — Carbon Flows and Emissions by Sector (average)
- Table entries (preserve values exactly as in source):
  - Basic metals: Exported emissions (percent total emissions) 0.7; Imported emissions (percent sector emissions) 15.7; Exported emissions (percent sector emissions) 14.7; Emissions (percent total emissions) 6.5
  - Chemicals: Exported emissions (percent total emissions) 0.6; Imported emissions (percent sector emissions) 5.5; Exported emissions (percent sector emissions) 5; Emissions (percent total emissions) 2.5
  - Construction: Exported emissions (percent total emissions) 0.0; Imported emissions (percent sector emissions) 0.1; Exported emissions (percent sector emissions) 0.2; Emissions (percent total emissions) 1.6
  - Electrical equipment: Exported emissions (percent total emissions) 0.6; Imported emissions (percent sector emissions) 0.2; Exported emissions (percent sector emissions) 0.2; Emissions (percent total emissions) 0.1
  - Electricity and gas: Exported emissions (percent total emissions) 0.2; Imported emissions (percent sector emissions) 31.7; Exported emissions (percent sector emissions) 24.2; Emissions (percent total emissions) 29.9
  - Electronics: Exported emissions (percent total emissions) 0.6; Imported emissions (percent sector emissions) 0.4; Exported emissions (percent sector emissions) 0.3; Emissions (percent total emissions) 0.1
  - Food: Exported emissions (percent total emissions) 0.3; Imported emissions (percent sector emissions) 0.9; Exported emissions (percent sector emissions) 1.7; Emissions (percent total emissions) 1.3
  - Machinery: Exported emissions (percent total emissions) 0.6; Imported emissions (percent sector emissions) 0.4; Exported emissions (percent sector emissions) 0.5; Emissions (percent total emissions) 0.2
  - Metal products: Exported emissions (percent total emissions) 0.5; Imported emissions (percent sector emissions) 0.3; Exported emissions (percent sector emissions) 0.4; Emissions (percent total emissions) 0.2
  - Mining energy: Exported emissions (percent total emissions) 0.5; Imported emissions (percent sector emissions) 6.3; Exported emissions (percent sector emissions) 4.7; Emissions (percent total emissions) 2.2
  - Mining non-energy: Exported emissions (percent total emissions) 0.6; Imported emissions (percent sector emissions) 1; Exported emissions (percent sector emissions) 1.2; Emissions (percent total emissions) 0.5
  - Mining non-metals: Exported emissions (percent total emissions) 0.3; Imported emissions (percent sector emissions) 3.6; Exported emissions (percent sector emissions) 3.7; Emissions (percent total emissions) 3
  - Mining support activities: Exported emissions (percent total emissions) 0.5; Imported emissions (percent sector emissions) 0.2; Exported emissions (percent sector emissions) 0.2; Emissions (percent total emissions) 0.1
  - Motor vehicles: Exported emissions (percent total emissions) 0.6; Imported emissions (percent sector emissions) 0.2; Exported emissions (percent sector emissions) 0.4; Emissions (percent total emissions) 0.2
  - Other manufacturing: Exported emissions (percent total emissions) 0.4; Imported emissions (percent sector emissions) 2.4; Exported emissions (percent sector emissions) 1.3; Emissions (percent total emissions) 0.7
  - Other transport equipment: Exported emissions (percent total emissions) 0.5; Imported emissions (percent sector emissions) 0.2; Exported emissions (percent sector emissions) 0.1; Emissions (percent total emissions) 0.1
  - Paper products: Exported emissions (percent total emissions) 0.4; Imported emissions (percent sector emissions) 0.7; Exported emissions (percent sector emissions) 1.4; Emissions (percent total emissions) 0.8
  - Plastics: Exported emissions (percent total emissions) 0.6; Imported emissions (percent sector emissions) 2.8; Exported emissions (percent sector emissions) 1.4; Emissions (percent total emissions) 0.8
  - Refined oil products: Exported emissions (percent total emissions) 0.4; Imported emissions (percent sector emissions) 4.8; Exported emissions (percent sector emissions) 5.3; Emissions (percent total emissions) 3.7
  - Textiles and clothing: Exported emissions (percent total emissions) 0.5; Imported emissions (percent sector emissions) 0.7; Exported emissions (percent sector emissions) 0.5; Emissions (percent total emissions) 0.3
  - Wood products: Exported emissions (percent total emissions) 0.4; Imported emissions (percent sector emissions) 0.2; Exported emissions (percent sector emissions) 0.2; Emissions (percent total emissions) 0.1
  - Total: Exported emissions (percent total emissions) 9.6; Emissions (percent total emissions) 54.8
  - Average: Exported emissions (percent total emissions) 0.5; Imported emissions (percent sector emissions) 3.7; Exported emissions (percent sector emissions) 3.2; Emissions (percent total emissions) 2.7

*Source: Appendix I. Summary of the Literature — wpiea2021207-print-pdf*

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*wpiea2021207-print-pdf - References*

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