## 1. Consumption- and Production-Based GHG Emissions

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---

### Key facts and context
- China contributes 23 percent of world emissions, which is larger than its 19 percent share of the world's population and 15 percent share of the world's GDP.
- The “pollution haven” hypothesis is referenced as a possible explanation for part of China's high emissions: emissions reductions in developed nations may partly reflect shifting dirty production to developing nations such as China.
- The paper distinguishes trend relationships from cyclical relationships between emissions and GDP.

### Trend relationship: Kuznets elasticities (trend emissions → trend GDP)
- The Kuznets elasticity (response of trend emissions to trend GDP) is about 0.6.
- The Kuznets elasticity is:
  - Higher than that in major advanced economies.
  - Lower than in many emerging markets.
- The Kuznets elasticity is somewhat higher with production-based emissions than with consumption-based emissions.
- Aggregate evidence over time:
  - The Kuznets elasticity was almost three times as large over the 1950 to 1982 period than in the period since then.
  - This decline suggests the elasticity may be falling over time.
- Provincial evidence:
  - For 29 provinces, the Kuznets elasticity initially increases with provincial per capita real GDP and then declines.
  - The inverted U-shape relationship between the intensity of the emissions–GDP relationship and the level of per capita GDP is reminiscent of the Environmental Kuznets Curve.

### Cyclical relationship: Environmental Okun's Law (EOL) (cyclical emissions ↔ cyclical GDP)
- The Okun elasticity (response of the cyclical component of emissions to the cyclical component of GDP) ranges from 0.35 to 0.65, depending on:
  - The filtering method used.
  - Whether production-based or consumption-based emissions are used.
- Evidence of asymmetry in EOL:
  - The Okun elasticity is higher for booms than during busts.
  - China's emissions go up more when GDP is above trend than they decrease when GDP is below trend.

### Robustness and methods
- Trend–cycle distinctions and elasticities are robust to alternate detrending methods:
  - Hodrick-Prescott (HP) filter.
  - Hamilton (2017) filter.
- The comparison of production-based and consumption-based emissions aligns directionally with the pollution haven hypothesis, but:
  - The quantitative difference between the two elasticities is not large.
  - This suggests shifts in allocation of global production across countries are not a major driver of shifts in emissions growth patterns.

### Comparative and literature context
- Related findings in the literature noted in the paper:
  - Csereklyei and Stern (2015): long-run growth rates for 93 countries find weak decoupling.
  - Jakob et al. (2012): average developing economy experienced above-average growth of total CO2 emissions over 1971-2005.
  - Pao and Tsai (2010): CO2 long-run elasticity with respect to real GDP is positive and statistically significant for China.
  - Provincial-level studies: Auffhammer and Carson (2008); Du et al. (2012); Wang et al. (2014); Xu and Lin (2015); Zhang et al. (2017); Mi et al. (2016).
- The paper states it provides the first comprehensive look for China that:
  - Distinguishes trends and cycles.
  - Uses both production-based and consumption-based emissions.
  - Uses both national and sub-national (provincial) data.

### Implications and interpretation
- The declining Kuznets elasticity (aggregate and provincial evidence) provides some grounds for hope that the emissions–GDP relationship will weaken as China gets richer.
- The modest difference between production- and consumption-based Kuznets elasticities implies that trade-related relocation of production is not the dominant factor driving emissions growth differences.

### Aggregate-level findings (Section IV)
- Focusing on the trend relationship, there is little evidence of a decoupling at the aggregate level for China.
- The Kuznets elasticity (trend emissions vs. trend GDP) was three times higher during the three decades of the 1950s to 1970s than in the three decades since China opened up to the world and enjoyed a sharp rise in per capita GDP.
- This historical decline in the Kuznets elasticity "holds out the hope" that further gains in per capita GDP will lead to even lower Kuznets elasticities (i.e., further progress toward decoupling).

### Production- vs. consumption-based emissions (Section IV)
- The Kuznets elasticities for production-based emissions are somewhat bigger than for consumption-based emissions.
- The quantitative difference between production- and consumption-based elasticities is not large, suggesting that China’s role in the world trading system need not be a big barrier to reducing emissions growth.

### Provincial heterogeneity and the value of disaggregation (Section IV)
- Province-level analysis provides important additional evidence on decoupling prospects.
- Most provinces have positive Kuznets elasticities, but richer provinces (measured in real income per capita) tend to have lower Kuznets elasticities.
- Signs of decoupling are likely to start emerging at the provincial level, supporting the need for a more disaggregated approach than country-level analysis alone.
- The comparison with U.S. states suggests a pattern worth exploring further in future research.

### Environmental Okun’s Law and business-cycle asymmetries (Section IV)
- The Environmental Okun's Law holds in China: emissions tend to be procyclical.
- The relationship is asymmetric: emissions increase more during booms than they decline during busts.
- Okun elasticities differ across provinces; understanding the drivers of these differences requires further research.
- Policies that tame emissions during business cycle upswings could contribute to achieving China's intended emissions target.

### Policy implications (Section IV)
- Because China’s economy is large, putting the country on a sustainable carbon trajectory requires much more disaggregated analysis and policy focus than has been typical in previous research.
- Subnational entities (provinces) could be effective loci for low-carbon policies; the results point to provinces where such policies could be more effective.
- Targeting emissions during cyclical upswings is a recommended policy lever to reduce aggregate emissions growth.

### Directions for future research (Section IV)
- Link changes in the Kuznets elasticity to the rebalancing of the Chinese economy (for example, quantifying the contribution of the transition from manufacturing to services to decoupling).
- Use the province-level framework developed here to explore the extent to which structural shifts across sectors explain cross-province differences in both Kuznets and Okun elasticities.

### Appendix Figures — Kuznets Residuals
- Figure A.1: Kuznets Residuals at the Aggregate Level (figure present; no numeric table values shown in text).
- Figure A.2: Kuznets Residuals at the Provincial Level
  - Vertical axis ticks shown: -.15, -.1, -.05, 0, .05, .1.
  - Year axis: 1990, 1995, 2000, 2005, 2010.
  - Filters indicated: HP, Hamilton, BK, CF.
  - Caption: "Kuznets residuals for all provinces" (visual series by filter; no additional numeric table provided in text).

### Appendix Figures — Okun and Kuznets Elasticities (Provincial)
- Figure A.3: Okun Elasticities across Chinese Provinces (map/chart displayed; individual province coefficients listed in Figure A.5 and A.4).
- Figure A.4: Kuznets Elasticities across Chinese Provinces
  - Listed provincial Kuznets coefficients (sequence as presented in figure):
    - 1.40**, 0.95**, 0.11, 1.55, 0.22, 0.22, 0.75*, 0.42, 0.56, 0.76, 1.04*, 2.08**, 0.29, 1.84***, 1.51***, 2.71***, 0.25, 1.35**, 1.64**, 1.00*, 2.07***, 1.55**, 1.38, 0.48, -0.52, -1.29, 1.48***, 1.40**, 0.21.
  - Legend bins shown: (2.5,3], (2,2.5], (1.5,2], (1,1.5], (.5,1], (0,.5], [-1.5,0], No data.
  - Additional provincial elasticity coefficients (Okun or related series) listed:
    - 0.47***, 0.91***, 0.71***, 0.53***, 0.56***, 0.58***, 0.93***, 0.39***, 0.61***, 0.58***, 0.92***, 0.60***, 1.07***, 0.98***, 0.87***, 0.87***, 0.63***, 0.69***, 0.63***, 0.65***, 0.96***, 0.75***, 0.76***, 1.12***, 0.64***, 1.10***, 0.88***, 0.78***, 1.32***.
  - Legend bins for this series: (.92,1.32], (.78,.92], (.75,.78], (.61,.75], [.39,.61], No data.

### Appendix Figures — Elasticities and Economic Structure (Figure A.5)
- Relationships plotted between provincial Okun and Kuznets coefficients and sectoral shares of GDP in 1995:
  - Agricultural GDP (%) (agrigdp_percent (1995)) vs Okun coefficients
  - Agricultural GDP (%) vs Kuznets coefficients
  - Industrial GDP (%) (indusgdp_percent (1995)) vs Okun coefficients
  - Industrial GDP (%) vs Kuznets coefficients
  - Services GDP (%) (sergdp_percent (1995)) vs Okun coefficients
  - Services GDP (%) vs Kuznets coefficients
- Regions indicated in figures: Eastern region, Central region, Western region.
- Method: Fractional-polynomial prediction overlays shown.
- Province abbreviations plotted: BJ, TJ, HB, LN, SH, JS, ZJ, FJ, SD, GD, HAIN, SANX, JL, HLJ, AH, JX, HN, HUB, HUN, IM, GX, SC, GZ, YN, SHX, GS, QH, NX, XJ.
- Axes and tick marks visible (examples):
  - Okun coefficient axis range displayed approximately from -1 to 3 in some panels.
  - Sector share axes examples: 0, .1, .2, .3, .4, .5, .6, .8, 1, 1.2, 1.4 in various panels (as shown on the figures).

### Appendix Tables
- Table B.1. Augmented Dickey-Fuller Test for Unit Root (HP filter, Production-based GHG, 1990-2012)
  - Reported values: -4.926***, -0.009***, 2.761***, -2.816***, 1.065***.
- Table B.1. (Hamilton filter, Production-based GHG, 1990-2012)
  - Reported values: -2.735**, -0.907**, 0.401, 0.281, 0.447.
- Table B.1. (BK filter, Production-based GHG, 1990-2012)
  - Reported values: -4.767***, -0.640***, 0.226, 0.623**, 0.697**.
- Table B.1. (CF filter, Production-based GHG, 1990-2012)
  - Reported values: -0.855, -0.182, -0.149, 0.149, 0.195.
- Note: *** p<0.01, ** p<0.05, * p<0.1.
- Table B.2. Okun and Kuznets Correlations at the Provincial Level (selected reported correlations)
  - Growth version: Okun 0.910; Kuznets 0.004.
  - Hamilton filtering: Okun 0.399; Kuznets 0.745.
  - BK filtering: Okun 0.610; Kuznets 0.967.
  - CF filtering: Okun 0.153; Kuznets 0.997.
  - Boom: Okun 0.919; Kuznets - .
  - Bust: Okun 0.950; Kuznets - .
  - Note: Columns (1) and (2) refer to the baseline calibration, with the HP filter.

*Source: wp1885 - 1. Consumption- and Production-Based GHG Emissions (excerpt) and Section IV; Appendix Figures and Tables as provided in the source PDF.*

### 1. Consumption- and Production-Based GHG Emissions ...................................................7

### 1. Consumption- and Production-Based GHG Emissions

### Key facts and context
- China contributes 23 percent of world emissions, which is larger than its 19 percent share of the world's population and 15 percent share of the world's GDP.
- The “pollution haven” hypothesis is referenced as a possible explanation for part of China's high emissions: emissions reductions in developed nations may partly reflect shifting dirty production to developing nations such as China.
- The paper distinguishes trend relationships from cyclical relationships between emissions and GDP.

### Trend relationship: Kuznets elasticities (trend emissions → trend GDP)
- The Kuznets elasticity (response of trend emissions to trend GDP) is about 0.6.
- The Kuznets elasticity is:
  - Higher than that in major advanced economies.
  - Lower than in many emerging markets.
- The Kuznets elasticity is somewhat higher with production-based emissions than with consumption-based emissions.
- Aggregate evidence over time:
  - The Kuznets elasticity was almost three times as large over the 1950 to 1982 period than in the period since then.
  - This decline suggests the elasticity may be falling over time.
- Provincial evidence:
  - For 29 provinces, the Kuznets elasticity initially increases with provincial per capita real GDP and then declines.
  - The inverted U-shape relationship between the intensity of the emissions–GDP relationship and the level of per capita GDP is reminiscent of the Environmental Kuznets Curve.

### Cyclical relationship: Environmental Okun's Law (EOL) (cyclical emissions ↔ cyclical GDP)
- The Okun elasticity (response of the cyclical component of emissions to the cyclical component of GDP) ranges from 0.35 to 0.65, depending on:
  - The filtering method used.
  - Whether production-based or consumption-based emissions are used.
- Evidence of asymmetry in EOL:
  - The Okun elasticity is higher for booms than during busts.
  - China's emissions go up more when GDP is above trend than they decrease when GDP is below trend.

### Robustness and methods
- Trend–cycle distinctions and elasticities are robust to alternate detrending methods:
  - Hodrick-Prescott (HP) filter.
  - Hamilton (2017) filter.
- The comparison of production-based and consumption-based emissions aligns directionally with the pollution haven hypothesis, but:
  - The quantitative difference between the two elasticities is not large.
  - This suggests shifts in allocation of global production across countries are not a major driver of shifts in emissions growth patterns.

### Comparative and literature context
- Related findings in the literature noted in the paper:
  - Csereklyei and Stern (2015): long-run growth rates for 93 countries find weak decoupling.
  - Jakob et al. (2012): average developing economy experienced above-average growth of total CO2 emissions over 1971-2005.
  - Pao and Tsai (2010): CO2 long-run elasticity with respect to real GDP is positive and statistically significant for China.
  - Provincial-level studies: Auffhammer and Carson (2008); Du et al. (2012); Wang et al. (2014); Xu and Lin (2015); Zhang et al. (2017); Mi et al. (2016).
- The paper states it provides the first comprehensive look for China that:
  - Distinguishes trends and cycles.
  - Uses both production-based and consumption-based emissions.
  - Uses both national and sub-national (provincial) data.

### Implications and interpretation
- The declining Kuznets elasticity (aggregate and provincial evidence) provides some grounds for hope that the emissions–GDP relationship will weaken as China gets richer.
- The modest difference between production- and consumption-based Kuznets elasticities implies that trade-related relocation of production is not the dominant factor driving emissions growth differences.

*Source: wp1885 - 1. Consumption- and Production-Based GHG Emissions (excerpt)*

### conclusion and policy implications of our findings are discussed in Section IV. Additional figures and

### IV.   CONCLUSION

### Aggregate-level findings
- Focusing on the trend relationship, there is little evidence of a decoupling at the aggregate level for China.
- The Kuznets elasticity (trend emissions vs. trend GDP) was three times higher during the three decades of the 1950s to 1970s than in the three decades since China opened up to the world and enjoyed a sharp rise in per capita GDP.
- This historical decline in the Kuznets elasticity "holds out the hope" that further gains in per capita GDP will lead to even lower Kuznets elasticities (i.e., further progress toward decoupling).

### Production- vs. consumption-based emissions
- The Kuznets elasticities for production-based emissions are somewhat bigger than for consumption-based emissions.
- The quantitative difference between production- and consumption-based elasticities is not large, suggesting that China’s role in the world trading system need not be a big barrier to reducing emissions growth.

### Provincial heterogeneity and the value of disaggregation
- Province-level analysis provides important additional evidence on decoupling prospects.
- Most provinces have positive Kuznets elasticities, but richer provinces (measured in real income per capita) tend to have lower Kuznets elasticities.
- Signs of decoupling are likely to start emerging at the provincial level, supporting the need for a more disaggregated approach than country-level analysis alone.
- The comparison with U.S. states suggests a pattern worth exploring further in future research.

### Environmental Okun’s Law and business-cycle asymmetries
- The Environmental Okun's Law holds in China: emissions tend to be procyclical.
- The relationship is asymmetric: emissions increase more during booms than they decline during busts.
- Okun elasticities differ across provinces; understanding the drivers of these differences requires further research.
- Policies that tame emissions during business cycle upswings could contribute to achieving China's intended emissions target.

### Policy implications
- Because China’s economy is large, putting the country on a sustainable carbon trajectory requires much more disaggregated analysis and policy focus than has been typical in previous research.
- Subnational entities (provinces) could be effective loci for low-carbon policies; the results point to provinces where such policies could be more effective.
- Targeting emissions during cyclical upswings is a recommended policy lever to reduce aggregate emissions growth.

### Directions for future research
- Link changes in the Kuznets elasticity to the rebalancing of the Chinese economy (for example, quantifying the contribution of the transition from manufacturing to services to decoupling).
- Use the province-level framework developed here to explore the extent to which structural shifts across sectors explain cross-province differences in both Kuznets and Okun elasticities.

*Source: https://www.imf.org/-/media/files/publications/wp/2018/wp1885.pdf (Section IV).*

### APPENDIX FIGURES

### APPENDIX FIGURES

### Kuznets Residuals
- Figure A.1: Kuznets Residuals at the Aggregate Level (figure present; no numeric table values shown in text).
- Figure A.2: Kuznets Residuals at the Provincial Level
  - Vertical axis ticks shown: -.15, -.1, -.05, 0, .05, .1.
  - Year axis: 1990, 1995, 2000, 2005, 2010.
  - Filters indicated: HP, Hamilton, BK, CF.
  - Caption: "Kuznets residuals for all provinces" (visual series by filter; no additional numeric table provided in text).

### Okun and Kuznets Elasticities (Provincial)
- Figure A.3: Okun Elasticities across Chinese Provinces (map/chart displayed; individual province coefficients listed in Figure A.5 and A.4).
- Figure A.4: Kuznets Elasticities across Chinese Provinces
  - Listed provincial coefficients (sequence as presented in figure):
    - 1.40**, 0.95**, 0.11, 1.55, 0.22, 0.22, 0.75*, 0.42, 0.56, 0.76, 1.04*, 2.08**, 0.29, 1.84***, 1.51***, 2.71***, 0.25, 1.35**, 1.64**, 1.00*, 2.07***, 1.55**, 1.38, 0.48, -0.52, -1.29, 1.48***, 1.40**, 0.21.
  - Legend bins shown: (2.5,3], (2,2.5], (1.5,2], (1,1.5], (.5,1], (0,.5], [-1.5,0], No data.
  - Additional provincial elasticity coefficients (Okun or related series) listed: 0.47***, 0.91***, 0.71***, 0.53***, 0.56***, 0.58***, 0.93***, 0.39***, 0.61***, 0.58***, 0.92***, 0.60***, 1.07***, 0.98***, 0.87***, 0.87***, 0.63***, 0.69***, 0.63***, 0.65***, 0.96***, 0.75***, 0.76***, 1.12***, 0.64***, 1.10***, 0.88***, 0.78***, 1.32***.
  - Legend bins for this series: (.92,1.32], (.78,.92], (.75,.78], (.61,.75], [.39,.61], No data.

### Elasticities and Economic Structure (Figure A.5)
- Relationships plotted between provincial Okun and Kuznets coefficients and sectoral shares of GDP in 1995:
  - Agricultural GDP (%) (agrigdp_percent (1995)) vs Okun coefficients
  - Agricultural GDP (%) vs Kuznets coefficients
  - Industrial GDP (%) (indusgdp_percent (1995)) vs Okun coefficients
  - Industrial GDP (%) vs Kuznets coefficients
  - Services GDP (%) (sergdp_percent (1995)) vs Okun coefficients
  - Services GDP (%) vs Kuznets coefficients
- Regions indicated in figures: Eastern region, Central region, Western region.
- Method: Fractional-polynomial prediction overlays shown.
- Province abbreviations plotted: BJ, TJ, HB, LN, SH, JS, ZJ, FJ, SD, GD, HAIN, SANX, JL, HLJ, AH, JX, HN, HUB, HUN, IM, GX, SC, GZ, YN, SHX, GS, QH, NX, XJ.
- Axes and tick marks visible (examples):
  - Okun coefficient axis range displayed approximately from -1 to 3 in some panels.
  - Sector share axes examples: 0, .1, .2, .3, .4, .5, .6, .8, 1, 1.2, 1.4 in various panels (as shown on the figures).

### Appendix Tables

- Table B.1. Augmented Dickey-Fuller Test for Unit Root
  - Column headings: (1) (2) (3) (4) (5) and labels COUNTRY, 푍(푡), 휀̂푡−1휏, Δ휀̂푡−1휏, Δ휀̂푡−2휏, Δ휀̂푡−3휏.
  - HP filter, Production-based GHG, 1990-2012: -4.926***, -0.009***, 2.761***, -2.816***, 1.065***.
  - Hamilton filter, Production-based GHG, 1990-2012: -2.735**, -0.907**, 0.401, 0.281, 0.447.
  - BK filter, Production-based GHG, 1990-2012: -4.767***, -0.640***, 0.226, 0.623**, 0.697**.
  - CF filter, Production-based GHG, 1990-2012: -0.855, -0.182, -0.149, 0.149, 0.195.
  - Note: *** p<0.01, ** p<0.05, * p<0.1.

- Table B.2. Okun and Kuznets Correlations at the Provincial Level
  - Variables and reported correlations:
    - Growth version: Okun 0.910; Kuznets 0.004.
    - Hamilton filtering: Okun 0.399; Kuznets 0.745.
    - BK filtering: Okun 0.610; Kuznets 0.967.
    - CF filtering: Okun 0.153; Kuznets 0.997.
    - Boom: Okun 0.919; Kuznets - .
    - Bust: Okun 0.950; Kuznets - .
  - Note: Columns (1) and (2) refer to the baseline calibration, with the HP filter.

*Source: wp1885 - APPENDIX FIGURES (appendix figures and tables as provided in the source PDF).*

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_Source: https://www.imf.org/-/media/files/publications/wp/2018/wp1885.pdf_