Convergence of Carbon Dioxide Emissions in China Juan Wang School - - PowerPoint PPT Presentation

Convergence of Carbon Dioxide Emissions in China

Juan Wang School of Management, Huazhong University of Science & Technology, Wuhan, China

Organization

Introduction Related Literature Data and empirical methodology Empirical results Conclusions

Introduction

Chinese government attach great attention on CO2 emissions The distribution of CO2 emissions varying widely across provinces in China CO2 emissions should converge at a specified target It is absolutely necessary to understand the CO2 emissions of each sector trends across the Chinese

Related Literature Ⅰ

Inverted-U relationship between CO2 emissions and income

• Dijkgraaf & Vollebergh, 2005; Jalil & Mahmud, 2009
• Cannot be explained whether CO2 emissions cross-

county converge to steady state

Studies on the convergence of CO2 emissions across countries/regions

• Strazicich & List, 2003; Romero-Avila, 2008; Westerlund

& Basher, 2008; Lee & Chang, 2008

• Nguyen-Van, 2005; Ezcurra, 2007; Jobert et al., 2010

Related Literature Ⅱ

Studies on the divergence of CO2 emissions across countries/regions

• Aldy, 2006; Bulte et al., 2007; Barassi et al., 2008; Nourry,

2009; Criado & Greth2011

It is very important in the CO2 emissions convergence issue to choose suitable estimation methods, building on considering character of sample fully, and re-examine the robust of tests

Data

Panel data of 28 provinces during 1996-2009 Total population at the end of year in 28 provinces during 1996-2009 is taken from China Statistical Yearbook Energy consumption of every sector is taken from China Energy Statistical Yearbook

CO2 Emissions Data

Calculated from energy consumption, according to IPCC guidelines for national greenhouse gas inventories, combining with the statistical characteristics of energy balance sheet of annual China Energy Statistical Yearbook

• is the energy consumption
• is the coefficient of energy type being converted into

standard coal

• is the carbon emissions factor of energy type

15 , , , , 1

( ) /

i t i t j j j i t j

C E B F peo

=

= × ×

∑

, , i t j

E

j

B

j

F

Sector Classification

Sector Abbr.

1.Farming, Forestry, Animal Husbandry, Fishery & Water Conservancy FAM 2.Industry IND

• 3. Construction

CON

• 4. Transportation, Storage, Postal & Telecommunications Services

TRA

• 5. Wholesale, Retail Trade and Catering Service

WSA

• 6. Residential Consumption

RES

• 2
• 1

1 2 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Fig.2 Cross-province carbon emissions in IND sector 1996-2009 Beijin Tianjin Hebei Shanxi Neimenggu Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Sicuang Guizhou Yunnan Shanxi Gansu Qinghai Xinjiang

Empirical Methodology

Cross-province difference (σ-convergence) Testing for β-convergence

( )

2 1 1

1 1 ln log ,ln ln

n n i i i i

c c c c n n

= =

− =

∑ ∑

2 1 1

1 1 1 ,

n n i i i i

c c c n n c

= =

  − =    

∑ ∑

, , 1 , i t i t i t

lngc lnc α β ε

−

= + +

Empirical results: σ-convergence

FAM IND CON TRA WSA RES Part A: logc Standard deviation in 1996 0.82 0.61 1.04 0.68 1.01 0.84 Standard deviation in 2009 0.63 0.44 0.85 0.59 0.98 0.55 Percentage change between 1996 and 2009

• 0.24
• 0.28
• 0.19
• 0.14
• 0.03
• 0.34

Table 3 Standard deviation of CO2 emissions per sector in 28 provinces during 1996-2009 Part B: c Percentage change between 1996 and 2009

• 0.14
• 0.30
• 0.02
• 0.13
• 0.40
• 0.18

Empirical results: β-convergence

Table 4 Unconditional β-convergence for CO2 emissions per sector in 28 provinces 1996-2009

FAM IND CON TRA WSA RES Part A: OLS regression β

• 0.0866***a -0.0373** -0.0738*** -0.0702*** -0.0431** -0.0959***

(0.000)b (0.0148) (0.000) (0.000) (0.0111) (0.000) Part B: FGLS regression β

• 0.0904*** -0.0591*** -0.0430*** -0.0558*** -0.0473*** -0.0972***

(0.000) (0.000) (0.000) (0.000) (0.006) (0.000)

Conclusion

Per capita CO2 emissions in all sectors do have σ- convergence in 28 provinces during 1996-2009 Per capita CO2 emissions in all the sectors have an absolute β-convergence across provinces in China from 1996 to 2009

• Narrow the gap of per capita CO2 emissions among

provinces though differentiated environmental protection