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 CO 2 emissions  The distribution of CO 2 emissions varying widely across provinces in China  CO 2 emissions should converge at a specified target  It is absolutely necessary to understand the CO 2 emissions of each sector trends across the Chinese

Related Literature Ⅰ  Inverted-U relationship between CO 2 emissions and income  Dijkgraaf & Vollebergh, 2005; Jalil & Mahmud, 2009  Cannot be explained whether CO 2 emissions cross- county converge to steady state  Studies on the convergence of CO 2 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 CO 2 emissions across countries/regions  Aldy, 2006; Bulte et al., 2007; Barassi et al., 2008; Nourry, 2009; Criado & Greth2011 It is very important in the CO 2 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

CO 2 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 15 ∑ = × × C ( E B F ) / peo i t , i t j , , j j i t , = j 1  is the energy consumption E i t j , , B  is the coefficient of energy type being converted into j standard coal  is the carbon emissions factor of energy type F j

Sector Classification Abbr. Sector 1.Farming, Forestry, Animal Husbandry, Fishery & Water FAM Conservancy 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 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 -1 -2 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 Fig.2 Cross-province carbon emissions in IND sector 1996-2009

Empirical Methodology  Cross-province difference ( σ -convergence) ( ) 1 1 ∑ ∑ 2 n n − = ln c log c ,ln c ln c = = i i i 1 i 1 n n 2   c 1 1 ∑ ∑ n − = n i  1  , c c = = i   i 1 i 1 n n c  Testing for β -convergence = α + β + ε lngc lnc − i t , i t , 1 i t ,

Empirical results: σ -convergence Table 3 Standard deviation of CO 2 emissions per sector in 28 provinces during 1996-2009 FAM IND CON TRA WSA RES Standard deviation in 1996 0.82 0.61 1.04 0.68 1.01 0.84 Part A: Standard deviation in 2009 logc 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 Part B: Percentage change between 1996 and 2009 c -0.14 -0.30 -0.02 -0.13 -0.40 -0.18

Empirical results: β -convergence Table 4 Unconditional β -convergence for CO 2 emissions per sector in 28 provinces 1996-2009 FAM IND CON TRA WSA RES Part A: OLS regression -0.0866 *** a -0.0373 ** -0.0738 *** -0.0702 *** -0.0431 ** -0.0959 *** β (0.000) b (0.0148) (0.000) (0.000) (0.0111) (0.000) Part B: FGLS regression -0.0904 *** -0.0591 *** -0.0430 *** -0.0558 *** -0.0473 *** -0.0972 *** β (0.000) (0.000) (0.000) (0.000) (0.006) (0.000)

Conclusion  Per capita CO 2 emissions in all sectors do have σ - convergence in 28 provinces during 1996-2009  Per capita CO 2 emissions in all the sectors have an absolute β -convergence across provinces in China from 1996 to 2009  Narrow the gap of per capita CO 2 emissions among provinces though differentiated environmental protection