The Chinese Academy of Agricultural Sciences (CAAS) and the International Food Policy Research Institute (IFPRI) jointly hosted the International Conference on Climate Change and Food Security (ICCCFS) November 6-8, 2011 in Beijing, China. This conference provided a forum for leading international scientists and young researchers to present their latest research findings, exchange their research ideas, and share their experiences in the field of climate change and food security. The event included technical sessions, poster sessions, and social events. The conference results and recommendations were presented at the global climate talks in Durban, South Africa during an official side event on December 1.

1. 1
WHAT DOES CLIMATE CHANGE MEAN TO
FOOD CONSUMPTION OF LOW-INCOME
GROUP IN RURAL CHINA？
LI Yun，Institute of Agricultural Economics and
Development，CAAS;
YU Wen，Agricultural Information Centre, CAAS

2. 2
Outline
• Motive
• Data
• Model and estimation
• Conclusions and implication

3. 3
Motive
• Climate change: a global issue.
• climate warming: Many studies find evidence indicating that
climate changing in general will benefit crop yield increase
annually (Zhao et al., 2010；Li et al.，2010; Yang et al.,2010;
Wang et al., 2011).
• climate warming will make the north boundaries of food crops move
toward northwest and southeast direction; suitable acreage of some
crops expands;
• the yield of rain-fed wheat in most regions of China will increase, as
suggested by Sun et al. (2005).
• Climate change also means the increase of extreme climate
including rainstorm, hail, frost, and drought etc.
• Wu et al. (2008) finds that drought among various plagues was the
chief disaster that severely affected major grain production in
northwest China.
• Li et al. (2008) show that the decline of rice meteorological yield was
caused by the cold wet weather in spring and summer drought.

4. 4
Motive
• Climate change: Household income? Food consumption?
• Quite a few studies investigate the income effect on
household consumption.
• Almost all studies suggest that price and income elasticity for
individual food and food collection for China is in general relatively
lower（Li et al., 2010; Cheng et al., 2009；Liu et al, 2009; Li et al,
2005）.
• However, less research links food consumption at
household level with climate change.
• This paper aims to fill in gap in this field.

5. 5
Data
• 10 western provinces are studied. They are Inner Mongolia, Guangxi,
Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, and
Xinjiang.
1. Total sown area of farm crops:47.85 million hectares in 2009, 30% of the
national total.
2. 47.21 million hectares farm lands were hit by disasters in 2009 all over
China, of which 31% were in these 10 western provinces.
3. Rural population:206.44 million in 2009, 28.9% of China’s rural population.
4. Lower income: Per capita net income of rural households in each of the 10
provinces is far below nation average level in 2009. The average of per
capita net income of rural households of the ten provinces is around 70% of
national average.
• China Statistics Yearbook and Agriculture Statistics Yearbook;2000-
2009.
• Including farm household income, agricultural income, cultivated area,
disaster-covered area, disaster-afflicted area, price index of crop
products, and growth rate of rural population.

6. 6
Model and Estimation
Per capita Net Income Net Agricultural Income
Year
(a) (b) (b)/(a)
Mean Std.Dev.Coef. Mean Std.Dev.Coef.
2000 1701.34 0.14 872.80 0.45 51.3%
2001 1753.08 0.15 890.40 0.39 50.8%
2002 1861.07 0.17 901.29 0.44 48.4%
2003 1961.98 0.16 932.57 0.46 47.5%
2004 2107.04 0.17 996.28 0.43 47.3%
2005 2272.57 0.18 1084.59 0.44 47.7%
2006 2439.85 0.18 1101.55 0.46 45.1%
2007 2690.22 0.20 1189.80 0.48 44.2%
2008 2900.11 0.20 1214.42 0.50 41.9%
2009 3140.61 0.19 1284.76 0.49 40.9%

7. 7
Model and Estimation
•

8. 8
Climate change
• w1:About 34.5% of the cultivated farm land are actually
covered by different kinds of disasters annually in 2000s.
• w2: About 19.7% of the cultivated farm land are actually
afflicted by different kinds of disasters annually in 2000s.
45
40
35
30 w1, 31.2
(%)
25
20
15 w2, 14.2
10
5
0

9. 9
the impact of climate change on
agricultural income
•

10. 10
Climate change & Agri. income
Equation (2)-1 Equation (2)-2
w1 pindex rpop T w2 pindex rpop T
Inner
0.0347 -0.00137 7.416*** 0.247*** 0.0514 -0.00142 7.421*** 0.247***
Mogolia
(0.27) (-0.88) (39.91) (20.63) (0.39) (-0.88) (40.22) (23.53)
Guangxi -4.016*** -0.0151*** 9.431*** 0.254*** -7.102*** 0.0151*** 5.570*** 0.320***
(-7.24) (-5.21) (17.32) (11.99) (-5.52) (5.06) (24.45) (26.29)
Sichuan 1.019 * -0.00375 7.317*** 0.0132 1.353 * -0.00376 7.433*** -0.00404
(2.26) (-1.05) (11.69) (0.23) (2.05) (-0.81) (10.16) (-0.06)
Guizhou -0.663*** 0.0141*** 4.732*** 0.205*** -0.723*** 0.0135*** 4.749*** 0.200***
(-3.98) (20.23) (68.83) (29.56) (-3.46) (22.02) (66.20) (30.32)
Yunnan 0.175 * 0.00223 6.308*** 0.147*** 0.350 * 0.00144 6.423*** 0.138***
(2.02) (0.95) (19.92) (5.85) (2.17) (0.56) (18.20) (4.80)
0.00514** 0.00512**
Shaanxi -0.141 5.572*** 0.225*** -0.292*** 5.599*** 0.218***
* *
(-0.71) (6.33) (27.79) (9.66) (-4.51) (6.52) (36.15) (10.53)
-
Gansu -0.226 -0.00455 7.138*** 0.163*** -0.640*** 0.00385** 7.113*** 0.174***
*
(-1.37) (-1.45) (20.10) (7.71) (-11.81) (-6.70) (94.89) (41.34)
Qinghai -0.405*** 0.0022 5.906*** 0.122*** -0.407*** -0.000221 6.175*** 0.0985***
(-5.16) (1.71) (30.88) (5.87) (-10.30) (-0.18) (30.70) (4.77)
Ningxia -0.519 0.00648 5.689*** 0.379** 0.921 -0.00283 6.692*** 0.257***
(-0.60) (0.72) (5.18) (3.23) (1.02) (-0.49) (9.06) (3.39)
0.00357**
Xinjiang -0.449*** 6.784*** 0.106*** -0.529 0.00315 6.797*** 0.111***
*
(-3.39) (3.46) (50.35) (8.58) (-1.75) (1.87) (34.47) (6.96)

11. 11
Results summary of equ.2
• The results show that disasters induced by adverse
climate do invade net agricultural income.
• The increase of price index of agricultural products has a
statistically significant impact on per capita net agri.
income in Guangxi, Guizhou, Shaanx, Gansu, and
Xinjiang.
• the increase of rural population facilitate the increase of
agriculture income.
• Time trend factors including technology and infrastructure
progress contribute to the increase of agricultural income.
• trend factors contribute to the increase of net agri. income by
1.1~1.46% annually.

12. 12
Food Consumption (per capita kg/year)
year rice wheat vegt oil meat pork beef lamb poultry egg fish
2003 80.0 102.8 88.6 5.5 18.9 14.9 1.3 2.8 2.2 2.2 1.0
2004 78.6 103.0 88.0 4.0 18.3 14.7 0.9 2.7 2.2 2.0 1.0
2005 79.4 105.1 86.0 5.1 20.3 16.6 1.1 2.6 2.6 2.1 1.1
2006 77.5 98.4 83.7 5.1 20.7 16.6 1.4 2.3 2.6 2.3 1.2
2007 75.9 95.5 81.1 5.0 18.7 14.8 1.3 2.7 2.9 2.2 1.3
2008 77.2 93.7 80.3 5.1 17.3 14.0 1.1 2.3 3.4 2.6 1.3
2009 77.2 88.1 86.0 5.3 20.9 15.1 1.1 2.5 3.4 2.5 1.3
Total 78.0 98.1 84.8 5.0 19.3 15.2 1.2 2.6 2.8 2.3 1.2

13. 13
Food consumption & Climate change
•

14. 14
the determinant of food consumption of western
rural residents: a GMM estimation
variable rice wheat veg oil pork beef lamb poultry egg fish
Ps/pr 3.319*** 4.078*** -0.00423 6.819*** 0.157 3.271 0.419 -0.816* 1.665
(3.96) (4.74) (-0.01) (6.36) (0.07) (1.14) (0.50) (-2.15) (1.71)
w1 -2.469* 2.124 -1.051** -0.728 3.214*** 0.996 3.153* -1.409* 0.59 -0.445
(-2.22) (1.76) (-2.95) (-1.81) (3.98) (0.89) (2.11) (-2.02) (0.79) (-0.57)
0.0472
pindex 0.0214 0.0326 0.0283*** -0.00613 0.0428* -0.0505 -0.0992* 0.0337* 0.0487***
*
(0.97) (0.87) (4.62) (-0.59) (2.15) (-1.61) (-2.25) (2.30) (3.77) (2.24)
rpop -0.281 -6.692 1.683* 3.228* -9.814** 12.23* 12.56* -9.029*** -1.716 -4.91
(-0.11) (-1.31) (1.97) (2.27) (-3.29) (2.33) (2.14) (-3.65) (-0.81) (-1.34)
trend 0.381 0.531 0.325*** 0.0399 0.119 -0.0697 -0.78 0.0798 0.466*** 0.325
(1.66) (1.31) (5.32) (0.34) (0.63) (-0.22) (-1.84) (0.46) (3.78) (1.54)
lnpr -2.511* -0.86 -1.215*** -0.368 0.848 -2.569* -0.938 2.271** -1.648** -1.694
(-2.49) (-0.36) (-4.06) (-0.82) (1.10) (-2.22) (-0.62) (2.86) (-2.81) (-1.28)
Ps/pr 2.902*** 4.160*** -0.0161 6.828*** 0.0879 3.364 0.28 -0.781* 1.623
(3.37) (4.53) (-0.03) (6.34) (0.04) (1.26) (0.34) (-2.10) (1.65)
w2 -4.479** 2.758 -1.562** -0.81 4.099*** 2.303 5.501** -1.313 0.578 -0.698
(-2.91) (1.61) (-2.62) (-1.65) (3.79) (1.54) (2.78) (-1.28) (0.48) (-0.65)
0.0466
pindex 0.0229 0.0367 0.0267*** -0.00743 0.0474* -0.0504 -0.0929* 0.0311 0.0501***
*
(1.07) (1.00) (4.50) (-0.68) (2.22) (-1.67) (-2.19) (1.96) (4.09) (2.24)
rpop -0.116 -7.205 1.772* 3.513* -10.90** 11.62* 11.1 -8.705*** -1.868 -4.67
(-0.05) (-1.44) (2.13) (2.30) (-3.12) (2.25) (1.90) (-3.37) (-0.92) (-1.27)
trend 0.418 0.525 0.309*** 0.0378 0.114 -0.0945 -0.781 0.0705 0.476*** 0.327
(1.83) (1.27) (5.05) (0.31) (0.58) (-0.31) (-1.95) (0.39) (3.72) (1.57)
lnpr -2.567** -0.437 -1.115*** -0.458 1.174 -2.357* -0.716 2.246** -1.654** -1.753
(-2.67) (-0.18) (-3.43) (-0.94) (1.40) (-2.08) (-0.48) (2.64) (-2.65) (-1.34)

15. 15
Results
1. the impact of climate change on food consumption
• Climate change has statistically significant and negative impact on rice
and vegetable consumption of rural residents. However, climate
change has significant and positive impact on pork and lamb
consumption.
2. the impact of substitute products on food
consumption
• results show that rice and wheat, as staple food in western
China, act evidently good substitute to each other. Eggs are
strong substitute for pork. There is no evidence to show that pork
acts a substitute for edible oil and the result is statistically
insignificant.
3. The result suggests that the increase of producer
price of agricultural products actually increase rural
residents’ consumption of vegetables, pork, eggs,
and aquatic products, and do not affect staple food
consumption including rice and wheat.

16. 16
Results
4. the impact of population growth and time trend on
food consumption
• the consumption of vegetables, edible oil, beef and lamb
increases as rural population grows, but the consumption
of pork and poultry meat declines.
• rural residents’ consumption preference to vegetables and
eggs goes up over time.
5. price elasticity and food consumption
• Results indicate that the consumption of rice, vegetables,
beef, and eggs is price elastic. Increase of price of these
items will significantly reduce their consumption.

17. 17
Conclusions and Implication
1. The impact of climate change on agricultural income varies
among different regions. Six out of ten provinces are
affected adversely and significantly. This might suggest
adaptation capability in these provinces particularly need
to be strengthened to tackle with adverse climate change.
2. The impact of climate change on food consumption differs
in accord with food varieties. Adverse climate change has
negative impact on the consumption of rice, vegetables
and poultry. However, climate change helps to increase
meat consumption including pork and lamb.
3. Rural population growth is an important factor affecting
household income. Per capita agricultural income increases
with the increase of rural population growth. One possible
explanation is that agricultural labor is deficient in many rural
regions as most prime rural labors migrate to the urban.

18. 18
Conclusions and Implication
4. Rural residents’ consumption of vegetables and eggs
increases over time, which indicates an improvement in
food nutrition balance. However, rural residents’
consumption of certain food items including vegetables,
beef, and eggs are quite elastic to price change.
5. Time trend variable including technological progress
factors plays a positive role in agricultural income
growth. However, the coefficient is relatively low.

19. 19
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