Tadayoshi Masuda
1
and Peter D. Goldsmith
2
1
National Soybean Research Laboratory
University of Illinois at Urbana-Champaign
Email: tmasuda@illinois.edu
2
Department of Agricultural and Consumer Economics
University of Illinois at Urbana-Champaign
Email: pgoldsmi@illinois.edu
Poster prepared for presentation at the Agricultural & Applied Economics Association 2010
AAEA, CAES, & WAEA Joint Annual Meeting, Denver, Colorado, July 25-27, 2010
Copyright 2010 by Tadayoshi Masuda and Peter D. Goldsmith. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies.

Introduction
Bennett (1941) suggests that the ratio of cerealpotato calories to total food calories is itself a rough
(inverse) index of income status, and a rougher index of quality diet.
In the light of what is called the
Bennett’s law, China (Mainland China + Hong Kong
+ Macau)’s per capita income growth as well as population growth and urbanization fuel the increase in meat consumption per capita and in total (Figures
1, 2, 3). During the half century, China’s per capita real GDP (constant US dollar in 2000) increased 14.3
times and its total population 1.9 times.
100%
Figure 1. China’s Ratio of Meat Calories to Total
Food Calories (1965-2005)
3500
15%
13% 12% 14% 16% 17% 19% 20%
22%
75%
50%
25%
0%
2970
3000
2842
2901
81% 78% 75%
2704
72%
64% 60% 56% 2500
78% 81%
1799
1854
1932
2%
6%
2167
3%
3%
7% 8%
5%
6%
11% 14%
7%
15%
2000
1500
1965 1970 1975 1980 1985 1990 1995 2000 2005
Meat Total (%)
Cereals & Starchy Roots (%)
Total Food Kcal/capita/day (Right)
Other Animal Products (%)
Other Vegetal Products (%)
Notes: 1. China = Mainland China + Hong Kong + Macau.
2. Meat = Bovine Meat + Mutton & Goat Meat + Pig Meat + Poultry Meat + Other Meat.
3. Other Animal Products include offals, animal fats, eggs, milk, aquatic products.
4. Other Vegetal Products include sugar crops, sugar & sweeteners, honey, pulses, tree nuts, oilcrops, vegetable oils, vegetables, fruits, stimulants, spices, alcoholic beverages.
Source: FAOSTAT and authors’ calculation.
Objectives
1) to estimate the long-term income elasticity of demand for meat by commodity (pig meat, poultry meat, bovine meat, and mutton & goat meat) in China and discuss the differences;
2) to project the long range meat consumption by commodity through 2030 in China; and
3) to discuss the policy and business implications regarding China’s livestock industry and international feed grain and oilseeds markets.
Figure 2. Shifts of Meat 1 Consumption Quantity
Share of China 3 , USA, Brazil and Continents
2
100% 250
80%
60%
40%
20%
0%
244
9% 9% 9% 9% 9% 8% 8% 9% 9%
191
165
48% 43%
38% 37%
51% 50% 52% 51% 50%
124
107
92
3% 3% 3%
4%
24% 23%
21% 20%
18%
4%
17%
16% 21%
6%
15%
6%
15%
26% 27%
6% 8% 9% 10%
12%
5%
16%
200
150
100
50
0
China
USA
Brazil
Eurasia excl. China
America excl. USA & Brazil
Africa
Oceania
World Meat Consumption (MMT, right)
Notes: 1. Meat = Bovine Meat + Mutton & Goat Meat + Pig Meat +
Poultry Meat + Other Meat.
2. Domestic supply quantity for food (million metric tons).
3. China = Mainland China + Hong Kong + Macau.
Source: FAOSTAT and authors’ calculation.
Figure 3. China’s Meat Consumption and Its
Composition (1961-2005)
100% 60.0
75%
17% 12% 12% 13%
11% 12%
16%
51.4
45.5
20% 20%
33.7
45.0
50% 30.0
23.3
67% 65%
25%
9.5
10.5 12.1
15.0
6.5
0% 0.0
Pig meat (%, left)
Poultry meat (%, left)
Bovine meat
Mutton & Goat meat
Other meat
Total Meat Consumption (kg/capita/yr, right)
Notes. Meat Consumption = Domestic Meat Supply for Food /
Population. Carcass retail weight loss is not considered.
Source: FAOSTAT and authors’ calculation.
Methods
We deal with time series of China’s domestic meat supply quantities for food (in metric tons) as meat consumption from 1961 to 2008. We employ the concept of income elasticity of demand using the per capita meat consumption and per capita real
GDP. Data sources are FAOSTAT (FAO) and WDI
Online (World Bank).
Vector Error Correction Model (VECM) is employed to estimate the cointegrating equations or long-term income elasticities. Gonzalo (1994) shows that Johansen’s (1988) maximum likelihood approach clearly has better properties. Following
Johansen (1995), the trend parameters are either set to zero or unrestricted to improve fitness. The damped-trend linear exponential smoothing model
Table 1. Long-term Income Elasticity of
Meat Consumption in China
Commodity Elasticity Std. Err.
Pig meat 0.151
0.048***
Poultry meat
Bovine meat
1.057
1.560
0.087***
0.143***
Mutton & Goat
Other meat
0.882
0.045***
0.944
0.088***
Log L # of lags Period # of Obs.
169.556
3 1964 -2008 45
168.582
154.035
3
3
1964 -2008
1964 -2008
45
45
169.507
132.126
3
3
1964 -2008
1964 -2008
45
45
Note. ***Denotes significant at 1%.
Source: Estimation by authors.
Table 2. China’s Meat Consumption: Projection Summary
Meat Consumption, Total (MMT)
-- Pig meat
-- Poultry meat
-- Bovine meat
-- Mutton & Goat meat
-- Other meat
Per Capita Meat Cons. (kg/capita/year)
-- Pig meat
-- Poultry meat
1999/01 2010
62.6
81.6
41.0
12.9
48.7
19.0
5.2
2.7
0.8
49.2
32.2
10.1
7.7
4.4
1.8
59.9
35.8
14.0
2020
111.8
54.9
31.6
15.8
6.7
2.8
77.7
38.2
21.9
2030
136.3
58.3
42.0
23.8
8.5
3.6
92.6
39.6
28.6
applied to estimate per capita GDP beforehand.
Given the estimated income elasticities and per capita income, China’s meat consumption quantities are projected using a recursive form through 2030.
Results, Projections, and Discussion
-With respect to income increase, pig meat consumption is inelastic (0.151), mutton & goat meat and poultry meat are rather unity (0.882 and
1.057, but bovine meat consumption is elastic
(1.560) (Table 1).
- As GDP grows annually at 4.9% in 2010-20 and
2.8% in 2020-30, total meat consumption increases at 3.2% and 2.0%, respectively, and reaches 136 mil. metric tons in 2030 (Table 2).
- China’s per capita meat consumption (54 kg/ca/yr in 2006-07) is already above the world average
(41) and will exceed the current Brazil’s per capita meat consumption (81) in 2020s.
- China is a top importer of feed crop (soybean) and now meat importer (Table 3).
- As food policy, China needs to consider selfsufficiency and distribution of protein foods.
- International meat and feed crop markets will be affected by China’s livestock industry.
-- Mutton & Goat meat
-- Other meat
GDP (billion constant 2000 USD)
Per Capita GDP (cons. 2000 USD/capita)
Population, Total (million people)
2.1
0.7
1,372
1,077
1,274
3.2
1.3
3,276
2,406
1,362
Meat Consumption, Total (CAGR %)
-- Pig meat
-- Poultry meat
-- Bovine meat
-- Mutton & Goat meat
-- Other meat
Per Capita Meat Consumption (CAGR %)
-- Pig meat
-- Poultry meat
-- Bovine meat
-- Mutton & Goat meat
-- Other meat
Gross Domestic Product (CAGR %)
Per Capita GDP (CAGR %)
Population, Total (CAGR %)
Note. 1. Projection starts from 2009.
2. CAGR = Compound Annual Growth Rate.
Sources: FAOSTAT, World Bank WDI, and estimation by authors.
4.7
1.9
5,302
3,683
1,439
5.8
2.4
6,956
4,728
1,471
1999/01-2010 2010-20 2020-30
2.7% 3.2% 2.0%
1.8%
4.0%
4.0%
1.2%
5.2%
7.5%
0.6%
2.9%
4.2%
5.0%
7.6%
2.0%
1.1%
3.3%
3.3%
4.3%
6.9%
9.1%
8.4%
0.7%
4.4%
4.7%
2.6%
0.6%
4.6%
6.9%
3.8%
4.1%
4.9%
4.4%
0.6%
2.2%
2.4%
2.8%
2.5%
0.2%
2.5%
2.6%
1.8%
0.4%
2.7%
4.0%
Table 3. Meat Supply Balances in China, USA, Brazil
& India (2006-07 year average)
Element
Production (million metric tons)
Net Import (million metric tons)
Dom. Supply (million metric tons)
Per Capita Supply (kg/capita/year)
Population, Total (million people)
Source: FAOSTAT and authors’ calculation.
World China USA Brazil India
269.9
71.6
41.5
21.1
6.4
0.7
-3.0
-5.8
-0.5
269.9
72.3
38.5
15.3
5.9
40.7
54.2
125.5
80.8
6,631 1,332 307 189
5.1
1,156

Denver
100%
15%
Meat Calories to Total Food Calories (1965-2005)
3500
13% 12% 14% 16% 17%
19% 20%
75%
50%
25%
0%
78% 81% 81% 78% 75%
2469
2704
64%
2842
2901
2970
3000
60% 56% 2500
2167
2%
4%
1799
2%
4%
1854
2%
5%
1932
2%
6%
3%
7%
3%
8%
5%
11%
6%
14% 15%
1965 1970 1975 1980 1985 1990 1995 2000 2005
2000
1500
Meat Total (%)
Page 3 of 11

Denver
Figure 2. Shifts of Meat
1
Consumption Quantity
2
Share of China
3
100%
9% 9% 9% 9% 8% 8%
80%
191
60%
51%
50% 52% 51%
124
141
165
48%
43%
40%
20%
24%
92
3%
3%
23% 21% 20%
4%
18%
4%
17%
5%
16%
21%
12%
16%
0%
6% 8% 9% 10%
244
9%
38% 37%
6% 6%
15% 15%
26% 27%
250
200
150
100
50
0
Page 4 of 11

Denver
100%
75%
50%
25%
17%
76%
12% 12% 13% 11%
12%
16%
33.7
2005)
60.0
45.5
20% 20% 45.0
30.0
81%
9.5
23.3
81% 80% 82% 80%
10.5
12.1
73%
67% 65%
15.0
6.5
0% 0.0
considered.
Page 5 of 11

Denver
100%
75%
18% 18% 18% 20%
1148
1362
1404
23% 28%
32% 36%
1218
1274
1320
41% 45%
50% 53%
2030)
1,500
1,250
50%
25%
720
916
986
77% 72%
68% 64%
59% 55%
50% 47%
1,000
750
0% 500
Urban population (%, left)
Page 6 of 11

Poster #11972, Masuda and Goldsmith, 2010 AAEA Annual Meeting in Denver commodity
Pig meat
Poultry meat
Bovine meat
Mutton & Goat
Table 1. Long-term Income Elasticity of Meat Consumption in China
Elasticity Std. Err.
0.151
1.057
1.560
0.882
0.048 ***
Cons.
-
0.087 *** -4.706
0.143 *** -8.572
0.045 *** -5.761
Std. Err.
-
-
-
-
Log L
169.556
168.582
154.035
169.507
- 132.126 Other meat 0.944 0.088 *** -6.566
Note. ***Denotes significant at 1%.
Source: Estimation by authors.
# of lags Period
3 1964 -2008
3 1964 -2008
3 1964 -2008
3 1964 -2008
3 1964 -2008
# of Obs.
45
45
45
45
45
Page 7 of 11

Poster #11972, Masuda and Goldsmith, 2010 AAEA Annual Meeting in Denver
Table 2. China’s Meat Consumption: Projection Summary
Meat Consumption, Total (million metric tons)
-- Pig meat
-- Poultry meat
-- Bovine meat
-- Mutton & Goat meat
-- Other meat
Per Capita Meat Consumption (kg/capita/year)
-- Pig meat
-- Poultry meat
-- Bovine meat
-- Mutton & Goat meat
-- Other meat
GDP (billion constant 2000 USD)
Per Capita GDP (constant 2000 USD/capita)
Population, Total (million people)
1999/01
62.6
41.0
12.9
5.2
2.7
0.8
49.2
32.2
10.1
4.1
2.1
0.7
1,372
1,077
1,274
2010
81.6
48.7
19.0
7.7
4.4
1.8
59.9
35.8
14.0
5.6
3.2
1.3
3,276
2,406
1,362
Meat Consumption, Total (CAGR
2
%)
-- Pig meat
-- Poultry meat
-- Bovine meat
-- Mutton & Goat meat
-- Other meat
Per Capita Meat Consumption (CAGR %)
-- Pig meat
-- Poultry meat
-- Bovine meat
-- Mutton & Goat meat
-- Other meat
Gross Domestic Product (CAGR %)
Per Capita GDP (CAGR %)
1999/01-2010 2010-20 2020-30
2.7%
1.8%
4.0%
4.0%
5.0%
7.6%
2.0%
1.1%
3.3%
3.3%
4.3%
6.9%
9.1%
8.4%
3.2%
1.2%
5.2%
7.5%
4.4%
4.7%
2.6%
0.6%
4.6%
6.9%
3.8%
4.1%
4.9%
4.4%
0.6%
2.0%
0.6%
2.9%
4.2%
2.5%
2.6%
2.5%
0.2%
1.8%
0.4%
2.7%
4.0%
2.2%
2.4%
2.8%
Population, Total (CAGR %)
Note. 1. Projection starts from 2009.
2. Compound Annual Growth Rate.
Sources: FAOSTAT, World Bank WDI, and estimation by authors.
0.7%
2020
111.8
54.9
31.6
15.8
6.7
2.8
77.7
38.2
21.9
11.0
4.7
1.9
5,302
3,683
1,439
2030
136.3
58.3
42.0
23.8
8.5
3.6
92.6
39.6
28.6
16.2
5.8
2.4
6,956
4,728
1,471
Page 8 of 11

Poster #11972, Masuda and Goldsmith, 2010 AAEA Annual Meeting in Denver
Table 3. Meat Supply Balances in China, USA, Brazil & India (2006-07 year average)
Element
Production (million metric tons)
Per Capita Supply
3
(kg/capita/year)
World China USA Brazil India
269.9
40.7
71.6
54.2
41.5
125.5
21.1
Net Import
1
(million metric tons) - 0.7 -3.0 -5.8
Domestic Supply
2
(million metric tons) 269.9 72.3 38.5 15.3
80.8
6.4
-0.5
5.9
5.1
307 189 1,156 Population, Total (million people)
Notes: 1. Net Import = Import – Export.
2. Domestic Supply = Production + Net Import.
3. Per Capita Supply = Domestic Supply / Population.
Source: FAOSTAT and authors’ calculation.
6,631 1,332
Page 9 of 11

Poster #11972, Masuda and Goldsmith, 2010 AAEA Annual Meeting in Denver
References
Bennett, M.K., 1941. Wheat in National Diets. Wheat Studies of the Food Research Institute,
Stanford University. 18(2), 35-76.
Deaton, A., Muellbauer, J., 1983. Economics and Consumer Behavior. Cambridge Univ. Press.
Delgado, C., Rosegrant, M., Steinfeld, H., Ehui, S., Courbois, C., 1999. Livestock to 2020: The
Nest Food Revolution. Food, Agriculture, and Environmental Discussion Paper 28. IFPRI,
Washington, D.C.
FAO. FAOSTAT. http://faostat.fao.org/
FAO. 2006. World Agriculture: Towards 2030/2050 Interim Report. Rome.
Gardner, E.S.Jr., 1985. Exponential Smoothing: The State of the Art. J. of Forecasting. 4, 1-28.
Gardner, E.S.Jr., Mckenzie E., 1985. Forecasting Trends in Time Series. Management Science.
31 (10), 1237-1246.
Gonzalo, J., 1994. Five alternative methods of estimating long-run equilibrium relationships. J. of Econometrics. 60, 203-233.
Hamilton, J.D., 1994. Time Series Analysis. Princeton Univ. Press.
Johansen, S., 1988. Statistical Analysis of Cointegration Vectors. J. of Econ. Dynamics &
Control. 12, 231-254.
Johansen, S., 1995. Likelihood-Based Inference in Cointegrated Vector Autoregressive Models.
Oxford University Press, New York.
Keyzer, M., Merbis, M., Pavel, F., 2001. Can We Feed the Animals? Origins and Implications of
Rising Meat Demand. Center for World Food Studies, Amsterdam.
Page 10 of 11

Poster #11972, Masuda and Goldsmith, 2010 AAEA Annual Meeting in Denver
Keyzer, M.A., Merbis, M.D., Pavel, I.F.P.W., van Wesenbeek, C.F.A., 2005. Diet shift towards meat and the effects on cereal use: can we feed the animals in 2030? Ecological
Economics. 55, 187-202.
Mills, T.C., 1990. Time series techniques for economists. Cambridge Univ. Press.
World Bank. WDI Online. http://publications.worldbank.org/WDI/
Page 11 of 11