Please wait a minute...
Journal of Integrative Agriculture  2015, Vol. 14 Issue (6): 1008-1022    DOI: 10.1016/S2095-3119(14)60985-0
Section 1: Consumption Advanced Online Publication | Current Issue | Archive | Adv Search |
Economic growth and nutrition transition: an empirical analysis comparing demand elasticities for foods in China and Russia
 Christine Burggraf, Lena Kuhn, ZHAO Qi-ran, Ramona Teuber, Thomas Glauben
1、College of Economics and Management, China Agricultural University, Beijing 100083, P.R.China
2、Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle (Saale) 06120, Germany
Download:  PDF in ScienceDirect  
Export:  BibTeX | EndNote (RIS)      
摘要  This study provides empirical evidence on the link between economic growth and nutrition transition in two emerging economies, China and Russia. Both countries have experienced rising average incomes, accompanied by an increasing rate of nutrition-related chronic diseases in recent years. Given the regional heterogeneity between these two countries, we analyze the extent to which income growth as a major driver of nutrition transition has a significant effect on the consumption of different food aggregates and how these effects differ between Chinese and Russian consumers. Our results indicate that with increasing household incomes over time the demand for carbohydrates decreases, while the demand for meat and dairy products, as well as fruits increases. This is a development generally known as nutrition transition. Further, we estimate a Quadratic Almost Ideal Demand System (QUAIDS) for nine different food aggregates for China and Russia. Our results indicate that in both countries all food aggregates have positive expenditure elasticities and are thus normal goods. Moreover, our results indicate that in 2008/2009 meat is still a luxury good in China yet a necessity good in Russia. For 2009, the highest own-price elasticities in China are found for non-meat protein sources and dairy products. Within the meat group, beef, poultry and mutton have the highest price elasticities in China. In Russia, the milk and dairy group, together with the vegetable group, is the most price-elastic food group in 2008. In line with the definition of a nutrition transition, our overall results underscore the finding that income growth in China and Russia tends to increase the demand for animal-based products much stronger than, for example, the demand for carbohydrates. Despite being a positive signal for problems of malnutrition in rural China, this trend of increasing meat consumption might further increase the incidence of chronic diseases in urban areas since there is convincing scientific evidence that increasing meat consumption, especially red and processed meat, is associated with an increased risk of chronic diseases.

Abstract  This study provides empirical evidence on the link between economic growth and nutrition transition in two emerging economies, China and Russia. Both countries have experienced rising average incomes, accompanied by an increasing rate of nutrition-related chronic diseases in recent years. Given the regional heterogeneity between these two countries, we analyze the extent to which income growth as a major driver of nutrition transition has a significant effect on the consumption of different food aggregates and how these effects differ between Chinese and Russian consumers. Our results indicate that with increasing household incomes over time the demand for carbohydrates decreases, while the demand for meat and dairy products, as well as fruits increases. This is a development generally known as nutrition transition. Further, we estimate a Quadratic Almost Ideal Demand System (QUAIDS) for nine different food aggregates for China and Russia. Our results indicate that in both countries all food aggregates have positive expenditure elasticities and are thus normal goods. Moreover, our results indicate that in 2008/2009 meat is still a luxury good in China yet a necessity good in Russia. For 2009, the highest own-price elasticities in China are found for non-meat protein sources and dairy products. Within the meat group, beef, poultry and mutton have the highest price elasticities in China. In Russia, the milk and dairy group, together with the vegetable group, is the most price-elastic food group in 2008. In line with the definition of a nutrition transition, our overall results underscore the finding that income growth in China and Russia tends to increase the demand for animal-based products much stronger than, for example, the demand for carbohydrates. Despite being a positive signal for problems of malnutrition in rural China, this trend of increasing meat consumption might further increase the incidence of chronic diseases in urban areas since there is convincing scientific evidence that increasing meat consumption, especially red and processed meat, is associated with an increased risk of chronic diseases.
Keywords:  nutrition transition       food demand       QUAIDS       China       Russia  
Received: 05 January 2014   Accepted:
Corresponding Authors:  ZHAO Qi-ran, Tel: +86-10-62736564,E-mail: zhaoqr.ccap@igsnrr.ac.cn     E-mail:  zhaoqr.ccap@igsnrr.ac.cn
About author:  Christine Burggraf, E-mail: burggraf@iamo.de; Lena Kuhn,E-mail: kuhn@iamo.de; Ramona Teuber, E-mail: teuber@iamo.de; Thomas Glauben, E-mail: glauben@iamo.de;

Cite this article: 

Christine Burggraf, Lena Kuhn, ZHAO Qi-ran, Ramona Teuber, Thomas Glauben. 2015. Economic growth and nutrition transition: an empirical analysis comparing demand elasticities for foods in China and Russia. Journal of Integrative Agriculture, 14(6): 1008-1022.

[1]Bai J F, Thomas I W , Bryan T L, Huang J K. 2010. Food awayfrom home in Beijing: Effects of wealth, time and “free”meals. China Economic Review, 21, 432–441.

[2]Bai J F, Thomas I W, James S J, Bryan T L. 2013. Meatdemand analysis in urban China: To include or not to includemeat away from home? Agricultural & Applied EconomicsAssociation Annual Meeting. Washington, D.C.

[3]Chen Q. 2010. Study on the meat consumption of urban andrural residents in China. MSc thesis, Chinese Academy ofAgricultural Sciences, Beijing. (in Chinese)

[4]FAO. 2013. FAOSTAT. [2014-8-1]. http://faostat3.fao.org/download/T/TP/

[5]EFuller F, Hayes D, Smith D. 2000. Reconciling Chinese meatproduction and consumption data. Economic Developmentand Cultural Change, 49, 23–43.

[6]Jiang N H. 2002. Theories and methods to adjust national andprovincial meat products statistics. Journal of AgrotechnicalEconomics, 6, 11–20. (in Chinese)

[7]Lu F. 1998. The lack fidelity and inconsistency about certainagricultural production and consumptions statistics in China.Chinese Rural Economy, 10, 47–53. (in Chinese)

[8]Luo W C, Liu R. 2011. Analysis of meat price volatility in China.China Agricultural Economic Review, 3, 402–411.

[9]Ma H Y, Huang J K, Frank F, Scott R. 2006. Getting rich andeating out: consumption of food away from home in urbanChina. Canadian Journal of Agricultural Economics, 54,101–119.

[10]Ma H Y, Rae A, Huang J K, Rozelle S. 2004. Chinese animalproduct consumption in the 1990s. Australian Journal ofAgricultural and Resource Economics, 48, 560–590.

[11]Ma H Y, Zhang Z R. 2000. Development of dietary market andestimation on Chinese residents’ diet away from home.Economic Survey, 6, 45–46. (in Chinese)

[12]NBSC (National Bureau of Statistics of China). 2005–2013.China Statistical Yearbook. China Statistics Press, Beijing,China. (in Chinese)

[13]Wang J J, Chen Y F, Zheng Z H, Si W. 2014. Determinantsof pork demand by income class in urban western China.China Agricultural Economic Review, 6, 452–469.

[14]Wang J M, Yuan X G. 2000. Livestock products consumptionstructure and consumer behavior of Chinese urban and ruralresidents. Food and Nutrition in China, 2, 9–12. (in Chinese)

[15]Wang J M, Zhou Z Y, Rodney J C. 2005. Animal productconsumption trends in China. Australasian AgribusinessReview, 13, 2–29.

[16]Wang J M, Zhou Z Y, Yang J. 2004. How much animal productdo the Chinese consume? Empirical evidence fromhousehold surveys. Australasian Agribusiness Review,12, 1–16.

[17]Xin X, Yin J, Jiang N H. 2003. The Market of China’s LivestockProducts: Regional Supply, Demand and Trade. ChinaAgriculture Press, Beijing. (in Chinese)

[18]Yu X H, David A. 2014. Where have all the pigs gone?Inconsistencies in pork statistics in China. China EconomicReview, 3, 1–16.

[19]Yuan X G, Wang J M. 2001. Is the China’s livestock productionstatistics overestimated? The survey on the livestockproducts consumption from six provinces in China. Chinese Rural Economy, 1, 48–54. (in Chinese)

[20]Zhang X Q. 2010. Zhang Xiao Qiang, deputy director of theNational Development and Reform Commission of China,answers journalists’ questions on “Cold Chain Logistics Development Plan of Agricultural Products”. [2014-4-28]http://www.gov.cn/gzdt/2010-07/28/content_1665697.htm(in Chinese)

[21]Zhang T T. 2012. Animal husbandry headlines. Modern Journalof Animal Husbandry and Veterinary Medicine, 3, 3–6. (in Chinese)

[22]Zhong F N. 1997. Analysis of the overestimation in China’smeat production statistics and its causes. Chinese RuralEconomy, 10, 63–66. (in Chinese)
[1] Libin Liang, Yaning Bai, Wenyan Huang, Pengfei Ren, Xing Li, Dou Wang, Yuhan Yang, Zhen Gao, Jiao Tang, Xingchen Wu, Shimin Gao, Yanna Guo, Mingming Hu, Zhiwei Wang, Zhongbing Wang, Haili Ma, Junping Li. Genetic and biological properties of H9N2 avian influenza viruses isolated in central China from 2020 to 2022[J]. >Journal of Integrative Agriculture, 2024, 23(8): 2778-2791.
[2] Xuan Li, Shaowen Wang, Yifan Chen, Danwen Zhang, Shanshan Yang, Jingwen Wang, Jiahua Zhang, Yun Bai, Sha Zhang.

Improved simulation of winter wheat yield in North China Plain by using PRYM-Wheat integrated dry matter distribution coefficient [J]. >Journal of Integrative Agriculture, 2024, 23(4): 1381-1392.

[3] Dian Chen, Xiangming Fang, Yu Chen, Xiaodong Zheng, Zhuo Chen, Rodney B.W. Smith.

The impact of the Rural Minimum Living Standard Guarantee (Rural Dibao) Program on child nutrition outcomes [J]. >Journal of Integrative Agriculture, 2024, 23(2): 444-456.

[4] Yi Cui, Qiran Zhao, Thomas Glauben, Wei Si. The impact of Internet access on household dietary quality: Evidence from rural China[J]. >Journal of Integrative Agriculture, 2024, 23(2): 374-383.
[5] Xiao Han, Kaiyu Lyu, Fengying Nie, Yuquan Chen.

Resilience effects for household food expenditure and dietary diversity in rural western China [J]. >Journal of Integrative Agriculture, 2024, 23(2): 384-396.

[6] Jie Xue, Xianglin Zhang, Songchao Chen, Bifeng Hu, Nan Wang, Zhou Shi.

Quantifying the agreement and accuracy characteristics of four satellite-based LULC products for cropland classification in China [J]. >Journal of Integrative Agriculture, 2024, 23(1): 283-297.

[7] ZHANG Sha, YANG Shan-shan, WANG Jing-wen, WU Xi-fang, Malak HENCHIRI, Tehseen JAVED, ZHANG Jia-hua, BAI Yun. Integrating a novel irrigation approximation method with a process-based remote sensing model to estimate multi-years' winter wheat yield over the North China Plain[J]. >Journal of Integrative Agriculture, 2023, 22(9): 2865-2881.
[8] YU Wen-jia, LI Hai-gang, Peteh M. NKEBIWE, YANG Xue-yun, GUO Da-yong, LI Cui-lan, ZHU Yi-yong, XIAO Jing-xiu, LI Guo-hua, SUN Zhi, Torsten MÜLLER, SHEN Jian-bo. Combining rhizosphere and soil-based P management decreased the P fertilizer demand of China by more than half based on LePA model simulations[J]. >Journal of Integrative Agriculture, 2023, 22(8): 2509-2520.
[9] LI Dong-qing, ZHANG Ming-xue, LÜ Xin-xin, HOU Ling-ling. Does nature-based solution sustain grassland quality? Evidence from rotational grazing practice in China[J]. >Journal of Integrative Agriculture, 2023, 22(8): 2567-2576.
[10] YANG Rui, XU Hang. Water diversion and agricultural production: Evidence from China[J]. >Journal of Integrative Agriculture, 2023, 22(4): 1244-1257.
[11] HOU Jing, ZHOU Li, Jennifer IFFT, YING Rui-yao. The role of time preferences in contract breach: Evidence from Chinese poultry farmers participating in contract farming[J]. >Journal of Integrative Agriculture, 2023, 22(2): 623-641.
[12] SHI Peng-fei, HUANG Ji-kun. Rural transformation, income growth, and poverty reduction by region in China in the past four decades[J]. >Journal of Integrative Agriculture, 2023, 22(12): 3582-3595.
[13] YANG Xu, ZHANG Jia-hua, YANG Shan-shan, WANG Jing-wen, BAI Yun, ZHANG Sha. Modelling the crop yield gap with a remote sensing-based process model: A case study of winter wheat in the North China Plain[J]. >Journal of Integrative Agriculture, 2023, 22(10): 2993-3005.
[14] FENG Lu, CHI Bao-jie, DONG He-zhong. Cotton cultivation technology with Chinese characteristics has driven the 70-year development of cotton production in China[J]. >Journal of Integrative Agriculture, 2022, 21(3): 597-609.
[15] CHU Zhen-dong, MING Bo LI Lu-lu, XUE Jun, ZHANG Wan-xu, HOU Liang-yu, XIE Rui-zhi, HOU Peng, WANG Ke-ru, LI Shao-kun . Dynamics of maize grain drying in the high latitude region of Northeast China[J]. >Journal of Integrative Agriculture, 2022, 21(2): 365-374.
No Suggested Reading articles found!