‍Quality measurement for China’s agricultural exports: based on the nested logit model

DONG Yinguo1 HUANG Junwen2

(1.School of Business, East China University of Science and Technology)
(2.School of Economics, Shanghai University)

【Abstract】The Sanitary and Phytosanitary (SPS) Measures which are closely related to food safety, animal and plant health and environmental safety have become the main obstacles to China’s export of agricultural products since China joined the World Trade Organization. Improving the quality of agricultural products and the efficiency of agricultural production is the urgent problem for China’s agricultural development. This paper takes the most important export market for Chinese agricultural products—Japan as an example. The quality of China’s agricultural exports is measured by the nested logit model and based on the subdivided trade data of Japanese agricultural imports with HS9 customs code from 2005 to 2012. The result of the empirical analysis shows that the quality of China’s agricultural exports within the sample interval has gone through a positive N-type change of ascension, fall and re-ascension. The comparison with other major agricultural exporters reveals that the quality of four categories of Chinese agricultural products, namely vegetables, fruits, coffee and tea, spices and dried fruits and nuts, is basically equal to that of the India products, but it still has great disparity with the agricultural product quality of the Netherlands, France and other countries.

【Keywords】 agricultural exports; quality; nested logit model; SPS measures;


【Funds】 National Natural Science Foundation of China (71373154) National Natural Science Foundation of China (71673087) National Natural Science Foundation of China (71303152) Shanghai Pujiang Scholars Foundation (15PJC048) Liberal Arts Education Foundation of East China University of Science and Technology (222201522026)

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    [1]. ① The original equation by Hausman et al. (2006) was, where (xjk /Xj) represents the value share of product k exported from country j accounting for the total export of the country; Yj represents the per capita GDP of country j; PRODYk is the technical complexity index of product k. [^Back]

    [2]. ② What Shi (2013) quoted was from Gervais’s conference paper in 2009 which was officially published in 2015. Gervais’s conference paper in 2009 can be found in http://economics.yale.edu/sites/default/files/files/Workshops-Seminars/International-Trade/gervais-110406.pdf [^Back]

    [3]. ① Quality as an important feature of vertical differentiation in products reflects the degree of consumer recognition for different differentiated products of the same category. [^Back]

    [4]. ① Suppose a Japanese consumer chooses between Chinese onions and Australian radishes. When the US onions enter the Japanese market, the traditional logit and CES framework predicts that Chinese onions and Australian radishes will decrease by the same market share, but in fact, Chinese onions as the same category of products with the US onions will lose more market share than Australian radishes. This may overestimate the quality of Chinese onions. [^Back]

    [5]. ② It is applied to agricultural products, for example, grouping “lemon” (HS 080550010) and “lime” (HS 080550090) in “lemon and lime” (HS 080550). [^Back]

    [6]. ③ The nested logit model breaks the restriction of the independence and irrelevance between products in the previous logit model by grouping similar products, because in reality it is difficult to meet the mutual independence between products, such as the classic “issue of red car and blue car.” [^Back]

    [7]. ④ That is, when consumers choose similar products with strong homogeneity, what they consider more is the horizontal differentiation rather than the vertical differentiation. [^Back]

    [8]. ① Considering the acquisition, processing and matching of the original data, relevant explained variables and explanatory variables have been uniformly calculated by nominal indexes. In addition, because the product unit value and per capita GDP in the model have been processed logarithmically, the exchange rate and the price level have little influence on the two logarithmic values. The quality parameter expectancy results assessed by the model do not change much. Even if the sample data go through deflator processing of large workload, the expected result is still stable. Therefore, this paper does not conduct the deflator processing on the raw data considering the cost-effectiveness. [^Back]

    [9]. ① According to the Japanese input statistics catalog, the agricultural products under HS6 bit coding are classified in one group, and the variety number of subdivided agricultural products of HS9 customs code imported by Japan in this group is the number of the intra-group products. Again, the case of lemon is taken as an example. “Lemon and lime” (HS 080550) is a product number (a group); “lemon” (HS 080550010) and “lime” (HS 080550090) are the category number of two different products. In addition, the Japanese customs code has been formally transitioned from HS2002 to HS2007 since 2011. This paper has made corresponding adjustments. [^Back]

    [10]. ① Trade Statistics of Japan, Department of Finance (e-stat) (http://www.customs.go.jp/toukei/info/tsdl.htm). [^Back]

    [11]. ② Statistics of the Ministry of Agriculture, Forestry and Fisheries of Japan (MAFF) (http://www.maff.go.jp/j/tokei/kouhyou/kokusai/index.html). [^Back]

    [12]. ③ The World Bank Data (http://wits.worldbank.org/). [^Back]

    [13]. ① Within one year, Japan will import the same kind of agricultural products from different countries. At the same time, the same country will export different kinds of agricultural products to Japan. Therefore, the original sample data used in this paper do not meet the requirements of panel data. The exporting country and the agricultural products that it exports shall be fixed as an independent individual, that is, the symble ch meaning product h exported from country c. [^Back]

    [14]. ① Data source: Ministry of Commerce: Monthly Statistical Report on Import and Export of Chinese Agricultural Products 2011, http://wms.mofcom.gov.cn/article/ztxx/ncpmy/ncpydtj/200603/20060301783733.shtml [^Back]

    [15]. ② Department of Foreign Trade of the Ministry of Commerce, China Chamber of Commerce of Foodstuffs and Native Produce, Chinese Agricultural Products Export Analysis Report, http://finance.sina.com.cn/roll/20111108/080610773162.shtml [^Back]

    [16]. ① Data source: http://www.agri.ac.cn/news/ztqbfw/2014415/n793096815.html [^Back]

    [17]. ① Data source: Zhang Bin, Yao Shuihong: Pesticides in the Environment: Survey on Pesticide Residues in Soil, Water and Atmosphere of Chinese Typical Intensive Agricultural Region, Greenpeace Research Report, January 2013. [^Back]

    [18]. ② Data source: http://news.xinhuanet.com/fortune/2011-06/17/c_121551163.htm [^Back]


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This Article


CN: 11-1262/F

Vol , No. 11, Pages 30-43

November 2016


Article Outline



  • 1 Introduction
  • 2 Literature review
  • 3 Model and data
  • 4 Results of empirical analysis
  • 5 Conclusion and policy enlightenment
  • Footnote