【摘要】加入世界贸易组织以来, 与食品安全、动植物健康和环境安全密切相关的卫生与植物检疫 (SPS) 措施成为中国农产品出口的主要障碍。提升农产品质量、提高农业生产效益是中国农业发展亟待解决的关键问题。本文以中国农产品最主要的出口市场——日本为例, 基于2005~2012年日本海关进口HS9位编码农产品贸易细分数据, 采用嵌套Logit模型对中国出口农产品质量进行测度。实证分析结果显示, 样本区间中国出口农产品质量经历了“上升、下降、再上升”的“正N型”变动;与其他主要农产品出口国的横向比较发现, 中国蔬菜、水果、咖啡茶叶及香料和杂食干果四大类农产品质量与印度基本持平, 但与荷兰、法国等国家农产品质量相比仍有较大差距。
【基金资助】 国家自然科学基金项目“农产品SPS适度保护水平的形成机理与应用策略” (项目编号:71373154) ; “SPS措施与农产品质量升级的耦合机制研究” (项目编号:71673087) ; “省级经济增长分布在空间趋同效应下的关联机制研究” (项目编号:71303152) ; 上海市浦江学者基金项目“农产品进口与中国SPS保护水平研究” (项目编号:15PJC048) ; 华东理工大学文科培育基金项目 (项目编号:222201522026) 的阶段性研究成果;
Quality measurement for China’s agricultural exports: based on the nested logit model
(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);
. 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 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]
. 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]
. 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]
. ② It is applied to agricultural products, for example, grouping “lemon” (HS 080550010) and “lime” (HS 080550090) in “lemon and lime” (HS 080550). [^Back]
. 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]
. 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]
. 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]
. 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]
. ① Trade Statistics of Japan, Department of Finance (e-stat) (http://www.customs.go.jp/toukei/info/tsdl.htm). [^Back]
. 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]
. ③ The World Bank Data (http://wits.worldbank.org/). [^Back]
. 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]
. 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]
. 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]
. ① Data source: http://www.agri.ac.cn/news/ztqbfw/2014415/n793096815.html [^Back]
. 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]
. ② Data source: http://news.xinhuanet.com/fortune/2011-06/17/c_121551163.htm [^Back]
1. Dong, Y. & Qiu, H. Issues in Agricultural Economy (农业经济问题), (2) (2014).
2. Dong, Y. & Jiang, P. Journal of International Trade (国际贸易问题), (11) (2012).
3. General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China. 2009 Annual Report of China’s Technical Measures to Trade (中国技术性贸易措施年度报告2009), 2012 Annual Report of China’s Technical Measures to Trade (中国技术性贸易措施年度报告2012). Beijing: China Zhijian Publishing House, (2009), (2012).
4. Han, H. & Xu, K. China Industrial Economics (中国工业经济), (4) (2014).
5. Huang, Z., Wang, X. & Song, H. Journal of Agricultural Economics (农业技术经济), (1) (2009).
6. Li, K., Jiang, W. & Song, L. Social Sciences in China (中国社会科学), (3) (2014).
7. Liu, C. West Journal (西部学刊), (7) (2014).
8. Shi, B., Wang, Y. & Li, K. The Journal of World Economy (世界经济), (9) (2013).
9. Shi, B. China Economic Quarterly (经济学 (季刊)), (1) (2013).
10. Wang, G. Rural Economy (农业经济), (10) (2008).
11. Wang, M. Statistical Research (统计研究), (5) (2014).
12. Wang, M. Economic Review (经济评论), (6) (2013).
13. Wei, F. Journal of International Trade (国际贸易问题), (1) (2015).
14. Yao, Y. & Zhang, Y. Social Sciences in China (中国社会科学), (2) (2008).
15. Zhang, Y. & Zhu, S. Journal of World Economics and Politics (世界经济与政治论坛), (2) (2014).
16. Baldwin, R. and Harrigan, J.: Zeros, Quality and Space: Trade Theory and Trade Evidence, American Economic Journal: Microeconomics, 3(2): 60–88, 2011.
17. Bernard, A. B.; Jensen, J. B. and Schott, P. K.: Survival of Best Fit: Exposure to Low-Wage Countries and the (Uneven) Growth of U.S. Manufacturing, Journal of International Economics, 68(1): 219–237, 2006.
18. Berry, S.: Estimating Discrete-choice Models of Product Differentiation, RAND Journal of Economics, 25(2): 242–262, 1994.
19. Crozet, M.; Head, K. and Mayer, T.: Quality Sorting and Trade: Firm-level Evidence for French Wine, The Review of Economic Studies, 79(2): 609–644, 2012.
20. Feenstra, R. C. and Romalis, J.: International Prices and Endogenous Quality, Quarterly Journal of Economics, 129(2): 477–527, 2012.
21. Feenstra, R.: New Product Varieties and the Measurement of International Prices, American Economic Review, 84(1): 157–177, 1994.
22. Flam, H. and Helpman, E.: Vertical Product Differentiation and North-South Trade, American Economic Review, 77(5): 810–822, 1987.
23. Gervais, A.: Product Quality, Firm Heterogeneity and International Trade, Canadian Journal of Economics, 48(3): 1152–1174, 2015.
24. Grossman, G. M. and Helpman, E.: Quality Ladders in the Theory of Growth, Review of Economic Studies, 58(1): 43–61, 1991.
25. Grunert, K. G.: Food Quality and Safety: Consumer Perception and Demand, European Review of Agricultural Economics, 32(3): 369–391, 2005.
26. Hallak, J. C.: Product Quality and the Direction of Trade, Journal of International Economics, 68(1): 238–265, 2006.
27. Hallak, J. C. and Schott, P. K.: Estimating Cross-country Differences in Product Quality, Quarterly Journal of Economics, 126(1): 417–474, 2011.
28. Hausman, R.; Huang Y. and Rodrik, D.: What You Export Matters, Journal of Economic Growth, 12(1): 1–25, 2006.
29. Helpman, E. and Krugman, P.: Market Structure and Foreign Trade, Cambridge: MIT Press, 1985.
30. Hummels, D. and Klenow, P.: The Variety and Quality of A Nation’s Exports, The American Economic Review, 95(3): 704–723, 2005.
31. Hummels, D. and Skiba, A.: Shipping the Good Apples Out? An Empirical Confirmation of the Alchian-Allen Conjecture, Journal of Political Economy, 112(6): 1384–1402, 2002.
32. Kugler, M. and Verhoogen, E.: Prices, Plant Size, and Product Quality, Review of Economic Studies, 79(1): 307–339, 2012.
33. Khandelwal, A.: The Long and Short of Quality Ladders, NBER Working Paper No.15178, 2009.
34. Linder, S. B.: An Essay on Trade and Transformation, New York: Wiley & Sons, 1961.
35. Melitz,M. J.: The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity, Econometrica, 71(6): 1695–1725, 2003.
36. Melitz, M. J. and Trefler, D.: Gains from Trade When Firms Matter, Journal of Economic Perspectives, 26(2): 91–118, 2012.
37. Michaely, M.: Trade, Income Levels and Dependence, Amsterdam: North-Holland, 1984.
38. Sexton, R.: Market Power, Misconceptions, and Modern Agricultural Markets, American Journal of Agricultural Economics, 95(2): 209–219, 2013.
39. Schott, P. K.: Across-product versus Within-product Specialization in International Trade, Quarterly Journal of Economics, 119(2): 647–678, 2004.
40. Sutton, J.: Quality, Trade and the Moving Window: The Globalization Process, Economic Journal, 117(524): 469–498, 2007.
41. Verhoogen, E.: Trade, Quality Upgrading and Wage Inequality in the Mexican Manufacturing Sector, Quarterly Journal of Economics, 123(2): 489–530, 2008.