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中国农产品中价格稳定的“锚”是什么?

全世文1 毛学峰2 曾寅初2

(1.中国社会科学院农村发展研究所)
(2.中国人民大学农业与农村发展学院)

【摘要】本文基于协整检验和误差修正模型分析了中国玉米、稻谷、小麦、大豆、棉花、白糖、猪肉7种主要农产品之间的长期价格均衡与价格传导路径。考虑到单次回归结果对样本期的敏感性,本文在总样本期内通过滚动窗口抽选了多个子样本期重复进行协整检验并回归误差修正模型。结果显示,从长期来看,玉米、棉花和白糖处于价格传导链的基础地位,小麦和大豆处于中间环节,稻谷和猪肉处于末端环节。其中,玉米价格与其它农产品价格之间通过协整检验的次数最多,且玉米价格在协整系统中被识别为弱外生变量的频率也最高。考虑到玉米种植区域广泛、总产量高、用途丰富、产业链深度与广度都较高,且玉米价格与原油价格的联系紧密,本文认为玉米是中国农产品价格稳定中的“锚”产品。政府应当加强对玉米市场的重视,在对农产品制定价格调控政策时要充分利用玉米作为“锚”产品的市场地位。

【关键词】 农产品价格;价格稳定;价格传导;价格联动;玉米;

【DOI】

【基金资助】 中国社会科学院创新工程A类项目“农业农村绿色发展理论与政策研究”(编号:2018NFSA01);

What is the anchor of China’s agricultural price stabilization?

QUAN Shiwen1 MAO Xuefeng2 ZENG Yinchu2

(1.Rural Development Institute, Chinese Academy of Social Sciences)
(2.School of Agricultural Economics and Rural Development, Renmin University of China)

【Abstract】This article uses a co-integration test and an error correction model to analyze the long-term price equilibrium and price transmission among China’s seven main agricultural products, namely maize, rice, wheat, soybean, cotton, sugar and pork. Taking into account the sensitivity of the single regression results to the sample period, this study uses a rolling window technique to select a wide range of sub-samples in the full sample period, repeats the co-integration test and uses the error correction model in each sub-sample for test. The results show that, in the long run, maize, cotton and sugar are in the basic position of price transmission chain, wheat and soybean are in the intermediate link, and rice and pork are in the terminal link. Among them, the number of times passing co-integration tests between the maize price and other product prices is the largest, and maize price is most frequently identified as weakly exogenous in the co-integration system. The study identifies maize as the anchor product in the price stability of China’s agricultural products, since the planting area of maize is wide, the production of maize is high, the depth and breadth of the maize industrial chain are much greater than those of other agricultural products, and maize price is closely linked with crude oil price. The government should attach more importance to the maize market, and make full use of the market position of maize as anchor product when formulating price intervention policies for agricultural products.

【Keywords】 agricultural price; price stabilization; price transmission; price co-movement; maize;

【DOI】

【Funds】 Type A Program of Innovation Project of Chinese Academy of Social Sciences (2018NFSA01);

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    Footnote

    [1]. ① Two questions need to be clarified. First, from the aspect of concept definition, food price is not equivalent to agricultural price, while the two are highly correlated. Second, dispute over whether currency policies of China should focus on food price still exists in academic circle (Hou and Gong, 2013), and a uniform conclusion on whether the second-round effect exists in food price in China is not reached in academic circle. For example, Zhang and Luo (2010) think that food price rise does not have the second-round effect on non-food price rise. However, Lyu and Zeng (2016) found that food price shock can cause certain second-round effect after considering multiple core CPI calculation methods and effect of financial crisis. [^Back]

    [2]. ① Vertical and transverse price transmission also exists in different markets of the same product. The former usually reflects market integration of different links in supply chain, and the latter reflects spatial market integration. Price transmission of the same product is not discussed in this paper. [^Back]

    [3]. ① It cannot be excluded that preference of specific consumers to specific agricultural product is complementary. [^Back]

    [4]. ② In contrast, present studies on price transmission focus more on price transmission and spatial price transmission of the same product in different links of industry chain. [^Back]

    [5]. ③ This system does not consider that the two kinds of agricultural products are in different links of the industry chain, namely, the situation where one kind of agricultural product is the production material of another agricultural product. Such situation mainly involves some agricultural products able to be used as pig feed in following analysis. [^Back]

    [6]. ① Specific presentation form of the common factor is not stressed in this paper. Ftcan be directly defined as the vector composed by macro-economic variables, or the principal component or latent variable extracted from macro-economic variables. [^Back]

    [7]. ② The common factor of agriculture sector also includes input of production factors (labor, land, fertilizer and machinery). The action mechanism of such common factor is similar to macro-economic factors but different from natural geographical conditions. [^Back]

    [8]. ③ The coefficient γ can also be used to reflect complementation among products: γ < 0 represents the complementation between agricultural products i and j. [^Back]

    [9]. ① Technically, the existence of linear co-integration relationship is the necessary condition for regression of error correction model. However, as mentioned above, not all of 21 agricultural product combinations can pass co-integration test within the full sample period. Moreover, significant structural break might exist in co-integration relationship of specific combinations in specific sample period. Nevertheless, considering the comparability of analysis results and the fact that this paper does not focus on price transmission relationship of individual specific agricultural product combination, regression on error correction model is conducted for all combinations in Table 4. As co-integration relationship is sensitive to the selection of sample period, this means that the estimation result of error correction model will also be sensitive to selection of sample period, and this problem will be further analyzed in following text. [^Back]

    [10]. ② It is hard to directly demonstrate the contribution of each above-mentioned cause to co-integration coefficient based on existing data. In addition, the precondition for direct comparison between the two models (maize and rice, and maize and wheat) is that price difference between rice and wheat is not big. Considering the difference in price level among other agricultural products and the difference in lag order of models and other factors, direct comparison among estimated parameters of different models is less meaningful. As the goal of this paper is not to focus on the formation mechanism of price correlation of specific agricultural products, the estimated values of model parameters will not be discussed in following text. [^Back]

    [11]. ① Analysis result of price transmission of specific agricultural product is sensitive to not only sample period selection but also model setting. Therefore, technically, in any sample period, if relevant test supports non-linear co-integration relationship (for example, including structural mutation or threshold co-integration), more advanced error correction model should be used for regression. However, this paper considers sample period sensitivity as a more serious problem. Although more advanced model can increase validity of analysis result of specific agricultural price in specific period, the problem of sample period sensitivity can still be confronted. In contrast, the author finds through estimation that in most cases, a more advanced model will not change basic conclusion reached through common error correction model. [^Back]

    [12]. ② Considering the long production cycle of agricultural products, the shortest sub-sample period length is set as 12 months in this paper. [^Back]

    [13]. ① Another possible cause is that the trading behavior of cross-product hedging in futures market interferes with substitution among agricultural products. [^Back]

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This Article

ISSN:1002-8870

CN: 11-1262/F

Vol , No. 05, Pages 54-71

May 2019

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Article Outline

Abstract

  • 1 Introduction
  • 2 Identification method of anchor product
  • 3 Data
  • 4 Results and discussion
  • 5 Conclusion and implication
  • Footnote

    References