国际粮价波动的周期性特征研究
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摘要
我国是世界粮食生产大国也是消费大国,近年来我国粮食的进口量也开始大幅地增长,但国际粮食市场自2000年以来粮价波动程度愈发剧烈,特别是在2008年-2009年快速上涨及回落之后,2011年-2013年又再次快速上涨及回落。国际粮价如此频繁且剧烈的波动引起了社会各界的广泛关注。粮食是国民经济命脉,是人类生产生活的基本必需品,而粮价又是百价之基,在我国其在CPI的权重中高达的1/3以上。从国际粮价波动的周期性特征入手,把握其波动周期的客观规律性,提出相应政策建议来缓和国际粮价周期波动对国内粮价周期波动的相关影响,对于稳定我国国内经济,维护粮食产品安全,改善国计民生,具有重要的意义。
     国际粮价波动中呈现出的周期性特征是文章研究的重点内容,采取以经济学理论为基础,理论分析与实证研究相结合的方法,主要通过实证分析来分辨国际粮价波动周期的基本特征及主要周期和次要周期。在周期特征的研究中,第三章首先界定了粮食的概念和相关数理模型得到国际粮价相关数据;其次,使用EVIEWS7.0工具对国际粮价时间序列进行H-P滤波分解,并对分解所得的周期成分进行简单周期“波峰-波峰”划分,通过波动高度、波动深度、波动幅度、平均位势、扩张时长、标准差和扩张收缩程度等描述性统计变量分析了不同周期的周期特征。
     在对周期的分解上,突破了通常研究国际粮价波动特征的时间序列分析,采用频域分析,即谱分析的方法,而非一般研究中使用的时间序列分析方法,将国际粮价周期序列从时域角度转换到频域角度进行研究,这种方法的优势在于,时域分析不能提取时间序列中不同周期信号对整体周期波动的贡献程度大小,只能通过简单的判断来实现周期的划分,无法确定主要的周期成分和次要周期成分,这对国际粮价波动未来趋势的判断和预测无法进行有效推断。文章进行的频域分析,采用了谐波分析与功率谱估计分析相结合的方法,在国际粮价周期序列主周期的判断上进行了有效的对比分析,加强了分析结论的科学性和稳健性。谱分析的结果表明,在国际粮价周期序列中,存在着一个16.5年左右的主周期,一个7.5年左右的次周期,以及一个3.5年左右的次周期。在此基础上通过使用固定带宽的B-P带通滤波对以16.5年为中心、7.5年为中心和3.5年为中心的国际粮价周期序列进行带通滤波处理,得到的结果显示,国际粮价在2014年应该会呈现出小幅回落的态势,之后中短期内将有所上涨,长期内应该会稳定回落。
     第四章首先通过理论分析,得出影响国际粮价周期波动的主要因素,从供给和需求的角度分别对这些影响因素与国际粮价周期波动之间的相关性进行了探讨。其中,重点分析了世界人口变化、全球经济发展、生物能源发展、美元汇率、气候变化、粮食作物耕地面积、粮食作物库存量以及能源价格和粮食生产成本对国际粮价周期波动的影响。在实证分析部分,结合数据可获得性,采用了以上因素中具有代表性的相关指标:全球二氧化碳排放量(C02)、国际石油平均价格(COA)、世界粮食作物耕地面积(GL)、世界粮食作物期末库存量(GS)、美元广义指数(USDIB),通过VAR模型研究这些影响因素与国际粮价(IGP)周期波动之间的相互关系。通过协整分析发现,上述变量之间存在长期协整关系,建立VEC模型,检验其稳定性,使用脉冲响应函数和方差分解函数分别检验IGP对影响其周期波动的五个重要因素的冲击反应。结果发现CO2、COA对IGP长期内有持续的正向冲击,GL、GS长期内对IGP有持续的负向冲击,USDIB对IGP短期内有负向冲击,长期呈现出正向冲击。方差分解结果显示,CO2、GS在IGP的变动中起到的解释力度较大,USDI、COAIGP的变动中起到的解释力度相对较小,GLIGP的变动中起到的解释力度最弱。
     第五章首先分析了国际粮价周期波动对国内粮价周期波动的传导途径,以及国内粮价周期波动对我国经济发展各方面的传导途径。接着同样采用频域分析方法,通过交叉谱分析的方法研究国际粮价与国内粮价的交叉谱分析各类相关指标,国际粮价与国内粮价的互振幅谱、凝聚谱以及相位谱,发现国际粮价波动周期在考察期内是明显领先于国内粮价波动周期的,其中在16.67年的长周期上,国际粮价波动领先国内粮价波动约1.74年,在7.14年的中周期上,国际粮价波动领先国内粮价波动约1.48年,在3.33年的短周期中,国际粮价波动领先国内粮价波动约4.6个月。
     最后,文章针对上述实证分析的结果,提出应对国际粮价周期性波动的相关政策建议:稳定国内粮食生产,力主国内供求平衡;加强粮食消费市场监控,稳定居民生活水平;稳定农工业生产资料价格水平,改善下游产业投资就业形势。
China is a large country of grain production and consumption. The qualities of production and consumption in China are very large. In recent years, international grain prices (short for IGP) fluctuate fiercely because of grain demand and supply factors. Especially in2008, the IGP rises into a highest peak; IGP has aroused widespread concern in the community. Grain is the lifeline of the national economy, and also is the basic necessities of human life. The price of grain is a price foundation in national economy; it's up to the weight in CPI above1/3. With China's economic development and the accelerated process of industrialization, the demand for grain imports and the degree of dependence on foreign trade are increasing. At the same time, the grain problem becomes another important concern in China, in addition to energy and finance. It also relates the entire country's economic operation. Study on the cyclical characteristics of fluctuation of international grain price, find suitable ways to protect the reference of IGP to domestic grain price (short for CGP), has significant meanings to hold economic system steady and improve the people's livelihood.
     The most important part of this paper is the study of cyclical characteristics of fluctuation of IGP. So, in this paper we use spectrum analysis replaces the analysis of time series to change the time series to frequency series. The method of spectrum analysis is better than time series analysis, because it can change the series into frequency, and then we can compare which cycle is the most important one for comparing the spectral density. The result of spectrum analysis shows that the series of IGPCYC has a main cycle about16.5years and a minor cycle about7.5and3.5years. So we can use the B-P filter to filter the unused cycles to get the fluctuation trend of IGP. We can find that in2014the IGP will reduce slightly, in the long term, the IGP will reduce and in middle and short term, it will rise up.
     In chapter4, we use theoretical analysis to decide the main factors affecting the fluctuation of IGP. We classify the factors in supply and demand. We focus on these factors:world population change, the development of global economy, the development of bioenergy, the change of the dollar exchange rate, the change of climate, the world grain cultivated area, the world grain stocks, the change of energy prices and the cost of grain production. In empirical part, we choose the world grain cultivated area(GL), the dollar's broad trade-weighted index(USDIB), the emissions of CO2in the world(CO2), the ending stock quantity of grain in the world(GS), and the international oil prices to average(COA) as the main indexes. Use VAR model to study the long-run co integration relationships between these factors to IGP. The results show that GL, GS has a negative impulse to IGP; COA, CO2, USDIB has a positive impulse to IGP. Variance decomposition result shows that GS and CO2have the greater explanation to IGP, USDIB and COA have a small explanation to IGP, GL has a little explanation to IGP.
     In chapter5, we first analyze the transmission mechanism of IGP to our national economy. Then use cross spectrum analysis to study the relationships of IGP and CGP. The main indexes we use are cross amplitude spectrum, coherence spectrum, and phase spectrum. The results show that the fluctuation cycle of IGP is short for CGP. Most numbers of phase spectrum are above zero, which means the fluctuation of IGP can change the fluctuation of CGP. In the cycle of16.67years, the fluctuation cycle of IGP short for1.74years to CGP. In the cycle of7.14years, the fluctuation cycle of IGP short for1.48years to CGP. In the cycle of3.33years, the fluctuation cycle of IGP short for4.6months.
     Finally, according to the empirical analysis results, we give advices mainly on:Proposed to stabilize domestic food production, domestic supply and demand balance advocated; strengthen market monitoring food consumption, stable living standards; stabilize the prices of agricultural and industrial production levels, suggestions to improve the employment situation in terms of investment in the downstream industry.
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