毕业论文外文翻译-农业风险——研究农作物产量分布和农作物保险.doc

《毕业论文外文翻译-农业风险——研究农作物产量分布和农作物保险.doc》由会员分享，可在线阅读，更多相关《毕业论文外文翻译-农业风险——研究农作物产量分布和农作物保险.doc（12页珍藏版）》请在淘文阁 - 分享文档赚钱的网站上搜索。

1、 Risk in Agriculture A Study of Crop Yield Distributions and Crop Insurance. IntroductionAgriculture is the provider of food security and is important to the economy of any country. According to the Food and Agricultural Organization, “Food security exists when all people, at all times, have access

2、to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life.” Food security is a major determinant of national security and self sufficiency in food production and is vital for any country.In India, agriculture and allied sectors employ abo

3、ut 60% of the total work force and account for 25% of the total GDP of the country. Since 1950, continuous improvements have occurred in irrigation, technology, application of modern agricultural practices, and availability of agricultural credit. This has been called the “green revolution” and has

4、resulted in development of high yielding varieties. These improvements have led to significant increase in crop yield per unit area. However, in comparison to other countries, the average yield in India is still low and is equal to 30% to 50% of the highest average yield in the world.(Wikipedia)In t

5、he US, agriculture has played an important role in the early years but its share of GDP and number of people employed has continuously decreased. According to the data compiled by the economic research service of the United States Department of Agriculture (USDA), in 1930 ,the agriculture sector emp

6、loyed 21.5%of the total work force in the US and agriculture GDP accounted for 7.7%of the total GDP of the country. But, in the year 2000, 1.9%of the total work force was employed in agriculture. In 2002, GDP of agriculture was just 0.7% of the total GDP of US (Wikipedia)Changes in commodity prices

7、in an important factor influencing the share of agriculture associated with GDP. The prices of agricultural commodities have increased over time; however the share of agriculture as part of GDP has decreased because of the higher production of goods and services in other sectors.Agriculture is a bus

8、iness in unique. Crop production is dependent on many climatic, geographical, biological, political and economic factors that are mostly independent of one another, These multiple factors introduce risk, The efficient management of these risks is imperative for the successful agricultural and consis

9、tent output of food.A. Concept of Risk in Agriculture:The Economic Research Service of the United States department of agriculture describes five categories of risks in agriculture.(a) Production risk: The quality and quantity of the commodities produced is affected by uncertainties associated with

10、the biological growth of the crops. These uncertainties can be caused by weather patterns, pest and disease incidence, and usage of various inputs like seeds, fertilizers and pesticides.(b) Price of market risk: This risk derives from the fluctuations in prices that the producers receives for the co

11、mmodities along with the prices paid by the farmer for inputs which will increase the cost of production.(c) Financial risk: This refers to the interest cost of the capital that the farmer invests in the production process. Availability of credit and fluctuations in the interest rates contribute to

12、the risk.(d) Institutional risk: Government regulations dealing with subsidies, export and import regulations of commodities, tax laws, chemical usage and environment regulations impose certain amount of risk on agribusiness.(e) Human or personal risk: This refers to the health risks associated with

13、 usage of agricultural inputs like chemicals, fertilizers and agricultural machinery that create certain personal risks to the farmers engaged in agricultural production. As evident from this categorization, agricultural risk primarily arises from a probability of adverse effects like fluctuations i

14、n weather conditions, crop failures because diseases and pests, difficulties in planning of harvest operations, and factors like price volatility and unexpected changes in global and local trade policies, these adverse situations result in disruptions and difficulties for agribusiness operations. Ef

15、fective risk management tools are necessary to estimate the probability of such unfavorable situations and to minimize the consequences. Accurate and reliable information about historical crop yields is, thus, vital for decisions relating to agricultural risk management.Historical crop yield informa

16、tion is also important for the supply chain operations of companies engaged in industries that use agricultural produce as raw material. Livestock, food, animal feed, chemical, poultry, fertilizer, pesticide, seed, paper and many other industries use agricultural products as ingredients in their pro

17、duction processes. An accurate estimate of crop sizes and risk helps these companies in planning supply chain decisions like production scheduling, raw material procurement, and inventory management, Businesses such as seed, fertilizer, agrochemical, and agricultural machinery industries plan produc

18、tion and marketing activities based on crop production estimates.Yield information also influenced price movements in commodity markets. Reliable estimates provide stability to the markets, help in establishing an orderly market for buyers and sellers, and in establishing futures markets for agricul

19、tural commodities. Crop size and commodity production information has a direct influence on policies for international trade in grains and other commodities. Important funding agencies, such as the IMF and the World Bank use crop production data and yield to make decisions about loans and support pr

20、ograms involving governments in the third world, Public agencies make policies dealing with agricultural subsidies, incentive and crop support programs, crop insurance, procurement, stock management, and distribution of grains based on the production estimates of crop size.However, it is observed th

21、at estimates of crop size, production and yield suffer from several important short comings,(a) In developing countries like India, crop estimates are largely a product of subjective reporting of crop area and yield.(b) In most countries, estimates are available only for major commodities like rice,

22、 wheat, maize, sugarcane, soybeans, and other commercially traded crops, Reliable estimates are difficult to obtain for fruit and vegetable crops, millets, and crops grown in relatively small acreages.(c) Estimates are available only at national and state level. Regional or county level forecasts ar

23、e rarely available.(d) Often conflicting figures are reported. In some instances more than one national agency issues crop production forecasts.Given this background, the primary objective of this thesis is to examine some of the assumptions used in crop size estimation. Further, the impact of these

24、 assumptions on risk management methods like crop insurance is evaluated.The next section describes the assumptions and crops examined in this study. Research Question and MethodologyHistorical yield is an important part of risk management and crop forecasting. The majority of risk management proced

25、ures used in agriculture assumes that yield is normally distributed within a statistical population and normally distributed for a sample within a crop year. This thesis examines the validity of the hypothesis that crop yields are normally distributed and analyses the importance of this hypothesis o

26、n crop insurance and agricultural supply chain decisions.A. A SuppositionThe null hypothesis is defined as “In India, historical crop yields for Sugarcane and Soybeans are normally distributed for a statistical population and are normally distributed for a sample within a crop year.”B. Importance of

27、 the Null Hypothesis in Agriculture Based on the central limit theorem, most agricultural studies assume that crop yields are normally distributed. The assumption of normality or non-normality affects the estimation of probabilities for the severity and occurrence of yield short falls and surplus pr

28、oduction. The assumption of normality attributes equal probabilities of high and low historical yields for a crop. It should be noted that crop yields can exhibit extreme variability caused by weather conditions, geological qualities of the soils, biological and genetic capabilities of the crop vari

29、eties grown and applications of inputs like fertilizers and pesticides. Thus the likelihood of low yields and high yields may or may not be equal, Assuming normal distribution of yields and ignoring skew ness may result in under estimation or over estimation of the likely yields and will result in a

30、n inaccurate estimate of risk.Understanding of the likelihood of yields is an important determinant of crop insurance premia. It is also critical for farm management decisions. Farmers use historical yield data to make product mix decisions, and also to determine the risk of crop loss. Thus this nul

31、l hypothesis is of great importance and influences many facets of agricultural supply chain ranging from farm operations to the establishment of insurance premiumsC. Methodology For examining the null hypothesis and its importance in crop insurance, an extensive literature survey was conducted. Rese

32、arch papers in journals like American Journal of Agricultural Economics, Canadian Journal of Agricultural Economics, Agribusiness, and North Central Journal of Agricultural Economics were reviewed to analyze the findings of various researchers working in the general area of frequency distributions f

33、or historical crop yields. Important observations from the literature are presented in Section 3.0.In addition to the literature survey, a quantitative analysis of actual yields was considered to test the null hypothesis. This appears in Section 5.0.As part of this testing, data on historical crop y

34、ields for sugarcane and soybeans were collected from India for analysis. Data pertaining to the yields for the entire country and district wise data for Madhya Pradesh and Maharashtra states make up the data set used for testing the assumption of normality. Sugarcane and Soybeans crops were selected

35、 for data collection and analysis because of their economic importance to Indias economy. A brief description of crops is provided below.(a) SugarcaneAccording to the FAO commodity reports, India is the second biggest producer of sugarcane in the would after Brazil with annual production of 244,800,

36、000 metric tones of Sugarcane in the year 2004,The USA is the 10th largest producer with an annual production of 27,501,310 metric tons, Sugarcane is used for producing different types of Sugar and Molasses. The products and by-products obtained from sugarcane are important raw materials in the food

37、 processing and chemical industries. The importance of Sugarcane is increasing because of its new uses in technologies like ethanol production for automobile fuel. Several countries such as India and Brazil have substantially reduced petroleum imports through the production of ethanol. (b) SoybeansA

38、ccording to the FAO commodity repots. Soybeans are an important crop in the USA, the biggest producer of soybeans in the world with an annual production of 85,740,952 metric tones in 2004; India is the 5th largest producer of soybeans in the world with an annual production of 7,000,000 metric tones

39、in 2004. The economic importance of the Soybean is primarily in the feed and food industries. Soy meal is used in animal feeds because of its high protein content.Derivatives or ingredients of soybeans are used in many manufactured foods. Tofu, miso, soy drinks and other food items are prepared from

40、 soybeans, Soy meal is used in animal feeds because of its high protein content. Before discussing the results of the statistical tests for normality, the nest section puts forth an intensive look at the literature associated with probability distributions of historical yield.Source：http:/escholarsh

41、ip.org/uc/item/5609x12n农业风险研究农作物产量分布和农作物保险1 引言农业是粮食安全的提供者，对任何一个国家的经济都是很重要的。根据联合国粮食及农业组织的报告称：“所有的人在食品安全时，都能获得足够的、安全的和有营养的食物来满足他们的饮食需要。”粮食安全是国家安全的决定因素，自给自足的粮食生产对于任何一个国家都是至关重要的。在印度，农业和相关产业的雇佣劳动力约占劳动力总数的60，占该国GDP总量的25。自1950年以来，印度在灌溉技术、应用现代农业实践、农业信贷和可用性等方面不断改进和提高，创新发展了高产品种，这被称为“绿色革命”。这些改进增加作物单位面积产量。然而，与其

42、他国家相比，印度的平均收益率仍低，它等于世界上最高的平均收益率的3050 (维基百科)。美国农业在初期发挥了重要作用，根据由美国农业部经济研究局（USDA）编制的数据显示：农业对GDP贡献和从事农业人口数量的比重不断下降。1930年，农业部门雇佣了21.5的劳动力总数创造的农业总产值占全国GDP总量的7.7。但是，在2000年，从事农业人口数量为总劳动力的1.9。2002年，农业国内生产总值只占美国国内生产总值的0.7（维基百科）。影响农业占GDP份额的一个重要因素是商品价格的变化。农业大宗商品价格随时间增加，然而农业作为GDP的一部分的比例减少了，因为转向生产其他领域价格更高的商品和服务。农

43、业是独特的产业。农作物生长依赖于许多气候、地理、生物、政治和经济因素。它们之间是相互独立的。这些因素引入的不同风险，而风险的有效管理是农业繁荣和粮食产量粮稳定的必要条件。1.1 农业风险的概念美国农业部经济研究局描述了五类在农业中的风险：1.1.1 生产风险生产的商品的数量和质量是由与农作物的生物生长相关的不确定性因素的影响。这些不确定性因素可以是天气、害虫、疾病的发病率和使用各种输入像种子，肥料和杀虫剂等引起的。1.1.2 市场价格风险这种风险来源于的生产商随着商品价格的波动以及农民的投入的资本变化将会增加生产成本。1.1.3 财务风险这是指资本的利息成本，农民在生产过程中进行投资、信贷受到

44、利率波动导致的风险。1.1.4 机构风险政府制定处理补贴，化学物质的使用，大宗商品的进出口法规，税收法律和环境法规对农业实施一定的风险。1.1.5 人类或个人风险这涉及健康风险是指与农业投入的化学品、化肥和农业机械，农民从事农业生产过程中创造一定的个人风险。从这个分类，农业风险主要来自不确定性因素的不利影响，如天气条件下的波动，作物歉收；由于病虫害，在收获作业规划的困难；如价格波动和全球和当地的贸易政策和意想不到的变化的因素，这些不利的情况下导致农业经营的中断和困难。根据准确可靠的历史作物产量信息，估计这些风险的概率，选择有效的风险管理工具，从而使损失最小化。因此，进行农业风险管理是至关重要的

45、。根据历史的农作物产量信息能为从事行业使用的农产品为原料的企业供应链运作提供了重要的帮助。畜牧业、食品、饲料、化工、化肥、农药、家禽、种子、纸张和许多其他行业使用的农产品在生产配料过程中，农作物的产量和风险的精确估计，帮助这些公司在规划供应链的决策，如生产计划、原材料采购、库存管理；像种子、肥料、农药和农业机械行业的企业，生产计划和营销活动基于农作物产量预测。农作物产量信息也影响商品市场价格的变动。可靠的估计能够稳定的市场，有助于建立买家和卖家的一个有序的市场，而在农产品期货市场的建立。产量规模和商品生产信息直接影响粮食和其它大宗商品的国际贸易政策。国际货币基金组织和世界银行利等重要的资助机构

46、是利用农作物生产数据和产量进行贷款，在涉及第三世界国家的政府支持项目的决策、公共机构处理农业补贴政策、激励和农作物的支持项目、农作物保险、采购、库存管理等是根据农作物的产量规模、产量分布估计。然而，它指出，估计农作物产量规模，有几个重要的缺点：第一是在像印度这样的发展中国家，农作物估计的仅仅是主要作物的种植面积和产量规模。第二是在大多数国家，农作物估计只是主要商品如大米、小麦、玉米、甘蔗、大豆和其他商业交易的农作物，像水果和蔬菜，小米和相对小面积种植的作物的可靠估计是很难获得的。第三是估计只有在国家和省级，县级区域或乡镇区域预测很少。第四是报道往往是相互矛盾的数据，在某些情况下，地区作物产量预

47、测超过国家机构预测。在此背景下，使用的一些农作物规模估计假设为本文在研究主要目的服务。此外，在这些假设下，使用风险管理方法评估农作物保险的影响。下一节描述了本研究的假设和农作物。2 问题与方法历史收益是风险管理和农作物产量预测的重要组成部分。农业生产中使用的风险管理程序是通常假定产量分布在一个人口统计和一个农作物年度内的样本。本文探讨的假设是农作物产量分布的有效性对农业保险和农业供应链决策重要性，以及对这一假设的重要性分析。2.1 一个假设零假设是“印度历史的定义，甘蔗和大豆作物产量分布在一个人口统计和一个农作物年度内的样本。”2.2 重视农业的零假设基于中心极限定理，大多数农业研究是假设农作

48、物产量正态分布。正态或非正态农作物产量假设的概率偏差估计影响生产不足和过剩的。我们可以假设农作物正常产量的高低与农作物的历史产量的概率相等。应当指出的是，农作物产量可以表现出极端的天气条件变化，土壤的地质特征，对农作物品种和输入，如化肥和杀虫剂应用生物学和基因等所造成的。因此，考虑农作物产量的低收益率和高收益率是否相等出现可能性，我们可以假设农作物产量收益率正态分布的偏度和忽视这种可能对农作物产量不准确的估计的风险。农作物保险溢价的重要决定因素是产生的这种不确定性因素的可能性的理解。这也是农场管理决策的关键。农民利用历史产量数据进行产品组合决策，并确定农作物损失的风险。因此，零假设的重要性在于

49、影响农产品供应链，从而建立农场经营多方面、多层次的的保险费。2.3 方法为检验零假设及其在农作物保险的重要性，本人对大量的文献进行了调查。期刊里像美国农业经济学杂志上的研究论文，加拿大的农业经济，农业学报，北部和中部的农业经济学杂志进行了综述分析各种研究人员研究成果，从中发现的历史的农作物产量频率总面积分布情况，在第3节考察其文学的重要性。除了文献调查，实际农作物产量的定量分析是为了检验的零假设。这从第5节开始介绍，作为这个测试的一部分，根据从印度收集甘蔗和大豆历史的农作物产量数据分析。为测试的假设正确性，应该选择甘蔗和大豆农作物对印度经济有重要性的数据，所以从中选取整个国家和地区的产量的数据和中央邦和马哈拉施特拉州的数据组成的数据收集和分析。下面对农作物作一个简短的描述：2.3.1 甘蔗根据联合国粮农组织的报告，印度的是甘蔗的第二大生产者，在2004年度的生产了244800000吨