基于广义线性模型的水稻种植风险评估
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摘要
农作物风险评估是农业风险管理的前提与基础.为探索科学有效的水稻种植风险评估模型,将水稻种植风险评估过程分为承灾体脆弱性评估和致灾因子危险性评估两个过程,利用广义线性模型解决自然灾害会对水稻产量造成多大程度的损失问题,在产量波动服从布尔分布的假设下,建立起致灾因子(用连续降雨天数、连续低温天数等指标表示)与产量波动之间的线性关系,完成承灾体脆弱性评估;利用天气发生器模型模拟各地区致灾因子发生情况解决自然灾害概率分布的问题,完成致灾因子危险性评估;最终给出风险评估的量化表达.通过黑龙江农垦气象及水稻产量数据的实证分析验证了模型的有效性,并讨论了该模型在保险费率厘定方面的应用.
Crop risk assessment is the premise and basis of agricultural risk management.To explore a scientific and effective rice planting risk assessment model, this paper divides the risk assessment process into two processes: vulnerability and hazard risk, and discusses the frequency of natural disasters and the impact on rice. In this paper, the generalized linear model is used to solve the problem of the loss of crop yield caused by natural disasters.Under the assumption that the yield fluctuates from the Burr distribution, the causative factors(continuous rainfall days, Continuous low temperature days and other indicators that)and the volatility of the linear relationship between production to complete the assessment of vulnerability. Using the weather generator model to simulate the occurrence of disaster risk factors in various regions to solve the problem of natural disaster probability distribution, to complete the hazard risk assessment. Finally, a quantitative expression of the risk assessment is given. This paper verifies the validity of the model through empirical analysis of meteorological and rice yield data in Heilongjiang Land Reclamation, and discusses the application of the model in determining the premium rate.
Crop risk assessment is the premise and basis of agricultural risk management.To explore a scientific and effective rice planting risk assessment model, this paper divides the risk assessment process into two processes: vulnerability and hazard risk, and discusses the frequency of natural disasters and the impact on rice. In this paper, the generalized linear model is used to solve the problem of the loss of crop yield caused by natural disasters.Under the assumption that the yield fluctuates from the Burr distribution, the causative factors(continuous rainfall days, Continuous low temperature days and other indicators that)and the volatility of the linear relationship between production to complete the assessment of vulnerability. Using the weather generator model to simulate the occurrence of disaster risk factors in various regions to solve the problem of natural disaster probability distribution, to complete the hazard risk assessment. Finally, a quantitative expression of the risk assessment is given. This paper verifies the validity of the model through empirical analysis of meteorological and rice yield data in Heilongjiang Land Reclamation, and discusses the application of the model in determining the premium rate.
引文
[1]张峭等.中国农作物生产风险评估及区划理论与实践[M].北京=中国农业科学技术出版社.2013.
[2]徐磊.农业巨灾风险评估模型研究[D].北京=中国农业科学研究院.2012.
[3]HarriA et al.Crop Yield Distributions:A Reconciliation of Previous Research and Statistical Tests for Normality[J].Review of Agricultural Economics,2009,31(1):163-182.
[4]Claassen R,and Just R E.Heterogeneity and distributional form of farm-level yields[J].American Journal of Economics,2011,93(1):144-160.
[5]Marra M C,and Shurle B W.Kansas wheat yield risk measures and aggregation:A meta-analysis approach[J].Journal of Agricultural and Resource Economics,1994,19(1):69-77.
[6]张峭,王克.农作物生产凤险分析的方法和模型[J]+AO农业展望,2007,8:7-10.
[7]李云辉,贺一梅,杨子生.云南金沙江流域因灾减产粮食量分析[J].山地学报,2002,20(増刊):43-48.
[8]徐磊,张蛸.中国农业巨灾凤险评估方法研究[J].中国农业科学,2011,44⑶:1財5_1奶2+
[9]张峭,王克,张希.农作物灾掼凤险的评估方法研究[J].上海农业学报,2010,26(増刊):22-26.
[10]张峭,王克.农作物生产凤险分析的方法和模型[J].农业展望,2007,8:7-10.
[11]张彩平.三参数Burr分布的估计和检验问题[D].上海:华东师范大学,2006.
[12]廖要明,张强,陈德亮.中国天气发生器的降雨模拟[J].地理学报,2004,59(5):689-698.
[13]林小娟.中国降雨特性分析与模拟[D].北京:北京师范大学.2009:7-12.
[14]Irving I.Gringorten.A Stochastic model of the frequency and duration of weather events[J].Journal of Applied Meteorology,2010,5(5):606-624.
[15]Sheldon M.Ross.统计模拟[M]+北京:人民邮电出版社,20〇6.
[16]James E.Hansen and Dennis M.Driscoll.A mathematical model for the generation of hourly temperature[J].Journal of Applied Meteorology,1977,16(9):935-948.
[2]徐磊.农业巨灾风险评估模型研究[D].北京=中国农业科学研究院.2012.
[3]HarriA et al.Crop Yield Distributions:A Reconciliation of Previous Research and Statistical Tests for Normality[J].Review of Agricultural Economics,2009,31(1):163-182.
[4]Claassen R,and Just R E.Heterogeneity and distributional form of farm-level yields[J].American Journal of Economics,2011,93(1):144-160.
[5]Marra M C,and Shurle B W.Kansas wheat yield risk measures and aggregation:A meta-analysis approach[J].Journal of Agricultural and Resource Economics,1994,19(1):69-77.
[6]张峭,王克.农作物生产凤险分析的方法和模型[J]+AO农业展望,2007,8:7-10.
[7]李云辉,贺一梅,杨子生.云南金沙江流域因灾减产粮食量分析[J].山地学报,2002,20(増刊):43-48.
[8]徐磊,张蛸.中国农业巨灾凤险评估方法研究[J].中国农业科学,2011,44⑶:1財5_1奶2+
[9]张峭,王克,张希.农作物灾掼凤险的评估方法研究[J].上海农业学报,2010,26(増刊):22-26.
[10]张峭,王克.农作物生产凤险分析的方法和模型[J].农业展望,2007,8:7-10.
[11]张彩平.三参数Burr分布的估计和检验问题[D].上海:华东师范大学,2006.
[12]廖要明,张强,陈德亮.中国天气发生器的降雨模拟[J].地理学报,2004,59(5):689-698.
[13]林小娟.中国降雨特性分析与模拟[D].北京:北京师范大学.2009:7-12.
[14]Irving I.Gringorten.A Stochastic model of the frequency and duration of weather events[J].Journal of Applied Meteorology,2010,5(5):606-624.
[15]Sheldon M.Ross.统计模拟[M]+北京:人民邮电出版社,20〇6.
[16]James E.Hansen and Dennis M.Driscoll.A mathematical model for the generation of hourly temperature[J].Journal of Applied Meteorology,1977,16(9):935-948.