Modelling of Catastrophic Farm Risks Using Sparse Data

V. A. Ogurtsov, M. A. P. M. Asseldonk and R. B. M. Huirne
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V. A. Ogurtsov: Wageningen University
M. A. P. M. Asseldonk: Wageningen University
R. B. M. Huirne: Wageningen University

Chapter Chapter 12 in Handbook of Operations Research in Agriculture and the Agri-Food Industry, 2015, pp 259-275 from Springer

Abstract: Abstract This paper compares alternative ways of conducting a farm risk analysis using sparse data with a special reference to catastrophe events. For this purpose kernel and multivariate normal smoothing procedures are proposed and applied to generate (simulate) the joint distributions of crop yields and prices. The analysis showed that the functional forms chosen to generate the joint distribution substantially impacted the density in the tail of the distribution, although they were parameterised with the same data. The differences in the optimal farm plan (i.e. activity levels) resulting from the optimisation of net farm income, obtained from a utility-efficient programming model, were less profound.

Keywords: Catastrophic risk; Kernel; Normality; Utility-efficient programming; SERF; Arable farmer (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-1-4939-2483-7_12

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DOI: 10.1007/978-1-4939-2483-7_12

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