Weather index‐based insurances for farmers in the North China Plain

Abstract

Purpose -The purpose of this paper is to analyze the extent to which weather index-based insurances can contribute to reducing shortfall risks of revenues of a representative average farm that produces corn or wheat in the North China Plain (NCP). The geographical basis risk is quantified to analyze the spatial dependency of weather patterns between established weather stations in the area and locations where the local weather patterns are unknown. Design/methodology/approach -Data are based on the Statistical Yearbook of China and the Chinese Meteorological Administration. Methods of insurance valuation are burn analysis and index value simulation. Risk reduction is measured non-parametrically and parametrically by the change of the standard deviation and the value at risk of revenues. The geographical basis risk is quantified by setting up a decorrelation function. Findings -Results suggest significant differences in the potential risk reduction between corn and wheat when using insurance based on a precipitation index. The spatial analysis suggests a potential to expand the insurance around a reference weather station up to community level. Research limitations/implications -Findings are limited by a weak database in China and, in particular, by the unavailability of individual farm data. Moreover, the low density of weather stations currently limits the examination of the approach in a broader context. Practical implications -The risk reduction potential of the proposed insurance is encouraging. From a policy point of view, the approach used here can support the adjustment of insurers towards different crops. Originality/value -This paper is believed to be the first that investigates a weather index-based insurance designed for an average farm in the NCP and the quantification of geographical basis risk.

Can Gridded Precipitation Data and Phenological Observations Reduce Basis Risk of Weather Index–Based Insurance?

“…This is of particular relevance for precipitation indices, because the correlation between the index and losses quickly declines with increasing distance (Odening et al 2007;Norton et al 2012). To overcome problems with low densities of weather stations, other authors (Heimfarth and Musshoff 2011;World Bank 2013) suggest either interpolating weather station data to on-farm locations or creating a portfolio of contracts from different stations around the farm. For instance, kriging techniques have been used to estimate on-farm rainfall based on nearby weather stations' data (Paulson et al 2010) and to explain the relationship between rainfall at the two locations (Norton et al 2015).…”

“…Crop production, particularly winter wheat, is an important part of a farm's portfolio in this region (Lower Saxony Ministry of Food, Agriculture, Consumer Protection and Regional Development 2011). The average farm size in the study area is around 60 ha (Heimfarth et al 2012) with podzols and luvisols being predominant soil types. The yield data have been provided by Pelka and Musshoff (2013) in detrended form.…”

“…This monthly accumulation is an often used index in the context of WII for our case study on German wheat production (Heimfarth et al 2012;Pelka and Musshoff 2013).…”

“…The yield data have been provided by Pelka and Musshoff (2013) in detrended form. The detrending to control for technological change conducted by Pelka and Musshoff (2013) was based on linear regressions as motivated by Heimfarth et al (2012). 19 The yield data are summarized in Table 3.…”

Impact of Weather Index Insurance on Groundnut Farmers’ Technical Efficient in Senegal: A Propensity Score Matching Approach

“…2010;Burke, Janvry and Quintero 2010;Burke and al. 2010;Erec and Musshoff, 2011;Mabul et al 2012;Clarke et al 2012;Carter et al, 2014), there is no previous study that investigated its impact on smallholder farmers' technical efficiency in developing countries. Meanwhile, improving farm technical efficiency is an important element of agriculture based growth policies in order to ensure long-term sustainability of agricultural resources, food security and poverty alleviation.…”