Wilm Fecke, Jan-Henning Feil and Oliver Musshoff
The purpose of this paper is to empirically investigate the influencing factors of loan demand in agriculture. With the structural changes that agriculture is undergoing and the…
Abstract
Purpose
The purpose of this paper is to empirically investigate the influencing factors of loan demand in agriculture. With the structural changes that agriculture is undergoing and the accordingly higher financing requirements and volumes, the analysis of loan demand in agriculture is of particular interest.
Design/methodology/approach
Detailed actual loan data at farm level, which is provided by a major German development bank for the agricultural sector, is used for the analysis. The data set covers the period from 2010 to 2014 and consists of 68,430 observations. Due to the data structure, an ordinary least square regression is conducted with the loan amount as the dependent variable. Many explanatory variables are included, such as the interest rate, the intended use of the loan, grace periods, the gross value added (GVA) and the business climate index for agriculture.
Findings
Amongst others, the authors find that interest rate, GVA, grace periods and farmers’ business expectations have significant effects on the loan demand in agriculture. According to the results, the interest rate has a significant negative effect, whereas the granted grace periods, the GVA in agriculture and farmers’ business expectations have significant positive effects on the loan demand.
Originality/value
This paper investigates the determinants of loan demand in agriculture in a developed country by using unique and comprehensive data at loan and farm level. Amongst others, elasticities of loan demand in agriculture are determined.
Details
Keywords
Ron Weber, Wilm Fecke, Imke Moeller and Oliver Musshoff
Using cotton yield, and rainfall data from Tajikistan, the purpose of this paper is to investigate the magnitude of weather induced revenue losses in cotton production. Hereby the…
Abstract
Purpose
Using cotton yield, and rainfall data from Tajikistan, the purpose of this paper is to investigate the magnitude of weather induced revenue losses in cotton production. Hereby the authors look at different risk aggregation levels across political regions (meso-level). The authors then design weather index insurance products able to compensate revenue losses identified and analyze their risk reduction potential.
Design/methodology/approach
The authors design different weather insurance products based on put-options on a cumulated precipitation index. The insurance products are modeled for different inter-regional and intra-regional risk aggregation and risk coverage scenarios. In this attempt the authors deal with the common problem of developing countries in which yield data is often only available on an aggregate level, and weather data is only accessible for a low number of weather stations.
Findings
The authors find that it is feasible to design index-based weather insurance products on the meso-level with a considerable risk reduction potential against weather-induced revenue losses in cotton production. Furthermore, the authors find that risk reduction potential increases on the national level the more subregions are considered for the insurance product design. Moreover, risk reduction potential increases if the index insurance product applied is designed to compensate extreme weather events.
Practical implications
The findings suggest that index-based weather insurance products bear a large risk mitigation potential on an aggregate level. Hence, meso-level insurance should be recognized by institutions with a regional exposure to cost-related weather risks as part of their risk-management strategy.
Originality/value
The authors are the first to investigate the potential of weather index insurance for different risk aggregation levels in developing countries.