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Ökologischer Betrieb
© BLE, Bonn/Thomas Stephan
Ökologischer Betrieb
Institute of

BW Farm Economics

Risk exposition

The basis of agricultural risk management is the identification of the risks to which farmers are exposed. It is important that this identification is based on facts and figures and is not biased (i.e. overweighted or underweighted) by feelings and emotions. We start by asking ourselves the following fundamental questions: What are the causes of risk? How strongly do the identified risk factors affect arable yields or farm incomes in different regions of Germany? What role do farm characteristics such as size and production focus play?

In our work, we look at market- and weather-based risks that affect crop yields, gross margins and income. Using the national farm accountancy data network, we can provide data-based statements about which types of farms are particularly affected by certain risk factors. The available farm data also allows us to spatially differentiate differences in agricultural risks, and, e.g., estimate the value of historical weather-induced yield losses (estimated losses in Euros per hectare) for regions with higher weather risks.

The analysis of risk exposure helps us to derive recommendations regarding the need for action or adaptation by farmers or policy makers to prevent risks. Only through comprehensive data analyses is it possible to reach conclusions about which risks can have serious consequences for the continued existence of farms and which risk management measures are helpful and necessary. In addition, the prioritization of risks plays a crucial role, as both farmers and policy makers have a limited budget for risk prevention, which should be used in the best possible way. Our goal is to use the information on risk exposure in policy advice, to derive risk management recommendations, and to incorporate and further develop the consideration of risks in agricultural market modelling within the Thünen Model Network.

Selected literature

  1. 0

    Duden C, Nacke C, Offermann F (2024) German yield and area data for 11 crops from 1979 to 2021 at a harmonized spatial resolution of 397 districts. Sci Data 11:95, DOI:10.1038/s41597-024-02951-8

    https://literatur.thuenen.de/digbib_extern/dn067522.pdf

  2. 1

    Schmitt J, Offermann F, Söder M, Frühauf C, Finger R (2022) Extreme weather events cause significant crop yield losses at the farm level in German agriculture. Food Policy 112:102359, DOI:10.1016/j.foodpol.2022.102359

    https://literatur.thuenen.de/digbib_extern/dn065372.pdf

  3. 2

    Söder M, Berg-Mohnicke M, Bittner M, Ernst S, Feike T, Frühauf C, Golla B, Jänicke C, Jorzig C, Leppelt T, Liedtke M, Möller M, Nendel C, Offermann F, Riedesel L, Romanova V, Schmitt J, Schulz S, Seserman D-M, Shawon AR (2022) Klimawandelbedingte Ertragsveränderungen und Flächennutzung (KlimErtrag). Braunschweig: Johann Heinrich von Thünen-Institut, 234 p, Thünen Working Paper 198, DOI:10.3220/WP1659347916000

    https://literatur.thuenen.de/digbib_extern/dn065147.pdf

  4. 3

    Duden C, Offermann F (2020) Income risk of German farms and its drivers [online]. German J Agric Econ 69(2):85-107, zu finden in <https://www.gjae-online.de/articles/income-risk-of-german-farms-and-its-drivers/> [zitiert am 10.06.2020], DOI:10.30430/69.2020.2.85-107

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