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Farm diversification indicator

Description

Creation of a farm diversification indicator based on the distribution of three farm resources: land, labor and capital. To measure the degree of diversification per farm and year, the Shannon-Weaver Index for each of the three resource categories is applied. Contrary to former studies which used the Simpson or Gini index, the index will not only account for the richness (number of activities) but also the evenness (distribution of available resources among the activities) of a farm diversification. Using the Shannon index allows for more rare activities to affect the index in a similar way than dominant farm activities. This allows for an understanding of changes in resource patterns that have not been determined yet. Data is protected.

Main data sources to produce the data

Individual FADN data.

Articles

An article is under development.

Temporal and spatial coverage

Spatial coverage: Germany.

Temporal coverage: 2014-2021.

Resolution

Farm level data.

Contact

Contact address: hugo.storm@ilr.uni-bonn.de

Current application: examining field structural change

Description

The structure of agricultural fields changes over time based on institutional and farm economics rationales. These field changes can impact environmental and social outcomes such as biodiversity, farm output, and income. Hence, we employ the geospatial dataset of the German federal state of Lower Saxony from 2012 to 2023 to investigate field structural changes. We investigate changes in the size, shape and number of agricultural fields within defined landscape boundaries over time, the heterogeneity of change across regions and how these relate to change in the number of farms and average farm size. We use mapping and statistical techniques to show the outcomes of the regionally heterogeneous field structural change values and their relationship to farm development variables from various data sources.

Main data sources to produce the data

Data from the Integrated Administration and Control System (IACS), covering the shape and location of plots as well as the crops grown on the plots.

Temporal and spatial coverage

Spatial coverage: Lower Saxony Germany - Federal state of Germany

Temporal coverage: 2012 to 2024

Resolution

Field-level parcel data, which can be aggregated to different administrative units

Data

Possibility of publication of the complete data is still under review.

Contact

Contact address: damilola.aladesuru@ilr.uni-bonn.de

Productivity and output growth (JOS) and fertilizer and pesticides use (SOS)

Approach: Total Factor Productivity - A Flexible Production Function with Endogenous Inputs

Description

Total factor productivity (TFP) is a crucial indicator for investigating the economic consequences of sustainable practices. We analyse output and total factor productivity growth using Farm Accountancy Data Network (FADN) data on Czech cereal farms from 2008 to 2020. Treating pesticides and fertilisers as endogenous inputs, we propose an approach that employs a flexible translog production function in combination with a proxy-variable method. This approach generates robust results that strengthen the evidence base essential for data-driven agricultural policy formulation.

Main data sources to produce the data

Among others

Farm Accountancy Data Network and Eurostat

Article

Čechura, L., Kumbhakar, S., & Žáková Kroupová, Z. (2025). The role of pesticides and fertilizers in Czech cereal output and TFP growth: A flexible production function with endogenous inputs. Food Policy, 136, 102955, https://doi.org/10.1016/j.foodpol.2025.102955

Temporal and spatial coverage

Spatial coverage: Czech Republic.

Temporal coverage: 2008-2020.

Resolution

Farm level data.

Data

The data are available from the Farm Accountancy Data Network – Czech Republic. However, access to these data is restricted as they were used under license. Data can be obtained from the authors with permission from the Institute of Agricultural Economics and Information.