PASMA

Agricultural Sector Modelling for Austria
PASMA (Positive Agricultural Sector Model for Austria) is a regional optimisation model of the Austrian agricultural sector. It maximises regional agriculture value added, calibrated to observed production patterns using Positive Mathematical Programming. The model distinguishes arable and livestock farm types under conventional and organic systems across NUTS-3 regions, incorporating agri-environmental programme measures. Key input data include administrative data, farm structure surveys, and economic accounts for agriculture. PASMA integrates economic and environmental indicators within a coherent framework, enabling the assessment of agricultural policy reforms on production, income, land use, and environmental effects.

The agricultural sector model PASMA (Positive Agricultural Sector Model for Austria; Schmid & Sinabell, 2003) was developed to estimate the effects of the 2003 CAP reform on agricultural production and selected agricultural and environmental indicators. The model has been continuously improved and expanded since then (e.g. Schmid et al., 2007ab; Kirchner et al.; 2015, Kirchner et al., 2016; Schönhart, et al., 2013, 2014, 2018).

As an important basis for agricultural policy analyses, PASMA depicts the political, natural and structural complexity of the Austrian agricultural sector in great detail, i.e. differentiated according to production activities and income opportunities. Figure 1 provides an overview of the structure and most important components of PASMA. The most important input data include the Integrated Administration and Control System (InVeKoS; Federal Ministry for Agriculture and Forestry, Environment and Water Management, 2017) , the Agricultural Structure Survey (e.g. Statistics Austria, 2022a), the Economic Accounts for Agriculture (e.g. Statistics Austria, 2022b), the estimate of agricultural labour force and standard gross margins (Federal Institute of Agricultural Economics, Rural and Mountain Research, 2025). The input data provide the necessary information to map the resources and production facilities at regional (NUTS-3) level in Austria.

Figure 1: Model structure of the agricultural sector model PASMA

Two farm types (arable and livestock farms) and different farming systems (conventional and organic farming) as well as relevant management measures from the Austrian agri-environmental programme ÖPUL and the support programme for farms in disadvantaged areas (AZ) are mapped in PASMA. However, the detailed mapping of ÖPUL 2023 and the instrument mix after the reform of the Common Agricultural Policy in 2020 (i.e. in the GSP) requires an adjustment in the model structure and input data.

PASMA maximises the regional value added of farms and is calibrated to the observed situation using the Positive Mathematical Programming method (PMP; see Howitt, 1995; Heckelei et al., 2012). The PMP method is basically an extension of linear programming in which a profit-maximising equilibrium (i.e. marginal revenue equals marginal costs) is assumed in the base period. The coefficients of a non-linear target function are derived on the basis of the observed production activities.

PASMA is used to estimate agricultural production, labour, income and environmental indicators for each regional unit. The integration of economic and environmental indicators in a coherent framework is a key strength of PASMA and explains the frequent use of the model for agri-environmental analyses. Recent studies deal with evaluations (Sinabell et al., 2019) , scenario analyses and scenarios of the Austrian agricultural production system (Sinabell et al., 2019) and scenarios on greenhouse gas emission of the agricultural sector (Anderl et al., 2023; Sinabell et al., 2023).

Study
23.06.2025
Scenarios and Sensitivity Analyses on Land Use, Crop and Livestock Production
Finalization: SepSepSepSep 2023202320232023
Contractor project: Environment Agency Austria
Study
20.12.2018
Finalization: DecDecDecDec 2018201820182018
Contractor project: Environment Agency Austria
JEL-Codes: Q11
Study
04.09.2017
Finalization: JunJunJunJun 2017201720172017
Project partner Austrian Institute of Economic Research, University of Natural Resources and Applied Life Sciences, Vienna
Contractor project: Klima- und Energiefonds
JEL-Codes: Q10, Q54
Article in Peer-reviewed Journal
MarMarMarMar 2016201620162016
  • Mathias Kirchner
  • Martin Schönhart
  • Erwin Schmid
Specialist publication: Ecological Economics
Article in Peer-reviewed Journal
JanJanJanJan 2007200720072007
Specialist publication: Ecological Economics
Study
28.09.2015
Finalization: MayMayMayMay 2005200520052005
Contractor project: Environment Agency Austria
Study
28.09.2015
Finalization: AprAprAprApr 2011201120112011
Contractor project: Environment Agency Austria