FARMDYN - a dynamic mixed integer bio-economic farm scale model
FARMDYN provides a flexible, modular template to simulate farms with different branches (dairy, mother cows, beef fattening, pig fattening, piglet production, arable farming, biogas plants). Main characteristics of the model are:
- Fully dynamic, simulations typically cover several decades, alternatively comparative-static or short run version
- Integer variables capture indivisibilities in investments (machinery, buildings) and labour use
- Selected farm management decisions (e.g. feeding, manure management, labour use) depicted with a sub-annual temporal resolution, partially bi-weekly
- Deterministic or stochastic programming version. The latter treats all variables as state dependent, allows for sceneario tree reduction and covers different risk measures (value at risk, MOTAD ...)
- Farm labour, machinery and stable use are modelled in rich detail
- Arable cropping can be differentiated by tillage type and intensity
- For dairy farming, the model distinguishes several herds by number of lactations and lactation phase
- Beef fattening can be depcited in several phases, linked to different grazing options
- The machinery park is available in different mechanization levels
- Detail in grassland management (number of cuts, basles/silo/hay etc.)
- Highly differentiated modules for nitrogen fate, while covering German legislation on fertilizer use
- A range of economic, social and environmental indicators
The model is currently parameterized for German conditions using highly detailed farm planning data provided by KTBL in combination with farm structural statistics. It offers a complementary approach to other farm scale models used in the institute such as the farm group models integrated in CAPRI or FADN based farm-scale progamming models which both are comparative-static, calibrated against observed farm programs with Positive Mathematical Programming while being far less detailed with regard to technology, and not comprising explicit investement decisions.
The model is realized in GAMS, solved with the industry MIP solver CPLEX, linked to a Graphical User Interface realized in GGIG and hosted on a Software Versioning System. Design of experiments, building on R routines directly called from GAMS, can be used in combination with farm structural statistics to systematic sensitivity analysis by simulating different farm realizations (assets, farm branches) and boundary conditions such as input and output prices or emisisons ceilings using a computing server to solve several instances in parallel. That approach has e.g. been used to estimate a statistical meta model for Marginal Abatement Costs of Green House Gases from dairy farms. Code development and testing follows agreed upon guidelines.
The application and extension of FARMDYN is part of several ongoing research activities at ILR, in cooperation with international and national partners.
FARMDYN is used in the H2020 project MIND-STEP Modelling Individual Decisions to Support the European Policies Related to Agriculture , 2019-2023) by the team in Bonn and a team at WUR, Wageningen, to assess impacts of different policies and to inform a meta-modelling approach to be integrated in Agent Based Models.
FARMDYN is used in the H2020 project LIFT (Low-Input Farming and Territories - Integrating knowledge for improving ecosystem-based farming, 2018-2022) by the team in Bonn and a team at INRA, Rennes, to compare different farming systems with regard to sustainability indicators.
The FARMDYN team in Bonn and a group at INRA, Clermont-Ferrand merge their detailed farm scale models in the context of the project SustainBeef (Co-definition and evaluation of SUSTAINable BEEF farming systems based on resources non edible by humans, 2017-2020). For FARMDYN, that will mean more detail for grass management and a better representation of beef cattle systems, as well as a parameterization for several case studies in Germany, France, Italy and Ireland.
The project "Modeling structural change and agricultural nutrient flows across scales in regions of North Rhine-Westphalia", 2016-2019, financed by MKULNV (Ministry for environment and agriculture, state of North Rhine-Westphalia) analyzed nutrient exchanges between farms in regions of North Rhine-Westphalia based on the combination of FARMDYN with bio-physical and agent based modeling. The project was carried out by the Economic Modeling group and chair of Resource and Environmental Economics at ILR and the Institute of Crop Science and Resource Conservation (2016-2018).
In the project Understanding spatial interactions and structural change in the dairy production chain with a dynamic regional Agent Based Model covering dairy farms and dairy processing, 2015-2018, financed by the German Science Foundation DFG, dual profit functions for different farming systems were estimated from FARMDYN simulations to source an Agent Based Model (2015-2018).
The original model version was developed in the project "The relation between indicators for the crediting of emission rights and abatement costs - a systematic modeling approach for dairy farms", financed by the German Science Foundation and carried out by Karin Holm-Müller, Wolfgang Britz, Bernd Lengers and David Schäfer. In the context of the pdh-thesis of Johanna Budde, a first version of the pig module was developed (2012-2013).
The detailed model documentation is available as a Website and as printable PDF:
The documentation refers to a stable release of FARMDYN which represents a properly tested and documented version of the model (launched in September 2016, model revision 500):
Britz W., Lengers, B,.Kuhn, T. and Schäfer, D. (2014): A highly detailed template model for dynamic optimization of farms - FARMDYN, University of Bonn, Institute for Food and Resource Economics, Version September 2016, 147 pages.
FARMDYN contains several features that are currently developed (flagged in documentation as prototype) or not used anymore (flagged as deprecated). These features have not been subject to the intensive testing for the stable release. They are only visible in the developer mode of FARMDYN and listed here.
- Till Kuhn, work on fertilization, related environmental indicators and regulations such as the German Fertilizer Directive, link to crop growth models
- David Schäfer, biogas module, improved pig module, link to ABM
- Christoph Pahmeyer, grassland management, beef fattening
- Lennart Kokemohr, economic, social and environmental indicators
- Julia Heinreichs, production systems comparisons such as organic against conventional farming
- Wolfgang Britz, overall model design, solution algorithm, interface, stochastic programming extension, bi-level programming based calibration
- Bernd Lengers (2011-2014), main contributor of original model version, GHG indicators
- Johanna Budde (2012-2013), first version of pig module
Kuhn, T., Enders, A., Gaiser, T., Schäfer, D., Srivastava, A., Britz, W. (2019): Coupling crop and bio-economic farm modelling to evaluate the revised fertilization regulations in Germany, Agricultural Systems, Link.
Kuhn, T., Schäfer, D., Holm-Müller, K., Britz, W. (2019): On-farm compliance costs with the EU-Nitrates Directive: A modelling approach for specialized livestock production in northwest Germany, Agricultural Systems 173: 233-243, Link.
Mosnier, C., Britz, W., Julliere, T., De Cara, S., Jayet, P.-A., Havlik, P., Frank, S., Mosnier, A. (2019): Greenhouse gas abatement strategies and costs in French dairy production, Journal of Cleaner Production 236, Link.
Schäfer, D., Britz, W., Kuhn, T. (2017): Flexible Load of Existing Biogas Plants: A Viable Option to Reduce Environmental Externalities and to Provide Demand-driven Electricity?, German Journal of Agricultural Economics 66(2): 109-123, Link.
Lengers, B., Britz, W., Holm-Müller, K. (2014): What drives marginal abatement costs of greenhouse gases on dairy farms? A meta-modeling approach , Journal of Agricultural Economics 65(3):579–599 , Link.
Lengers, B., Schiefler, I.& W. Büscher (2013): A comparison of emission calculations using different modeled indicators with 1-year online measurements. Journal of Environmental Monitoring and Assessment, 185:9751-9762. doi:10.1007/s10661-013-3288-y
Lengers, B., Britz, W. and Holm-Müller, K. (2013): Comparison of GHG-emission indicators for dairy farms with respect to induced abatement costs, accuracy and feasibility, Applied Economic Perspectives and Policy, 35(3):451-475. doi:10.1093/aepp/ppt013
Lengers, B. and Britz,W. (2012): The choice of emission indicators in environmental policy design: an analysis of GHG abatement in different dairy farms based on a bio-economic model approach. Review of Agricultural and Environmental Studies, 93(2), 117-144.
Contributions to conferences and lecture series:
Jouan, J., Heinrichs, J., Britz, W., Pahmeyer, C. (2019): Legume production challenged by European policy coherence: a case-study approach from French and German dairy farms, selected paper presented at the 172nd EAAE seminar: „Agricultural policy for the environment or envrionmental policy for agriculture“, Brussels (Belgium), 28-29th May 2019, Link.
Kuhn, T., Schäfer, D., Britz, W. (2017): Estimating impacts of the revised German fertilizer ordinance on manure transport flows within North Rhine-Westphalia, poster presented at the EAAE XVth Congress, Parma (Italy).
Schäfer, D., Britz, W. (2017): Estimating impacts of the revised German fertilizer ordinance on manure transport flows within North Rhine-Westphalia, poster presented at the EAAE XVth Congress, Parma (Italy).
Seidel, C., Britz, W. (2017): Can we derive plausible land rents based on Mathematical Programming? A critical assessment of a dual profit function estimation from simulated farm programs, selected paper presented at the EAAE XVth Congress, Parma (Italy).
Schäfer, D., Seidel, C., Britz, W. (2016): Estimating Dual Profit Functions to Depict Farmer Behavior in Agent-Based Models – a Meta-Modelling Approach, poster presented at the 56th Annual Conference of the German Association of Agricultural Economists (GEWISOLA), Bonn, 28-30 September 2016.
Remble, A., Britz, W., Keeney, R. (2013): Farm Level Tradeoffs in the Regulation of Greenhouse Gas Emissions, selected paper presented at the Agricultural and Applied Economics Association, 2013 Annual Meeting, August 4-6, 2013, Washington, D.C (USA).
Lengers, B., Britz, W. & K. Holm-Müller (2013): What drives marginal abatement costs of greenhouse gases on dairy farms -a meta-modeling approach. Paper presented at the 2012 AURÖ-Workshop, Frankfurt (Oder), Germany, February 18-19.
Britz, W. and Lengers, B. (2012):
Abatement options for GHG emissions in a dynamic bio-economic model for dairy farms - DAIRYDYN -. Presentation contributed to the CIDRe lecture series “modeling across scales and disciplines”. University of Bonn, 09.10.2012, Bonn. Download
Lengers, B. and Britz, W. (2011):
Farm specific marginal abatement costs for dairy GHG emissions which base upon different emission indicators - a bio-economic model approach , selected paper presented at the 2011 EAAE PhD Workshop, April 27-29, 2011, Nitra (Slovak Republic)
Discussion and technical papers:
Lengers, B., Britz, W. and Holm-Müller, K. (2013): Trade-off of feasibility against accuracy and cost efficiency in choosing indicators for the abatement of GHG-emissions in dairy farming, Discussion Paper 2013: Download
Lengers, B.(2012): Construction of different GHG accounting schemes for approximation of dairy farm emissions. Technical paper referring to DFG-project HO 3780/2-1. Download
Lengers, B. (2012): Up to date relevant GHG abatement options in German agricultural dairy production systems. Technical Paper referring to DFG-project HO 3780/2-1. Institute for Food and Resource Economics, University of Bonn. Download
Lengers, B. (2011): GHG survey of German agriculture -specific view on dairy production systems. Technical paper referring to DFG-project HO 3780/2-1. Download
Last updated: Wednesday, November 13, 2019
- Contribution to DFG Excellence cluster Phenorob, 2020-2024
- New H2020 research project MINDSTEP, 2019-2023
- New BMBF research project BEST, 2019-2022
- New BioSC research project Transform2Bio, 2019-2022
- GTAP research fellow award for Wolfgang Britz
- Aus unserer Forschung: Oekonomische und oekologische Bewertung eines Glyphosatverzichts am Beispiel der Silomaisproduktion in Nordrhein-Westfalen
- Aus unserer Forschung: Effiziente Politikmassnahmen zur Foerderung von Kurzumtriebsplantagen
- Coupling crop and bio-economic farm modelling to evaluate the revised fertilization regulations in Germany (2019) Kuhn, T., Enders, A., Gaiser, T., Schäfer, D., Srivastava, A., Britz, W. (2019): Coupling crop and bio-economic farm modelling to evaluate the revised fertilization regulations in Germany , Agricultural Systems
- On-farm compliance costs with the EU-Nitrates Directive: A modelling approach for specialized livestock production in northwest Germany (2019) Kuhn, T., Schäfer, D., Holm-Müller, K., Britz, W. (2019): On-farm compliance costs with the EU-Nitrates Directive: A modelling approach for specialized livestock production in northwest Germany, Agricultural Systems 173: 233-243
- An economic and environmental assessment of a glyphosate ban for the example of maize production (2019) Boecker, T., Moehring, N., Finger, R., Britz, W. (2019): An economic and environmental assessment of a glyphosate ban for the example of maize production, European Review of Agricultural Economics, available online 5th February 2019
- Econometric mathematical programming: an application to the estimation of costs and risk preferences at farm level (2019) Arata, L., Britz, W. (2019): Econometric mathematical programming: an application to the estimation of costs and risk preferences at farm level, Agricultural Economics, available online 8th January 2019
- Economic Impacts and Land Use Change from Increasing Demand for Forest Products in the European Bioeconomy: A General Equilibrium Based Sensitivity Analysis (2019) Haddad, S., Britz, W., Boerner, J. (2019): Economic Impacts and Land Use Change from Increasing Demand for Forest Products in the European Bioeconomy: A General Equilibrium Based Sensitivity Analysis, Forests, 10(1) 52: 1-27