Positive mathematical programming approaches – Recent developments in literature and applied modelling

Bio-based and Applied Economics

Volumn 1, Issue 1, 2012, Pages 109-124

  Heckelei, Thomas ^a   Britz, Wolfgang ^a   Zhang, Yinan ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

Estimation of programming models; Farm and sector models; Policy impact assessment; Positive mathematical programming; Review

Indexed keywords

EID: 84888322643     PISSN: 22806180     EISSN: 22806172     Source Type: Journal    
DOI: None     Document Type: Review

References (44)

1. Arfini, F. and Donati, M. (2011). Impact of the Health Check on Structural Change and Farm Efficiency: A Comparative Assessment of Three European Agricultural Regions. Proceedings of the OECD Workshop on Disaggregated Impacts of CAP Reforms. Paris: OECD, 75-90.
2. Arfini, F., Donati, M. and Paris, Q. (2003). A National PMP Model for Policy Evaluation in Agriculture using Micro Data and Administrative Information. Paper presented at the International Conference Agricultural Policy Reform and the WTO: Where Are We Heading? Capri, Italy, June 23-26, 2003.
3. Arfini, F., Donati, M., Grossi L. and Paris, Q. (2008). Revenue and Cost Functions in PMP: a Methodological Integration for a Territorial Analysis of CAP. Paper presented at the 107th EAAE Seminar Modelling of Agricultural and Rural Development Policies. Sevilla, Spain, January 29 – February 1st, 2008.
4. Britz, W. (2008). Automated Model Linkages: the Example of CAPRI. German Journal of Agricultural Economics 57(8): 363-367.
5. Britz, W. and Adenäuer, M. (2009). Calibration of Regional Programming Models to Exogenous Supply Elasticities by a Variable Cost Function: The CAPRI-EXPAMOD Example. In: Integrated Assessment of Agriculture and Sustainable Development (AgSAP), March 10-12, 2009, Egmont an Zee (The Netherlands), 52-53.
6. Britz, W. and Witzke, P. (2008). CAPRI Model Documentation 2008: Version 2. , last accessed March 2, 2012.
7. Buysse, J., Fernagut, B., Harmignie, O., Henry de Frahan, B., Lauwers, L., Polomé, P., Van Huylenbroeck, G. and Van Meensel, J. (2007a). Farm-Based Modelling of the EU Sugar Reform: Impact on Belgian Sugar Beet Suppliers. European Review of Agricultural Economics 34(1): 21-52.
8. Buysse, J., Van Huylenbroeck, G. and Lauwers, L. (2007b). Normative, Positive and Econometric Mathematical Programming as Tools for Incorporation of Multifunctionality in Agricultural Policy Modelling. Agriculture, Ecosystems and Environment 120: 70-81.
9. Cortignani, R. and Severini, S. (2009). Modeling Farm-Level Adoption of Deficit Irrigation using Positive Mathematical Programming. Agricultural Water Management 96: 1785-1791.
10. Cypris, C. (2000). Positive Mathematische Programmierung (PMP) im Agrarsektormodell RAUMIS. PhD dissertation, Department of Economic and Agricultural Policy, University of Bonn. Bonn, Germany.
11. De Cara, S., Houzé, M. and Jayet, P. A. (2005). Green House Gas Emissions from Agriculture in the EU: a Spatial Assessment of Sources and Abatement Costs. Environmental and Resource Economics 32(4): 551–583.
12. Doole, G.D., Ramilan T. and Pannell D. (2011). Framework for Evaluating Management Interventions for Water-Quality Improvement across Multiple Agents. Environmental Modelling and Software 26: 860-872.
13. Gocht, A. (2009). Methods in Economic Farm Modelling. PhD dissertation, Department of Economic and Agricultural Policy, University of Bonn. Bonn, Germany.
14. Gocht, A. and Britz, W. (2011). EU-Wide Farm Type Supply Models in CAPRI-How to Consistently Disaggregate Sector Models into Farm Type Models. Journal of Policy Modeling 33(1): 146-167.
15. Havlík, P., Schneider, A.U., Schmid, E., Böttcher, H., Fritz, S., Skalský, R., Aoki, K., de Cara, S., Kindermann, G., Kraxner, F., Leduc, S., McCallum, I., Mosnier, A, Sauer, T. and Obersteiner, M. (2011). Global Land-Use Implications of First and Second Generation Biofuel Targets. Energy Policy 39: 5690-5702.
16. Heckelei T. and Wolff, H. (2003). Estimation of Constrained Optimisation Models for Agricultural Supply Analysis based on Generalised Maximum Entropy. European Review of Agricultural Economics 30(1): 27-50.
17. Heckelei, T. and Britz, W. (2005). Models based on Positive Mathematical Programming: State of the Art and Further Extensions. In Arfini, F. (eds.), Modelling Agricultural Policies: State of the Art and New Challenges. Proceedings of the 89th European seminar of the European Association of Agricultural Economics. Parma, Italy: University of Parma, 48–73.
18. Heckelei, T. (2002). Calibration and Estimation of Programming Models for Agricultural Supply Analysis. Habilitation Thesis, University of Bonn. Bonn, Germany.
19. Heckelei, T. and Britz, W. (2000). Positive Mathematical Programming with Multiple Data Points: a Cross-Sectional Estimation Procedure. Cahiers d’Economie et Sociologie Rurales 57(4): 28-50.
20. Helming, J.F.M. (2005). A Model of Dutch Agriculture Based on Positive Mathematical Programming with Regional and Environmental Applications. PhD dissertation, Wageningen University. Wageningen, Netherlands.
21. Henry de Frahan, B., Buysse, J., Polomé, P., Fernagut, B., Harmignie, O., Lauwers, L., Van Huylenboreck, G. and Van Meensel, J. (2007). Positive Mathematical Programming for Agricultural and Environmental Policy Analysis: Review and Practice. In: Weintraub, A., Romero, C., Bjørndal, T., Epstein, R. and Miranda, J. (eds.), Handbook of Operations Research in Natural Resources. International Series in Operations Research & Management Science, 2007, Volume 99, 1, 129-154.
22. Horner, G., Corman, J., Howitt, R. E., Carter, C. A. and MacGregor, R. (1992). The Canadian Regional Agriculture Model, Structure, Operation and Development. Technical Report 1/92, Ottawa, Ontario, Canada: Agriculture and Agri-Food Canada.
23. Howitt, R.E. (1995). Positive Mathematical Programming. American Journal of Agricultural Economics 77(2): 329-342.
24. Jansson, T. and Heckelei, T. (2009). A New Estimator for Trade Costs and its Small Sample Properties. Economic Modelling 26: 489-498.
25. Jansson, T. and Heckelei, T. (2010). Estimation of Parameters of Constrained Optimization Models. In: Gilbert, J. (eds.), Frontiers of Economics and Globalization, Emerald Group Publishing Limited, Vol. 7, 1-26.
26. Jansson, T. and Heckelei, T. (2011). Estimating a Primal Model of Regional Crop Supply in the European Union. Journal of Agricultural Economics 62(1): 137-152.
27. Johansson, R., Peters, M. and House, R. (2007). Regional Environment and Agriculture Programming Model. Technical Bulletin 1916. United States Department of Agriculture, Economic Research Service.
28. Júdez, L., Andres, R., Ibanez M., de Miguel, J.M. and Miguel, J.L. (2008). Impact of the CAP Reform on the Spanish Agricultural Sector. Paper presented at the 109th EAAE Seminar the CAP after the Fischler Reform: National Implementations, Impact Assessment and the Agenda for Future Reforms. Viterbo, Italy, November 20-21st, 2008.
29. Júdez, L., Chaya, C., Martinez, S., and Gonsalez, A.A. (2001). Effects of the Measures Envisaged in “Agenda 2000” on Arable Crop Producers and Beef and Veal Producers: an Application of Positive Mathematical Programming to Representative Farms of a Spanish Region. Agricultural Systems 67: 121-138.
30. Kanellopoulos, A., Berentsen, P., Heckelei, T., Van Ittersum, M. and Oude Lansink, A. (2010). Assessing the Forecasting Performance of a Generic Bio-Economic Farm Model Calibrated with Two Different PMP Variants. Journal of Agricultural Economics 61(2): 274-294.
31. Kasnakoglu, H. and Bauer, S. (1988). Concept and Application of an Agricultural Sector Model for Policy Analysis in Turkey. In: Bauer, S. and Henrichsmeyer, W. (eds.), Agricultural Sector Modelling, Proceedings of the 16th Symposium of the EAAE, Kiel: Wissenschaftsverlag Vauk, 71-84.
32. Mann, S., Mack, G. and Ferjani, A. (2003). Können Produktionsentscheidungen als Investitionsentscheidungen modelliert werden? German Journal of Agricultural Economics 52(7): 333-340.
33. McCarl, B.A. (1982). Cropping Activities in Agricultural Sector Models: a Methodological Approach. American Journal of Agricultural Economics 64: 768-772.
34. Merel, P.R. and Bucaram, S. (2010). Exact Calibration of Programming Models of Agricultural Supply against Exogenous Sets of Supply Elasticities. European Review of Agricultural Economics 37: 395-418.
35. Mérel, P.R., Simon, L., and Yi, F. (2011). A Fully Calibrated Generalized Constant-Elasticity-of-Substitution Programming Model of Agricultural Supply. American Journal of Agricultural Economics 93(4): 936–948.
36. Offermann, F., Kleinhanß, W., Hüttel, S. and Küpker, B. (2005). Assessing the 2003 CAP Reform Impacts on German Agriculture using the Farm Group Model FARMIS. In: Arfini, F. (eds.), Modelling Agricultural Policies: State of the Art and New Challenges. Proceedings of the 89th European seminar of the European Association of Agricultural Economics. Parma, Italy: Monte Università Parma, 546-564.
37. Paris, Q. and Howitt, R.E. (1998). An Analysis of ill-Posed Production Problems using Maximum Entropy. American Journal of Agricultural Economics 80(1): 124-138.
38. Paris, Q. (2010). Economic Foundations of Symmetric Programming. Cambridge University Press, Cambridge.
39. Petsakos, A. and Rozakis, S. (2011). Integrating Risk and Uncertainty in PMP Models. Paper presented at the EAAE 2011 Congress Change and Uncertainty Challenges for Agriculture, Food and Natural Resources. ETH Zurich, Zurich, Switzerland, August 30-September 2nd, 2011.
40. Schmid, E. and Sinabell, F. (2007). On The Choice of Farm Management Practices after the Reform of the Common Agricultural Policy in 2003. Journal of Environmental Management 82(9): 332-340.
41. Schneider, U.A. and Schwab, D.E. (2006). The European Forest and Agricultural Sector Optimization model. Working Paper, Hamburg University, , last accessed March 2, 2012.
42. Schneider, U.A., McCarl, B.A. and Schmid, E. (2007). Agricultural Sector Analysis on Greenhouse Gas Mitigation in US Agriculture and Forestry. Agricultural Systems 94: 128–140.
43. Severini, S. and Cortignani R. (2011). Modeling Farmer Participation to a Revenue Insurance Scheme by means of Positive Mathematical Programming. Paper presented at the EAAE 2011 Congress Change and Uncertainty Challenges for Agriculture, Food and Natural Resources. ETH Zurich, Zurich, Switzerland, August 30 – September 2nd, 2011.
44. Takayama, T. and Judge, G.G. (1971). Spatial and Temporal Price and Allocation Models. Journal of International Economics 3(3): 304-304.