Empirical test of an agricultural landscape model: The importance of farmer preference for risk aversion and crop complexity

SAGE Open

Volumn 3, Issue 2, 2013, Pages 1-16

  Cooke, Ira R ^a,b   Mattison, Elizabeth H A ^c   Audsley, Eric ^d   Bailey, Alison P ^c   Freckleton, Robert P ^e   Graves, Anil R ^d   Morris, Joe ^d   Queenborough, Simon A ^e   Sandars, Daniel L ^d   Siriwardena, Gavin M ^f   Trawick, Paul ^d   Watkinson, Andrew R ^g   Sutherland, William J ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b LA TROBE UNIVERSITY   (Australia)

^c UNIVERSITY OF READING   (United Kingdom)

^d CRANFIELD UNIVERSITY   (United Kingdom)

^e UNIVERSITY OF SHEFFIELD   (United Kingdom)

^f THE NUNNERY   (United Kingdom)

^g UNIVERSITY OF EAST ANGLIA   (United Kingdom)

Author keywords

Agriculture; Multiattribute utility theory; Socioeconomic model; Stated preferences

Indexed keywords

EID: 84882995907     PISSN: None     EISSN: 21582440     Source Type: Journal    
DOI: 10.1177/2158244013486491     Document Type: Article

References (44)

1. Agro Business Consultants. (2004). The agricultural budgeting and costings book (59th ed.). Melton Mowbray, UK: Author.
2. Annetts, J. E., & Audsley, E. (2002). Multiple objective linear programming for environmental farm planning. Journal of the Operational Research Society, 53, 933-943.
3. Arfini, F. (2005). Modelling agricultural policies: State of the art and new challenges. Proceedings of the 89th Seminar of the European Association of Agricultural Economists, University of Parma, Italy.
4. Arriaza, M., & Gómez-Limón, J. A. (2003). Comparative performance of selected mathematical programming models. Agricultural Systems, 77, 155-171.
5. Beale, E. M. L., & Forrest, J. J. H. (1976). Global optimization using special ordered sets. Mathematical Programming, 10, 52-69.
6. Belton, V., & Stewart, T. J. (2002). Multiple criteria decision analysis: An integrated approach. Dordrecht, Netherlands: Kluwer Academic.
7. Brodt, S., Klonsky, K., & Tourte, L. (2006). Farmers' goals and management styles: Implications for advancing biologically based agriculture. Agricultural Systems, 89, 90-105.
8. Cowles, M. K., & Carlin, B. P. (1996). Markov Chain Monte Carlo convergence diagnostics: A comparative review. Journal of the American Statistical Association, 91, 883-904.
9. de Frahan, B. H. (2005, August). PMP Extensions and alternative methods: Introductory review of the state of the art. XIth European Association of Agricultural Economists Congress, Copenhagen, Denmark.
10. Department for Environment, Food and Rural Affairs. (2008). Agriculture in the United Kingdom. Retrieved from http://www.defra.gov.uk/statistics/files/defra-stats-foodfarm-farmgate-api-2005-130321.xls
11. Department for Environment, Food and Rural Affairs & National Assembly for Wales. (2002). Farm Business Survey. Colchester, Essex: UK Data Archive (SN: 4604).
12. Department for Environment, Food and Rural Affairs & National Assembly for Wales. (2003). Farm Business Survey. Colchester, Essex: UK Data Archive (SN: 4830).
13. Department for Environment, Food and Rural Affairs & National Assembly for Wales. (2004). Farm Business Survey. Colchester, Essex: UK Data Archive (SN: 4831).
14. Department for Environment, Food and Rural Affairs & National Assembly for Wales. (2005). Farm Business Survey. Colchester, Essex: UK Data Archive (SN: 5228).
15. Edwards-Jones, G., Dreary, I., & Willcock, J. (1998). Incorporating psychological variables in models of farmer behaviour: Does it make for better predictions? Etudes & Recherches sur les Systèmes Agraires et le Développement, 31, 153-173.
16. Fairweather, J. R., & Keating, N. C. (1994). Goals and management styles of New Zealand farmers. Agricultural Systems, 44, 181-200.
17. Gasson, R. (1973). Goals and values of farmers. Journal of Agricultural Economics, 24, 521-542.
18. Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2002). Bayesian data analysis (2nd ed.). Boca Raton, FL: Chapman and Hall/CRC.
19. Geweke, J. (1992). Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments. In J. M. Bernardo, J. Berger, A. P. David, & A. F. M. Smith (Eds.), Bayesian statistics 4 (pp. 169-193). Oxford, UK: Oxford University Press.
20. Harper, W. M., & Eastman, C. (1980). An evaluation of goals hierarchies for small farm operators. American Journal of Agricultural Economics, 62, 742-747.
21. Hazell, P. B. R. (1971). A linear alternative to quadratic and semivariance programming for farm planning under uncertainty. American Journal of Agricultural Economics, 53, 53-62.
22. Howitt, R. E. (1995). Positive mathematical programming. American Journal of Agricultural Economics, 77, 329-342.
23. Janssen, A., & van Ittersum, M. K. (2007). Assessing farm innovations and responses to policies: A review of bio-economic farm models. Agricultural Systems, 94, 622-636.
24. Just, R. E., & Pope, R. D. (2003). Agricultural risk analysis: Adequacy of models, data, and issues. American Journal of Agricultural Economics, 85, 1249-1256.
25. Lin, W., Dean, W., & Moore, C. V. (1974). Profit maximization in agricultural production. American Journal of Agricultural Economics, 56, 497-508.
26. McGregor, M., Willock, J., Dent, B., Deary, I., Sutherland, A., Gibson, G., & Grieve, B. (1996). Links between psychological factors and farmer decision making. Farm Management, 9, 228-239.
27. Ministry of Agriculture, Fisheries and Food & National Assembly for Wales. (2001). Farm Business Survey. Colchester, Essex: UK Data Archive (SN: 4603).
28. Moffett, A., Dyer, J. S., & Sarkar, S. (2006). Integrating biodiversity representation with multiple criteria in North-Central Namibia using non-dominated alternatives and a modified analytic hierarchy process. Biological Conservation, 129, 181-191.
29. Mustajoki, J., Hämäläinen, R. P., & Salo, A. (2005). Decision support by interval SMART/SWING - incorporating imprecision in the SMART and SWING methods. Decision Sciences, 36, 317-339.
30. Nix, J. (2007). Farm management pocketbook (37th ed.). Leicestershire, UK: The Andersons Centre.
31. Pacini, C., Wossink, A., Geisen, G., & Huirne, R. (2004). Ecological-economic modeling to support multi-objective policy making: A farming systems approach implemented for Tuscany. Agriculture, Ecosystems and Environment, 102, 349-364.
32. Perez, I., & Muller-Holm, K. (2001). Economic incentives and technological options to global warming emission abatement in European Agriculture. In F. Arfini (Ed.), Modelling agricultural policies: State of the art and new challenges: Proceedings of the 89th Seminar of the European Association of Agricultural Economists (pp. 413-425). Parma, Italy: University of Parma.
33. Perkin, P., & Rehman, T. (1994). Farmers' objectives and their interactions with business and life styles: Evidences from Berkshire, England. In J. B. Dent, & M. J. McGregor (Eds.), Rural and farming systems analysis: European perspectives (pp. 193-212). Wallingford, UK: CAB International.
34. Plummer, M., Best, N., Cowles, K., & Vines, K. (2006). CODA: Convergence diagnosis and output analysis for MCMC. R News, 6, 7-11.
35. Pöyhönen, M., Vrolijk, H. C. J., & Hämäläinen, R. P. (2001). Behavioral and procedural consequences of structural variation in value trees. European Journal of Operational Research, 134, 218-227.
36. Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1992). Numerical Recipes in Fortran 77 (2nd ed.). New York, NY: Cambridge University: Press.
37. R Development Core Team. (2008). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available from http://www.R-project.org
38. Rounsevell, M. D. A., Annetts, J. E., Audsley, E., Mayr, T., & Reginster, I. (2003). Modelling the spatial distribution of agricultural land use at the regional scale. Agriculture, Ecosystems and Environment, 95, 465-479.
39. Seo, S. N., & Mendelsohn, R. (2008). An analysis of crop choice: Adapting to climate change in South American farms. Ecological Economics, 67, 109-116.
40. Solano, C., Léon, H., Pérez, E., & Herrero, M. (2001). Characterising objective profiles of Costa Rican dairy farmers. Agricultural Systems, 67, 153-179.
41. Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & van der Linde, A. (2002). Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society: Series B, 64, 583-639.
42. von Winterfeldt, D., & Edwards, W. (1986). Decision analysis and behavioral research. Cambridge: Cambridge University Press.
43. Watkinson, A. R., Freckleton, R. P., Robinson, R. A., & Sutherland, W. J. (2000). Predictions of biodiversity response to genetically modified herbicide-tolerant crops. Science, 289, 1554-1557.
44. Weber, M., & Borcherding, K. (1993). Behavioral influences on weight judgments in multi-attribute decision making. European Journal of Operational Research, 67, 1-12.