Estimation of constrained optimisation models for agricultural supply analysis based on generalised maximum entropy

European Review of Agricultural Economics

Volumn 30, Issue 1, 2003, Pages 27-50

  Heckelei, Thomas ^a   Wolff, Hendrik ^a  

^a WASHINGTON STATE UNIVERSITY   (United States)

Author keywords

Agricultural supply analysis; Constrained optimisation models; Mathematical programming models; Maximum entropy estimation; Prior information

Indexed keywords

EID: 0037863917     PISSN: 01651587     EISSN: None     Source Type: Journal    
DOI: 10.1093/erae/30.1.27     Document Type: Article

References (28)

1. Arfini, F. and Paris, Q. (1995). A Positive Mathematical Programming model for regional analysis of agricultural policies. In F. Sotte (ed.), The Regional Dimension in Agricultural Economics and Policies. EAAE, Proceedings of the 40th Seminar, 26-28 June 1995, Ancona, 17-35.
2. Britz, W., Heckelei, T. and Wolff, H. (2003). Symmetric Positive Equilibrium Problem: a framework for rationalizing economic behavior with limited information: Comment. American Journal of Agricultural Economics (forthcoming).
3. Chambers, R. G. and Just, R. E. (1989). Estimating multioutput technologies. American Journal of Agricultural Economics 71(4): 980-995.
4. Chirinko, R. S. (1993). Business fixed investment spending: modeling strategies, empirical results, and policy implications. Journal of Economic Literature 31: 1875-1911.
5. Cypris, C. (2000). Positiv Mathematische Programmierung (PMP) im Agrarsektormodell RAUMIS. Dissertation, University of Bonn.
6. Gallant, A. R. and Golub, G. H. (1984). Imposing curvature restrictions on flexible functional forms. Journal of Econometrics 26: 295-321.
7. Golan, A., Judge, G. and Miller, D. (1996). Maximum Entropy Econometrics. Chichester: John Wiley.
8. Golan, A., Judge, G. and Perloff, M. (1996). A maximum entropy approach to recovering information from multinomial response data. Journal of the American Statistical Association 91(434): 841-853.
9. Guyomard, H., Baudry, M. and Carpentier, A. (1996). Estimating crop supply response in the presence of farm programmes: application to the CAP. European Review of Agricultural Economics 23: 401-420.
10. 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: 28-50.
11. Helming, J. F. M., Peeters, L. and Veendendaal, P. J. J. (2001). Assessing the consequences of environmental policy scenarios in Flemish agriculture. In T. Heckelei, H. P. Witzke and W. Henrichsmeyer (eds), Agricultural Sector Modelling and Policy Information Systems. Proceedings of the 65th EAAE Seminar, 29-31 March 2000, Bonn. Kiel: Vauk, 237-245.
12. House, R. M. (1987). USMP Regional Agricultural Model. National Economics Division Report, ERS, 30. Washington DC: USDA.
13. Howitt, R. E. (1995a). Positive Mathematical Programming. American Journal of Agricultural Economics 77(2): 329-342.
14. Howitt, R. E. (1995b). A calibration method for agricultural economic production models. Journal of Agricultural Economics 46: 147-159.
15. Howitt, R. E. and Gardner, B. D. (1986). Modeling production and resource interrelationships among California crops in response to the 1985 Food Security Act. In Impacts of Farm Policy and Technical Change on US and Californian Agriculture. Davis (USA), 271-290.
16. Kasnakoglu, H. and Bauer, S. (1989). Concept and application of an agricultural sector model for policy analysis in Turkey. In S. Bauer and W. Henrichsmeyer (eds), Agricultural Sector Modelling. Kiel: Vauk: 71-84.
17. Lau, L. J. (1978). Testing and imposing monotonicity, convexity, and quasi-convexity. In M. Fuss and D. McFadden (eds), Production Economics: a Dual Approach to Theory and Applications. Amsterdam: North-Holland, 409-453.
18. Lence, H. L. and Miller, D. (1998a). Estimation of multioutput production functions with incomplete data: a Generalised Maximum Entropy approach. European Review of Agricultural Economics 25: 188-209.
19. Lence, H. L. and Miller, D. (1998b). Recovering output specific inputs from aggregate input data: a generalized cross-entropy approach. American Journal of Agricultural Economics 80(4): 852-867.
20. McElroy, M. B. (1987). Additive general error models for production, cost, and derived demand or share systems. Journal of Political Economy 95(4): 737-757.
21. Mittelhammer, R. C. and Cardell, S. (2000). The data-constrained GME-Estimator of the GLM: asymptotic theory and inference. Working Paper of the Department of Statistics. Pullman, WA: Washington State University.
22. Moro, D. and Sckokai, P. (1999). Modelling the CAP arable crop regime in Italy: degree of decoupling and impact of Agenda 2000, Cahiers d'Economie et Sociologie Rurales 53: 50-73.
23. Oude Lansink, A. (1999). Generalised Maximum Entropy and heterogeneous technologies. European Review of Agricultural Economics 26: 101-115.
24. Paris, Q. (2001). Symmetric Positive Equilibrium Problem: a framework for rationalizing economic behavior with limited information. American Journal of Agricultural Economics 83(4): 1049-1061.
25. 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.
26. Pope, R. D. and Just, R. E. (2002). Random profits and duality. American Journal of Agricultural Economics 84(1): 1-7.
27. Preckel, P. V. (2001). Least squares and entropy: a penalty function perspective. American Journal of Agricultural Economics 83(2): 366-377.
28. Zhang, X. and Fan, S. (2001). Estimating crop-specific production technologies in Chinese agriculture: a Generalized Maximum Entropy approach. American Journal of Agricultural Economics 83(2): 378-388.