Journal of Bioeconomics

, Volume 12, Issue 2, pp 145–167 | Cite as

Bio-economic modelling of soil erosion externalities and policy options: a Tunisian case study

  • Kamel Louhichi
  • Guillermo Flichman
  • Jean Marie Boisson
Article

Abstract

Soil erosion is one of the most important of today’s environmental externalities and a major threat to sustainability of agricultural system. It constitutes the most widespread forms of land degradation throughout the world. The aim of this paper is to estimate the amount of soil erosion generated by the current cropping systems in Tunisia and to assess the economic and ecological impacts of policy instruments designed to handle this problem. The analysed policy options are based on soil conservation practices and direct incentive farming anti-erosive measures. The selected measures are the reduction of tillage, the avoidance of bare fallow and the use of legume-based crop rotation. A bio-economic modelling framework coupling the biophysical model EPIC to a non-linear dynamic programming farm model was used for this impact analysis. It was performed in a set of representative farms belonging to a region in North-Eastern Tunisia (Zaghouan) strongly affected by this phenomenon. The main finding of this research is the non-convexity of the crop yield—soil erosion space. That is, the use of more intensive techniques to increase productivity (i.e. crop yield) may be accompanied by rough changes in soil erosion (damage) curves, manifested either by non-monotony or non-convexity. In term of policy options and because of giving up convexity assumptions, incentive anti-erosive measures appear more efficient than conventional environmental policies such as Pigouvian taxes or quota systems. The implementation of soil conservation practices would leads to a net decrease in soil erosion and an increase in farm income. However, with the current interest rate of 7% the possible rise in income is not enough to stimulate farmers to invest on these practices. A maximum rate of 4% would be necessary to make this policy option more effective.

Keywords

Soil erosion Agricultural system Environmental externalities Non-convexities Policy analysis Bio-economic model 

JEL Classification

O1 Q2 Q5 

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References

  1. Abdouli, H., & Kraiem, K. (1990). Intake, digestion and feeding behaviour of the one-humped stall fed straw-based diets. Livestock Research for Rural Development, 2. http://www.cipav.Org.co/Irrd/Irrd2/2/abdouli.htm.
  2. Barbier B., Benoit-Cattin M. (1997) Viabilité à moyen et long-terme d’un système agraire villageois d’Afrique Sudano-Sahélienne: Le cas de Bala au Burkina Faso. Economie Rurale 239: 35–51Google Scholar
  3. Barbier B., Bergeron G. (1999) Impact of policy interventions on land management in Honduras: Results of a bio-economic model. Agricultural Systems 59: 1–16CrossRefGoogle Scholar
  4. Baumol W. J. (1964) External economies and the second order optimality conditions. American Economic Review 54: 358–372Google Scholar
  5. Baumol W. J., Bradford D. F. (1972) Detrimental externalities and non-convexity of the production set. Economica 39: 160–176CrossRefGoogle Scholar
  6. Baumol W. J., Oates W. E. (1975) The theory of environmental policy: Externalities public outlays, and the quality of life. Prentice-Hall INC, New JerseyGoogle Scholar
  7. Berck P., Stohs S., Geoghegan J., Strong A. (2000) Test of the von Liebig hypothesis. American Journal of Agricultural Economics 82(4): 948–955CrossRefGoogle Scholar
  8. Berentsen P. B. M. (2003) Effects of animal productivity on the costs of complying with environmental legislation in Dutch dairy farming. Livestock Production Science 84: 183–194CrossRefGoogle Scholar
  9. Bonnieux F., Desaigues B. (1998) Economie et politiques de l’environnement. Dalloz, Paris, p 327Google Scholar
  10. Boussemart J. P., Jacquet F., Flichman G., Lefer B. H. (1996) Prévoir les effets de la réforme de la politique agricole commune sur deux régions agricoles françaises : application d’un modèle bio économique. Canadian Journal of Agricultural Economics 44: 121–138CrossRefGoogle Scholar
  11. Bouzaher A., Shogren J. F., Gassman P. W., Holtkamp D. J., Manale A. P. (1995) Use of a linked biophysical and economic modelling system to evaluate risk-benefit tradeoffs of corn herbicide use in the midwest. In: Leng M. L. (eds) Agrochemical environmental fate: state of the art. CRC Press, Boca Raton, FL, pp 369–381Google Scholar
  12. Boyd J. H., Conley J. P. (1997) Fundamental nonconvexities in Arrovian markets and a Coasian solution to the problem of externalities. Journal of Economic Theory 72(2): 388–407CrossRefGoogle Scholar
  13. Brisson N., Mary B., Ripoche D., Jeuffroy M. H., Ruget F., Nicoullaud B., Gate P., Devienne-Barret F., Antonioletti R., Durr C., Richard G., Beaudoin N., Recous S., Tayot X., Plenet D., Cellier P., Machet J.-M., Meynard J.-M., Delecolle R. (1998) STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn. Agronomie 18: 311–346CrossRefGoogle Scholar
  14. Burrows P. (1986) Non-convexity induced by external costs on production: Theoretical curio or policy dilemma?. Journal of Environmental Economics and Management 13: 101–128CrossRefGoogle Scholar
  15. Burrows P. (1995) Non-convexities and the theory of external cost. In: Bromley D. (eds) The handdbook of environmental economics. Basil Blackwell Ltd, UK, p 437Google Scholar
  16. Cabelguenne, M., & Debaeke P. H. (1995). Manuel d’utilisation du modèle EWQTPR EPIC-PHASE temps réel, INRA, Toulouse.Google Scholar
  17. CDCGE. (2006). Plan d’action regional de lutte contre la désertification du gouvernorat de Zaghouan. Direction Générale de l’Environnement et de la Qualité de la Vie. Rapport Final, 95 p.Google Scholar
  18. Chambers R. G., Lichtenberg E. (1996) A nonparametric approach to the von Liebig-Paris technology. American Journal of Agricultural Economics 78(2): 373–386CrossRefGoogle Scholar
  19. Chenery H. (1949) Engineering production functions. Quarterly Journal of Economics 634: 507–531CrossRefGoogle Scholar
  20. Clark C. W. (1990) Mathematical bioeconomics: The optimal management of renewable resources (2nd ed.). Wiley-Intersciences, New YorkGoogle Scholar
  21. De Wit C. T. (1992) Resource use efficiency in agriculture. Agricultural Systems 40: 125–151CrossRefGoogle Scholar
  22. Deybe D. (2002) Bio-economic modelling for better quantification of the environmental impacts of agriculture. Montpellier, CIRADGoogle Scholar
  23. Deybe D., Flichman G. (1991) A regional agricultural model using a plant growth simulation program as activities generator. Agricultural Systems 37: 369–385CrossRefGoogle Scholar
  24. Donaldson A. B., Flichman G., Webster J. P. (1995) Integrating agronomic and economic models for policy analysis at the farm level: The impact of CAP reform in two European regions. Agricultural Systems 48: 163–178CrossRefGoogle Scholar
  25. Ezekiel M. (1938) The cobweb theorem. Quarterly Journal of Economics 52: 255–280CrossRefGoogle Scholar
  26. Flichman G., Jacquet F. (2003) Le couplage des modèles agronomiques et économiques—acquis et perspectives. Cahiers d’économie et de sociologie rurales 67: 52–69Google Scholar
  27. Foltz J. C., Lee J. G., Marshall A. M., Preckel P. V. (1995) Multi-attribute assessment of alternative cropping systems. American Journal of Agricultural Economics 77: 408–420CrossRefGoogle Scholar
  28. Freund R. J. (1956) The introduction of risk into a programming model. Econometrica 21: 253–263CrossRefGoogle Scholar
  29. Hanley N., Shogren J.F., White B. (1997) Environmental economics in theory and in practice. Macmillan Press LTD, London, p 464Google Scholar
  30. Hanley N., Spash C., Walker L. (1995) Problems in valuing the benefits of biodiversity protection. Environmental and Resource Economics 5: 249–272CrossRefGoogle Scholar
  31. Hazell P. B. R., Norton R. D. (1986) Mathematical programming for economic analysis in agriculture. Macmillan Publishing Co, New YorkGoogle Scholar
  32. Howitt R. E. (1995) Positive mathematical programming. American Journal of Agricultural Economics 77: 329–342CrossRefGoogle Scholar
  33. Judez L., Chaya C., Martinez S., Gonzalez 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: 121–138CrossRefGoogle Scholar
  34. Kirschke, D., Odening, M., Doluschitz, R., Fock, T., Hagedorn, K., Rost, & von Witzke, H. (1998). Weiterentwicklung der EU-Agrarpolitik: Aussichten für die neuen Bundesländer. Agrarökonomische Monographien und Sammelwerke Kiel: Wissenschaftsverlag Vauk Kiel KG.Google Scholar
  35. Kula E. (1994) Economics of natural resources, the environment and policies (2nd ed.). Chapman & Hall, LondonGoogle Scholar
  36. Kurz H. (2001) Critical essays on Piero Sraffa’s legacy in Economics. Cambridge University Press, CambridgeGoogle Scholar
  37. Lakshminarayan P. G., Gassman P. W., Bouzaher A., Izaurralde R. C. (1996) A meta modelling approach to evaluate agricultural policy impact on soil degradation in Western Canada. Canadian Journal of Agricultural Economics 44: 277–294CrossRefGoogle Scholar
  38. Leonard R. A., Knisel W. G., Still D. A. (1987) GLEAMS: Groundwater loading effects of agricultural management systems. Transactions of the ASAE 305: 1403–1418Google Scholar
  39. Louhichi, K. (2001). Essai de modélisation bioéconomique de la relation agriculture-environnement. Le cas de l’érosion en Tunisie. Thèse de doctorat de l’université de Montpellier I. Montpellier, 250 p.Google Scholar
  40. Louhichi K., Alary V., Grimaud P. (2004) A dynamic model to analyse the bio-technical and socio- economic interactions in dairy farming systems on the Réunion Island. Animal Research 53: 363–382CrossRefGoogle Scholar
  41. Louhichi K., Flichman G., Zekri S. (1999) Un modèle bioéconomique pour analyser l’impact des politiques de conservation des eaux et du sol : le cas d’une exploitation agricole tunisienne. Economie rurale 252: 55–64CrossRefGoogle Scholar
  42. Mas-Collel A., Whinston M. D., Green J. R. (1995) Microeconomic theory. Oxford University Press, OxfordGoogle Scholar
  43. Mimouni M., Zekri S., Flichman G. (2000) Modelling the trade-offs between farm income and the reduction of erosion and nitrate pollution. Annals of Operations Research 94: 91–103CrossRefGoogle Scholar
  44. Mottelet, S., & Elbagdouri, M. (2000). Optimisation non linéaire. Université de Technologie de Compiègne, 227 p.Google Scholar
  45. OECD. (1993). Agricultural and environmental policy integration: Recent progress and new directions. Paris, 95 p.Google Scholar
  46. Oldeman, L. R., van Engelen, V. W. P., & Pulles, J. H. M. (1990). The extent of human-induced soil degradation. In L. R. Oldeman, R. T. A. Hakkeling, & W. G. Sombroek (Eds.), World map of the status of human-induced soil degradation: An explanatory note, rev. 2nd ed. Wageningen, the Netherlands: International Soil Reference and Information Centre, Table 7.Google Scholar
  47. Onate J. J., Atance I., Bardaji I., Llusia D. (2006) Modelling the effects of alternative CAP policies for the Spanish high-nature value cereal-steppe farming systems. Agricultural Systems 94: 247–260CrossRefGoogle Scholar
  48. Paris Q. (1992) The von Liebig hypothesis. American Journal of Agricultural Economics 74(4): 1019–1028CrossRefGoogle Scholar
  49. Passet R. (1996) L’économie et le vivant. Economica, Paris, p 291Google Scholar
  50. Pearce D.W., Turner R.K. (1990) Economics of natural resources and the environment. Hemel Hempstead, Harvester WheatsheafGoogle Scholar
  51. Riesgo L., Gomez-Limon J. A. (2006) Multi-criteria policy scenario analysis for public regulation of irrigated agriculture. Agricultural Systems 91: 1–28CrossRefGoogle Scholar
  52. Robinson J. (1969) The accumulation of capital. Macmillan, LondonGoogle Scholar
  53. Ruben H. M., Arie K. (1998) Integrating agricultural research and policy analysis: Analytical framework and policy applications for bioeconomic modelling. Agricultural Systems 58: 331–349CrossRefGoogle Scholar
  54. Ruben R., van Ruijven A. (2001) Technical coefficients for bio-economic farm household models: A meta-modeling approach with applications for Southern Mali. Ecological Economics 36: 427–441CrossRefGoogle Scholar
  55. Sadoulet E., Janvry A. (1995) Quantitative development policy analysis. John Hopkins University Press, Baltimore, MDGoogle Scholar
  56. Schuler, J., & Sattler, C. (2008). The estimation of agricultural policy effects on soil erosion—an application for the bio-economic model MODAM. Land Use Policy. doi:10.1016/j.landusepol.2008.05.001.
  57. Semaan J., Flichman G., Scardigno A., Steduto P. (2007) Analysis of nitrate pollution control policies in the irrigated agriculture of Apulia Region (Southern Italy): A bio-economic modelling approach. Agricultural Systems 94: 357–367CrossRefGoogle Scholar
  58. Sraffa P. (1960) Production of commodities by means of commodities: Prelude to a critique of economic theory. Cambridge University Press, CambridgeGoogle Scholar
  59. Starrett D. A. (1972) Fundamental non convexities in the theory of externalities. Journal of Economic Theory 4: 180–199CrossRefGoogle Scholar
  60. Stockle C. O., Martin S., Campbell G. S. (1994) CropSyst, a cropping systems model: water/nitrogen budgets and crop yield. Agricultural System 46: 335–359CrossRefGoogle Scholar
  61. Van Ittersum M. K., Ewert F., Heckelei T., Wery J., Alkan Olsson J., Andersen E., Bezlepkina I., Brouwer F., Donatelli M., Flichman G., Olsson L., Rizzoli A. E., van der Wal T., Wien J. E., Wolf J. (2008) Integrated assessment of agricultural systems—a component-based framework for the European Union (SEAMLESS). Agricultural Systems 96: 150–165CrossRefGoogle Scholar
  62. Vatn A., Bakken L.R., Bleken M.A., Botterweg P., Lundeby H., Romstad E.M., Rørstad P.K., Vold A. (1996) Policies for reduced nutrient losses and erosion from norwegian agriculture. Norwegian Journal of Agricultural Sciences 23: 1–319Google Scholar
  63. Vatn A., Bakken L., Botterweg P., Romstad E. (1999) ECECMOD: An interdisciplinary modelling system for analyzing nutrient and soil losses from agriculture. Ecological Economics 302: 189–205CrossRefGoogle Scholar
  64. Vermersch, D. (1992). Internalisation efficiente et agriculture durable. Economie Rurale, 208–209, 144–148.Google Scholar
  65. Veysset P., Bebin D., Lherm M. (2005) Adaptation to Agenda 2000 (CAP reform) and optimisation of the farming system of French suckler cattle farms in the Charolais area: A model-based study. Agricultural Systems 83: 179–202CrossRefGoogle Scholar
  66. Vicien C. (1991) Les modèles de simulation comme fonctions de production. Economie Rurale 204: 46–50CrossRefGoogle Scholar
  67. Waugh, F. V. (1964). Demand and price analysis, some examples from agriculture. Technical Bulletin No. 1316, U.S. Department of Agriculture, Washington, DC.Google Scholar
  68. Williams J. R., Jones C. A., Dyke P. T. (1984) A modelling approach to determining the relationship between erosion and soil productivity. Transactions of the ASAE 271: 129–144Google Scholar
  69. Wischmeier W. H. (1976) Use and misuse of the universal soil loss equation. Journal of Soil and Water Conservation 31(1): 5–9Google Scholar

Copyright information

© Springer Science+Business Media, LLC. 2010

Authors and Affiliations

  • Kamel Louhichi
    • 1
  • Guillermo Flichman
    • 2
  • Jean Marie Boisson
    • 3
  1. 1.INRA-AgroParisTech, UMR Economie PubliqueThiverval-GrignonFrance
  2. 2.CIHEAM-Institut Agronomique MéditerranéenMontpellierFrance
  3. 3.Faculté des sciences économiquesMontpellierFrance

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