Optimising the effect of policy instruments: a study of farmers' decision rationales and how they match the incentives in Danish pesticide policy

Pedersen, Anders Branth; Nielsen, Helle Ørsted; Christensen, Tove; Hasler, Berit

doi:10.1080/09640568.2011.636568

Cited by 55 publications

(57 citation statements)

References 26 publications

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“…There is partly a strong similarity between this factor and 'entrepreneurial attitude', as in both cases one's self-image as a farmer plays a strong role. The results here are mixed, partly because of the large differences in what was measured specifically, from the importance of 'clean fields' [53] to 'farm image' [14], but also the influence of 'symbolic capital', for example on participation in AESs, depends strongly on which type of image is important to the farmer. However, it seems that overall symbolic capital has some influence on farmers' decision-making, though this influence varies depending on context.…”

Section: Discussionmentioning

confidence: 65%

Leverage Points for Governing Agricultural Soils: A Review of Empirical Studies of European Farmers’ Decision-Making

2018

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What drives farmers’ decision-making? To inform effective, efficient, and legitimate governance of agricultural soils, it is important to understand the behaviour of those who manage the fields. This article contributes to the assessment and development of innovative soil governance instruments by outlining a comprehensive understanding of the determinants of farmers’ behaviour and decision-making. Our analysis synthesises empirical literature from different disciplines spanning the last four decades on various farm-level decision-making problems. Based on a conceptual framework that links objective characteristics of the farm and the farmer with behavioural characteristics, social-institutional environment, economic constraints, and decision characteristics, empirical findings from 87 European studies are presented and discussed. We point out that economic constraints and incentives are very important, but that other factors also have significant effects, in particular pro-environmental attitudes, goodness of fit, and past experience. Conversely, we find mixed results for demographic factors and symbolic capital. A number of potentially highly relevant yet understudied factors for soil governance are identified, including adoption of technologies, advisory services, bureaucratic load, risk aversion and social capital, social norms, and peer orientation. Our results emphasise the importance of a broad behavioural perspective to improve the efficiency, effectiveness, and legitimacy of soil governance.

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Section: Discussionmentioning

confidence: 65%

Leverage Points for Governing Agricultural Soils: A Review of Empirical Studies of European Farmers’ Decision-Making

2018

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“…To estimate the utility functions of the farmers we set a priori three farmers' objectives; profit maximization, environmental sustainability maximization, and the minimization of hired labour. The assumption of profit maximization in our model is in line with general assumptions in economic modelling (Pedersen et al, 2012;Peerlings & Polman, 2009). The assumption of labour minimization is in line with the findings of Berbel & Rodriguez-Ocana (1998) Rozakis, Sintori & Tsiboukas (2012), and Sumpsi, Amador & Romero (1997).…”

Section: Model Descriptionsupporting

confidence: 84%

“…In this paper we assume that farms' main goal is to optimize their gross margin or profit. The assumption of profit maximization is in line with assumptions that are generally made in economic modelling (Pedersen et al, 2012), although it should be mentioned that in reality farms might have other objectives such as the minimization of labour use and risk or the environmental impact of farming as well (Berbel & Rodriguez-Ocana, 1998;Rozakis, Sintori & Tsiboukas, 2012;Sumpsi, Amador & Romero, 1997;Willock et al, 1999). Mathematical programming allows us to study changes in the optimal farming decisions, which are the result of constraints becoming more or less binding.…”

Section: Mathematical Programmingmentioning

confidence: 93%

Complexity in land use change; the case of the Dutch dairy sector

Groeneveld

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2.1. Introduction 2.2. Background 2.3. Method 2.4. Results 2.5. Sensitivity Analysis 2.6. Discussion 2.7. Conclusions Appendix 2A. Model description Appendix 2B. Data used Appendix 2C. Additional model results Appendix 2D. Sensitivity Analysis Chapter 3 Complex dynamics in the uptake of new farming practices: a case study for organic waste application Abstract 3.1. Introduction 3.2. Methods 3.3. Results 3.4. Discussion 3.5. Conclusions Appendix 3A. Farm model Appendix 3B. Exogenous values for determining utility functions Appendix 3C. Sensitivity analysis Appendix 3D. Weights for profit, sustainability and labour Chapter 4 Effects on participation and biodiversity of reforming the implementation of agri-environmental schemes in the Netherlands Abstract 4.1. Introduction 4.2. Methods 4.3. Data 4.4. Experimental design 4.5. Results 4.6. Conclusions and Discussion Appendix 4A. GAMS model Appendix 4B. Sensitivity analysis Chapter 5 Effects of changing social influence on participation and biodiversity in agri-environmental schemes in the Netherlands Abstract 5.1. Introduction 5.2. Modelling framework 5.3. Study area 5.4. Method and Data 5.5. Model 5.6. Scenarios 5.7. Results 5.8. Conclusions and Discussion Appendix 5A. Determining the weights of the farmer Appendix 5B. Indicator species and biodiversity scores Appendix 5C. Mathematical programming models Appendix 5D. Variation in model runs Appendix 5E. Initial weights Chapter 6 Conclusions and Discussion References Summary Acknowledgements

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“…Moreover, implementing a broad array of policy interventions may better match different rationales for pesticide use and improve the effect of the overall policy (Pedersen et al, 2012). Of course, agricultural groundwater quality is not only affected by pesticide leaching but also by pollution caused by nitrates from agricultural sources (e.g.…”

Section: Discussionmentioning

confidence: 99%

Evaluating alternative policies to reduce pesticide groundwater pollution in Dutch arable farming

Skevas

2019

Journal of Environmental Planning and Management

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This article develops a dynamic optimal control modelof farmers' production decisions and applies it to panel data from Dutch arable farms to assess the effectiveness of different policy interventions in reducing pesticide groundwater pollution. Three different policy measures are examined in turn: namely, a flat tax on pesticides; a groundwater contamination tax; and a quantity restriction on pesticide use. The examined policies are compared against both quantitative and qualitative criteria drawn from the pesticide policy literature. Results show that the groundwater contamination tax is the most preferred policy for reducing pesticide groundwater pollution. A way to apply such a tax is proposed and discussed.

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Optimising the effect of policy instruments: a study of farmers' decision rationales and how they match the incentives in Danish pesticide policy

Abstract: 2012) Optimising the effect of policy instruments: a study of farmers' decision rationales and how they match the incentives in Danish pesticide policy,

Cited by 55 publications

References 26 publications

Leverage Points for Governing Agricultural Soils: A Review of Empirical Studies of European Farmers’ Decision-Making

Leverage Points for Governing Agricultural Soils: A Review of Empirical Studies of European Farmers’ Decision-Making

Complexity in land use change; the case of the Dutch dairy sector

Evaluating alternative policies to reduce pesticide groundwater pollution in Dutch arable farming

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