Agri-environmental payment schemes are increasingly popular amongst policy makers. However, their environmental and cost effectiveness depends largely on payment design, including whether participating farmers are paid to adopt environmental practices, to achieve environmental results, or for both. This chapter introduces the key research and policy questions that are covered in this report.
Making Agri-Environmental Payments More Cost Effective
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1. Introduction
Abstract
Tackling the environmental challenges facing agriculture will require improvements to the current set of policy instruments available to policy makers. Agri-environmental payment schemes that are voluntary programmes which pay farmers for achieving certain environmental criteria have gained increased interest and popularity among policy makers and farmers. However, there is growing evidence that a large majority of implemented schemes have had relatively low environmental effectiveness. The focus of this paper is on agri-environmental payment mechanisms and thus excluding other kinds of agri-environmental policies, such as regulatory instruments and taxes. This paper does not assess whether payment schemes are better than or preferred policy instruments over the spectrum of alternatives including regulatory, offsets, and cap and trade type of mechanisms. Within the agri-environmental payment mechanisms there are many different options policy makers can consider, and the recommendations from the existing literature on what constitutes “best practice” in policy design are diverse and often limited to specific aspects of policy design or implementation (DeBoe, 2020[1]).
Moreover, there are a number of newer policy options described in the literature, for which there is not a lot of empirical evidence and policy experience. In particular, many economists are recommending that policy makers shift policies to becoming more ‘performance-based’ or “results-based” rather than ‘practice-based’, on the basis that such policies are more cost-effective in delivering environmental improvements (Savage and Ribaudo, 2016[2]; Shortle et al., 2012[3]; Lankoski, 2016[4]; Batáry et al., 2015[5]; Burton and Schwarz, 2013[6]; Engel, 2016[7]). Some authors have argued that viewing these policies in binary terms, ‘practice-based’ versus ‘results-based’, limits the analysis of exactly how and why practice-based policies are flawed, which in turn may limit analysis of options to improve existing policies (Moxey and White, 2014[8]). For example, Hardelin and Lankoski (2018[9]) and Lankoski (2016[4]) show that incorporating environmental targeting to regions where highest environmental benefits can be achieved greatly improves the budgetary cost-effectiveness of practice-based policies.
A more flexible policy classification is needed, based on a spectrum of uniform practice-based policies at one end and policies based on measured environmental results at the other. Using the policy spectrum framework allows a deeper analysis of factors that contribute towards a policy’s success, and allows for the possibility that, rather than simply recommending a shift from practice-based to results-based policies, different policy types could perform well in different contexts and for different environmental effects.
While results-based schemes could be theoretically defined as schemes that are based on actual measurement of environmental results through monitoring, measurement of environmental results are not always feasible at field parcel level. Many important agri-environmental issues, such as nitrogen leaching and runoff, particulate and dissolved phosphorus runoff, sediment runoff, pesticide runoff, and greenhouse gas (GHG) emissions from field parcels, which are considered “non-point source pollution”, are extremely difficult and costly to measure at field parcel level, rendering direct environmental results measurement infeasible (or even impossible). Alternative payment design options are thus required to keep these environmental issues within the scope of results payments schemes. These options should as closely as possible resemble payments based on measured environmental results. One option is to base payments on modelled environmental results when the modelling is sophisticated and considers site-specific agronomic, ecological and biophysical features of a given field parcel, such as field slope, soil type, hydrology, or crop rotation to predict the effects of selected practices on environmental results.
Given that in this report both the policy simulations and the choice experiment focus on three environmental issues; nutrient runoff, GHG emissions, and biodiversity, of which two represent non-point source pollution, the payments based on modelled environmental results are considered as one type of results-based payments.1
To achieve its objectives, the report:
synthesises the existing available evidence to provide “best practice” design principles for agri-environmental payment schemes, building on past OECD work
identifies “new” design elements for which the current evidence is insufficient, and advances the evidence base for promising new design elements
acknowledges the limits of the work and identifies promising pathways for new kinds of policy design options.
This is undertaken by completing the following components:
Literature review and policy spectrum framework: The review aims to extract design and implementation principles for which there is a well-established evidence base and to identify key policy design elements to be tested in the simulation and experiment components. On the basis of the literature review, a policy spectrum framework classifying different types of mechanisms is developed.
Policy simulations: On the basis of the policy spectrum framework, policy simulations are developed to assess cost-effectiveness (including environmental effectiveness and policy-related transaction costs) of policies ranging from practice-based to results-based payment mechanisms.2
In-country economic choice experiments with farmers. To complement the policy simulations, a choice experiment is being developed to elicit farmers’ preferences for different attributes of agri-environmental payments, including practice-based and results-based payment mechanisms.
References
[5] Batáry, P. et al. (2015), “The role of agri-environment schemes in conservation and environmental management”, Conservation Biology, Vol. 29/4, pp. 1006–1016, https://doi.org/10.1111/cobi.12536.
[6] Burton, R. and G. Schwarz (2013), “Result-oriented agri-environmental schemes in Europe and their potential for promoting behavioural change”, Land Use Policy, Vol. 30, pp. 628-641, https://doi.org/10.1016/j.landusepol.2012.05.002.
[1] DeBoe, G. (2020), Economic and environmental sustainability performance of environmental policies in agriculture.
[7] Engel, S. (2016), “The Devil in the Detail: A Practical Guide on Designing Payments for Environmental Services”, International Review of Environmental and Resource Economics, Vol. 9/1-2, pp. 131-177, https://doi.org/10.1561/101.00000076.
[9] Hardelin, J. and J. Lankoski (2018), “Land use and ecosystem services”, OECD Food, Agriculture and Fisheries Papers, No. 114, OECD Publishing, Paris, https://doi.org/10.1787/c7ec938e-en.
[4] Lankoski, J. (2016), “Alternative Payment Approaches for Biodiversity Conservation in Agriculture”, OECD Food, Agriculture and Fisheries Papers, No. 93, OECD Publishing, Paris, https://doi.org/10.1787/5jm22p4ptg33-en.
[8] Moxey, A. and B. White (2014), “Result-oriented agri-environmental schemes in Europe: A comment”, Land Use Policy, Vol. 39, pp. 397-399, https://doi.org/10.1016/j.landusepol.2014.04.008.
[2] Savage, J. and M. Ribaudo (2016), “Improving the Efficiency of Voluntary Water Quality Conservation Programs”, Land Economics, Vol. 92/1, pp. 148–166, E-ISSN 1543-8325.
[3] Shortle, J. et al. (2012), “Reforming agricultural nonpoint pollution policy in an increasingly budget-constrained environment”, Environmental Science and Technology, https://doi.org/10.1021/es2020499.
Notes
← 1. The major differences between payments based on modelled environmental results and payments based on measured environmental results are that monitoring costs are lower for the former and there is no payment uncertainty due to external factors in the case of modelled results.
← 2. The aim of the policy simulations is to assess the cost-effectiveness of alternative policy designs, taking into account policy-related transaction costs and a range of different design features and a range of context-specific factors. The micro-economic modelling framework constructed in Lankoski (2016[4]) will form the basis for the policy simulations.