This article deals with the consequences of uncertainties about the societal valuation of landscape benefits and environmental costs for multiple policy goal trade-offs that may result when internalising external benefits and costs by abolishing commodity subsidies, introducing land subsidies and intermediate input taxes. Numerical results of an illustrative model of the German agricultural sector are presented and trade-off curves for farm income, environmental cost reduction and landscape benefits are discussed. If the relevant criterion for policy decisions was a simple aggregation of the single policy goal indicators with constant weights, the optimality of policy options would be rather robust to valuation errors.
Expected exchange ratios between the different policy goals, however, can be severely distorted if policy-makers have wrong estimations of the true societal valuation of externalities. This may make targeted incentives that aim at a better orientation of agriculture towards societal demands appear too risky for policy-makers and finally leads to the blockage of policy changes. An appropriate policy portfolio should therefore comprise non-distorting compensations for negatively affected policy goals. The EU’s commitment in the WTO to multifunctional agriculture has to be underlined by effective domestic policy reforms, if this concept is not to be discredited as an attempt to justify disguised protectionism.
Table of Contents
1 Introduction
2 Methodological approach
3 The base version of MULTSIM – a reference for analysing uncertainty
3.1 Valuation of externalities
3.2 Policy scenarios
3.3 Policy goal trade-offs
4 Implications of uncertain knowledge on the societal valuation of public goods and externalities
5 Conclusions for policy design
Research Objectives and Topics
This paper aims to numerically illustrate the implications of uncertainty regarding public good production and the societal valuation of externalities for agricultural policy design, specifically investigating how biased information affects policy goal trade-offs.
- Impact of valuation uncertainty on policy goal trade-offs
- Analysis of agricultural policy reform scenarios (commodity subsidies, land subsidies, input taxes)
- Numerical assessment using the MULTSIM model
- Evaluation of optimal policy design under uncertain knowledge
Excerpt from the Book
1 Introduction
The liberalisation of agricultural trade and the reduction of domestic support for farming are major objectives of the current WTO round. The European Union and many other developed countries like Norway and Japan fear, however, that important domestic policy objectives may be missed if their agricultural sectors are exposed to stronger international competition. They demand that so-called non-trade concerns (NTCs) are taken into account in the future trade agreement. The European Union favours the concept of a multifunctional agriculture, which emphasises that agriculture produces so-called non-commodity outputs as for example landscape amenities, maintenance of recreational areas, biodiversity and flood control. Common to most of these non-commodity outputs is that they possess characteristics of externalities and public goods, which are jointly produced with commodity output and not traded on markets. Since they are perceived as benefits for the society, it is often argued that the farm sector should not base factor allocation and production decisions on the basis of world commodity prices only and that, in addition, policy should create economic incentives that support farmers in producing such societal benefits. However, agriculture also produces societal costs as for example water pollution and soil erosion that are not completely internalised by farmers. The co-existence of positive and negative externalities and, in particular, their blurred valuation makes national and international policy design for multifunctional agriculture a complex task.
Chapter Summaries
1 Introduction: This chapter outlines the context of multifunctional agriculture, the role of non-trade concerns in WTO negotiations, and the research objective regarding the impact of valuation uncertainty on policy design.
2 Methodological approach: This section introduces the MULTSIM model, describing its functional relationships, farm types, and use of production elasticities to analyze agricultural policy impacts.
3 The base version of MULTSIM – a reference for analysing uncertainty: This chapter establishes the baseline by discussing valuation of externalities, detailing the specific policy scenarios used, and analyzing the resulting trade-offs between agricultural policy goals.
4 Implications of uncertain knowledge on the societal valuation of public goods and externalities: This section investigates how biased information about the societal valuation of environmental costs and landscape benefits affects the outcomes of policy decisions and overall social welfare.
5 Conclusions for policy design: This chapter summarizes the findings, highlighting the imbalance between the EU's commitment to multifunctionality and its current policy design, and suggests an appropriate policy portfolio to mitigate risks arising from valuation uncertainty.
Keywords
environmental costs, landscape benefits, multifunctional agriculture, valuation of non-marketable outputs, uncertainty, agricultural sector modelling, policy advice, WTO, public goods, externalities, policy design, social welfare, land subsidies, agricultural reform, trade-offs
Frequently Asked Questions
What is the core focus of this research paper?
The paper examines the consequences of uncertainty regarding the societal valuation of public goods and externalities in agriculture, specifically how this affects the design of policy interventions.
What are the primary thematic areas covered?
The research covers multifunctional agriculture, policy goal trade-offs (farm income vs. environment), the use of numerical modeling for policy support, and the implications of information deficits in policy design.
What is the main objective of the study?
The primary objective is to numerically demonstrate how policy-makers' decisions and resulting trade-offs are biased if they rely on incorrect estimations of the true societal value of environmental and landscape benefits.
Which scientific methodology is employed?
The study uses the quantitative supply model MULTSIM, which is based on a system of non-linear Kuhn-Tucker conditions to simulate various policy scenarios and welfare indicators.
What topics are discussed in the main body?
The main body discusses the MULTSIM model structure, compares different agricultural policy scenarios, analyzes trade-off curves between income and environmental indicators, and performs sensitivity analyses regarding valuation assumptions.
Which keywords best characterize the work?
Key terms include multifunctional agriculture, environmental costs, landscape benefits, uncertainty, agricultural sector modelling, and policy advice.
How does valuation uncertainty affect policy-making according to the model?
The model shows that while overall social welfare might be relatively robust, the exchange ratios between specific policy goals—such as farm income and environmental cost reduction—can be significantly distorted if valuations are incorrect.
What is the implication for the European Union's agricultural policy?
The paper suggests that the EU’s current policy fails to effectively target multifunctionality, often prioritizing farm income, which risks undermining the credibility of the multifunctionality concept in international trade negotiations.
Does the redistribution of budgetary savings influence the policy outcomes?
Yes, the analysis demonstrates that redistributing budgetary savings to farmers can significantly flatten the trade-off curves, making environmental improvements less costly in terms of farm income losses.
- Arbeit zitieren
- Gerald Weber (Autor:in), 2003, Uncertainty on Agricultural Public Good and Externality Production. Implications for Domestic and International Agricultural Policy Design, München, GRIN Verlag, https://www.grin.com/document/985991
