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Economics of Low Carbon Agriculture

Summary and Keywords

Climate change is already having a significant impact on agriculture through greater weather variability and the increasing frequency of extreme events. International policy is rightly focused on adapting and transforming agricultural and food production systems to reduce vulnerability. But agriculture also has a role in terms of climate change mitigation. The agricultural sector accounts for approximately a third of global anthropogenic greenhouse gas emissions, including related emissions from land-use change and deforestation. Farmers and land managers have a significant role to play because emissions reduction measures can be taken to increase soil carbon sequestration, manage fertilizer application, and improve ruminant nutrition and waste. There is also potential to improve overall productivity in some systems, thereby reducing emissions per unit of product. The global significance of such actions should not be underestimated. Existing research shows that some of these measures are low cost relative to the costs of reducing emissions in other sectors such as energy or heavy industry. Some measures are apparently cost-negative or win–win, in that they have the potential to reduce emissions and save production costs. However, the mitigation potential is also hindered by the biophysical complexity of agricultural systems and institutional and behavioral barriers limiting the adoption of these measures in developed and developing countries. This includes formal agreement on how agricultural mitigation should be treated in national obligations, commitments or targets, and the nature of policy incentives that can be deployed in different farming systems and along food chains beyond the farm gate. These challenges also overlap growing concern about global food security, which highlights additional stressors, including demographic change, natural resource scarcity, and economic convergence in consumption preferences, particularly for livestock products. The focus on reducing emissions through modified food consumption and reduced waste is a recent agenda that is proving more controversial than dealing with emissions related to production.

Keywords: agriculture, greenhouse gases, mitigation, policy


Carbon is a fundamental element of biological processes and farming; food production would be technically impossible without it. But the release of carbon dioxide (CO2) and other more powerful greenhouse gases (GHGs) such as methane and nitrous oxide are by-products of agricultural practices, which include land use change, the use of nitrogen fertilizers, and the rearing of livestock. Globally, these emissions have been increasing with rising food production and are estimated to contribute approximately 30% to anthropogenic greenhouse gas emissions (Le Quéré et al., 2015; Tubiello, 2014). Action on mitigation is therefore required, but several factors complicate the economics of identifying emission potential in the agricultural sector.

First, the GHG estimates can vary depending on the extent of land-use change emissions attributable to agriculture and the extent to which food product life-cycle impacts generated beyond the farm gate are actually counted. Either way, the potential contribution in some countries is high, and the sector is therefore under increasing scrutiny in terms of its potential contribution to emissions reduction.

Second, different forms of agricultural production (i.e., livestock versus arable) offer different mitigation opportunities, but the effectiveness of these measures is complicated by the biophysical and behavioral heterogeneity that characterizes global farm systems (Smith et al., 2008; IPCC, 2014). This means that the cost of achieving emissions reductions (i.e., cost per ton of carbon dioxide equivalent—CO₂e) will vary by measure and spatially, a factor that complicates the economics of mitigation. Nevertheless, the mitigation agenda can be clarified by some basic economic principles that include evaluation of the relative abatement potential of measures, the cost of implementing them, their likely external costs if implemented, and the nature of incentives and behavioral barriers that can lead to implementation at a significant scale. This economic and scientific agenda answers to some extent the key production side question, namely, the overall global abatement potential from farming systems. However, it is also important to recall that all production is ultimately consumed or wasted, and so several consumption or demand-side issues also warrant attention as part of the potential solution to mitigation in this sector.

Finally, it is important to set the mitigation agenda in the wider context of the importance of farming and food supply in national economic development in different countries, particularly developing countries, where rural subsistence and livelihood concerns, including adaptation, are more immediate constraints than emissions mitigation. This difference is recognized in the global policy architectures that define mitigation obligations differently. This reflects the fact that the obligation to seek emissions reductions needs to be balanced and informed by an understanding of the potential economic and social trade-offs implicit in altering production and consumption patterns.

While acknowledging the wider evidence on the emissions from food systems and the importance of life-cycle analysis, the focus here is on emissions generated within the farm gate. These are a subcomponent of the wider definition used in national emissions inventories that count emissions from agriculture land use and land-use change (ALULUCF). These distinctions are important for at least two reasons. First, the calculation of life-cycle emissions associated with the final product leads to the development of a different metric of emissions intensity—that is, the amount of GHG emitted per unit of output or input, for example, the kgCO2e/kg product or kgCO2e/ha/year. In the life-cycle methodology, emissions are included that take place outside of the farm. This is distinct from the measure of specific on-farm mitigation potential, which can be useful for benchmarking and for facilitating cross (food) system comparisons (Reisinger & Ledgard, 2013). Second, consideration of ALULUCF introduces the potential for significant natural offsetting or negative emissions potential by deploying afforestation and the potential carbon sink capacity of managed soils. In national emissions inventory protocols, these negative emissions need to be correctly recorded. Some may occur on farmland, but other nonagricultural land uses can offer negative emissions potential.

Global Policy

The need to respond to global climate change has focused attention on the main sources of emissions, with all significant sources coming under scrutiny (Worldbank, 2010; Wreford, Moran, & Adger, 2010). This is largely because developed countries (referred to as Annex 1 countries before the Paris Agreement [United Nations, 2015]1) have committed themselves to externally determined emissions reductions (mitigation) targets that must somehow be shared amongst polluting industries within their jurisdictional control. Agricultural emissions account for a significant share of emissions in many countries, including the United States, United Kingdom, Brazil, New Zealand, and Ireland. Overall, agricultural emissions are dominated by methane from enteric fermentation by livestock and nitrous oxide from crop and soil management. In some systems, there is also a small proportion of CO₂ emissions arising from energy use in heating and transportation. These gases are commonly expressed in terms of carbon dioxide equivalent (CO₂e) as a common metric for gases that have different global warming potentials.

In economic jargon, global GHG emissions are essentially negative externalities. The agent causing the emission imposes a cost on others, and there is no penalty or mechanism for those affected to be compensated. Ultimately, the emission of global greenhouse gases contributes to climate change scenarios and potentially compromises the welfare of billions of people. There is no obvious medium or market to redress or transact compensation, leading Stern (2007) to conclude that global warming represents the biggest market failure of all time. However, a collective institutional response to this failure exists under the auspices of the United Nations Framework Convention on Climate Change (UNFCCC) and successive global agreements on emissions reductions. Under these agreements, developed countries have signed up to binding emissions caps to be shared by responsible industries in the respective countries. Developing countries are largely outside this deal, with obvious implications for the external impacts from agricultural production in fast-growing countries such as Brazil, India, and China. Nevertheless, these countries are encouraged to make more voluntary commitments under specific modalities.

Developed countries have adopted different approaches to burden-sharing among polluting industries, including voluntary industry codes and accords, direct regulation, and the use of market-based instruments (MBIs). The most notable example of MBIs is the use of cap and trade schemes, which set overall GHG limits and then allocate emissions allowances or permits that can then be traded (Hood, 2010). The EU Emissions Trading Scheme (ETS) is perhaps the most well-established and highest volume trading regime to date. Despite teething problems in terms of initial allocations, trading volumes, and permit prices, such a system has experienced a relatively straightforward implementation, with initial allocations to polluting industries such as energy and transport. In these sectors, the origin of the emissions or so-called point of obligation is more easily identified and monitored. A central feature of a trading scheme is that trades allow the market to reveal an implicit carbon price, which provides a new benchmark for abatement costs for emitting sectors. Since polluters can now buy and sell extra permits on the market, the scheme provides a dynamic incentive for reducing emissions.

Globally, agriculture has been omitted from either direct regulation or any form of MBI. In contrast to other industries, the sector is more complex, with many thousands of small and medium producers giving rise to emissions from multiple diffuse sources (Figure 1). Difficulties in monitoring emissions from complex systems, together with forceful sector lobbying, have so far meant that the sector has passed under the policy radar. But this situation is becoming more conspicuous, with some studies (e.g., Radov, Klevnas, & Skurray (2007)) suggesting the feasibility of including large livestock producers in mandatory schemes that could feasibly focus on observable inputs (e.g., fertilizer use, animal numbers) rather than outputs. The threat of more direct regulation of MBIs has accelerated industry interest in confronting the emissions problem to head off more stringent government regulation. Agricultural sector bodies and farm unions have therefore promoted voluntary or self-regulating approaches, with industry-driven initiatives to monitor report and verify progress. It is becoming apparent that a voluntary approach is not yielding significant reductions. Furthermore, relatively high mitigation costs in other sectors increasingly draw attention to cheaper mitigation options in agriculture, and there is increasing research focusing on the technical, economic, and behavioral barriers to be overcome.

Mitigation Measures

The definition of agriculture includes all major livestock groups, arable and field crops and soils. The proportion of different emissions will obviously vary across farm systems and countries, and there is an extensive list of technically feasible measures for mitigating emissions in agriculture. For example, Smith et al. (2008) considered 64 agricultural measures, grouped into 14 categories. Measures can broadly be categorized as improved farm efficiency, including alternative animal feeds, selective breeding of livestock and use of nitrogen; replacing fossil fuel emissions via alternative energy sources; and enhancing the removal of atmospheric CO₂ via sequestration into soil and vegetation sinks. Some abatement options, typically current best management practices on fertilizer practices, deliver improved farm profitability as well as lower emissions and thus might be adopted in the baseline without specific intervention, beyond continued promotion, revision of benchmarking, and related advisory and information services.

Economics of Low Carbon AgricultureClick to view larger

Figure 1. The main on-farm agricultural greenhouse gas emission sources, removals, and processes in managed ecosystems.

Note: Carbon sequestration, including bioenergy, is not explicitly represented but may also play a significant role in the GHG balance.

Source: IPCC (11): 16.

Marginal Abatement Cost Curves

From an economic perspective, efficient pollution abatement policy requires an understanding of which abatement options are cheapest to implement. In other words, it requires a view of the marginal costs of abatement costs and preferably the marginal benefits (Figure 2). In the first instance, agricultural GHG mitigation efforts should systematically identify measures that achieve the desired reduction at least cost (i.e., are cost-effective). If marginal benefits are identifiable, then mitigation should be achieved up to the point that is socially efficient—that is, reducing emissions to the point where the costs of mitigation are equal to the social benefits of reducing the emissions. A range of studies have attempted to quantify the relative cost-effectiveness of mitigation measures (Vellinga et al., 2011; MacLeod et al., 2010). This information is frequently depicted on a marginal abatement cost curve (MACC), which approximates the theoretical construct in Figure 2 (MacLeod et al., 2010; Moran et al., 2011).

Economics of Low Carbon AgricultureClick to view larger

Figure 2. Marginal abatement costs and benefits.

For a given technical measure, optimal pollution abatement occurs where the marginal cost of abatement equals the marginal benefit, that is, where the two curves cross.

Bottom-Up versus Top-Down MACCs

MACCs can be constructed as bottom-up engineering models that compare in-field technologies or more top-down programming or partial and general equilibrium models. Programming models are used to show how farmers optimize the resources at their disposal, subject to technical and economic constraints. A MACC curve is generated by observing how production and resource use, and thus emissions, respond as a “price” is placed on emissions. Equilibrium studies take into account output and input price reactions as emissions are priced to derive a more policy-relevant abatement potential. Both top-down approaches tend to optimize using information on fewer mitigation measures applied in average farm conditions. Each approach has its strengths and weaknesses. Vermont and De Cara (2010) found that equilibrium studies tended to show higher abatement potential than estimates from the other two approaches. MACCs derived from programming or equilibrium modeling are less detailed and are often depicted as smooth curves, while those based on bottom-up or a cost-engineering approach typically consist of a series of discrete bars (Figure 3), each of which represents a mitigation measure. In this example, the width of each bar represents the reduction in GHG emissions, while the height of the bar shows the cost-effectiveness of the measure. The area under each bar is therefore equal to the total cost of the measure.

A bottom-up MACC can be constructed nationally or regionally and is typically more detailed in terms of the number of measures considered, enabling emission budgets to be set based on a collection of measures. The information also allows a comparison of the relative cost of mitigation across sectors and relative to any carbon price, which approximates the marginal benefit function of Figure 2. Key steps in MACC construction are: (1) short listing measures using existing literature and measure-specific expertise; (2) characterization of baseline practice and above-baseline applicability of each measure across the target spatial scale; (3) calculation of the abatement potential of each measure used independently and assuming potential measure interactions; (4) implementation of cost calculation considering private and social (i.e., external) costs where relevant; (5) identification of cost-effective (or economic) aggregate potential with and without life-cycle potentials; (6) consideration of wider (economic and ecosystem) effects of measure implementation; and (7) review of technical and institutional barriers to adoption (Moran et al., 2011).

Economics of Low Carbon AgricultureClick to view larger

Figure 3. Example of the marginal abatement cost curve (MACC) for UK dairy mitigation measures.

(On-farm anaerobic digestion: OFAD), adapted from MacLeod et al. (2015).

One strength of bottom-up MACCs is the identification of negative cost or win–win measures, which are ruled out in programming and equilibrium approaches. Thus, any measures on the left-hand side and below the axis imply that some GHG mitigation is possible at negative costs. In other words, the measure may also save money for the farm. Measures are then progressively more expensive until those on the right-hand side exceed the carbon price threshold and are thus excluded from any notional carbon budget until such time as their cost may be reduced.

Policy Development

In theory, the measures identified by the MACC are additional to an existing baseline or business as usual practice, and their implementation should not imply any significant loss in terms of reduced or displaced production. If all technically effective measures were implemented, then the MACC represents a full or maximum technical abatement potential. However, this upper limit of abatement is unlikely to be realized owing to other constraints. First, efficient policy will seek to limit implementation to the most economically efficient measures below the carbon price threshold, thus defining a lower economic abatement potential. This potential will in turn be reduced by the availability of appropriate policies to accommodate the specific measures. This reduced policy potential will be reduced further by significant behavioral barriers that limit on-farm uptake of some measures even where policy exists. Ultimately, in any country the residual feasible potential may be much lower than any technical potential.

The efficient carbon volume identified by the MACC is a normative ex ante representation of the mitigation potential of a sector if effective policy were to exist and if behavioral barriers could be overcome. If this were so, they could be deducted from the baseline emissions trajectory, for the agricultural sector, thereby leaving the so-called residual carbon budget or envelope within which the sector can operate, and/or contribute in terms of meeting an exogenous carbon emissions target. Government can use a variety of voluntary, mandatory, or market-based approaches to incentivize mitigation measures and thus remain inside this budget. The urgency of this policy agenda varies across countries, depending on the contribution of agricultural emissions relative to other sectors and the availability of relatively low-cost mitigation measures that are more easily quantified. It also varies between developed and developing countries.

Policy Options

In broad terms, approaches can be characterized in terms of carrots, sticks, or sermons; or the use of mandatory policy, more sophisticated market-based instruments (MBIs), or voluntary codes. In reality, these approaches can overlap.

Mandatory Measures

Mandatory approaches can involve carrots and sticks. The carrots include existing agri-environmental policies in member countries of the Organisation for Economic Co-operation and Development (OECD), which are increasingly being scrutinized for their ability to accommodate emissions reduction activities in addition to, or complimentary to, existing environmental cross-compliance requirements for farm support. Several governments are also seeing a role for new investment funds to promote renewable energy from anaerobic digestion of farm waste or afforestation. Other alternatives can include the use of mandatory farm carbon foot printing tools or soil testing kits that can improve productivity and therefore reduce the emissions intensity of production. Evaluation methods to monitor, report, and verify (MRV) compliance and mitigation outcomes are currently under development, and so there is limited information on how well mandatory approaches are performing. They are likely to remain an important part of the policy mix.

Market-Based Approaches (MBIs)

MBIs combine carrots with sticks, an approach that uses more punitive penalties or the enactment of the polluter pays principle applied to GHG. In theory, a carbon tax could be applied to livestock, based on animal numbers multiplied by relevant emissions coefficients. A theoretically equivalent outcome could also be derived from the use of an emissions trading system, which would require producers to hold emissions permits (initially allocated for free or by auction) to account for all their emission sources. These permits allow some flexibility in that those producers who are more efficient in managing their emissions could choose to sell to less efficient producers. Several countries (e.g., the UK, New Zealand, and Australia) have investigated the feasibility of such schemes in the livestock sector or for fertilizer supply chains; results suggest that only the largest producers could realistically be included in a scheme that would not be prohibitively expensive to administer. To date, no country has applied a comprehensive MBI approach to agricultural emissions.

An MBI element is nevertheless evident in the increasing development of voluntary carbon credit trading in the voluntary carbon market that sits alongside formal cap and trade schemes and can sometimes be allowed to trade into them. The voluntary credit market has developed to accredit carbon offsets in the forestry and renewable energy sectors, including biogas digesters often found on farms. Using this entry point, agriculture potentially offers certifiable emission-offsetting opportunities that can be traded with industries inside formal trading schemes that find it more costly to comply with their obligations. The carrot in this case is the development of voluntary credit schemes that permit such offsetting. Such schemes already exist—for example, in California, where a statewide cap and trade scheme admits agricultural offsets to be purchased by industries covered by the cap. This has led to the development of MRV and certification protocols for soil carbon management and the use of animal manures in anaerobic digesters. Similarly, the Canadian province of Alberta has been developing a carbon offset system founded on a compliance-based carbon offset market, with protocols developed for dairy system efficiencies (Haugen-kozyra, 2010).

Voluntary agricultural credits currently have no formal entry point to the ETS. But outside the scheme there is a nascent voluntary credit and offset market, which in theory is open to anyone who can offer valid emissions reductions to anyone who wants to buy them. The question of what constitutes a valid reduction is a crucial sticking point. Indeed, there is much uncertainty about how to verify the variety of agricultural emissions reductions as the basis of valid credits. This uncertainty is reflected in a variety of farm-based calculators, none of which can claim to be an industry protocol or standard. Even if a standard tool could be agreed upon, further concerns relate to the permanence of reductions and whether they are additional to what would have happened anyway. Ultimately, this means that voluntary contracts in agriculture are more complex and viewed as less reliable than, say, woodland credits, which are technically more verifiable and relatively permanent. This in turn means that such credits are likely to be valued much less than more definite emissions reductions from, say, forestry. Indeed, forestry offsets constitute the majority of early voluntary trades worldwide.

Voluntary Approaches

Despite the theoretical attraction of MBIs, most governments typically seek voluntary compliance as a lower-cost option than increased regulation of industry. Voluntary approaches can build on existing use of farm advisory services seeking to raise awareness of GHG mitigation actions overcoming informational barriers involving the adoption of win–win measures in particular. While several countries are currently engaged in this approach, the current lack of evaluation evidence is a specific evidence gap in our understanding of the reach of voluntary measures. Monitoring programs that stimulate voluntary measures is challenging. It is, for instance, impossible to measure the contribution of one program via national statistics, since national inventory indicators focus on total emission reductions and therefore cannot attribute the reduction to a specific measure stimulated by a voluntary measure.

Voluntary compliance is also challenging because a significant gap exists in our understanding of the relevant beliefs, motives, and behavioral responses of farmers in relation to the issues of climate change in general and to the narratives about their role in the problem and their moral or ethical responsibilities in terms of mitigation versus responding to equally powerful rhetoric on global food security. At this point, economic and psychological research converges in an attempt to identify behavioral segments and to develop appropriate methods to nudge pro-environmental behaviors. A significant effort has, for example, been directed toward understanding the adoption of no-cost or so-called win–win measures.

Monitor, Report, and Verify (MRV)

Scientific and policy discourse about the role and feasibility of agricultural mitigation is qualified by a lack of consistent MRV in all farm systems. As noted, MBIs can to some extent drive the development of MRV practices, but related uncertainties, both real and perceived, remain a sticking point in developing regulatory approaches and demand-side pressures for change. In economic terms, market failure is preceded by information failures at different levels, causing an asymmetry of information between producers, potential regulators, and consumers. This impedes the realization of the fullest mitigation from the sector.

At the highest level, field-scale measurement uncertainty drives a wedge between mitigation that is officially recorded in national inventories and a potential that includes measures that are currently not formally accepted. In essence, this reporting handicap limits policy development and hence the policy potential of several technically feasible mitigation measures. Improved scientific information brokered through the Intergovernmental Panel on Climate Change (IPCC) is a requirement for reducing this uncertainty and hence enabling policy.

The current policy hiatus also has an effect at the farm scale, where there is actually limited incentive to implement measures or comply with any MRV. This inevitably extends to the development of farm-scale tools to audit or “footprint” within farm gate and supply chain emissions. The availability of different, often competing, tools and thus potentially different market standards is symptomatic of the prevailing combined market and institutional failures. Without policy, there is limited private incentive to seek information to reduce uncertainty or to declare ones carbon status. This applies to farmers and consumers and ultimately influences the level of demand-side engagement. Consumers cannot see or demand what retailers do not (or choose not to) see and emphasize as a product attribute. Limited consumer demand in turn limits engagement with tools for labeling and the inclusion in corporate reporting.

Ultimately, the supply and demand side inertia is likely to be overcome by a combination of policy and private-sector approaches that drive informed behavioral change. Arguably, the behavioral challenges on the supply (or production) side are more tractable than changing consumer demand, with fewer producers dependent on a range of proximate government support schemes.

Behavioral Challenges

Uptake of win–win opportunities identified in MACC exercises conducted in several countries is the most egregious behavioral challenge for farm-scale mitigation. Such opportunities have been identified in other sectors, including energy and transport. For example, the installation of home insulation can lower bills and reduce emissions. Such messages are attractive and politically expedient. But win–wins present a policy challenge because they are often not adopted.

The literature on energy consumption, for example, reminds policymakers to “mind the gap” between a full technical potential that assumes all mitigation measures are fully implemented and the actual proportion of people who can realistically be expected to change their behavior (Dietz, Stern, & Weber, 2013). Reasons for this behavioral plasticity have been explored for that sector (Attari, 2010), but how the lessons might translate to other sectors has so far received less attention. However, such work is beginning in agriculture (OECD, 2012), where mitigation technologies and biophysical conditions are less certain and behavioral motivations may be different.

MACCs for agriculture typically reveal a suite of mitigation measures that make good business sense in reducing production costs and emissions (Moran et al., 2011). Yet, farmers are proving surprisingly reluctant to implement these measures. This inertia introduces a similar discrepancy between technical or theoretical potentials and how farmers actually behave. There are at least three possible explanations for this discrepancy.

First, closer scrutiny of the data suggests a mundane oversimplification of some commonly used cost and adoption assumptions that underlie MACC construction. This construction may show that specific measures such as nitrogen use efficiency or reduced soil tillage are, on average, cost-saving (or win–win) if implemented. In reality, farm finances, structures, and biophysical characteristics vary widely, reducing the significance of any average. Indeed, mean figures, often derived from limited experimental data, can mask the fact that implementation costs are actually positive for a significant proportion of farms. Thus win–wins based on averages will not apply to all farmers.

Second, transaction costs associated with (1) learning and implementing new techniques, and (2) MRV are, as suggested, absent or poorly recorded. They therefore remain largely unobserved by researchers identifying win–wins, as well as those using them to make policy prescriptions. A central issue, then, is whether MACC analysis can ever incorporate farm-level heterogeneity and whether all real costs can be accurately captured.

Third, and more fundamentally, nonadoption further challenges the rational-actor model that implicitly underpins win–win narratives and their use in policy. This assumes that individuals make rational decisions and act individually to maximize self-interest. Were this true, and assuming low transactions costs, farmers would quickly adopt win–wins, weighing the private costs and benefits of available options. In fact, a portfolio of research from the fields of experimental psychology, behavioral economics, environmental values, and management of the commons has long contested the assumption that human decision making is perfectly rational (Ostrom et al., 2002). Furthermore, situating this psychological evidence within an evolutionary framework adds a powerful dimension to understanding behavioral change, as well as providing a unique perspective on how farmers might be persuaded to mitigate climate change.

Social Learning, Cooperation, and Altruism

Gene-culture coevolution, or dual inheritance theory, suggests that the success of human beings as a species was heavily reliant on (1) high-fidelity social learning (Boyd, Richerson, & Henrich, 2011; Tennie, Call, & Tomasello, 2009), and (2) the development of strong instincts for cooperation and altruism (Chudek & Henrich, 2011; Tomasello, Melis, Tennie, Wyman, & Herrmann, 2012; Whiten & Erdal, 2012). With regard to high-fidelity social learning, theorists of cultural evolution recognize that a major difference between human beings and other primates is the human capacity for cumulative culture. Advanced imitation and teaching skills—greatly surpassing those of our closest evolutionary relatives—allow the transmission of cumulative improvements in knowledge (more complex than any one person could invent in a lifetime) faithfully to the next generation. The upshot is that humans are almost completely dependent on learning from others. Empirical studies and mathematical modeling suggest that individuals do not copy what others do randomly but, according to certain biases, such as conformity and prestige, that make social learning more adaptive.

Conformity refers to the tendency to do what others are doing. This may underpin the “social norms” effect documented in the psychological literature, whereby individuals can be induced to change their behavior by making the activities of others in the community visible (Cialdini, 2007). Prestige bias may have evolved from the propensity to copy successful others. A short-cut proxy of success is the amount of attention and deference an individual receives. This resonates with the diffusion of innovations literature, which demonstrates that behavioral change can be accelerated if “opinion leaders” (i.e., prestigious individuals) are targeted (Rogers, 2003).

Farmers may be particularly responsive to both conformity and prestige effects because, as is well known, they conduct “over-the-hedge” farming to advertise their “good farmer” credentials to peers (Burton, 2004). This tradition has great potential to be harnessed to aid social learning. Emulating schemes from the community-based social marketing literature that have successfully used visual symbols to motivate community change (McKenzie-Mohr Associates, 2003), carbon-certification flags could be placed in roadside fields. This may encourage social learning by contagion (i.e., the influence of neighboring farms), and with careful social network analysis, prestigious farmers could be targeted first.

Beyond the economic assumption of self-interest, contemporary theories of gene-culture coevolution suggest that individuals are endowed with cooperative inclinations. The resulting trade-off in human nature between self-interest and cooperation accords with a growing body of psychological research demonstrating that financial incentives actually diminish the human capacity for cooperation and altruism, accentuating tendencies toward independence and selfishness (Schwartz, 1992).

Such findings have led a group of influential nongovernment organizations, including the World Wildlife Fund, Oxfam, and the Public Interest Research Centre to initiate the “Common Cause” campaign. This move has popularized, for policymakers, the antagonism between altruism and self-interest long documented in the values literature. It argues that repeated messages appealing to “extrinsic values” (e.g., self-interest and financial gain) result in displacing “intrinsic values” (e.g., a sense of community, fair mindedness, and altruism) in society. Since climate change mitigation involves collective action for the public good (i.e., the recruitment of intrinsic values), it follows that it will not be best achieved through a “win–win” appeal to extrinsic values. Indeed, experimental evidence suggests that environmental messages far outperform both self-interested and win–win messages in effecting environmental behavior in individuals (Evans et al., 2013).

Behavioral Influences and Agricultural Mitigation

In agriculture then, an appeal to financial benefits may displace farmers’ intrinsic (or altruistic) motivations, which can be strongly held in relation to environmental stewardship. Farmers all over the world collaborate to contribute to ecological improvements in watersheds, forestry, irrigation, and wildlife management; studies of such collaboration reveal they are not motivated by self-interest (Pretty, 2003).

However, current agricultural policy offers further challenges to interventions based on both social learning and stewardship. Farmers’ custodianship motives are being countered by a dominant food security narrative that appeals to a production mentality. This narrative is further embedded in some forms of farm support payment in OECD countries. Further, climate skepticism about, and responsibility for, climate change is a dominant group norm (OECD, 2011) in a sector where peer recognition and legacy are more immediate concerns. Social kudos comes traditionally from ploughing straight furrows, displaying healthy animals, and planning for farm succession. In contrast, greenhouse gas mitigation actions are largely invisible to peers and the wider public. Indeed, such measures may be in conflict with traditional symbols of “good farming.” A system of social learning based on prestige and success is ill aligned with mitigation measures that are prescriptive and action based. As such, the measures may fail to promote innovation and new expertise. They are unlikely, therefore, to be successful in motivating farmers to engage in cultural exchange around their new environmental credentials.

These productivist issues sit alongside strong adherence to habits and routine and general loss aversion. Behavioral economics suggests that this is a recipe for heuristics or behavioral shortcuts that can be highly intransigent. They manifest themselves in the persistent overuse of low-cost inputs like fertilizer, a tendency that can be amplified by perverse policies such as input subsidization. Prospect theory (Kahneman, 2011) helps explain a more entrenched mentality where farmers are tacitly anchored to a reference point for their behaviors; they are less motivated by win–wins but more strongly influenced by incentive payments. In the European Union, for example, voluntary climate action is struggling to gain credence in the traditional institutional mechanism of incentive payments under the Common Agricultural Policy. Here, loss-averse farmers recognize an implicit property right to emit and are waiting to see what they will be paid rather than taking voluntary action that may not be rewarded retrospectively. Again, any intrinsic (or altruistic) capacity to work collaboratively is being inadvertently undermined by an extrinsically focused policy environment (i.e., one that appeals to self-interest). The overall result is that not just win–wins, but a whole package of cost-effective mitigation actions (e.g., all those that lie below the carbon price) are more difficult to implement.

Understanding the win–win narrative for agriculture in the context of psychological evidence and cultural evolutionary theory provides important behavioral caveats and insights for mitigation policy. A focus on social learning and peer exchange leads to understanding the importance of visibility of behaviors and the generation of prestige in the trading of cultural knowledge. The tension between cooperative instincts and self-interest helps to recognize the need to emphasize stewardship rather than the financial benefits of mitigation measures. These perceptions in turn suggest how the current institutional context for European agriculture could be reshaped to maximize potential from either voluntary or mandatory policy instruments for abatement.

Tying support payments to mitigation performance and making carbon explicitly negotiable may potentially separate carbon issues from property rights, while also helping to promote new innovation. Such a process could be supported by carbon labels for products or certified performance flags for farms that would encourage peer-to-peer learning. These would also serve as visual symbols of new expertise, which may help create a new vision of what is to be a “good farmer”—that is, moving from productivist behavior to stewardship.

Finally, an appeal to those values that are known to matter to farmers may increase buy-in and overcome the skepticism that has become a group norm. For instance, farmers’ preoccupation with inheritance could be broadened to refer to an environmental legacy in which they must secure farm viability in a carbon-conscious future. Moreover, framing mitigation measures within a package of adaptation guidelines may appeal to farmers’ growing concern about adapting to the changing weather. These multiple approaches, informed by psychological and evolutionary insights, should supersede a generic win–win narrative that is a politically convenient, yet overly simplistic and potentially counterproductive, basis for mitigation policy.

Mitigation–Adaptation Trade-offs

The implementation of mitigation measures at scale has the potential to contradict or negate other policy objectives, not least the need to develop resilience and adaptability to a changing climate. GHG mitigation has been elevated as a policy priority, but it is vital to understand the co-benefits and adverse impacts arising from such actions on our environment, economy, and society (IPCC, 2014). To the extent possible, it is important to reflect these costs and benefits in the MACC calculations. Beyond the overlap with adaptation needs, such side-effects could include other environmental effects (e.g., biodiversity loss or water pollution), effects on human health, or local and regional employment. Adopting a multiobjective perspective can help to identify areas where synergies make policies more robust and to mitigate the adverse impacts of policies that impose trade-offs (Wang & McCarl, 2013).

Activities related to land use can be particularly challenging because of multiple, often conflicting, societal needs. A prime example is land use itself, as it provides food, fuels, area for human settlements, and environmental benefits. Biological and chemical processes result in further need to consider trade-offs; for example, reducing one particular form of reactive nitrogen (e.g., NH3) might cause an increase in other forms of reactive nitrogen pollution (e.g., NOx or nitrogen leaching) (Sutton, 2011).

Integrated assessment models, which are used to integrate the main causes and effects of climate change, require the consolidation of the various environmental and economic processes and a framework to evaluate the potential solutions (De Bruin et al., 2009). For most economists, the ultimate end point is the human welfare effects, which are ideally quantified by translating physical effects (e.g., NH3 pollution or human health effects) into monetary values. Though difficult to obtain, such estimates already exist in relation to certain wider impacts and are important in impact assessment.

Developing Country Actions and Obligations

Much of our focus has been on the development of policy in developed countries, previously covered by Annex 1 commitments under the UNFCCC. But many developing countries are outside such commitments, meaning that the urgency of seeking mitigation in agriculture or any sector can take second place to broader development needs. In early UNFCCC debates, the issue of global equity and responsibility for past emissions led to considerable rhetoric about emission responsibilities and rights and the inherent (in)justices around the need to emit to secure economic growth. In recent discussions, this adversarial position, and the strict distinction between Annex I and non-Annex I countries, has been tempered by recognition of the need for developing countries to play a role in emissions reductions pending support from the international community (United Nations, 2015). Specific modalities, including Nationally Appropriate Mitigation Actions (NAMA) and Independently Nationally Determined Contributions (INDC) have allowed developing countries to identify voluntary mitigation opportunities across all sectors, including agriculture. These proposals are often advanced with a view to seeking financial support from bilateral multilateral or other donor sources. Other countries such as Brazil have made significant unconditional commitments in their INDC, which they see as consistent with domestic development goals. In the Brazilian case, this has involved significant investment in pasture restoration as a route to sustainably intensifying livestock production (de Oliveira Silva et al., 2016).

NAMA and INDC commitments are important because many agricultural systems in developing countries can offer significant low-cost emission and potential to offset emissions from other domestic sectors and internationally. Moreover, a growing area of research shows how some measures may be pro-poor in the sense of improving livelihoods and reducing emissions. A growing interest in Climate Smart practices (Steenwerth et al., 2014) has emphasized these climate (mitigation and adaptation) and growth synergies, although the actual evidence of the effectiveness of specific measures is still limited. Such potential is only likely to be unlocked with further research and technology transfer between developed and developing country researchers. INDCs are a window of opportunity for this exchange.


While focusing on the within farm gate emissions, it is impossible to ignore demand-side challenges related to the management of global food consumption, particularly emissions-intensive livestock products. Advocates of plant-based diets have been quick to point out the relative emissions intensity of livestock products and how other ancillary health costs essentially outweigh the social benefits of meat production (Stehfest et al., 2009). As well as meat consumption, demand-side messages can touch on how transport, storage, and cooking of meat products can all contribute to true life-cycle emissions reductions.

The topic is politically sensitive, and governments are understandably wary of tackling the behavior of millions of voters when they can more pragmatically target many fewer conspicuous producers. Moreover, most consumption or sustainable dietary advocates tend to point to evidence that is at best partial in consideration of the likely effects of dietary change. Such studies tend to consider change within one country or region, neglecting the likely general equilibrium or second-round effects, including relative price shifts and displacement of production from one part of the world to another, with no net overall reduction in the global external cost.

An interesting but wider political debate has highlighted the idea that national inventories should reflect both production and consumption emissions. That is, life-cycle emissions related to a product should be counted in the inventories of the country where final consumption takes place. This notion is in contrast to current production-based inventories and negotiations. Under a consumption accounting protocol, exporting countries are likely to see emissions liabilities reduced relative to countries with high imports of carbon-intensive products (Helm, Smale, & Phillips, 2007). Such a switch would be politically divisive, though clearly beneficial to some producing countries.


Reducing agricultural emissions is a challenge for both science and policy. However, much progress has been made in terms of understanding the measures that can be implemented on farms and communicating the basic economic criteria for developing an efficient policy for carbon reduction. Globally, the implementation of this agenda is differentiated between developed and developing countries, which is reflected in the differing requirements laid out in UNFCCC. This in turn reflects the countervailing challenges presented by the need to maintain food security as a more immediate social and political objective in many countries. A key challenge is to seek mitigation budgets that do not compromise sector productivity.

Analysis of marginal abatement costs in agriculture reveals a variety of technical, economic, and behavioral challenges that are specific to the sector and that require further research to avoid excessive generalization about the cost-effectiveness and acceptability of specific measures. While some behavioral constraints to the attractive win–win narrative that has characterized some debates about agricultural mitigation have been highlighted here, it is also important to emphasize the need for further research on horizon agricultural technologies, including the role of genetic modification (GM) as part of the solution to sector emissions. GM technologies are contested in many countries, and their cost-effectiveness is unproven. Their introduction as mitigation measures may eventually become unavoidable if agriculture is to play a significant role in global GHG mitigation.

Finally, it is important to reiterate that our focus has been on within-farm gate emissions. This tells a partial story of the emissions liability of the agri-food sector more generally. Agricultural products are either consumed or wasted, and in both cases and prior to this fate, products have a broader life-cycle story that includes emissions related to inputs, production processes, distribution, and storage. Product consumption also opens a variety of ethical and behavioral issues that have yet to be fully addressed by policy. While economics can have a role in demand management, the experience with putative sugar and fat taxes in the United States, Mexico, and Denmark is indicative of some of the likely resistance to demand management targeting GHGs. Instead, policy development ultimately requires engaging in a more delicate balancing act to identify the behavioral thresholds and tipping points, as well as appropriate tools and messages, to nudge pro-environmental choices. When it comes to food choice, economists need to be mindful of the behavioral approaches that changed social norms in relation to alcohol tolerance, smoking bans, and of seatbelt use.


We acknowledge funding from the UK Economic and Social Research Council (ESRC) under grant number ES/N013255/1. Dominic Moran also acknowledges HEFCE funding to the N8 Agrifood project at the University of York, UK.

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                                                                                              (1.) The United Nations Framework for Climate Change (UNFCCC) recognized the historical emission differences between developing and developed countries by labeling developed countries Annex I countries. The most recent agreement no longer makes this strict distinction (United Nations, 2015).