Chapter 1. Developments in agricultural policy and support

The key economic and market developments which provide the framework for the implementation of agricultural policies are analysed in the first part of this chapter. The next part presents the main recent changes and new initiatives in agricultural policies 2018-19 in OECD countries and key Emerging Economies. Then the developments in the estimated support (using the OECD Producer Support Estimate methodology) are evaluated in terms of its level, composition and changes over time in the OECD countries and Emerging Economies included in this report. The chapter also focuses on the sustainability performance of agriculture.

    

Key economic and market developments

Conditions in agricultural markets are heavily influenced by macro-economic variables such as global gross domestic product (GDP) growth (which supports demand for agricultural commodities) and energy prices, especially for crude oil (which determines the price of inputs into agriculture, such as fuel, chemicals and fertiliser, and influences demand for cereals, sugar crops, and vegetable oils through the market for biofuels).

Global economic growth has slowed in the latter half of 2018 amidst persistent trade tensions and declines in business and consumer confidence (OECD, 2019[1]). World GDP growth reached 3.5% on average, but developments across countries have diverged (Table 1.1). GDP growth in the OECD economies averaged 2.3%, compared to 2.6% in 2017, with large differences within the area. On the one hand, GDP growth slowed down significantly in the Euro area, as both external and internal demand softened, and in Japan, where it fell from 1.9% in 2017 to 0.8% in 2018. High corporate profits, capacity constraints and severe labour shortages in Japan stimulated investment, but industrial production and exports have been very weak recently. On the other hand, US economic growth increased further to reach 2.9% in 2018, as fiscal easing due to tax reform, higher government spending, elevated confidence and the strong labour markets continued to support demand (OECD, 2018[2]).

Despite moderate output growth, labour market conditions are improving in most OECD economies. The OECD-wide unemployment rate fell further to 5.3% of the labour force, which is below pre-crisis levels, and labour shortages are biting in some countries. In many countries, inflation remains moderate, although higher than in previous years on average in the OECD area.

Growth in the emerging economies is on average higher than in the OECD area, but even more contrasted across countries. In both India and the People’s Republic of China (hereafter, “China”), GDP growth, supported by domestic demand, remains strong. In India new infrastructure programmes and recent structural reforms boosted domestic demand growth, while in China growth slowed down due to lower growth in infrastructure investment and credit, the decline in working age population and trade tensions (OECD, 2018[2]). The economy in Brazil continued to grow at moderate rates in 2018. Some other emerging economies experienced temporary difficulties in 2018. In particular, the Argentinian economy plunged into recession in 2018 following a large depreciation of the peso, and the government sought support from the IMF tightening fiscal and monetary policies (OECD, 2019[1]).

Trade tensions have increased uncertainty and risk disrupting global value chains and investment, especially in regions tightly linked to the United States and China (OECD, 2018[2]). Global trade growth, which peaked at 5.5% in 2017, fell back to 3.9% in 2018, which is below the annual average in the period 2006-15. This slowdown is linked to increases in trade restrictions, in particular the higher tariffs on bilateral trade between China and the United States (Box 1.1 in OECD (2018[2])). Global investment, which had fuelled the expansion of emerging market economies, also slowed down as many of them are experiencing capital outflows and a weakening of their currency (OECD, 2018[2]). Higher (and more volatile) oil prices had a mild negative effect on global growth, and contributed to the higher inflation (OECD, 2019[1]).

Table 1.1. Key economic indicators

 

Average 2006-15

2016

2017

2018

Real GDP growth (%)1

World2

3.6

3.1

3.7

3.5

OECD2

1.5

1.8

2.6

2.3

United States

1.6

1.6

2.2

2.9

Euro area

0.8

1.9

2.5

1.8

Japan

0.6

0.6

1.9

0.8

Non-OECD2

5.8

4.3

4.6

4.5

Argentina

3.3

-2.1

2.7

-2.5

Brazil

2.8

-3.3

1.1

1.1

China

9.6

6.7

6.8

6.6

India

6.8

8.2

7.2

7.0

South Africa

2.7

0.4

1.4

0.8

 

OECD area

Unemployment rate (%)3

7.2

6.3

5.8

5.3

Inflation (%)1,4

1.8

1.1

2.0

2.3

World real trade growth (%)1

4.5

2.4

5.5

3.9

Notes:1. Percentage changes; last three columns show the increase over a year earlier.

1. Moving nominal GDP weights, using purchasing power parities.

2. Per cent of labour force.

3. Private consumption deflator.

Source: OECD (2019[1]), OECD Economic Outlook, Volume 2019 Issue 1, Preliminary version, https://doi.org/10.1787/b2e897b0-en. Last updated May 2019. OECD Economic Outlook 105 database.

World prices for primary non-agricultural commodities continued to rise in 2018 (Figure 1.1). Crude oil prices increased by 27% on an annual basis between 2017 and 2018, but started to decline in the fourth quarter of 2018. The increase partly reflected strong industrial demand as well as geopolitical risks and supply constraints (OECD, 2018[2]). However, prices are still considerably below the historical peaks of 2011-13, and hence did not induce increases in agricultural commodity prices.

Food commodity prices declined by less than 1% between 2017 and 2018, but by 4% between January 2018 and January 2019 (Figure 1.1). This decline results from a combination of higher cereal prices and lower sugar, meat and dairy prices, but with different trends by commodity within these groups as discussed below (OECD/FAO, 2019[3]).

According to OECD/FAO estimates, wheat and barley world prices increased between 2017 and 2018 due to lower world cereal production estimated for 2018, mainly driven by large, weather-related, falls in wheat and barley production in the European Union, the Russian Federation and Australia. But world prices for maize remained stable, despite the decline in stocks. Higher demand pushed rice prices up to its highest level since 2014 (OECD/FAO, 2019[3]).

Figure 1.1. Commodity world price indices, 2007 to 2018
Index 2002-04=100
Figure 1.1. Commodity world price indices, 2007 to 2018

Note: The top part of the graph relates to the left scale, while the bottom part of the graph to the right scale.

Source: IMF (2019[4]), Commodity Market Review, for all commodities, food and energy indices (base year: 2005), www.imf.org/external/np/res/commod/index.aspx; FAO (2019[5]), FAO Food Price Index dataset, for meat, dairy and cereal indices (base period: 2002-04), www.fao.org/worldfoodsituation/foodpricesindex/en.

 StatLink http://dx.doi.org/10.1787/888933935933

While soybean prices remained stable on a calendar year basis (World Bank Group, 2019[6]), the price for soybean seeds decreased in the second half of 2018 as world soybean production expanded in 2018, and feed demand declined (OECD/FAO, 2019[3]). The high levels of stocks among major exporters, coupled with market uncertainties related in part to trade talks between the United States and China, have influenced the price declines. Higher world production of sugar in 2017/18, combined with the long-term decline in consumption, have depressed world sugar prices in 2018. Cotton prices continued to increase in 2018, as world production fell in the 2018 marketing year. Limited water availability, pest problems and bad weather contributed this production decline, which mainly occurred in India, China and the United States (OECD/FAO, 2019[3]).

Average world meat prices, as measured by the FAO Meat Price Index (FAO, 2019[5]), decreased in 2018, reflecting the decline in pig and poultry meat prices, while the price of bovine meat remained stable, as higher supplies met strong demand. The spread of ASF and the consequent import restrictions weighed on international pig meat price quotations, while generally sluggish import demand caused poultry prices to decline. The price of sheep meat increased on world markets (OECD/FAO, 2019[3]).

World dairy prices, as measured by the FAO Dairy Price Index (FAO, 2019[5]), decreased in 2018 because of the increase in milk production in three major dairy product exporters, the European Union, New Zealand and the United States. Butter prices declined compared to their 2017 record level, but a pronounced increase appeared from mid-year, as demand for milk fat products remains strong in North America and Europe. Skim milk powder prices started to recover from low levels towards the end of 2018 as the European Union considerably reduced its intervention stocks (OECD/FAO, 2019[3]).

Recent developments in countries’ agricultural policies

Many policy developments announced or implemented in 2018 took place in the context of new multi-annual agricultural policy framework, changes in government, and re-orientation of policies. Others were in response to fluctuations in production and markets, market disruptions, natural disasters and pest and diseases. A number of countries introduced changes in food safety management, animal welfare requirements and labelling to improve information to domestic and foreign consumers. Actions were also taken to improve the functioning of the food chain, and to reinforce sustainability in food and agriculture, notably in the context of climate change mitigation. A number of countries also introduced institutional changes to consolidate organisations and clarify roles.

New multi-annual agricultural policy frameworks are generally in line with previous frameworks

In Canada, the new five-year framework for agricultural policy, the Canadian Agricultural Partnership (the Partnership) 2018-23, continues, with some changes to Business Risk Management (BRM) programmes and strategic initiatives introduced under the previous framework Growing Forward 2 (GF2) (AAFC, 2018[7]). In particular, support to research and innovation is split into two programmes, AgriScience and AgriInnovate, which support different elements of the innovation chain. In addition, the Partnership includes two new programmes: AgriAssurance aims to prevent and control risk to the animal and plant resource base, provide safe food and meet new market demands for assurance; AgriDiversity aims at increasing the capacity of youth, women, Indigenous Peoples and persons with disabilities to better participate in the agricultural sector. It supports skills, leadership, and entrepreneurial development, and facilitates knowledge sharing and best management practices. Provinces have started implementing new programmes within this framework.

In the United States, the Agriculture Improvement Act of 2018 (the 2018 Farm Bill) came into force in 2019 and will remain through 2023. The 2018 Farm Bill largely continues programmes under the 2014 Farm Bill, with few major changes to agricultural and food policies, but some adjustments that are noted in the following sub-sections. The 2018 Farm Bill continues significant changes to farm support programmes introduced by the Bipartisan Budget Act of 2018 (BBA) enacted in February 2018.

In Korea, the Agriculture and Rural Community and Food Industry Development Plan for 2018-22 foresees measures to strengthen the income safety-net via changes to direct payments, and the expansion of crop insurance programmes. The plan also includes support for young innovative farmers, the use of digital technologies along the value chain, and the promotion of renewable energy production. A number of provisions aim to enhance food safety and quality in the supply chain, as described in the corresponding sub-sections.

In Turkey, the 2018-22 Strategic Plan of the Ministry of Food, Agriculture and Livestock (MoFAL) was finalised during 2018. The main agricultural policy framework in the Russian Federation — the State Programme for the Development of Agriculture — was edited in 2018 to cover the period up to 2025. The main policy changes in these frameworks are below.

Newly elected governments defined new policy objectives or measures

In Chile, Colombia and Costa Rica, the new governments that came into office in 2018 defined new policy objectives for the coming four or five-year period, or announced new policy measures. Common emphases include the modernisation of institutions, the provision of public goods, the organisation of farmers and their integration in markets, better management of sanitary, phytosanitary and food safety risks, rural development, and improved productivity and sustainability.

In Mexico, the new government that took office in December 2018 lowered the 2019 budget allocated to agriculture, and announced new agricultural policy measures, which target small family farms with a view to increasing food security. They include cheap credits for livestock producers with smaller operations, and changes to price support and payments for small-scale farmers as described below. A new National Fertilizer Program aims to increase the domestic production of phosphate and nitrogen fertilisers, and to distribute fertilisers to small producers located in poor areas.

In Brazil, the new Government that took office in January 2019 has made two important decisions on agricultural policies. First, the Ministry of Agriculture, Livestock and Food Supply has taken over the responsibilities for small-scale family farming (see section on institutional changes). Second, in line with the macroeconomic directions of the new government, a resolution from the Central Bank in January 2019 changed the conditions for the allocation of part of the rural credit programmes that will be provided at market interest rates rather than preferential rates (see below).

Some countries reduced intervention on markets, while others increased support to producer prices

Among measures that support domestic market prices, changes in 2018 concerned minimum and target prices, stock management, output-based payments to producers, including deficiency payments, and supply management.

In China, the reforms initiated in 2017, with respect to the minimum purchase price system for wheat and rice, were continued and deepened in 2018. The minimum purchase prices for both wheat and rice were further lowered. In addition, adjustments were made to the guidelines for quality requirements in grain procurement and to the market price conditions for activating minimum price procurement of wheat and rice. In the European Union, previous measures to ease market conditions in the dairy, pig, and fruit and vegetable sectors were scaled down, and tenders took place to discharge SMP stocks.

In contrast, the central government of India increased the Minimum Support Prices (MSPs) in 2018 for all crops covered by the system. It also introduced additional schemes (such as a Price Support Scheme and a Price Deficiency Payment Scheme) to encourage the procurement of crops other than grains and cotton, such as pulses or oilseeds. Mexico introduced minimum prices for small producers of maize, beans, wheat and milk, with a cap on support by producer. Norway increased target prices from 1 July 2018 with a total budgetary effect of NOK 198 million (USD 24 million). In May 2018 the government of Mexico increased, by an average of 23%, the rates of payments based on output under the Objective Income programme.

Regarding supply management, the administratively allocated rice production quotas in Japan were abolished in 2018. Accompanying measures include support to farmers who shift from table rice to other crops (wheat, soybeans, and rice for feed and processing) using their paddy fields. The sugar quota regime in Ukraine was abolished in September 2018 with effect in the 2018/19 marketing year, and minimum prices for sugar beet within the sugar quota no longer exist. From 2018, agricultural producers no longer receive the price supplements previously paid to help them purchase farm inputs.

Some countries also changed measures supporting dairy markets. Israel signed an agreement with farmers to undertake a comprehensive reform of the dairy sector in October 2018. The outline of the reform includes a reduction of target prices, further reduction of customs tariffs and support for farmers leaving dairy production, and the introduction of subsidies for increasing the efficiency of dairy farms. The reform agreement requires a change in legislation to be implemented. In Switzerland, compulsory standard milk delivery contracts for all milk producers were extended for another four years, i.e. 2018-21. Since the abolition of the milk quota in 2009, these contracts set prices and quantities for different classes of milk, acting as another supply control mechanism but on a private basis.

Several countries introduced new direct payments, or extended existing ones

In Kazakhstan, area payments for crop production, and output and headage payments for livestock production were reduced, eliminating 20 out of 54 types of the payments. The remaining payments were simplified in order to shorten the application process for subsidies and to reduce corruption risks. The system of direct payments in Switzerland is maintained over the new programming period 2018-21. The main structural change is the gradual reduction of transitional payments, while the saved budgetary resources are shifted to finance payments to biodiversity. Following the abolition of export subsidies to processed food products from milk and wheat in 2019, budgetary savings will finance direct payments to milk and bread wheat to compensate the price reduction related to the elimination of export subsidies. In Mexico, payments based on area will target small and medium producers and include producers from indigenous communities from 2019. In addition, very small producers will receive payments per hectare. In Norway, support for areas with poor conditions for agricultural production and a new subsidy for small- and medium-sized dairy farms was introduced in 2019. In China, the programme encouraging crop shifting from maize to soybeans initiated in 2017 in the four Northeast provinces was extended to 2018-19.

As part of the Development Plan for 2018-23, Korea will introduce a new direct payment scheme combining the existing direct payments for rice, upland crops and less favoured areas. The government also aims to decouple payments further from production of a specific commodity, and to reinforce the cross-compliance of farmers. In February 2019, India introduced an unconditional income support payment to small-scale farmers, with landholdings of up to 2 hectares. Furthermore, several states announced significant packages for loan write-offs for small-scale farmers in 2017 and 2018 to reduce farm indebtedness. In Kazakhstan, a new seed subsidisation mechanism was introduced in 2018. The programme reimburses seed producers the full cost of producing the quality seeds distributed to farmers. In return, the farmers are required to return 30% of the subsidies to the Seed Development Fund, which finances the acquisition and modernisation of machinery and equipment for certified seed producers at preferential interest rates.

Risk management instruments were adjusted, extended or introduced

Canadian and US farm programmes include both direct payment and insurance programmes to help reduce farm income variability. The Canadian BRM programmes continue in the 2018-23 agreement. The 2018 US Farm Bill makes only limited changes to the Federal Crop Insurance Program (FCIP). However, there are new provisions that address conservation issues. Also in the United States, a number of changes made to disaster assistance and farm programmes, such as the Agriculture Risk Coverage (ARC) and Price Loss Coverage (PLC) programmes, and the Margin Protection Program for Dairy (MPP-Dairy) under the BBA came into effect (OECD, 2018[2]). In particular, the BBA established seed cotton as a covered commodity under the ARC and PLC programmes.

Various disaster payments were available to affected farmers. In New Zealand, they ranged from safety net support to loss compensations, to support for clearing ground after major flooding. In Norway, several measures were launched to help farmers with the consequences of drought during the spring and summer of 2018. They include payments and grants; a dispensation from the requirement to gather feed from pastures; an exemption for harvesting area with catch crops; and an exemption to retain grants for organically fertilised areas even if the pasture is used for feed or grazing instead of crops. Moreover, the advance compensation payment for crop damage increased from 50% to 70% of the total; import duties on hay were removed; and Crop Insurance Compensation support increased. In the United States, the BBA made a number of changes in eligible losses and payment limits to Supplemental Disaster Assistance Programs – the standing disaster programmes for livestock and trees, bushes, vines. EU and national disaster support was also available for farmers affected by disasters (floods and droughts) in different EU Member States. Several natural disasters in 2017 and 2018 provoked exceptional aid assistance in EU Member States, including payments, adjustment aid, tax delays, and the easing of greening conditions provided that they notified the Commission.

Several countries extended the coverage of subsidised agricultural insurance programmes to additional commodities, risks and farmers. Some Provinces in Canada extended the coverage of insurance programmes or introduced new ones. Chile increased the coverage of public agricultural insurance (Agroseguros) in particular to reach small and medium-scale farmers. Agroseguros also developed and implemented a catastrophic parametric insurance and has reactivated the price hedging programme for wheat and maize. Japan launched the Revenue insurance programme, which provides farm revenue protection against losses due to natural disasters or market price fluctuations. Korea increased the commodity coverage of the insurance scheme and lowered the minimum age of farmers to extend participation. Turkey extended the coverage of the agricultural insurance programme to more products and risks (barley, rye, oat and triticale due to drought, frost, hot winds, heat waves, excess moisture and excessive precipitation in 2018, and chickpeas, red lentils and green lentils in the beginning of 2019).

Several EU Member States introduced new risk management tools, and changes to existing programmes co-financed by the Common Agricultural Policy (CAP). Some also provided incentives to promote uptake of available tools. In early 2019, Austria reduced the tax rate (0.02% instead of 11%) for some insurance policies covering natural hazards in order to incentivise farmers’ uptake of insurance schemes. In France, changes were made to precautionary savings tax provisions. From May 2018, the focus of risk management approaches with respect to hail in Hungary shifted towards more preventative approaches in lieu of ex post compensation. In Italy, new risk management tools were offered to farmers, including the establishment of producer mutual funds, and extended protections against natural disasters, pests, and diseases. In Slovenia, the insurance premium subsidisation rate was raised in 2018. The government of Spain increased by 46% authorised funding for use in agricultural insurance in response to increased demand from producers in 2018.

In Viet Nam, crop and livestock producers will receive subsidies for insurance premiums of up to 20%, and up to 90% for producers classified as being in or near poverty. Enterprises that apply high technologies in large-scale agricultural production are eligible for insurance premiums subsidies of up to 20%. The types of events supported by insurance include natural disasters, animal diseases and plant pests. The government of Kazakhstan started to consider the transformation of the mandatory crop insurance system to a voluntary insurance scheme with a view to expand crop insurance markets in Kazakhstan. The new subsidy would cover insurance premium instead of indemnity. The creation of an electronic platform is planned to monitor fields based on remote sensing data, and thus facilitate the development of insurance products.

Incentives to facilitate or guide agricultural investment

Support to investment is an important form of support to agriculture in many countries, and has increased in several countries. In Brazil, as market interest rates continued to decline during 2018, the preferential interest rate margins were reduced or abolished, depending on the type of rural credit. In Canada, under a new Accelerated Investment Incentive, manufacturers, food processors and farmers will be able to deduct a larger portion of the depreciation in the year an investment is made. Kazakhstan reintroduced interest rate subsidies for acquiring fixed assets and leasing agricultural equipment and livestock. In addition, the rate of the investment subsidy is standardised to 25% of the cost of investment, except for pastures watering, where the subsidy rate remains at 80%. Korea introduced incentives for crop diversification away from rice production, in the form of support to drainage, seeds and agricultural machines. In Norway, support for investments and development programme was increased.

In Viet Nam, a number of preferential support measures were introduced to encourage enterprises to invest in agriculture and rural areas. They include exemptions from or reductions in land or water surface rents; preferential credit; support for the transfer and the application of high-technology in agriculture, human resources training and market expansion; and support for investments in facilities and equipment for processing or preserving agricultural products. In addition, the Government amended the credit policy for agricultural and rural development, doubling the loan amount available to farming households and farm owners without collateral. Hi-tech agricultural enterprises can also access credit without providing collateral, up to 70% of the project value.

Measures affecting land transfer were introduced or are envisaged

Some measures aimed to facilitate land transactions. In China, the 2019 Policy Document No. 1 calls for strengthened transparency of rural land transactions and for speeding up the establishment of a unified land market between rural and urban areas. For rural development, the Document foresees enhanced actions for improving rural living environments and public services; as well as for improving rural infrastructure (roads, electricity grids and logistics networks), enhancing pollution treatment and environmental protection. To facilitate the transition to a new generation of farmers, the Korean Plan for 2018-22 foresees enhanced direct payments for retirement, farmland pensions and basic pensions to encourage aged and low income farmers to retire, as well as support to young farmers.

In South Africa, following a series of policy changes aiming to enhance land redistribution, a 2017 Bill established a register of public and private agricultural land ownership. Under this Act, foreign persons cannot buy agricultural land and may only conclude long-term leases of agricultural land (30 to 50 years) and such leases must be registered in a Deeds Registry within 90 days. In March 2018, the Parliament voted a bill, which allows for the expropriation without compensation of the commercial farms (mostly owned by white farmers). In order to be applied in practice, this legislation requires a change in the Constitution.

New measures were implemented to enhanced sustainable management of pest and diseases

Measures to control pest and disease were taken in many countries. In response to the African Swine Fever (ASF) outbreak, in October 2018 China suspended the inter-province pig transport across 28 provinces, covering about 98% of China’s live pig production. In the European Union, different Member States implemented measures to combat the spread of ASF, including animal culls, physical barriers, informational campaigns, and swine movement restrictions. At EU level, the European Food Safety Authority (EFSA) recommended intensive hunting and quick carcass removal, also the European Union increased funding for knowledge and information platforms, and began soliciting proposals for an ASF vaccine. Since March 2018, Agriculture and Agri-food Canada (AAFC) has helped build public trust in the sector by facilitating the development of industry led assurance systems to respond to a variety of issues, including biosecurity and animal welfare. In 2018, plant and animal health partners across Canada established separate co-ordinating councils to implement priority activities identified in the “Plant and Animal Health Strategy for Canada” launched in 2017.

In 2019, Korea converted the regulation on pesticides to a positive list system, which aims to prevent overuse or misuse of pesticides, and sets maximum residue limits of registered pesticides. The criteria for breeding facilities in animal farms were tightened to prevent animal disease and manage animal product safety, and a comprehensive quarantine policy plan was established, focusing on prevention of animal diseases and policy measures to block the spread of diseases after outbreak.

In May 2018, the New Zealand Government and agricultural sector leaders agreed to work towards the eradication of Mycoplasma bovis, which was first detected in 2017. The Government will meet 68% of the eradication costs, with the two industry groups DairyNZ and Beef+Lamb New Zealand to meet the remaining 32%. The cost estimation includes losses of production borne by farmers, and the cost of the biosecurity response (including compensation to farmers), and the funding for scientific research to support the eradication programme. In the meantime, affected farmers can apply for compensation from the Ministry for Primary Industries, under the Biosecurity Act 1993.

Plans to improve the sustainable management of natural resources and environmental performance of agriculture were introduced or extended

Argentina established two important strategic plans aiming to preserve natural resources used in agriculture in 2018. One is to promote the integration of irrigation projects throughout the national territory, and the other to promote the conservation, restoration and sustainable management of agricultural soils. Both plans involve structural actions between different agencies and levels of government and private and international stakeholders. In addition, several regulations, including on the applications of plant protection products, minimum environmental protection requirements for the management of empty containers of agrochemicals and the prohibition of certain agrochemicals, aim to reduce the negative impacts of agriculture on the environment. In New Zealand, federal funding of irrigation investment projects is winding down. As part of the Development Plan for 2018-22, Korea plans to strengthen cross-compliance in the Direct payment scheme and to provide support for environmentally-friendly livestock production to reduce pollution. The plan also includes improvements in pesticide registration and traceability management systems. It will also promote renewable energy generation, including solar photovoltaic, biomass and geothermal heat. Some of the farmland regulations, which hindered the establishment of solar power facilities on farmland, have been alleviated in 2018.

The 2018 US Farm Bill makes no major changes to the suite of conservation programmes operated by USDA. Mandatory funding for conservation programmes is increased by a total of roughly 2% during 2019-23, but working land programme funding as a share of total conservation funding continues at the same level as under the 2014 Farm Bill, ending the shift in conservation programme funding towards working lands programmes that has held for the last three Farm Bills. In August 2018, USDA released a three-year action plan that outlines its priorities and goals for using current and future Farm Bill conservation programmes to help agricultural producers improve the water quality and overall health of the Chesapeake Bay watershed, which has been the focus of ongoing efforts to improve water quality and natural resources.

In October 2018, the European Union launched an updated bioeconomy strategy action plan designed to accelerate activities in line with the Paris Agreement and the 2030 Sustainable Development Agenda. Member States also develop national plans to shift towards agricultural production systems that are based in either the bio- or the circular economy, including endeavours to reduce food loss and waste.

Various actions aim to mitigate climate change and its effects

In response to Brazil’s commitments under the Paris Climate Agreement, the regulation of the national biofuel policy RenovaBio, approved in March 2018, sets a target to reduce emissions from fossil fuels by 10% in 2028. In pursuit of the objective to increase the use of biofuels and reduce petroleum as a source of energy, the biodiesel blending mandate was increased from 8% to 10% in March 2018, and increases by one percentage point per year were proposed, starting from June 2019 to reach 15% by 2023. In Brazil, support for reforestation activities has been expanded and farmers can obtain financing for investments in reforestation, at interest rates below the market rate.

Efforts towards a lower carbon agriculture continue. In Canada, the agriculture and agri-food sector’s contribution to the Pan-Canadian Framework (PCF) on Clean Growth and Climate Change will be primarily delivered through the Partnership. In addition, the 2018-21 Agricultural Clean Technology programme supports investments made by provincial and territorial governments in research, development and adoption of clean technologies for the agriculture, agri-food and agri-based products sector, specifically precision agriculture and agri-based bioproducts; and the Low Carbon Economy Leadership Fund supports a number of agriculture and agri-food related provincial projects with a focus on energy efficiency, soil health and carbon sequestration, manure management, and waste treatment and processing. In South Africa, the Carbon tax bill is an integral part of the system for implementing government policy on climate change. South Africa implements the Carbon tax through a phase-in approach. Primary agriculture is exempted from the carbon tax during the first phase covering 2017-20, but this may be reassessed in a second phase. Ukraine made further steps towards implementing its commitments under the 2016 Paris Agreement of the UNFCCC. In December 2018, the Cabinet Ministers of Ukraine approved the Concept for the implementation of the state policy on climate change for the period up to 2030 and the Action Plan on the Concept implementation. The multi-sectoral Action Plan foresees constant monitoring, reporting and verification of greenhouse gas emissions, emissions trading, the application of financial instruments for emission reductions, and mechanisms towards public-private partnerships. Much of the EU-wide action on climate change in 2018 was not specific to the agricultural sector, but instead addressed emissions more broadly. At the same time, support to fuel use in agriculture continues in many countries, and several EU Member States extended the scope and level of fuel tax rebates in 2018.

In September 2018, the government of Iceland launched a new Climate Strategy aiming for the country to be carbon neutral before 2040. The strategy consists of 34 measures ranging from the phasing out of fossils fuels in transport to measures aiming to increase carbon sequestration in land use (including limiting deforestation). The government will also support efforts to reclaim drained wetlands, which in recent years have been shown to be a significant source of carbon emissions. A collaboration with sheep farmers is expected to be launched in 2019, with the goal of increasing carbon sequestration within the sector. In Norway, the revised National Environmental Programme gives higher priority to climate change challenges, while work continues on simplification and enhancement of goal-orientation of programmes.

Australia and Turkey made efforts to improve drought resilience. In 2018 the Government of Australia announced a range of initiatives that aim to increase the agricultural sector’s resilience to drought. The Australian Government appointed a Coordinator General for Drought to provide advice on developing a long-term drought resilience and preparedness strategy, and a new National Drought Agreement was signed between the Commonwealth and the states and territories, continuing to shift the policy framework towards prioritising long-term preparedness, sustainability, and resilience and risk management. In Turkey, the 2018-22 Strategic Plan of the Ministry of Food, Agriculture and Livestock (MoFAL) gives particular attention to increasing efficiency of water use in agriculture. An Agricultural Drought Strategy and Action Plan covering 2018-22 was published. Activities in the Action Plan are grouped under five headings: 1) drought risk estimation and crisis management; 2) ensuring sustainable water supply; 3) effective management of agricultural water demand; 4) increasing support to R&D activities, and training and extension services; and 5) institutional capacity building.

Actions were taken to improve the functioning of the food chain

A mandatory code of conduct is being developed in Australia for the dairy sector, in response to a multi-year inquiry by the Australian Competition and Consumer Commission (ACCC) into the state of competition in the sector. The inquiry concluded that there are some market competition issues within the industry, particularly in relation to the dynamics between producers and processors. The Government of Canada is currently developing a federal food strategy “A Food Policy of Canada”, which is expected to address issues such as increasing access to safe, nutritious and culturally appropriate food; supporting food’s contribution to human health; promoting environmental sustainability, resilience and conservation; and building a strong agriculture and food sector. AAFC (2018[8]) published the results of a consultation of stakeholders supporting the development of the food strategy. France enacted in November 2018 the Law to promote balanced commercial relationships in the agricultural and food sector and healthy sustainable food. In parallel to several provisions aiming to improve sanitary and environmental conditions in production, it reinforces the producers' negotiating stand with the distribution sector, on the basis of "indicators of reference" for production costs and market variables agreed among actors in each commodity sector. A committee was set up to monitor commercial transactions.

In China, the 2018 Foreign Investment Industrial Guidance Catalogue removes restrictions on foreign investment in the processing of maize, rice, flour, oilseeds and sugar. In Viet Nam, a decree provided for support for the organisation developing value chain linkages for the production and sale of agricultural products, including support to hire consultants. A given linkage project may also receive support for investments in machinery, equipment and infrastructural facilities serving the linkage, as well as subsidies for agricultural extension and training, and for plant varieties, livestock breeds, packaging and labels. The government also approved a scheme for developing 15 000 efficient co-operatives and unions of co-operatives. The scheme aims to improve the operating efficiency of existing agricultural co-operatives; establish an additional 5 200 co-operatives, and promote the application of high technology by co-operatives.

New regulations were developed, mainly to improve the efficiency of food safety procedures, and clarify the labelling of food characteristics

Regarding food safety, the Canadian Food Inspection Agency has developed the new Safe Food for Canadians Regulations (SFCR), which came into force on 15 January 2019. The SFCR focuses on prevention and allows for faster removal of unsafe food from the marketplace. During 2018, the State Service of Ukraine for Food Safety and Consumer Protection resumed its official controls and veterinary checks, following the entry into force of the “Law on State Control for Food, Feed, Animal Health and Animal Welfare” in April 2018.

On food labelling, several countries adopted regulations to clarify information for consumers. The European Parliament and Council endorsed a new regulation that will apply from 1 January 2021, aiming to harmonise rules on organic production across Member States, improve competition and prevent frauds. Ukraine adopted a Law “On Foodstuff Information”, and a Law “On the Basic Principles and Requirements for Organic Production, Circulation and Labelling of Organic Products”. The Russian Federation adopted its first law on organic products, which is to take effect on 1 January 2020. It will regulate manufacturing, storage, transportation, labelling, and marketing of organic products.

On 20 December 2018, the US Secretary of Agriculture announced the National Bioengineered Food Disclosure Standard for disclosing foods that are or may be bioengineered. The Standard defines bioengineered foods as those that contain detectable genetic material that has been modified through certain lab techniques and cannot be created through conventional breeding or found in nature. The implementation date of the Standard is 1 January 2020, and one year later for small food manufacturers. The mandatory compliance date is 1 January 2022.

In France, an experimental programme that introduced labelling of origin of milk and meat in processed food has been renewed through March 2020. A similar regulation entered into force in Spain in January 2019, requiring food manufacturers to indicate the origin of milk, and milk products. Outside of the dairy and livestock sectors, Italy introduced mandatory country of origin labelling on rice in February 2018.

In 2018, substantial policy change was made with respect to the usage of neonicotinoid insecticides in EU Member States. On 27 April 2018, EU Member States voted on a total ban of three of these products for outdoor use beginning in December 2018. In May 2018, the European Court of Justice confirmed the Commission’s discretion to regulate these pesticides under the precautionary principal given updated risk assessments and upheld earlier restrictions on the products that were first put in place in 2013. France went further, banning the use of five neonicotinoid pesticides for both indoor and outdoor use beginning in September 2018. At the same time, producers in several countries applied for emergency exemptions from the regulation, based on the current lack of commercially available alternative products.

The Cannabis Act, which came into force in Canada on 17 October 2018, provides a strict legal framework for the production, distribution, sale, and possession of cannabis in Canada. Producers of cannabis need to be federally licensed to operate. The cannabis industry is eligible to apply for federal programmes under the Partnership.

Several countries are strengthening animal welfare regulations

A number of large exporters reviewed their animal welfare regulations. The Government of Australia concluded a review into the Australian Standards for the Export of Livestock (ASEL). This review recommended mandatory animal welfare outcomes, better reporting and increased transparency of exporter performance, and the institution of penalties when ASEL requirements are not met on export voyages. Across Canada, animal welfare and public trust issues have become more important and have led some provinces to develop new programmes. For example, the Ag Action Manitoba Assurance programme supports the ethically sound treatment of animals by providing assistance for the adoption of monitoring, training, equipment and facility upgrades that support improved animal care. New Brunswick promotes agriculture awareness at trade shows, seminars and school events through the Agriculture Awareness programme. In New Zealand, since the Ministry for Primary Industries has the ability to make animal welfare regulations, the regulatory programme is being developed and implemented in three tranches. The set of regulations introduced in 2018 relate to stock transport, farm husbandry, companion and working animals, pigs, layer hens, rodeos, surgical or painful procedures, inspection of traps, and crustaceans. The final substantive package of regulations focuses on significant surgical procedures and is due to be completed in early 2020.

Importers are also making efforts to improve animal welfare. Israel is seeking ways to reduce its reliance on imports of live animals and improving the welfare of animals imported by sea. In particular, in 2018, the government implemented the extension of shelf life of chilled meat imports to 85 days, enabling imports of meat from distant origins. The Korean Development Plan for 2018-22 foresees the development of a comprehensive animal-welfare road-map to provide standards for facilities, maintenance and rearing density, and the development of a labelling system informing consumers about animal welfare and health in each livestock farm.

Efforts to strengthen agricultural innovation systems continue

In Colombia, at the beginning of 2018, twelve programmes were created directed mostly on land restructuring and extension services. Chile’s animal and plant health institution (SAG) developed a plan to modernise inspection process using a web/mobile platform that has a single repository of audits, with gradual change from the use of paper to mobile equipment kits. The Chilean Food Safety Agency (ACHIPIA) initiated information campaigns for consumers about associated risks with food, and developed methodologies that allow continuous education of the population on food risks and food safety. Kazakhstan restructured the agricultural R&D system in 2018, consolidating 23 Research Institutes (SRI) to twelve, and increasing the number of agricultural experimental stations. In addition, business associations have participated in making decisions on the financing of R&D projects with a view to introduce co-financing schemes in R&D projects.

In Austria, the Federal Institute for Agricultural Economics merged with the Federal Institute for Less-favoured and Mountainous Areas early in 2019. In October 2018, the French government announced the proposed merging of two agricultural research institutes, the Institut national de la recherche agronomique (INRA) and the Institut national de recherche en sciences et technologies pour l’environnement et l’agriculture (IRSTEA) into a single research organisation for agricultural, agronomic, and environmental issues. In March 2018, the European Commission’s Joint Research Centre announced the future creation of a Knowledge Centre on Food Fraud and Quality in response to consumer concerns about food quality and fraudulent practices concerning food.

The digitalisation of rural areas received increasing attention

The European Union reaffirmed their commitment to the digitalisation of rural areas through the issuance of the Bled Declaration in April 2018 and work on digitalisation progressed in Member States. The Austrian Federal Ministry for Sustainability and Tourism prioritised farmer access to digitalisation and training for young farmers by setting up a digital model farm (the so-called “Innovation Farm”) and establishing a new five-year study programme focused on agriculture and the digitalisation of secondary schools (beginning in the coming school year). In Spain, a revised Rural Development Plan provides funds to create and implement innovative projects in rural areas from 2018 and an Agenda for the digitalisation of the agro-food, forestry, and rural sectors is under preparation for 2019. In the Russian Federation, digital agriculture is a new component of the State Programme for the Development of Agriculture for 2018-25.

Institutional consolidation is taking place

In 2018-19, a few countries introduced changes in the governance of agricultural policy. In Argentina, the Ministry of Agroindustry became a Secretariat of Government under the Ministry of Production and Labour. In Brazil, the Ministry of Agriculture, Livestock and Food Supply has incorporated the responsibilities for small-scale family farming and related support. These had been under separate authorities reporting directly to the Presidency since 1999. In 2018, Turkey merged the Ministry of Food, Agriculture and Livestock (MoFAL), and the Ministry of Forestry and Water Affairs to form the Ministry of Agriculture and Forestry. In Spain, the management of water changed as follows: the management of water (supply) was shifted from the extinct Ministry of Agriculture Food and Environment to the new Ministry of Ecological Transition and the management of irrigation is a competence of the new Ministry of Agriculture, Fisheries and Food.

Institutional consolidation also took place in China. The Ministry of Agriculture and Rural Affairs (MARA) superseded the Ministry of Agriculture (MOA) and the Ministry of Ecology and Environment superseded the previous Ministry of Environmental Protection. In addition, the National Food and Strategic Reserves Administration (NFSRA), a vice-ministerial agency affiliated with the National Development and Reform Commission (NDRC), is now responsible for overseeing the strategic reserves of wheat, rice, maize, oilseeds, cotton, sugar, natural gas, and petroleum, previously under separate organisations. Similarly, the State Administration of Market Regulations (SAMR) consolidates in one agency the market regulation functions previously shared by three separate bodies.

In Mexico, the Secretariat of Agriculture has been renamed Secretariat of Agriculture and Rural Development, and the headquarters were decentralised. The new Secretariat is structurally smaller and for 2019 will operate with a budget 20% smaller than the previous year. In addition, a single agency, resulting from the merging of two organisations, will be in charge of administering the minimum price support programme and the distribution of fertiliser according to the National Fertilizer Program.

Import bans and changes in tariffs occurred outside trade agreements.

As of July 2018, China removed tariffs on soybeans (from 3%) and soybean cake (from 5%) imported from Bangladesh, India, Laos, Korea and Sri Lanka. In October 2018, China also allowed imports of rapeseed meal from India, subject to certain inspection and quarantine requirements. China restored market access for chilled and frozen beef for France, Ireland, and the United Kingdom, after banning such products in the 1990s due to the Bovine spongiform encephalopathy (BSE) outbreaks. During 2018, China implemented tariffs on United States-origin products, which included a large number of agricultural and food products, such as soybeans (25% tariff), wheat, sorghum, cotton, milk, pig meat and pig meat products, fresh and dried fruits, tree nuts, wine, ginseng, and denatured ethanol.

India increased the tariffs for wheat, chickpea and sugar in 2018, up to 30%, 60% and 100%, respectively. The European Union revised downward import tariffs for maize, sorghum and rye that had been introduced in August 2017 in response to lower prices, and set them to zero again on 3 March 2018 as prices for cereals rose. In September 2017, South Africa lowered wheat import tariffs and maintained them in 2018.

In 2018 existing imports bans or restrictions were extended, and new ones were introduced. For example, the Russian Federation ban on agro-food imports from the European Union, the United States, Canada, Australia, Norway and several other countries, initially introduced in 2014, was extended until 31 December 2019. Mutual trade restrictions between the Russian Federation and Ukraine continued. On 29 December 2018, the Russian government prohibited importation of certain agricultural goods from Ukraine and their transit through the territory of the Russian Federation. Ukraine continued prohibiting imports of a broad range of agro-food imports from the Russian Federation until 2020. In June 2018, the European Union suspended the application of import duty concessions under the GATT 1994 to the trade of the United States and imposed additional import duties of 25% to a list of 182 products of US origin defined at the CN 8 digit level, of which 21% are food and non-alcoholic beverages.

Changes in trade measures also affected exports, including support to mitigate the effect of tariffs

From 1 January 2019, Switzerland implemented the legislation abolishing export subsidies on processed food products. The Argentinian government established temporary (until end of 2020) taxes on all exports, including agricultural products, reverting the progressive elimination of all non-soya export taxes initiated in 2015. These export taxes are an emergency measure to raise government revenue and reduce the budget deficit following the economic crisis in 2018. In Brazil, the elimination of the tax on leather exports leaves most agro-food products free of export taxes.

In July 2018, the US Department of Agriculture announced a package of trade mitigation programmes to assist farmers affected by recently imposed tariffs that resulted in the loss of traditional export markets. The package included three programmes: the Market Facilitation Program (MFP), the Food Purchase and Distribution Program (FPDP), and the Agricultural Trade Promotion Program (ATP). The MFP provided payments to producers of eight commodities — soybeans, cotton, wheat, sorghum, hogs, milk, fresh sweet cherries, and shelled almonds — directly impacted by tariffs during the 2018 crop year, resulting in the loss of traditional export markets. The FPDP provides for purchases in other commodities affected by tariffs. The ATP will provide cost-share assistance to eligible US organisations to develop foreign markets for US agricultural products through activities such as consumer advertising, public relations, point-of-sale demonstrations, participation in trade fairs and exhibits, market research, and technical assistance.

A number of regional and bilateral trade agreements were signed

On 30 November 2018, the United States, Mexico, and Canada signed a new trade agreement, which will replace the North American Free Trade Agreement (NAFTA) once ratified by all three countries. The agreement creates new market access opportunities for United States exports of dairy, poultry, and eggs to Canada, and in exchange the United States will provide new access to Canada for dairy, peanuts, processed peanut products, and a limited amount of sugar and sugar containing products. All other tariffs on agricultural products traded between the United States and Mexico will remain at zero.

The Comprehensive and Progressive Agreement for a Trans-Pacific Partnership (CPTPP) came into force on 30 December 2018 among Australia, Canada, Japan, Mexico, New Zealand, and Singapore, followed by Viet Nam in January 2019. CPTPP will represent 13.5% of global GDP when fully implemented by the rest of member countries (Brunei, Chile, Malaysia, and Peru). This agreement contains a number of provisions on agriculture, with expanded market access for a range of products in the various member countries, including reduced Japanese beef tariffs; new access to dairy products into Japan, Canada, and Mexico; and the elimination of all tariffs on sheep meat, cotton, and wool. It covers nearly one-fourth of New Zealand’s good and services trade and almost a fourth of its exports of agro-food products. Viet Nam has committed to a schedule for tariff elimination and reduction for imports of some agricultural goods.

The Treaty on the Eurasian Economic Union (EAEU), which groups Belarus, Kazakhstan, Armenia, Kyrgyzstan and the Russian Federation, signed trade agreements with Iran and China during the Astana Economic Forum on 17 May 2018. The part related to agriculture of the interim agreement with Iran foresees a reduction from 25% to 100% of EAEU import duties on a broad range of products imported from Iran, notably, certain fish products, vegetables and fresh and dried fruits. The EAEU will enjoy from 20% to 75% tariff reductions on products such as beef and veal, butter, certain confectionery and chocolate, mineral waters, oil and fat products. Articles of relevance to agricultural trade in the agreement on economic and trade cooperation between the EAEU and China include transparency, technical barriers to trade, sanitary and phyto-sanitary measures, trade facilitation, and sectoral cooperation including in agriculture.

In February 2018, the EU-South African Development Community Economic Partnership (EU-SADC) came into force. While the agreement is largely intended to provide improved access for SADC countries to the EU market, it also provides greater access for some EU products into SADC.

On 1 February 2019, the EU-Japan Economic Partnership Agreement (EPA) entered into force. The agreement substantially reduces tariffs and trade barriers for both partners. The European Union is scheduled to eliminate duties on 99% of imports from Japan. Tariffs on beef, tea, alcoholic beverages and other priority products are to be eliminated (most upon the agreement’s entry into force). Once fully in place after 21 years, the agreement is set to liberalise tariffs on 85% of the EU’s agro-food products exported to Japan, including the elimination of duties on 90% of agricultural products. Additionally, tariffs on hard cheeses and processed agricultural goods like chocolate, pasta, and tomato sauce are to be eliminated over time. For pork and beef, tariffs are reduced over time, but not fully eliminated. Finally, improved EU access to the Japanese market is also secured under the agreement through the establishment of country-specific TRQs for products including wheat and wheat flour, barley and barley flour, malt, butter, skimmed milk powder, and soft cheeses. Duties and trade restrictions on rice, however, were excluded from the negotiations. Aside from market access, the agreement establishes recognition of more than 200 EU Geographical Indications (GIs), as well as more than 50 GIs for Japanese wine, spirits and food products.

The European Union and Viet Nam reached an agreement on the final text for a bilateral free trade agreement in July 2018, with the agreement awaiting signatures and conclusion. The agreement includes the progressive elimination of duties on many major EU exports to Viet Nam, including for chicken, dairy, beef, wine, spirits, chocolate, pasta, apples, wheat, and olive oil. Protections for nearly 170 EU GIs are also included in the agreement.

Revisions to the European Economic Area (EEA) agreement, which links the EU Member States and three European Free Trade Association (EFTA) states (Iceland, Liechtenstein, and Norway) were finalised and entered into force in May and October 2018 for trade with Iceland and Norway respectively. The revised agreements improved agricultural market access for several commodities for all parties, including increased and new tariff rate quotas.

The Korea-US FTA negotiation amendment came into effect in 2019. Israel and Ukraine signed an FTA in January 2019, with pending ratification of the signatories. In 2018, Israel signed a FTA with EFTA, Turkey signed the Free Trade Agreements (FTA) with Venezuela and Qatar. In 2018, Kazakhstan and China signed a number of sanitary and phytosanitary protocols on the export of agricultural products, including beef, rapeseed and alfalfa. Australia concluded negotiations for three FTAs in 2018, with respectively Peru, Indonesia and Hong-Kong, but they have yet to enter into force. These agreements secure tariff reductions or new quotas for some of Australia’s most important agricultural exports, including beef, sheep meat, dairy, and sugar.

The European Union and Mexico reached an “agreement in principle” in April 2018 to modernise their existing trade agreement (which had been in place since 2000), superseding it with the EU-Mexico Global Agreement. The revised agreement will further liberalise agricultural trade between the two partners, including eliminating Mexican tariffs on many EU agricultural exports (including pasta, chocolate, apples and pork products), and creating duty-free TRQs for milk powder, other cheeses, and fresh and processed cheeses.

Trade negotiations continued or were launched

Major steps occurred in the negotiations on the EU-Mercosur Free Trade Agreement (FTA) between the European Union and the countries of Mercosur (Argentina, Brazil, Paraguay and Uruguay), which started 20 years ago. By the end of 2018, the parties had agreed on 12 of the 15 chapters in the agreement. Other countries like Canada, Korea and the European Free-Trade Association (EFTA) are also discussing trade agreements with Mercosur.

In June 2018, negotiations began for two bilateral free trade agreements between the European Union and Australia and between the European Union and New Zealand. On 16 October 2018, the US Trade Representative notified the US Congress that the Administration intended to initiate negotiation on trade agreements with the European Union, Japan, and the United Kingdom. In April 2019, European Union countries approved the conditions for negotiating a new and strictly limited trade deal with the United States, paving the way for talks to begin.

While trade agreements facilitate trade between signatories, countries covered in the report are parties to a number of on-going trade disputes, which affect trade flows.

Developments in agricultural support

This section provides a quantitative assessment of developments in policy support to agriculture in 2018, and compares policy support in recent years (2016-18) with support provided to the agricultural sector in the early 2000s (2000-02). It covers the 36 OECD countries as well as the five non-OECD EU Member States and twelve emerging and developing economies. In much of this report, the European Union is presented as one economic region.

Two additional emerging economies are included in the 2019 report: Argentina and India. Box 1.1 provides a brief overview of agricultural policies in the two countries, and the impact of their inclusion on aggregate indicators of support for countries covered in the report.

Box 1.1. The inclusion of Argentina and India improves significantly the coverage of agricultural support in the report

Argentina and India account respectively for 3.1% and 3.7% of world’s agricultural land. The inclusion of the two countries increases agricultural land coverage in this report from 55% to 61% of world total.

Agriculture is an important sector in both countries, in India because of its high share in GDP and employment, and in Argentina because of its contribution to exports. Given the size of their agricultural sector, the inclusion of the two countries has significant impacts on aggregate support indicators.

The two countries have different emphasis for agricultural policies, but both tax farm producers. Argentina provides only few payments to farmers and hardly any highly distorting measures other than export taxes, which remain the major component of policy transfers from the agricultural sector resulting in negative market price support. Budgetary support to agriculture focuses on the provision of general services and public goods such as the agricultural knowledge and innovation system and inspection control services. In India, the combination of complex domestic marketing regulations and trade policy measures targeting several commodities often leads to producer prices below comparable international market levels, generating negative market price support for such commodities. More specifically, the policies that govern the marketing of agricultural commodities in India influence pricing, procuring, stocking, moving, and trading commodities; the restrictions stemming from these regulations together with the differences in their implementation across states drive up transaction costs and contribute to depressing producer prices. In addition, over the course of the period studied, a variety of trade policy measures with a price depressing effect - such as export prohibitions, export quotas, export duties, and minimum export prices – have been applied to several key commodities. The largest share of budgetary transfers to agricultural producers in India are subsidies for variable input use, such as fertilisers, and electricity, including to pump irrigation water.

The negative market price support accounts for -16.9% of gross farm receipts in Argentina and -14.8% in India in 2016-18. As budgetary support to producers is lower than the implicit tax, overall support to producers is negative, accounting for -15.3% of gross farm receipts (%PSE) in Argentina and -5.7% in India in 2016-18. As a result, the addition of Argentina and India in the report reduces the %PSE for the total of countries covered from 15.4% to 12.4%, and the %PSE for the emerging economy aggregate from 13.2% to 9.0% for the period 2016-18.

Support to general services in Argentina was 34% higher than budgetary support to producers and accounts for 2% of agricultural value added in 2016-18. In contrast, India’s support to general services was about half of budgetary support to producers, and accounted for almost 5% of agricultural value added.

Reflecting the implicit tax on producers, the share of total support to the sector in GDP is negative in Argentina (-1.1% in 2016-18), but positive in India (0.6%). Given the size of India, the inclusion of the two countries decreases the %TSE aggregates for all countries from 0.91% to 0.88%, and that for emerging economies from 1.64% to 1.43% in 2016-18.

Source: Chapters 3 and 13 of this report; OECD (2019[9]), Agricultural Policies in Argentina, https://doi.org/10.1787/9789264311695-en; OECD/ICRIER (2018[10]), Agricultural Policies in India, https://doi.org/10.1787/9789264302334-en.

The assessment of policy developments is based on a set of OECD indicators that express the diversity of support measures applied in different countries in a few simple numbers that are comparable across countries and over time, where different indicators focus on different dimensions of countries’ support policies. Annex 1.A provides definitions of the indicators used in the report, while Figure 1.2 illustrates the relationships between the different indicators and their components.

The Total Support Estimate (TSE) is the OECD’s broadest indicator of agricultural support. The TSE combines three elements: 1) transfers to agricultural producers individually; 2) policy expenditures that have primary agriculture as the main beneficiary, but do not go to individual producers; and 3) budgetary support to consumers of agricultural commodities.

The transfers to agricultural producers individually are measured by the Producer Support Estimate (the PSE), which comprises Market Price Support (MPS), defined and explained in Box 1.2, and various categories of budgetary support defined in Box A A.1. Similarly, the Consumer Support Estimate (the CSE), measured at the farm gate level and net of the market price support element, includes market transfers that mirror MPS for consumers, as well as budgetary support to consumers, which are part of the TSE.

Policy expenditures that have primary agriculture as the main beneficiary, but do not go to individual producers are measured by the General Services Support Estimate (the GSSE). As the PSE and the CSE, the TSE includes both market transfers (MPS) and budgetary support from the PSE, the CSE and all of the GSSE.

Figure 1.2. Structure of agricultural support indicators
Figure 1.2. Structure of agricultural support indicators

Note: *Market Price Support (MPS) is net of producer levies and excess feed cost.

Source: Annex 1.A.

Box 1.2. Market price support – concept and interpretation

Market price support (MPS) is defined as the “annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, arising from policy measures that create a gap between domestic market prices and border prices of a specific agricultural commodity, measured at the farm gate level” (OECD, 2016, p. 98[11]). It is calculated for individual commodities, as the gap between the domestic price paid to producers and the equivalent price at the border (market price differential, MPD), multiplied by the quantity produced, and aggregated to the national level.

This definition contains three key elements. First, it measures the transfers that arise from policy measures that create a price gap (e.g. import tariffs, minimum prices, export taxes, etc.). Second, it measures gross transfers (positive or negative) to agricultural producers from consumers and taxpayers, independent of whether these are generated through expenditures from or revenue to the public budget (e.g. public storage costs or export taxes revenue) or through altered consumer expenditures. Third, it is measured at the farm gate level to ensure that MPS values are consistent with the production and price data for the farming sector overall. In order to measure MPD, the domestic farm gate price needs to be compared to an equivalent border reference price representing the opportunity price (cost) for domestic market participants, at the given world market conditions.

The calculation of the MPD for individual commodities requires information not only on product prices, but also on differences in product qualities, processing and transportation margins, to compare like with like. Domestic handling and transportation margins may be particularly high (while at the same time particularly difficult to obtain) in countries with less well-developed physical and institutional infrastructure.

The price gap (MPD) is calculated only if policies exist that can cause the gap such as border measures that restrict or promote imports or exports, and government purchases, sales and intervention prices in the domestic market (these policies are described later in the text). If countries do not implement such policies, the MPD is assumed to be zero. A non-zero MPD, whether positive or negative, originates from price-distorting policies. It is important to note that MPS measures the “policy effort” (or level of support to prices), not the policy effect (e.g. the impact on farm income) (Tangermann, 2005[12]). In addition to policy instruments that restrict price transmission (say, a target price), market developments (such as exchange rate movements affecting world prices expressed in local currencies) may influence the policy effort and, hence, the transfers implied.

When interpreting MPS values, it is important to bear in mind that it is not a measure of public expenditures but an estimation of implicit or explicit transfers. MPS estimates published by the OECD therefore often differ from, and should not be confused with, those published by other organisations, including by the World Trade Organization, which may use very different concepts to calculate their indicators, despite similar names (Diakosavvas, 2002[13]; Effland, 2011[14]; Brink, 2018[15]).

This section first discusses changes in producer support between 2017 and 2018 (Box 1.3). It then takes a longer term perspective on developments in producer support, and other agricultural support indicators since the early 2000s, starting from PSE levels and composition, including a focus on Market Price support (MPS), and related Nominal Protection Coefficient (NPC) and support to consumers (CSE). Developments in and composition of expenditures on general services to the sector (GSSE) are also considered, followed by an overview of the size of total support to agriculture (TSE) relative to the economy and the agricultural sector.

Box 1.3. Producer support in 2018 increased in most countries

Increased producer support in 2018 was widespread among OECD countries, as only producers in New Zealand, Chile, Turkey, Japan and Iceland received lower support. On average, producer support in OECD countries increased from 17.7% of gross farm receipts in 2017 to 19.2% in 2018. Producer support in emerging and developing economies covered in this report decreased on average from 9.1% to 8.1% of gross farm receipts between 2017 and 2018, reflecting mainly the decline in China.

In the majority of countries, the observed change in the PSE was largely driven by the change in market price support (MPS) or counter-cyclical payments, reflecting the widening or narrowing of the gap between domestic and border prices. In fact, diverging trends in some countries could be explained by the importance in their agricultural production of specific commodities (e.g. rice in Japan, sheep in Turkey and Iceland) that experienced price increases in world markets. Exceptions include Brazil, where producer support fell due to a 30% decline in budgetary payments, originating mainly from lower credit subsidies. Changes in budgetary support were also important in some countries (Figure 1.3).

Lower MPS drove changes in the monetary value of support in Chile, Colombia, Japan, New Zealand,1 and Turkey, with lower budgetary payments also contributing in Chile and Japan. Higher MPS increased producer support in the European Union, Israel, Korea, Mexico, Switzerland and the United States, as well as all emerging economies except Brazil, China and Costa Rica.

Lower budgetary payments reduced producer support in Brazil, and, to a lesser extent, in Chile, Iceland, Korea, the Russian Federation and Colombia. In contrast, budgetary payments were the main drivers of producer support increases in the United States (output payments), Canada (risk management payments), and Norway (Statistical Annex Table A.118).

Figure 1.3. Contribution of MPS and budgetary payments to the change in PSE, 2017 to 2018
Figure 1.3. Contribution of MPS and budgetary payments to the change in PSE, 2017 to 2018

Notes: The horizontal axis shows the contributions of market price support (MPS) and the vertical axis of budgetary payments to the annual change in the monetary value of support to farmers (PSE, expressed in local currencies) between 2017 and 2018, all other variables being constant. Country points farther from the vertical axis indicate a higher contribution of changes in MPS to the change in PSE. Points farther from the horizontal axis indicate a higher contribution of budgetary payments.

Argentina, India, Kazakhstan, Ukraine and Viet Nam are not shown due to negative MPS data.

The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933935952

In most countries, year-on-year developments in MPS were driven by changes in price gaps, with changes in production quantities having a smaller effect, although significant in South Africa (Statistical Annex Table A.117).

As border prices increased on average for most countries, changes in the price gap depended on relative movements in domestic (producer) prices (Statistical Annex Table A.119). In the OECD countries on average, producer prices were relatively stable between 2017 and 2018, and the decline in border prices, enhanced by currency movements, contributed the most to the increase in MPS in 2018. But there is a wide diversity among OECD countries. For example domestic price decreased in many of them, but increased in the European Union, Japan, Norway and Turkey. Depreciation of national currencies against the US dollar played a dominant role in explaining the decrease in border prices in the European Union and Turkey. In contrast with OECD countries, producer prices decreased on average in the emerging and developing economies, but less than border prices resulting in a higher MPS between 2017 and 2018.

1. In New Zealand, price support is measured only for poultry and eggs and is due to non-tariff protection applied on sanitary and phytosanitary (SPS) grounds.

Support to producers in the OECD area and emerging economies has converged until 2015, but diverged since

On average, the level of support provided to individual producers in the countries covered by this report has followed a declining trend over time, although changes in the average %PSE have been marginal in recent years (Figure 1.4). In 2018, around 12% of gross farm receipts were due to policies that support producers, as in 2017. The monetary value of this support was USD 442 billion (EUR 375 billion) in 2018, up from USD 440 billion (EUR 390 billion) in 2017. This stability results from a decrease in MPS mainly due to market developments, including movements in world prices for agricultural commodities and exchange rates, combined with an increase in budgetary support.

The trend in the average %PSE masks differences between the OECD countries and the emerging and developing economies (Figure 1.4). The average level of producer support in the OECD countries has followed a declining trend to fall below 20% of gross farm receipts in 2010, and it has fluctuated since around 17-19%. In the early 2000s the emerging and developing economies on average provided very low levels of support to agricultural producers. Since then, the level of producer support in the emerging and developing economies has increased from less than 4% to around 9% of gross farm receipts in 2016-18, with lower levels of support in 2008 and 2011 reflecting periods of higher world commodity prices. Since it peaked at 11% in 2015, the %PSE in the emerging and developing economies has fallen to reach 8% in 2018. In large part, the %PSE change in the emerging and developing economies is driven by producer support in China and India. The inclusion of China raises the %PSE in the emerging and developing economies, which would otherwise be negative, to 9% in 2016-18. The inclusion of India reduces the %PSE for emerging and developing economies by about 4 percentage points, and the inclusion of Argentina by 0.5 percentage points in 2016-18, as both countries have a negative PSE.1

These broad trends are also evident when looking at countries individually (Figure 1.5). In most countries, producer support has declined since the early-2000s, although the extent varies across countries. Levels of producer support have fallen by about two-thirds in Chile, Mexico and Kazakhstan, while producer support in Australia, Brazil, South Africa Canada, the United States, Colombia and the European Union fell by 40% or more. However, producer support has increased since the early-2000s in China, the Russian Federation, and to a lesser extent in the Philippines. In Ukraine and Viet Nam, support to producers became negative in recent years, and the implicit tax on producers from negative support increased in Argentina and India since the early 2000s.

Nevertheless, current levels of producer support continue to vary widely across countries (Figure 1.5). New Zealand, Australia, Chile, Brazil and South Africa provide very low levels of support to producers, with %PSEs below 3% in 2016-18. Argentina, Viet Nam, India and Ukraine even tax their producers, with negative %PSEs. In contrast, Japan, Korea, Switzerland, Iceland and Norway support their producers at levels from 45% to 60% of gross farm receipts, despite reductions in support since the early-2000s. Of the emerging and developing economies, only the Philippines provides support at higher levels than the OECD average (PSE of 25% in 2016-18 compared with the OECD average of 18%).

Figure 1.4. Evolution of the Producer Support Estimate, 2000 to 2018
Percentage of gross farm receipts
Figure 1.4. Evolution of the Producer Support Estimate, 2000 to 2018

Notes: 1. The All countries total includes all OECD countries, non-OECD EU Member States, and the 12 Emerging Economies.

1. The OECD total does not include the non-OECD EU Member States. Latvia and Lithuania are included only from 2004.

2. The 12 Emerging Economies include Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933935971

Figure 1.5. Producer Support Estimate by country, 2000-02 and 2016-18
Percentage of gross farm receipts
Figure 1.5. Producer Support Estimate by country, 2000-02 and 2016-18

Notes: Countries are ranked according to the 2016-18 levels.

1. EU15 for 2000-02 and EU28 for 2016-18.

2. The OECD total does not include the non-OECD EU Member States. The Czech Republic, Estonia, Hungary, Poland, the Slovak Republic and Slovenia are included in the OECD total for both periods and in the European Union for 2016-18. Latvia and Lithuania are included in the OECD and in the European Union only for 2016-18.

3. The 12 Emerging Economies include Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam.

4. The All countries total includes all OECD countries, non-OECD EU Member States, and the Emerging Economies.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933935990

Market price support remains the main component of producer support on average, but varies across countries and commodities

A number of domestic and border policy measures, described in the next section, can create a gap between the domestic market prices and border prices of agricultural commodities (Box 1.2), which generate MPS. In most cases where such policies exist, domestic prices are higher than border prices and the price gap generates transfers from consumers to producers. But this is not always the case. In six of the economies reviewed by this report, agricultural policies depressed domestic prices for a number of commodities. As a result, MPS calculated for these commodities is negative and producers are effectively taxed. Negative MPS is particularly important in India and Argentina, where during the last three-year period these policies reduced producers’ average gross receipts by 13% and 16% relative to their value at world market conditions. Export taxes are to a large extent responsible for negative MPS (see next section).

On average across the OECD, MPS accounted for almost half of all support received from the government or more than 8% of farmers’ gross farm receipts in 2016-18. These shares have generally declined but continue to differ significantly across countries. In the five countries with the highest levels of support, the share of market price support in gross farm receipts represented between 25% and 50%, while it amounted to less than 5% in eight other countries.

Price distortions remain important – both across and within countries: the average shares of MPS in gross farm receipts in one country often hide significant variation across commodities. In many countries, price support remains particularly important for a subset of commodities. For instance, in seven national commodity markets (poultry and eggs in both Switzerland and Iceland, soybeans, red pepper and barley in Korea), revenues were inflated by more than 70% due to MPS during 2016-18. Put differently, for these commodities farm revenues are more than three times what they would be if valued using the border reference price. Even in countries with high average price support, there are commodities with substantially lower or even zero price support. Figure 1.6 shows, for each country covered by this report, the distribution of relative MPS shares across the commodities for which MPS is estimated. In addition to the country average, the whiskers also show the lowest and highest MPS share as well as their respective first, median and third quartiles.

Significant variations across commodities also exist for countries with negative average MPS. In Argentina, which taxes its average producer through depressed domestic prices, negative price support is maintained only for a subset of exporting commodities, notably soybeans where the negative MPS accounts for almost half gross farm receipts. In India, negative price support affects a larger set of commodities and reaches up to 90% of commodity receipts. In other words, MPS cuts gross farm receipts for these commodities by almost half.

Several other countries with small total MPS rates like Kazakhstan, the Russian Federation, Ukraine and Viet Nam, maintain both positive MPS for some commodities and negative for others. The low average MPS estimates hide significant positive and negative rates of support across commodities. A meaningful interpretation of average rates of MPS (and indeed of other aggregate indicators such as the percentage PSE or the percentage TSE) needs to account for these hidden distortions. These average indicators hence need to be read as indicators of net transfers to or from the sector because they may aggregate both positive and negative components.

Figure 1.6. Relative magnitude of product-specific market price support by country, 2016-18
Simple average of MPS as a percentage of gross farm receipts
Figure 1.6. Relative magnitude of product-specific market price support by country, 2016-18

Notes: A. Number of MPS commodities. B. Number of MPS commodities with non-zero MPS values.

The ends of the whiskers represent the minimum and maximum values across commodities, while the boxes indicate ranges between the first and the third quartiles with the horizontal line inside indicating the median. Diamonds represent mean values for total agriculture.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936009

The level of price distortions is generally falling, although there are large gaps between domestic and world prices in some countries

Prices received by producers have become more closely aligned with those prevailing on world markets, as countries provide a larger share of support through less distorting measures. The Nominal Protection Coefficient (NPC) in Figure 1.7 compares effective prices received by producers – including per unit output payments – with world market prices. In a number of countries, the gap between domestic and world market prices has narrowed considerably, meaning that market signals are becoming more important for producers’ decisions. For the OECD countries, effective producer prices were, on average, 11% higher than world market prices in 2016-18, compared with around 30% higher in the early 2000s. Countries that have made substantial progress (reduction of NPC of 5% or more) in aligning effective producer prices with world market prices since the early 2000s include Chile, Colombia, the European Union, Iceland, Japan, Kazakhstan, Korea, Mexico, Norway, South Africa, Switzerland, Turkey, the United States and Viet Nam.

As with the other indicators of producer support, there are significant differences between countries. Effective prices received by producers are closely aligned with international levels only in Australia, Brazil, Chile and New Zealand. Effective producer prices are less than 4% above world market prices in Mexico, South Africa and the United States, while are less than 4% below world market prices in Kazakhstan, Ukraine and Viet Nam. In 2016-18, effective prices received by producers were 15% and 12% below world market prices in Argentina and India respectively.

In almost all other countries, effective prices received by producers are, on average, higher than world prices. Effective producer prices in Iceland, Japan, Korea, Norway and Switzerland are 50% to 110% higher than world prices, suggesting that producer support plays an important role in guiding producers’ decisions. Nevertheless, gaps between domestic and world price have narrowed also in those countries since the early 2000s.

A number of the emerging and developing economies have increased their price support, widening the gap between domestic and world market prices. Effective producer prices in China were, on average, close to world price levels in the early-2000s, but 12% higher than world market prices in 2016-18. Effective producer prices have also increased in the Philippines.

Figure 1.7. Producer Nominal Protection Coefficient by country, 2000-02 and 2016-18
Figure 1.7. Producer Nominal Protection Coefficient by country, 2000-02 and 2016-18

Notes: Countries are ranked according to 2016-18 levels.

1. EU15 for 2000-02 and EU28 for 2016-18.

2. The OECD total does not include the non-OECD EU Member States. The Czech Republic, Estonia, Hungary, Poland, the Slovak Republic and Slovenia are included in the OECD total for both periods and in the European Union for 2016-18. Latvia and Lithuania are included in the OECD and in the European Union only for 2016-18.

3. The 12 Emerging Economies include Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam.

4. The All countries total includes all OECD countries, non-OECD EU Member States, and the Emerging Economies.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936028

A wide range of policies contribute to raise or depress farm prices

MPS and NPCs are useful indicators for discussing the implied distortions, but do not provide information about the underlying policies that create the price gap. Many countries implement several policy measures simultaneously, often combining domestic market regulations and public marketing agencies with trade policies targeting imports or exports (Table 1.2). This diversity of measures may result in transfers differing in magnitude and even in sign across commodities. While it is not possible to attribute shares of the transfers to individual policies – and hence identify the most relevant policy in a given market – it is useful to look at the policies in place to provide more tangible recommendations on possible policy changes. The policy measures and country examples in this section are based on background information available from the PSE database, but they are not intended to be an exhaustive list of existing measures.

Table 1.2. Selected policy measures affecting agricultural prices and trade

 

Domestic measures

Import protection

Export enhancement

Export restriction

 

Minimum prices

Public stockholding

Support to private stockholding

Production quotas

Marketing agencies

Tariffs

Tariff Rate Quotas

Bans, quotas, other quantitative restrictions

Seasonal restrictions

Export subsidies (1)

Export taxes

Bans, quotas

Minimum export prices

MoU on export limits

Argentina

x

x

x

Australia

x

x

1999

Brazil

x

Canada

x

x

x

2015

Chile

x

x

China

x

x

x

x

Colombia

x

x

x

1998

Costa Rica

x

x

x

EU28

x

x

x

x

x

x

2013

India

x

x

x

x

x

x

Iceland

x

x

x

1997

Israel

x

x

x

2016

Japan

x

x

Kazakhstan

x

Korea

x

x

Mexico

x

x

x

1999

Norway

x

x

x

2016

New Zealand

x

Philippines

x

x

x

Russia

x

x

x

x

Switzerland

x

x

2016

South Africa

x

x

2000

Turkey

x

x

x

2000

Ukraine

x

x

United States

x

x

x

2008

Viet Nam

x

x

x

x

Note: MoU: Memorandum of Understanding. This table identifies the type of measures applied by countries, but ignores the scale and significance of such measures.

1. Latest year of reported non-zero export subsidy outlays: WTO, 2018, G/AG/W/125/Rev.9, https://docs.wto.org/dol2fe/Pages/FE_Search/ExportFile.aspx?id=247031&filename=q/G/AG/W125R9.pdf.

Domestic price support policies and marketing agencies

Domestic price support policies are regulations and operations by public agencies in the domestic market. They may be key to raising farm gate prices for agricultural products, even if they generally require measures at the border to be effective.

For instance, Israel, Costa Rica, Turkey and recently Mexico, have minimum prices for some commodities, while the European Union applies minimum prices for public intervention and for triggering support to private storage for several products. In Viet Nam, farm gate target prices for rice may result in implicit taxation of rice producers in some years while creating support to farmers in others.

Production quotas limit the supply on domestic markets and may help to maintain prices above world market levels. Production quotas used to be common in sugar and dairy, but have often been dismantled like those for milk in Switzerland (since 2009), for milk and sugar in the European Union (since 2015/16 and 2017/18 respectively) and for sugar in Ukraine (since 2018/19). Milk production continues to be controlled by the quota system in Canada.

More generally, domestic market regulations may affect pricing and other activities within a number of markets. This is particularly the case in India where the Essential Commodities Act and other state-level Acts obliges producers of some commodities to sell in regulated markets. In many cases, market regulations and minimum prices are enforced through government marketing agencies like the state level agencies and the Food Corporation in India.

Policies that restrict commodity imports

Imports face tariffs in all countries analysed in this report, and nearly for all commodities (UNCTAD, 2019[17]). Across these countries, applied tariffs in ad valorem equivalents are either zero or less than 10% for more than a third of the commodities for which MPS is calculated. On the other hand, tariffs exceed 100% for almost 9% of these commodities and can be above 300% in some cases. Markets with high price support tend to be protected by high import tariffs even if this correlation is weak due to the complexity of policies that combine different measures. Import tariffs also exist in markets with little or even negative price support.

In some cases, variable import tariff rates apply. These tariffs depend on the level of international prices relative to levels defined by policies, or change seasonally like for many fruits and vegetables in the European Union. Furthermore countries sometimes impose additional duties as safeguard measures when imports grow very rapidly.

Another key measure restricting imports is the tariff-rate quota (TRQ), allowing for a limited amount of imports at zero or low tariff rates, whereas imports exceeding the quota are subject to a higher tariff. TRQs became a market access tool after the Uruguay Round Agreement on Agriculture to open markets at least for minimum import volumes even in sensitive products. Domestic markets for bovine products (dairy, beef), pig meat and poultry products, and major grains and sugar are often protected by TRQs. TRQs apply to one or several markets in practically all countries covered by this report. TRQs are frequently linked to high levels of price support but their impact on domestic prices may be small in specific circumstances.

Imports in many countries also face sanitary and phytosanitary (SPS) non-tariff measures (NTMs). These measures may be implemented to protect the country from biotic or abiotic threats (WTO, 1995[18]), such as pathogens or pesticide residues. SPS-related NTMs often increase trade costs, but they can possibly raise domestic demand for such products and even increase trade (Cadot, Gourdon and van Tongeren, 2018[19]). Trade costs may be particularly important if SPS measures differ between exporting and importing countries (von Lampe, Deconinck and Bastien, 2016[20]) and, in extreme cases, SPS measures may make imports impossible. NTMs may also respond to other societal concerns and circumstances beyond SPS. For instance, Israel requires imports of beef, poultry and sheep meat to be certified as kosher, thus potentially limiting import supplies.

Import quotas and bans may be related to factors other than agricultural or food safety policies. The Russian Federation has stopped imports of some agricultural products from Ukraine and other countries that impose sanctions on the Russian Federation. Ukraine in turn bans imports of many food products from the Russian Federation.

Countries may also require licences for imports that, if they are not automatic, may constrain import activity. For instance, many commodities including rice require specific permits to be imported to the Philippines. In some countries state-owned agencies control for all or significant parts of the countries’ commodity imports, exports, or both. While such entities as the Canadian Dairy Commission or the China Grain Reserves Corporation need not automatically distort trade and prices, they have the potential to do so.

Policies that enhance exports

To maintain positive price gaps in exporting countries, other measures need to be in place to allow products to be shipped from a high-price domestic environment to the lower-price international market. Export subsidies have been relevant for poultry and eggs in Turkey. The European Union was for a long time the largest subsidiser of agricultural exports among WTO members, but no longer provides such support. In the Nairobi Ministerial Decision of 2015, WTO members committed to remove export subsidies for agricultural products. Support to export credits for agricultural commodities has also been provided by several countries like the United States, Turkey and Canada.

Sometimes competition rules allow state-owned companies and private co-operatives with large export shares to use pricing methods such as price pooling that allow to maintain domestic producer prices above world market levels. In Canada, supply management systems exist for dairy, poultry and eggs, which allow, for instance, paying higher prices for milk used to produce fresh dairy products which cannot be traded, while paying lower prices for tradable milk. In South Africa, agreements between sugar traders, processors and producers allow to charge domestic consumers higher prices, cross-subsidising exports.

Policies that restrict exports

Restricting exports increases supply to the domestic market, thus potentially depressing domestic prices and reducing prices paid by the consumers or first buyers of agricultural commodities. For producers, this generates negative price support.

For many years, Argentina has applied export taxes to specific agricultural products to raise fiscal revenue, support downstream industries and depress consumer prices for staple products. The Russian Federation also charges taxes for sunflower seed exports.

Over the last decade, India has applied on and off a variety of export restrictive measures on key commodities such including export bans, export quotas, export duties, and minimum export prices – which have contributed to depressed producer prices. Export restrictions and licences also apply for rice, corn and sugar in the Philippines. In the late 2000s Argentina often used export quotas, licences and bans for main staple food commodities like wheat and beef. An annual Memorandum of Understanding between the Government of Ukraine and the grain exporting industry defines limits to exports of certain types of cereals, even if actual exports have regularly exceeded those limits. State-owned companies in Viet Nam have considerable influence over exports of some products, such as rice, rubber and coffee.

Consumers continue to bear most of the costs of producer support in many countries

Producer support also affects consumers of agricultural commodities, namely food processors, livestock producers and final consumers. In most of the countries covered in this report, domestic prices are higher than world market prices, which increases costs for consumers. In some countries, other policies may provide compensation for some or all of these additional costs, for example, through budgetary subsidies to food processors or through domestic food assistance programmes. The percentage Consumer Support Estimate (%CSE) expresses the monetary value of the transfers to consumers as a percentage of consumption expenditures (measured at the farm gate). When domestic prices are higher than those on the world market, they contribute negatively to the %CSE, indicating an implicit tax imposed on consumers. Inversely, when domestic prices are lower than prices on the world market, consumers receive positive transfers from markets.

A negative CSE burdens poor consumers relatively more than rich ones, as the share of food expenditures in household budgets tends to fall with rising incomes. Moreover, small agricultural producers may be net buyers of agricultural products, meaning that price support is ineffective in helping those most in need – this is particularly the case in emerging and developing economies. It also disadvantages food processing industries, which have to pay higher prices for their material inputs, making them less competitive on international markets. Finally, such support often creates significant distortions to markets and economies, reducing economic welfare.

Consumers in most countries are harmed by agricultural policies, although to different degrees (Figure 1.8). In 2016-18, the implicit tax on consumers – as indicated by a negative %CSE – ranged from less than 1% in Brazil, Chile and Mexico, to more than 40% in Iceland, Japan, Korea and Norway. In all cases, this negative CSE is due to market price support, implying transfers from consumers to domestic producers and, for importing countries, to taxpayers. In some emerging and developing countries, increasing use of market price support has increased the implicit taxation of consumers, while in others positive CSEs have benefited consumers.

Five countries provide positive net-support to their consumers, specifically India (%CSE of 22% in 2016-18), the United States (13%), Argentina (11%), Kazakhstan (7%) and Ukraine (6%). However, they do so in very different ways. The United States has significant domestic food assistance programmes for specific groups of the population, more than offsetting the somewhat higher domestic prices. In other countries, consumers benefit from market prices, which are, on average, below prices on world markets, at the expense of agricultural producers.

Figure 1.8. Composition of the Consumer Support Estimate by country, 2016-18
Percentage of consumption expenditure at farm gate
Figure 1.8. Composition of the Consumer Support Estimate by country, 2016-18

Notes: Countries are ranked according to percentage CSE levels. A negative percentage CSE is an implicit tax on consumption.

1. EU28.

2. The OECD total does not include the non-OECD EU Member States.

3. The 12 Emerging Economies include Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam.

4. The All countries total includes all OECD countries, non-OECD EU Member States, and the Emerging Economies.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936047

In most countries, support is predominantly provided through measures that are most distorting to production and trade

The way in which countries provide support to producers is as important as the overall level of that support. Governments have a large portfolio of measures at their disposal. In addition to raising or reducing domestic prices by intervening directly in markets or at the border. They can also provide subsidies to reduce farmers’ input costs; or they can provide payments to producers on the basis of farm output, area, animal numbers, or as a top-up to farmers’ income. Payments may be conditional on specific production practices, for example, to achieve environmental protection objectives.

These distinctions are important. The measures listed above will affect agricultural production, incomes, trade and other outcomes differently. For example, MPS has negative impacts on world markets and distorts price signals faced by producers, reducing incentives to improve efficiency in agricultural production. Moreover, the way in which producer support is provided also influences the ability of agricultural producers to participate in agriculture and supply chains, and the benefits obtained from participation. Some measures may target specific policy objectives or beneficiaries more effectively than others. For example, unlike MPS, payments per hectare, per animal or based on farm incomes can be targeted to specific locations or groups of farms, and tailored to specific policy objectives. These considerations highlight the need for a more detailed analysis of the measures through which producer support is provided.

Most countries provide the majority of producer support through measures that are most distorting for production and trade (Figure 1.9). OECD analysis has shown that MPS, payments based on output, and payments based on unconstrained variable input use have a significantly higher potential to distort agricultural production and trade than payments based on other criteria (OECD, 2001[21]). Moreover, depending on the exact policy design, this type of support tends to have negative impacts on the environment as it gives additional incentives to expand and intensify land use (see Box 1.4 on recent findings). Note that while the share of potentially most distorting policies in overall %PSE is an important indicator, a country with a relatively low share of potentially most distorting support may actually spend more on those policies than a country with a relatively high share, depending on the total PSE.

In addition to MPS discussed above, the other measures that are potentially most distorting for agricultural production and trade, payments based on output are provided to farmers in Iceland and Kazakhstan (21% and 22% of the PSE respectively in 2016-18) and account for 7% to 9% of the PSE in Norway, Turkey and the United States (Figure 1.9). Support for variable inputs without constraints (e.g. without conditions on how inputs are used or on any other farming practices) is provided to farmers in Kazakhstan and South Africa (20% or more of the PSE in 2016-18), as well as in Chile (17%), Mexico (15%), Canada (6%) and Israel (6%). In the European Union, around 6% of producer support is provided as support for variable inputs without constraints, where it is mostly provided within the national programmes of the Member States. While such measures reduce the impact on consumers relative to market price support (as they are transfers to producers from taxpayers), they also fail to target the market failures or policy objectives at the heart of government intervention in agricultural markets. For example, fertiliser subsidies lower costs to producers without considering their individual needs. Moreover, support for specific production inputs increases the risk of their over- or misuse, with potentially harmful consequences for farmers’ and consumers’ health and the environment.

Because both positive and negative MPS distorts market signals, this report introduces a new indicator that takes account of both positive and negative distortions, by summing the absolute value of negative MPS and support from positive MPS and budgetary support from payments based on output, and payments based on unconstrained variable input use. The “% potentially most distorting transfers” relates the sum of all most distorting transfers in absolute terms (i.e. using the absolute value of negative MPS) to the sum of all producer transfers in absolute terms (i.e. also using the absolute value of negative MPS). Commodities with negative MPS are concentrated in five emerging or developing economies: Argentina, Viet Nam, India, Ukraine and Kazakhstan. Thus, the consideration of negative MPS in absolute terms affects mainly these countries and the aggregates they enter in.

On average for all countries covered in the report, transfers provided through measures that are most distorting for production and trade (whether positive or negative, i.e. expressed in absolute terms) accounted for close to 70% of cumulated gross producer transfers, i.e. the sum of all producer transfers in absolute terms (using the absolute value of negative MPS) in 2016-18. In general, such measures are more important in the emerging and developing economies, where they account for over 80% of cumulated gross producer transfers, compared with 52% of these transfers in OECD countries. On the other hand, a larger share of producer support is provided through less-distorting measures in Australia, Brazil, Chile, the European Union, Kazakhstan and the United States.

Figure 1.9. Potentially most distorting transfers by country, 2016-18
Percentage of gross farm receipts
Figure 1.9. Potentially most distorting transfers by country, 2016-18

Notes: Countries are ranked according to the %PSE levels.

1. Support based on output payments and on the unconstrained use of variable inputs.

2. EU28.

3. The OECD total does not include the non-OECD EU Member States.

4. The 12 Emerging Economies include Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam.

5. The All countries total includes all OECD countries, non-OECD EU Member States, and the Emerging Economies.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936066

Among countries with the highest share of producer support in gross farm receipts (%PSE), Japan and Korea provide more than 85% using potentially most distorting transfers, while Switzerland and Norway make large use of less distorting forms (40% or more) (Figure 1.10). Differences among low support countries are even larger from Australia, where producers receive minimal support, mainly from least distorting measures, to countries where support is low or negative, but potentially most distorting support accounts for over 85% of cumulated gross producer transfers (e.g. Argentina, Costa Rica, India, South Africa, Ukraine and Viet Nam). Among countries with producer support between 10-20%, the European Union uses the lowest share of potentially most distorting transfers (26%), while over 90% of cumulated producer transfers are of the most distorting type in Colombia and Israel. As a result, EU agricultural policies provide higher support levels but less potentially most distorting transfers than in China or the Russian Federation, with their lower support levels.

Figure 1.10. Producer Support Estimate level and composition by country, 2016-18
Figure 1.10. Producer Support Estimate level and composition by country, 2016-18

Notes: 1. Producer Support Estimate (PSE) as a share of the gross farm receipts.

1. Potentially most distorting transfers in cumulated gross producer transfers. Potentially most distorting transfers include transfers based on output (including positive and absolute value of negative market price support, and output payments) and on the unconstrained use of variable inputs.

2. The OECD total does not include the non-OECD EU Member States.

3. The 12 Emerging Economies include Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam.

4. The All countries total includes all OECD countries, non-OECD EU Member States, and the Emerging Economies.

5. In New Zealand, price support is measured only for poultry and eggs and is due to non-tariff protection applied on SPS grounds.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936085

There is a trend towards payments that are less coupled with production decisions

Less distorting forms of support, which have a lower impact on commodity production than potentially most distorting support, include two broad categories of (tax-financed) payments. First, payments based on other inputs (mostly support for on-farm investments) or on variable inputs with constraints (e.g. restrictions on specific farming practices allowed) are used in a number of countries. Such payments account for more than 70% of producer support in Chile and Kazakhstan, and also a significant share of producer support in Brazil (45%), Australia (41%) and Mexico (37%).

Second, payments based on area, animal numbers, farm receipts or farm income are increasing in the OECD countries (Figure 1.11). In 2016-18, such payments accounted for a large share of producer support in the European Union (67% of the PSE in 2016-18), Australia (52%), Switzerland (44%), Norway (38%), the United States (38%) and Canada (32%) among other countries. These types of payments are also increasing in China, where they represented 20% of the PSE in 2016-18. However, they are less common in the other emerging and developing economies, accounting for less than 6% of the PSE.

Increasingly, payments are provided on the basis of historical criteria, in some cases without the need for recipient farmers to produce. In the European Union, Iceland, Norway and Switzerland, such payments accounted for between 6% and 10% of gross farm receipts in 2016-18. In the European Union, 61% of direct payments are based on non-current criteria without production requirements. Similar programmes also exist in Australia, Japan, Korea, Mexico and the United States, among others, although their importance as a share of producer support varies between those countries.

Figure 1.11. Use and composition of support based on area, animal numbers, receipts and income in selected countries, 2000-02 and 2016-18
Percentage of gross farm receipts
Figure 1.11. Use and composition of support based on area, animal numbers, receipts and income in selected countries, 2000-02 and 2016-18

Notes: Figure presents countries having share of payments based on area, animal numbers, farm receipts or farm income above 1% for 2016-18 period. Countries are ranked according to the total share of payments for 2016-18.

1. EU15 for 2000-02 and EU28 for 2016-18.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936104

Payments are increasingly tied to specific production practices, reflecting the importance of objectives related to society at large

In some countries, payments are increasingly tied to specific production practices to encourage producers to adopt practices that may improve the environmental performance of farming or animal welfare. Input subsidies may be subject to mandatory constraints on their use, or receipt of payments may be conditional on the adoption of specific production practices. Payments may also be linked to agri-environmental constraints or to programmes to which farmers can opt-in on a voluntary basis such as payments for reducing nutrient applications or creating buffer strips. The number of countries using these approaches and the levels of these payments has increased in recent decades, reflecting the growing importance of objectives for the sector that reflect societal concerns and the expectation that agriculture will provide various public goods, such as the maintenance of agricultural landscapes and biodiversity.

In addition to the European Union, ten countries have support conditional on the adoption of specific production practices accounting for more than 1% of gross farm receipts. In the European Union, most payments are conditional on the adoption of mandatory production practices and the 28 Member States have to spend a minimum share of Pillar 2 funds on voluntary climatic and agri-environmental measures. In Norway, half of direct payments are granted without constraints, while this share is small in Switzerland. In the United States, mandatory constraints were extended to crop insurance payments in the last Farm Bill. Most other countries not included in Figure 1.12, either provide low support levels and minimal payments to producers (for example Australia or New Zealand), or provide most support in the form of market price support and unconditional payments based on input use (emerging economies).

Payments linked to mandatory practices have become more important in Chile, the European Union, Switzerland and the United States (Figure 1.12). In these countries, up to half of the total support to producers is provided in the form of direct payments that are subject to “cross-compliance” with environmental conditions. Some support to fixed capital formation is also tied to investments in facilities for environmental and animal welfare friendly production. Brazil has made all its credit and insurance programmes subject to complying with an elaborate zoning scheme which determines planting times based on weather, soil and crop cycle related criteria; today these programmes make up over two-thirds of Brazil’s support to producers.

Payments linked to the adoption of voluntary agri-environmental constraints are increasingly used in Switzerland, and to a lesser extent Korea, Mexico and Norway. In Norway and Switzerland, a significant share of these payments are to adopt animal welfare friendly practices. Other countries also use voluntary payments to promote environmental objectives, including Australia, the European Union, and the United States. The decline in the share of payments linked to voluntary agri-environmental constraints since the early 2000s in the European Union reflects the move from payments based on animal numbers, which were conditional on low livestock density, to payments with mandatory practices, which are not linked to current production parameters.

In some countries, support conditional on the adoption of specific production practices has become more important for farmers as well, including in countries with high levels of support overall. Over 23% of gross farm receipts derive from such conditional payments in Switzerland, 15% in Norway, and 12% in the European Union. In contrast, payments tied to specific production practices are not widely used in the emerging and developing economies.

Figure 1.12. Budgetary support conditional on the adoption of specific production practices in selected countries, 2000-02 and 2016-18
Percentage of gross farm receipts
Figure 1.12. Budgetary support conditional on the adoption of specific production practices in selected countries, 2000-02 and 2016-18

Notes: Figure presents data for countries having share of budgetary support conditional on the adoption of specific production practices above 1% for one period or more. Countries are ranked according to 2016-18 levels of payments with input constraints.

1. Payments with other voluntary constraints include constraints related to animal welfare.

2. EU15 for 2000-02 and EU28 for 2016-18.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936123

Support to general services varies significantly across countries in both importance and priorities

Beyond support provided to individual producers, governments also support agriculture through public financing of services that create enabling conditions for the agricultural sector, measured by the General Services Support Estimate (GSSE). On average, support for general services is much lower than support provided directly to producers.

Support for general services to the sector (GSSE) is often well below support to producers (PSE). About two-thirds of countries have a ratio of GSSE relative to the absolute value of the PSE below 30%. In contrast, the GSSE is 25% higher than the PSE in Australia, 12% higher in Chile, and almost three times the PSE in New Zealand. The GSSE relative to the absolute value of the PSE is over 50% in Kazakhstan, India, South Africa and Brazil.

Countries emphasise different elements of general services to the agricultural sector. Investments in agricultural infrastructure are prioritised in a number of countries. More than 70% of expenditure on general services is on infrastructure in India, Japan, Turkey and Viet Nam, and infrastructure represents more than half of general services expenditure in Chile, Korea and the Philippines – often to expand irrigation coverage (Figure 1.13). The agricultural innovation system (AIS) accounts for more than half of support to general services in Brazil, Norway, Mexico, Australia, the European Union, Argentina and Colombia. It is also prioritised in Switzerland, New Zealand, Israel, Ukraine, South Africa, Costa Rica, Canada and the Russian Federation, where it accounts for half to a third of all support to general services. For the OECD countries on average, infrastructure (43% of the GSSE) and the AIS (31% of the GSSE) accounted for close to three-quarters of all expenditures on general services. Expenditures on inspection and control systems accounted for between 30% and 50% of general services expenditure in Canada, Iceland, Kazakhstan, New Zealand and Ukraine. Expenditures on public stockholding accounted for a significant share of the GSSE in China and Iceland.

Figure 1.13. Composition of General Services Support Estimate by country, 2016-18
Share in GSSE
Figure 1.13. Composition of General Services Support Estimate by country, 2016-18

Notes: AIS = Agricultural Innovation System. Aggregate “Others” includes Marketing and promotion, Public stockholding and Miscellaneous. Countries are ranked according to ASI share in the GSSE.

1. EU28.

2. The OECD total does not include the non-OECD EU Member States.

3. The 12 Emerging Economies include Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam.

4. The All countries total includes all OECD countries, non-OECD EU Member States, and the Emerging Economies.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936180

Support to general services generally increased in real terms in emerging and developing economies since the early 2000s, by around 6% per year on average, and up to 8% in India and 10% in the Philippines. Both expenditures on AIS and infrastructure increased on average (by 8% and 7% per year respectively), and in most countries between 2000-02 and 2016-18 (Figure 1.14). However, Brazil has reduced expenditures on infrastructure and South Africa has reduced support to agricultural innovation. Moreover, where support to general services have increased, they generally still have not kept pace with the growing size of the agricultural sectors.

In OECD countries, support to general services decreased in real terms between 2000-02 and 2016-18, by -1% per year on average. But support to agricultural innovation has generally increased on average and in most countries, while support to infrastructure investment has decreased on average, driven to a significant extent by a decline in the European Union.

Figure 1.14. Government expenditure on Agricultural Innovation Systems and Infrastructure by country
Average annual growth between 2000-02 and 2016-18
Figure 1.14. Government expenditure on Agricultural Innovation Systems and Infrastructure by country

Notes: Growth rates are calculated based on expenditures in real 2000 USD, using United States GDP deflator.

1. EU15 for 2000-02 and EU28 for 2016-18.

2. The OECD total does not include the non-OECD EU Member States. The Czech Republic, Estonia, Hungary, Poland, the Slovak Republic and Slovenia are included in the OECD total for both periods and in the European Union for 2016-18. Latvia and Lithuania are included in the OECD and in the European Union only for 2016-18.

3. The 12 Emerging Economies include Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam.

4. The All countries total includes all OECD countries, non-OECD EU Member States, and the Emerging Economies.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936142

The burden of agricultural support on countries’ economies has generally declined

The overall burden of agricultural support on the OECD countries’ economies has declined since the early-2000s, as measured by total support as percentage of GDP (%TSE, Panel A of Figure 1.15). In the OECD countries on average, total support to agriculture declined from 1.0% of OECD aggregate GDP in 2000-02 to 0.6% in 2016-18. Significant reductions have occurred in countries where the relative cost to the economy of agricultural support was highest, including Korea, Turkey, Iceland and Switzerland. Nevertheless, the %TSE is high in these countries – between 1.1% and 1.8% of GDP – despite the fact that agriculture is an important part of the economy only in Turkey.

There are contrasting trends in the overall burden of agricultural support on the emerging and developing economies covered in this report. The %TSE has declined significantly in Colombia, Costa Rica, and Viet Nam since the early-2000s. Viet Nam even effectively taxed their agricultural sectors on average in 2016-18, as do Ukraine and Argentina. When positive, total support as a percentage of GDP is the lowest (below 0.4%) in Australia, South Africa, New Zealand, Chile and Canada.

Public policy support continues to be important for the agricultural sector in some countries. In 2016-18, total support relative to the size of countries’ agricultural sectors varied widely across the OECD countries, from 167% of agricultural value added2 in Switzerland, 97% in Japan and 85% in Korea, to less than 8% of agricultural value added in Australia, Brazil, Chile, India and New Zealand (Panel B of Figure 1.15). In the European Union and Norway, TSE relative to agricultural value added was close to the OECD average of 44%, and it was higher in Israel (63%). In the emerging and developing countries, total support relative to the size of the agricultural sector ranges from negative numbers in Argentina, Ukraine and Viet Nam to 31% of agricultural value added in the Philippines. The total effective tax on agriculture relative to the size of the sector was the highest in Argentina (-15%) while it is around 5% in Ukraine and Viet Nam. For most countries, total support has declined relative to the size of the agricultural sector since the early-2000s.

Total support to agriculture averaged USD 622 billion (EUR 548 billion) a year in 2016-18 over all the countries covered in the report. The monetary value of agricultural support in OECD countries and in the emerging and developing economies covered by this report is roughly the same – in 2016-18 total support to agriculture in the OECD countries averaged USD 325 billion (EUR 286 billion) a year on average, compared with USD 292 billion (EUR 257 billion) a year on average in the emerging and developing countries.

Figure 1.15. Total Support Estimate by country, 2000-02 and 2016-18
Figure 1.15. Total Support Estimate by country, 2000-02 and 2016-18

Notes: Countries are ranked according to the %TSE in 2016-18.

1. For Kazakhstan and the Philippines, 2016-18 is replaced by 2016-17, due to missing GDP and agricultural value added for 2018.

2. EU15 for 2000-02 and EU28 for 2016-18.

3. The OECD total does not include the non-OECD EU Member States. The Czech Republic, Estonia, Hungary, Poland, the Slovak Republic and Slovenia are included in the OECD total for both periods and in the European Union for 2016-18. Latvia and Lithuania are included in the OECD and in the European Union only for 2016-18.

4. The 12 Emerging Economies include Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam.

5. The All countries total includes all OECD countries, non-OECD EU Member States, and the Emerging Economies.

Source: OECD (2019[16]), “Producer and Consumer Support Estimates”, OECD Agriculture statistics (database), http://dx.doi.org/10.1787/agr-pcse-data-en.

 StatLink http://dx.doi.org/10.1787/888933936161

Environmental performance of agriculture: policy impacts and developments

Agriculture can have significant environmental impacts, both negative and positive, and both on and off the farm. Negative impacts include pollution and degradation of soil, water and air. Agriculture can also provide ecosystem services, such as landscape amenities and habitats, trapping greenhouse gases within crops and soils, or mitigating flood risks through the adoption of certain farming practices.

Governments can influence the environmental sustainability of the agriculture sector in a variety of different ways, both intended and unintended. Most directly, governments can alter the incentives faced by producers and other actors, encouraging them to change their approaches and move towards more sustainable agriculture and food systems. In order to understand how policies affect environmental performance of agriculture, several elements are needed:

  • Understanding how policies affect the decision-making of farmers and other actors in the agriculture system, and how these decisions translate into environmental pressures, taking into account other non-policy factors which may shape policy impacts in different contexts.

  • Understanding how the state of the environment (environmental outcomes) changes over time, and the roles of the agriculture sector in contributing to this change.

This section presents findings from recent OECD evaluating the role of specific policy types in improving (or diminishing) agriculture’s environmental performance. It also provides an overview of how the environmental performance of agriculture is changing over time, using the OECD’s agri-environmental indicators. Finally, it considers how countries’ approaches to measuring the environmental sustainability of agriculture (including social and economic aspects) are changing as countries set up indicators to track progress towards UN Sustainable Development Goals (SDG), with a specific focus on indicators for SDG 2.4.

Recent findings on the environmental impacts of agricultural support policies

Recent OECD work shows that agricultural support policies tend to have negative environmental impacts, but not always (Henderson and Lankoski, 2019[22]). On the basis of these analytical frameworks, the selected environmental indicators, and the data used in this study (presented in Box 1.4), the findings suggest that market price support and payments based on output or unconstrained variable input use are found to be the most environmentally harmful among the various PSE measures. In contrast, fully decoupled support payments based on non-current crop area are the least harmful, even when considering their impacts on the behaviour of risk averse farmers. This suggests that in most cases, reforms to decouple support policies are likely to improve the environmental sustainability of the sector. Such reforms in OECD agricultural policies over the past couple of decades are therefore likely to have reduced the total negative environmental impact of support to agriculture (OECD, 2016[23]; OECD, 2014[24]; OECD, 2009[25]).

Interactions between different agricultural production activities with different environmental impacts (e.g. crop and livestock production) can complicate the relationship between agricultural support and environmental sustainability. This is particularly the case for support policies that clearly change the competitiveness of one production activity over another, such as payments based on current crop area or on animal numbers. These types of support can either increase or decrease environmental impacts depending whether they encourage the production of more or less environmentally harmful commodities. The results from the OECD study show that environmental impacts of current crop area payments are the most equivocal, in this respect, but their impacts are generally smaller than those of the other coupled support policies Similarly, results show that agri-environmental payments for complying with environmental constraints can improve environmental outcomes compared to coupled support without restrictions. However, they can also create unintended adverse environmental impacts, where they favour the conversion of more environmentally valuable land types such as from pastures to cereal production. Thus, despite the environmentally positive intentions of these policy measures, policy makers need to be aware of these potential pitfalls (Henderson and Lankoski, 2019[22]).

Box 1.4. Evaluating the environmental impacts of agricultural policies

A recent OECD study attempts to address the following questions:

  • What are the relationships between agricultural support policies and environmental impacts?

  • What conditions may alter the strength and direction of these relationships?

To address these questions, the study focuses on selected environmental impacts considered important by OECD countries: GHG emissions, water quality, biodiversity, and nitrogen (N) and phosphorus (P) balances. The relationship between these impacts and the following categories of agricultural support, adapted from the OECD Producer Support Estimate (PSE) classification, are analysed using farm level model and the Policy Evaluation Model (PEM): market price support; payments based on unconstrained variable input use; payments based on current crop area; payments based on non-current crop area; payments based on current animal numbers; and payments based on non-commodity criteria (Box A A.1). The two analytical frameworks used are applied to a diversity of cases, representing various EU countries’ situations in the farm-level assessment, and representing eight countries or regions (Canada, China, Japan, Korea, Mexico, the United States, Switzerland and the European Union) in the PEM assessment. Some of the insights of this analysis are limited to the farming systems and regions that were considered in this study.

Source: Henderson and Lankoski (2019[22]), “Evaluating The Environmental Impact Of Agricultural Policies”, OECD Food, Agriculture and Fisheries Papers No. 130.

Recent trends in the environmental performance of agriculture

Understanding the interactions between policies and the environmental performance of agriculture requires monitoring of the state of the environment (environmental outcomes) and changes over time. OECD, together with countries, has made significant progress in developing agri-environmental indicators (AEIs) to monitor these environmental impacts (OECD, 2018[26]). As well as providing valuable evidence of the state and trends in the environmental performance of agriculture, AEIs support analysis to explain the effects of different policies on the environment, and to assess whether budgets for policies are used effectively in terms of environmental outcomes and economic efficiency.

Recent trends in OECD countries show mixed results in the environmental performance of agriculture. Since 2000, agricultural production has expanded, and agricultural greenhouse gas emissions and agriculture-related biodiversity losses have increased. In contrast, certain environmental pressures associated with agriculture have declined, such as nutrient balances surpluses— a leading cause of water contamination in OECD countries —and agricultural water abstraction.

Agricultural nutrient surpluses have declined, deficits reduced, but pressures remain high in some countries

For the last two decades OECD countries have on average experienced declining trends in nutrient surpluses (Figure 1.16) (OECD, 2019[27]). From 1993 to 2015, the average nitrogen (N) surplus in OECD countries fell from 32.4 kg/ha to 30 kg/ha, while the average phosphorus (P) surplus fell from 3.3 kg/ha to 2 kg/ha. Almost all OECD countries are experiencing falling phosphorus surpluses, but the picture is more mixed in the case of nitrogen. Trends are more balanced for emerging economies; of the 12 included in this report, nitrogen balances fell for 7 countries and rose for 5, and phosphorous balances fell for 6 and rose for 6 countries (Figure 1.17).

Over the last decade, rates of decline have accelerated for phosphorus surpluses but have decelerated for nitrogen, raising concerns about the ability of OECD countries to continue to reduce nitrogen surpluses in the future. Australia, Austria, Iceland, Mexico and Turkey have reversed the reduction in P surpluses they made during the 1990s and have increased their surpluses per hectare since 2003. Nitrogen balances in Australia, Austria, Iceland, Japan, Mexico and Turkey reversed the declining trends seen in the period 1993-2005 and exhibited positive growth rates in the last decade.

The existing literature identifies three key drivers of nutrient balances: 1) livestock composition, crop mix and the adoption of improved cultivars; 2) agricultural policies; and 3) management practices. Key findings on drivers affecting nutrient balances in OECD countries are:

  • Reduced fertiliser application rates seem to be the main driver of reduced P surpluses, although livestock and crop-mix changes as well as policy interventions are associated with reductions in both N and P nutrient balances. Phosphorus fertiliser application rates fell for most OECD countries, possibly as a result of improved farm practices.

  • On average, OECD countries slightly reduced N inputs. While manure N inputs decreased, N fertiliser increased. In parallel, crop uptake significantly increased, mainly due to shifts in the crop mix towards oil crops (as on average they take up more N on a per kg basis compared to other crops), which further lowered the overall N surplus. A decrease in cattle as a share of total livestock also played a role on declining N manure inputs in some countries.

  • Recent work studying the impacts of different possible policies suggests that potentially most distortionary support policies, particularly those coupled with output and input use, seem to be associated with larger surpluses, mainly because they incentivise the use of inputs and production, while countries that adopted policies targeting nitrogen pollution, in particular Nitrate Vulnerable Zones mandated in EU countries to reduce nitrate pollution, also reduced both N and P surpluses (OECD, 2019[27]; Henderson and Lankoski, 2019[22]).

Figure 1.16. Nitrogen and phosphorus balance per hectare of agricultural land, OECD countries
Figure 1.16. Nitrogen and phosphorus balance per hectare of agricultural land, OECD countries

Notes: Countries are ranked according to the nitrogen balance per hectare change between 2003-05 and 2013-15.

1. Balance (surplus or deficit) expressed as kg nitrogen per hectare of total agricultural land.

2. Balance (surplus or deficit) expressed as kg phosphorus per hectare of total agricultural land.

3. For phosphorus, EU15 does not include Luxembourg for 1993-95.

4. For Switzerland, total agricultural area includes summer grazing.

5. The OECD total does not include Chile and Israel for both periods. For nitrogen, the OECD total does not include Estonia and Hungary for 1993-95; for phosphorus, it does not include Estonia, Hungary, Lithuania and Luxembourg for 1993-95.

Source: OECD (2018[26]), Agri-environmental indicators (database), http://www.oecd.org/tad/sustainable-agriculture/agri-environmentalindicators.htm.

 StatLink http://dx.doi.org/10.1787/888933936199

Figure 1.17. Nitrogen and phosphorus balance per hectare of agricultural land, Emerging Economies
Figure 1.17. Nitrogen and phosphorus balance per hectare of agricultural land, Emerging Economies

Notes: All data are preliminary. Countries are ranked according to the nitrogen balance per hectare change between 2003-05 and 2013-15.

1. Balance (surplus or deficit) expressed as kg nitrogen per hectare of total agricultural land.

2. Balance (surplus or deficit) expressed as kg phosphorus per hectare of total agricultural land.

3. For Argentina and Brazil, 2013-15 is replaced by 2012-14.

Source: OECD (2018[26]), Agri-environmental indicators (database), http://www.oecd.org/tad/sustainable-agriculture/agri-environmentalindicators.htm.

 StatLink http://dx.doi.org/10.1787/888933936218

Agricultural greenhouse gas emissions have increased and ammonia emissions have decreased

Agricultural activities affect air quality mainly via greenhouse gas emissions (methane and nitrous oxides) and ammonia (NH3) emissions. Agriculture is the main emitter of methane (CH4) and nitrous oxide (N2O), two non- CO2 greenhouse gases with more potential to warm the atmosphere than carbon dioxide (CO2), but with a shorter lifespan (IPCC, 2014[28]). GHG emissions from agriculture represent 10-12% of total global GHG emissions (Smith et al., 2014[29]).

Trends in agricultural greenhouse gas (GHG) emissions (Figure 1.18) and ammonia emissions (Figure 1.19) indicate a deterioration of agriculture’s performance in the OECD area. While GHG emissions were practically unchanged in the period 1993-2005, these emissions increased by 0.2% yearly on average in OECD countries from 2003 to 2015. Ammonia emissions in the OECD area decreased in the period 2003-15 but at a slower speed than they did in the period 1993-2005. Increasing emissions from agricultural soils, mainly from the use of synthetic fertilisers, explain most of the rise of agricultural GHG emissions during the period 2003-15.

Countries’ capacities to maintain the value of produced agricultural goods while reducing GHG emissions have weakened. GHG emissions per dollar of agricultural production (emissions intensities) kept declining on average in OECD countries in the period 2003-15, but at lower speed than they did in the period 1993-2005 (Figure 1.20). In highly productive OECD countries, a recent analysis that estimates the relationship between labour productivity and agricultural greenhouse gas emissions in OECD countries suggests further labour productivity3 improvements may not translate into a reduction of GHG emissions intensities (OECD, 2019, forthcoming[30]). Some OECD countries may be reaching a productivity level at which further improvements may induce more GHG emissions per unit of output.

Figure 1.18. Agricultural greenhouse gas emissions, OECD countries
Figure 1.18. Agricultural greenhouse gas emissions, OECD countries

Notes: Countries are ranked according to the average annual percentage change, between 2003-05 and 2013-15.

1. For Chile, 2013-15 is replaced by 2011-13.

Source: UNFCCC (2018[31]), Greenhouse Gas Inventory Database, http://ghg.unfccc.int/; OECD (2018[26]), Agri-environmental indicators (database), http://www.oecd.org/tad/sustainable-agriculture/agri-environmentalindicators.htm.

 StatLink http://dx.doi.org/10.1787/888933936237

Figure 1.19. Ammonia emissions from agriculture, OECD countries
Figure 1.19. Ammonia emissions from agriculture, OECD countries

Notes: Countries are ranked according to the average annual percentage change, between 2003-05 and 2013-15.

1. For the United States, data for agricultural ammonia emissions have been estimated based on the ratio agricultural ammonia/total ammonia emissions, using the share 90% as recommended by USEPA.

2. The OECD total does not include Australia, Chile, Japan, Mexico and New Zealand for both periods, and does not include Israel for 1993-95.

3. For agricultural ammonia emissions, for Korea, 2013-15 is replaced by 2012-14.

Sources: EMEP (2018[32]), Co-operative Programme for Monitoring and Evaluation of the Long-Range Transmission of Air Pollutants in Europe; OECD (2018[26]), Agri-environmental indicators (database), http://www.oecd.org/tad/sustainable-agriculture/agri-environmentalindicators.htm.

 StatLink http://dx.doi.org/10.1787/888933936256

Figure 1.20. Agricultural greenhouse gas emissions intensity,1 OECD countries
Figure 1.20. Agricultural greenhouse gas emissions intensity, OECD countries

Notes: Countries are ranked according to the average annual percentage change, between 2003-05 and 2013-15.

1. Greenhouse gas emissions per gross production value (in constant 2004-06 USD)

2. For Chile, 2013-15 is replaced by 2011-13.

3. The OECD total and EU15 do not include Belgium and Luxembourg for 1993-95.

Source: UNFCCC (2018[31]), Greenhouse Gas Inventory Database, http://ghg.unfccc.int/; OECD (2018[26]), Agri-environmental indicators (database), http://www.oecd.org/tad/sustainable-agriculture/agri-environmentalindicators.htm; FAO (2018[33]), Value of Agricultural Production, http://www.fao.org/faostat/en/#data/QV.

 StatLink http://dx.doi.org/10.1787/888933936275

The trend towards lower agricultural water abstraction continues

Agricultural water abstraction decreased in most OECD countries since 2005, continuing a trend observed since the early 2000s (Figure 1.21). This trend is particularly evident in countries where the irrigation sector is large relative to the agriculture sector. For some countries, the decrease is significant, and it is often associated with deep policy reforms (agricultural policies, water regulation policies), farmers’ capacities to adapt to new climate, the use of more pressurised irrigation systems and policy environments. Decrease of water use for irrigation explains most of the decreasing trends of agricultural water use in OECD countries. Reductions in agricultural water use4 have contributed to the observed decrease in water stress5 in a majority of OECD countries, especially in countries with high initial levels of water stress (OECD, 2018[34]).

Water application rates (e.g. quantity of irrigation water) have decreased in OECD countries with large irrigation sectors, suggesting significant gains in water use efficiency and changes in crop mixes towards less water-intensive crops. When expansion of irrigation areas is coupled with more efficient irrigation techniques, water use efficiency improves, however, expansion of irrigation may have led to the observed increase in water stress in Mexico and Turkey, the only OECD countries that expanded irrigation (OECD, 2018[34]).

Although, on average, agricultural water use trended downward in OECD countries, several countries increasingly rely on groundwater for agriculture use, continuing a trend observed since the mid-1990s. Increasing agriculture reliance on groundwater can raise serious sustainability issues in regions where groundwater withdrawals exceed recharge rates, leading to a drop in water tables, with potentially negative impacts on the environment as well as on the future resilience of such production systems (OECD, 2015[35]). Further, compared to surface water, the negative environmental impacts of groundwater irrigation can be generally more long lasting, if not irremediable (e.g. water pollution) (Ibid.).

Trends observed at the national level may mask important within-country variability of water use and water stress in OECD countries (OECD, 2017[36]). Recent severe droughts, with serious implications for regional and global agriculture in some OECD countries such as Chile, France, the United States (California) or in irrigated regions of Australia, illustrate this issue.

Figure 1.21. Change in irrigation water abstraction and irrigated areas, in selected countries
Average annual percentage change, from 2004-06 to 2012-14
Figure 1.21. Change in irrigation water abstraction and irrigated areas, in selected countries

Note: Average annual % change is calculated as geometric average growth rates between the two three-year averages.

Source: OECD (2016), Agri-environmental indicators (database), http://www.oecd.org/tad/sustainable-agriculture/agri-environmentalindicators.htm.

 StatLink http://dx.doi.org/10.1787/888933936294

The loss of crop diversity, landscape heterogeneity and increased pesticides use have strong impacts on farmland biodiversity

Changes in land and pesticide use are key drivers of change in farmland biodiversity, particularly farmland birds (Stanton, Morrissey and Clark, 2018[37]). Excess nutrient applications can negatively impact biodiversity due to increased toxicity in the environment and nutrient enrichment, oxygen depletion in aquatic ecosystems, soil or water acidification or intensifying the impact of other stressors such as pathogens, invasive species and climate change (OECD, 2019[27]). Declines in agricultural land area, the loss of crop diversity, landscape heterogeneity (the combination of different land uses and features such as shrubs, trees, cropland in a given space), and greater use of chemical inputs – all symptoms of the intensification of agriculture – are some of the main pressures faced by farmland birds in most OECD countries (Firbank et al., 2008[38]; Tilman et al., 2001[39]). The habitat quality for biodiversity in farmland also depends on the type of crops grown (Jerrentrup et al., 2017[40]; Turley, 2006[41]).

The area of land used for agriculture has continued to decline in the majority of OECD countries, particularly in Western Europe, over the period 2002-14. The rate of decline has accelerated during this period compared to the previous decade. Despite this, agricultural output has increased 0.5% per year in the OECD region on average over the same period, signalling an increase in land productivity. Variation in the area of permanent pasture land drove most of the changes in the use of agricultural land in OECD countries during the period 2002-14.

Farmland bird populations, an indicator for biodiversity in farmland, continued to decline over the most recent period of analysis (2002-14) in almost all OECD countries that monitor them. Moreover, the rate at which farmland bird populations declined has accelerated in the most recent decade.

Recent advances in indicators for monitoring progress towards international commitments on sustainability: Measuring progress on SDG 2.4

To sustain increasing food demand from a growing population and the economic development of lagging regions, the agricultural sector will need to be able to expand supply, while minimising its environmental impacts. Moreover, these goals need to be met under changing climatic conditions and a shrinking and aging labour force in the sector. These ambitions and challenges are embodied in Sustainable Development Goal 2 (“End hunger, achieve food security and improved nutrition and promote sustainable agriculture”) of the 2030 Agenda for Sustainable Development. Target 2.4 focuses particularly on sustainable agriculture and states that “[b]y 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems, that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding and other disasters and that progressively improve land and soil quality”.

The OECD surveyed all countries covered in this report on their progress in establishing indicators and sub-indicators in relation to Target 2.4. Responses were obtained from 37 countries. Surveyed countries have started tracking progress towards sustainable agriculture targets: 18 surveyed countries have developed sub-indicators needed to track progress, 12 are in the process of developing them and only 7 countries have not yet started the process.

However, information provided by countries raises concerns that current efforts are unlikely to yield information that is comparable across countries and which enables countries to meaningfully track global progress on SDG 2.4. First, 12 out of the 30 countries that have developed or started the process for developing indicators use or plan to use sub-indicators that cover the economic, environmental and social dimensions of sustainable agriculture. Second, 3 countries have defined the share of organic cultivated land in total agricultural land as the main SDG 2.4 indicator, which oversimplifies the Target and raises the risk that these countries will focus only on this aspect of sustainability, rather than the more holistic conception referred to in SDG 2.4. Lastly and perhaps most importantly, there is surprisingly little harmonisation in sub-indicators used by countries. Figure 1.22 shows the number of sub-indicators that are shared among one or more countries. Most sub-indicators (80%) are only used by a single country and the most commonly used indicator (share of organic land in cultivated land) is shared by only 13 countries.

Figure 1.22. Share of sub-indicators used by a group of countries
Figure 1.22. Share of sub-indicators used by a group of countries

Note: In total, there were 155 sub-indicators recorded.

Source: OECD questionnaire.

 StatLink http://dx.doi.org/10.1787/888933936313

The FAO’s recent methodological guidelines for constructing indicators is a useful first step towards harmonising indicators (Box 1.5). Of the countries surveyed by the OECD, only two are currently using or planning to use FAO-recommended sub-indicators and out of those recommended, water use and availability, pesticide risk management and land productivity are the most commonly adopted (Table 1.3). Also, the three most commonly-used indicators across surveyed countries (organic cultivated land, GHG and ammonia emissions) are not sub-indicators recommended by the FAO.

Beyond this, it is worth noting that the FAO’s proposed environmental sub-indicators are mostly response-based, meaning they capture policy action and farmers’ responses, rather than drawing on the most commonly used agri-environmental indicators to track environmental pressures and the state of the environment (e.g. those captured in the OECD AEIs database). Given that many surveyed countries are adopting their own pressure- or state-based indicators for tracking progress towards Target 2.4, agri-environmental indicators tracked by international organisations such as the OECD, FAO and EUROSTAT can be a useful source for harmonising such indicators.

Table 1.3. Commonly used and proposed sub-indicators for tracking SDG 2.4

Dimension

Indicators shared by 2 or more countries

Number of countries sharing the indicator

FAO sub-indicators

Economic

Agriculture factor income

3

Economic

Farm output value per hectare

2

X

Economic

Net farm income

2

X

Economic

Public expenditures in Agricultural R&D

2

Economic

Total Factor Productivity

2

Economic

Wage rate in agriculture

2

X

Environmental

Organic land

13

Environmental

Greenhouse gas emissions

5

Environmental

Ammonia emissions

4

Environmental

Management of pesticides

3

X

Environmental

Prevalence of soil degradation

3

X

Environmental

Management of fertilizers

2

X

Environmental

Pesticides use

2

Environmental

Risk mitigation mechanisms

2

X

Environmental

Soil erosion

2

Environmental

Use of biodiversity-friendly practices

2

X

Environmental

Variation in water availability

2

X

Social

Food insecurity experience scale (FIES)

2

X

Social

Secure tenure rights to land

2

X

Social

Training

2

Economic, Environmental, Social

Sustainable agriculture land

3

Note: This table reports indicators that are shared by more than one surveyed country.

Source: OECD questionnaire.

Box 1.5. FAO guidance on indicators for tracking progress towards SDG 2.4

The indicator to measure progress to achieve Target 2.4 has been defined by the FAO as the “Percentage of agricultural area under productive and sustainable agriculture”. The most recent methodological note released by the FAO, the custodian of this indicator, by the end of 2018, establishes that its construction should:

  1. 1. Consider issues related to resilience, productivity, ecosystem maintenance, adaptation to climate change and extreme events, and soils.

  2. 2. Use farm surveys as preferred data source.

  3. 3. Distinguish between sustainable and unsustainable areas, using a definition of sustainability that encompasses economic, environmental and social dimensions.

The FAO has defined 11 sub-indicators for measuring sustainable agriculture considering economic, environmental and social dimensions: 1) Farm output value per hectare; 2) Net farm income; 3) Risk mitigation mechanisms; 4) Prevalence of soil degradation; 5) Variation in water availability; 6) Management of fertilisers; 7) Management of pesticides; 8) Use of biodiversity-friendly practices; 9) Wage rate in agriculture; 10) Food insecurity experience scale (FIES); and 11) Secure tenure rights to land.

Source: FAO (2018[42]), “SDG Indicator 2.4.1: Proportion of Agricultural Area Under Productive and Sustainable Agriculture - Methodological Note, approved by the Inter-Agency and Expert Group on SDG indicators”, http://www.fao.org/3/CA2639EN/ca2639en.pdf.

Assessing support and reforms

In 2016-18, agricultural policies in the 53 countries covered in this report provided a total of USD 705 billion (EUR 620 billion) per year on average to their agricultural sectors. About three-quarters of this support, USD 528 billion (EUR 465 billion) per year, was transferred to individual producers. At the same time, six countries, in particular Argentina and India, taxed their agricultural producers using measures that depressed the domestic price of some commodities. These implicit taxes amounted to USD 83 billion (EUR 73 billion) per year in 2016-18, which when deducted from the gross positive transfers, resulted in net transfers to agricultural producers of USD 445 billion (EUR 392 billion) and to the sector overall of USD 623 billion (EUR 548 billion) per year. While lowering the level of aggregate support, these implicit taxes also increase overall market distortions.

While there has been considerable movement towards more effective and less distorting policies, progress has stalled over the last decade and support remains unequal across countries and commodities

Many OECD countries made significant progress in reducing agricultural producer support and in shifting agricultural policies towards less distorting and sometimes better targeted measures in the 2000s. On average, the share of producer support in gross farm receipts in OECD countries declined from 30% in 2000-02 to less than 20% during the 2010s, while the share of most distorting support in gross farm receipts fell below 10%.

This progress has largely stalled in the early 2010s in OECD countries, and support has increased in some emerging economies. In 2016-18, support to producers remained unequal across countries and commodities, with some agricultural sectors relying mainly on strongly production and trade distorting measures. On average, more than 18% of gross farm receipts in OECD countries continue to originate from policies, compared to 9% on average across the emerging and developing countries covered in this report. However, these averages mask much higher dependence of farm revenues on support in some countries (up to around 50% of farm receipts originate from agricultural policies in some countries), and significant negative support in several emerging economies, notably in Argentina and India.

Overall close to 70% of all transfers to and from agricultural producers continues to originate from measures that distort farm business decisions particularly strongly. In many countries, a large part of support to producers still comes from measures that create a gap between domestic and world market prices, and potentially distort world markets. The differences in support across commodities within countries, and the co-existence of significant price support for some products with depressed prices for others, exacerbate distortions in the domestic market. Very little of the current policy mix targets agriculture productivity growth, the sustainable use of natural resources and farm resilience.

Recent policy developments are often in response to trade and market developments

In several countries, changes to agricultural policies reflect recent market developments. Some countries continued using trade and market distorting measures, notably tariffs and minimum prices, in response to fluctuations in production and market disruptions, while many countries granted payments to producers affected by price declines, natural disasters and pest and diseases, on an ad hoc basis or as part of programmes with pre-conditions for compensation. Positive developments include changes in food safety, animal welfare, and labelling regulations to improve information to domestic and foreign consumers, as well as actions to improve the functioning of the food chain, and to reinforce sustainability in food and agriculture, notably in the context of climate change mitigation. A number of countries also introduced institutional changes to consolidate organisations and clarify roles, which should help improve the efficiency of the policy-making process and contribute to reducing policy inconsistencies. Recently concluded new and deeper free-trade agreements among key trading partners are a pragmatic step forward in a context of stalled negotiations at the multilateral level and on-going trade tensions.

Significant opportunities for the sector come with challenges to meeting them sustainably

Future growth in demand for diverse and high-quality food offers significant opportunities for agriculture and the food sector. These opportunities come, however, with a number of challenges in meeting this demand sustainably in the context of limited natural resources and the uncertain impacts of climate change. Key to meeting these challenges will be increased productivity growth, enhanced environmental performance, and improved resilience of farm households and the sector overall. For instance, while global growth in total productivity has been largely stable between the 1990s and the 2000s, it has fallen in some large exporting countries. While aggregate indicators suggest progress on several elements in the environmental footprint of the sector, including reduced nutrient balances and GHG emission intensities, environmental performance remains highly uneven across countries and, in many cases, across regions within countries. Some of the positive trends in environmental performance have slowed down, and major pressures remain at national and sub-national levels.

While the precise impacts of climate change remain uncertain, the frequency and magnitude of weather-related events are expected to increase, making greater resilience of farm households increasingly important.

Improving policy coherence and transparency is crucial to meeting future challenges and opportunities

Agricultural policies continue to provide inconsistent signals to producers. Policy incoherencies remain among policy goals, across policy domains, and between policy approaches. For example, support encouraging intensive input use and increased output may co-exist with payments for the adoption of more sustainable practices. In other cases, effective environmental regulations may simply be lacking, while some countries support renewable energy and yet provide tax concessions for fossil fuels.

Comprehensive food and agricultural strategies, giving full consideration to the mix of policies that can influence behaviour across the food value chain, are needed to improve the long-term productivity, sustainability and resilience of the sector and its capacity to respond to future challenges and opportunities.

Most distorting support undermining future productivity and sustainability improvement needs to be phased out

A key element for meeting future challenges is to remove most distorting forms of support that undermine efforts to improve agricultural productivity and sustainability, including barriers to trade that contribute to maintaining a gap between domestic and world market prices. The importance of market price support (MPS) has declined in many countries over the past decades. Nonetheless, average MPS continues to account for a large share of gross farm receipts in several OECD countries, and has gained in importance in some Emerging Economies (EEs). The continued reliance of many countries on market price support and other potentially most distortive forms of transfers, prevents producers from responding to market signal and hence from employing natural resources, investments and other production inputs in the most efficient and sustainable way. Even within countries, highly distorting support and notably MPS differs significantly across commodities, creating additional intra-sectoral distortions by providing signals to producers that are not consistent with market requirements.

Several countries effectively tax agricultural producers by lowering domestic prices relative to world markets. Such negative MPS distorts markets and production decisions as does positive MPS. The primary objectives of taxing producers – raising fiscal revenues, supporting downstream industries and increasing the purchasing power of poor consumers – would be more efficiently achieved using less distortive and more targeted policies, including non-agricultural ones.

Policies inducing MPS suffer from being inefficient tools for reaching given policy objectives such as transferring income to producers (OECD, 2002[43]), and from having negative environmental implications (Henderson and Lankoski, 2019[22]). MPS policies may also prevent other policies to develop their full potential in achieving their objectives as they reduce incentives for agricultural producers to take up risk-reducing or environmentally beneficial production methods, and discourage the development of market-based risk management tools.

Market price support is generated by a variety of policy measures both at the domestic and border levels. While the measured transfers are useful to track differences in support across time and space, it is important to recognise that the multiplicity of policies, in addition to creating the measured price gaps, often also reduces market responsiveness and transparency on the way they impact on markets.

As a first step towards targeting policy measures to specific objectives and reducing negative externalities, both positive and negative market price support as well as other potentially most distorting forms of support need to be reduced and eventually eliminated. Governments should give priority to reducing price policy measures for those commodities where MPS is particularly important, be it strongly positive or strongly negative, in particular the most opaque measures.

Governments should prioritise investment in general services that enable productivity and sustainable agricultural development

Public intervention is particularly important in areas where markets fail to provide socially optimal incentives. A key area is the provision of fundamental services to the agricultural sector, as these tend to be undersupplied by private agents.

Innovation is key to productivity and sustainability improvements in agriculture, but public support to R&D and innovation accounts for a small share of total support to the sector — about 4% on average. Governments should provide stable and sufficient funding for agricultural innovation systems, notably in areas under-supplied by the private sector. Improved governance and funding mechanisms should make agricultural innovation systems more responsive to needs and generate outcomes more widely taken up by the industry. Government strategies should also focus public funding in areas that complement rather than substitute private efforts and facilitate collaboration between private and public actors in the fields of research and development, and strengthen linkages between innovation actors, including researchers, advisors, and farmers. International co-operation in research allows national specialisation and benefits from knowledge spillovers, and improves capacity to respond to global or regional challenges.

Another area where public investments are important is physical and knowledge infrastructure, ranging from rural, national and international transportation systems to the provision of information and communication, in particular digital, technologies. Infrastructure is vital to the delivery of, and access to, other services, too, and are important for connecting producers to markets and knowledge. Investments in biosecurity, animal and plant health that create and maintain incentives for producers’ own prevention measures are also key. Sufficiently funded systems adapted to national needs, and efficient inspection services, can reduce the risk of pest and disease outbreaks that could damage agricultural industries, and open and maintain access to valuable export markets.

While public expenditures for general services to agriculture have generally increased in real terms in emerging and developing economies since the early 2000s, support generally has not kept pace with the growing size of agricultural sectors, and has decreased in real terms across the OECD area. However, expenditures on agricultural innovation systems have increased on average and in most countries both in the OECD and beyond. Expenditures on infrastructure have significantly increased across most emerging and developing economies, but have declined in several OECD countries and the OECD overall.

Public efforts in the provision of general services should be adapted to national conditions. Continued and increased infrastructure investments may be required particularly in some of the exporting emerging economies where the connections to international markets have not kept pace with growth in exportable production. Digital infrastructure, together with biosecurity efforts, are likely to become more important still in the context of changing climates and related threats and uncertainties. Countries should therefore shift the focus of agricultural support towards key general services where there is a net benefit for the society from doing so.

There is ample scope to improve policy efficiency by targeting producer support to sector goals

As a general principle, policy interventions are most effective and efficient if they target a specific problem at hand. There is significant scope to improve the targeting of producer support, and to reorient budget efforts towards payments that target well defined and measurable objectives for the sector, as well as broader societal objectives. In a small number of OECD countries, payments tied to specific production practices, or associated with mandatory or voluntary agri-environmental constraints, account for a significant share of gross farm receipts. In further countries, they are increasing as a share of producer support, albeit from a low base. Their use reflects the growing importance of societal concerns about the environmental performance of farming or animal welfare, and the expectation that agriculture will provide various public goods, such as the maintenance of agricultural landscapes and biodiversity. Such payments are a more effective instrument for achieving policy objectives if they target the intended beneficiaries and specific investments where market failures prevent an efficient allocation of resources (such as those addressing agriculture’s environmental externalities and public goods). A limited number of countries use support associated with mandatory or voluntary constraints to a significant extent. On average, this support accounted for 20% of producer support in 2016-18, while support with voluntary constraints accounted for only 4% of producer support.

Progress towards improved targeting has been limited and most tax-financed support to producers remains largely provided via payments that are untargeted to beneficiaries or outcomes, without consideration of specific needs or objectives. To the extent some of this support ends up in areas where it is not needed, its effectiveness is reduced. This includes direct payments based on area, animal numbers, farm receipts or farm income, which are increasing in the OECD countries, as well as payments based on outputs and on variable inputs without constraints.

These payments are often used to support farm incomes. However, farm income support often privileges large farms if linked to historical production data. Governments should therefore identify and target the market failures that lead to persistent low incomes in agriculture. A better understanding of the financial situation of farm households is essential in order to design appropriate policy responses, depending on the scope of the problem. For example, a territorial, bottom-up approach to rural development may be more effective than a sectoral policy. The general social security system in OECD countries can be adapted to provide an income safety net for farm households. The specific needs of small, semi-subsistence farmers require using a wider range of policy approaches than agricultural policy.

In the area of risk management, government support should focus only on managing catastrophic risks for which private solutions cannot be developed. Care should be taken that public support does not crowd out private solutions based on market tools. Disaster assistance criteria should adapt to changing temperatures and precipitation patterns that may characterise the new “normal” due to climate change, keeping farmers’ incentives to increase self-reliance and improve preparedness. Care should also be taken that programmes do not over compensate producers, or lead them to adopt risky and unsustainable practices. Current support systems for risk management tools involve a large range of insurance and stabilisation schemes, as well as ad hoc assistance in response to extreme weather events. This can blur the borders between the normal business risks, medium-size marketable risks and those of catastrophic nature, reducing incentives for on-farm or market-based risk management options.

The provision of non-market goods and services sought by society often require government action. Payments to producers should target for instance the adoption of technologies and practices able to improve environmental performance and animal welfare, or to address other societal concerns. Tailoring the payments requires information on both the size of the problem at hand and the marginal costs of reducing it. Such information may not always be readily available or prohibitively costly to obtain. However, both appropriate proxies (often already applied for objectives related to natural resources) and the improvements in data availability that come with modern information technology should help to overcome such shortcomings. Payments should also be conditional on delivery of the outcomes and public goods demanded by society. Current cross-compliance requirements could be made mandatory, to provide a baseline for delivering new and more ambitious public good and environmental outcomes linked to support payments.

More efforts are needed to monitor and evaluate the environmental implications of agricultural support policies

Agricultural support policies often have multiple objectives, and may in fact not be primarily directed at improving the environmental impact of agriculture. Nevertheless, the evidence shows that they can affect the environmental performance of agriculture, for example by influencing farmers’ decisions about use of inputs, choice of outputs, or whether to remain in farming.

Recent OECD work evaluating the environmental impacts of agricultural policies allows understanding how different kinds of support differ in their environmental impacts. The OECD agri-environmental indicators also monitor key environmental pressures from agriculture and related internationally-comparable data and analysis, there are several opportunities to deepen the analysis; particularly to take into account variations at the sub-national level, and to assess the impacts of specific policy packages implemented by different countries. However, to achieve such deeper analysis, several data and knowledge gaps remain.

Further efforts are needed to close data gaps and improve data resolution and quality. Some existing OECD AEIs have poor coverage, which impedes comparability across countries and also efforts to link specific policies to environmental outcomes; particularly important gaps are observed in biodiversity, soil erosion and water-related indicators. The quality of some existing AEIs, such as nutrient balances and pesticides, needs to be improved to better assess environmental pressures and outcomes of agricultural activities. Some currently developed indicators on biodiversity, such as the Biodiversity Habitat Index, are too complex to be used for policy monitoring. The development of indicators needs to be co-ordinated between researchers and policy makers to potentiate their use and impact.

Developing analysis that accounts for heterogeneity and linkages between environmental and other impacts would help design more effective policies. There is a need more generally for more granular data and analysis of how environmental impacts of agricultural policies differ across different contexts. Examples include greater spatial resolution, more data at the farm- or even field-level, data identifying specific agricultural policy instruments, etc. Developing consistent datasets (including agri-environmental indicators) at the regional level can help to identify ‘hot spots’ of environmental pressures from agriculture. There is a need for more studies to consider both economic and environmental impacts at once, in order to gain more evidence on the potential for complementarities or trade-offs between productivity and sustainability objectives. To improve understanding of how agricultural policies affect agricultural sustainability holistically (i.e. taking into account environmental, economic and social aspects of sustainability), there is a need to develop holistic indicators and related analysis. The OECD commenced work on developing holistic green growth indicators for agriculture (OECD, 2014[44]), but more work is needed. The OECD and others are working towards establishing agreed methodologies for environmentally-adjusted total factor productivity and sustainable productivity indicators. In order to isolate the influence of policies vis-à-vis other factors, there is a need for an improved understanding of biological and economic processes which determine how farmer decision-making affects, and is affected by, environmental outcomes.

In conclusion, while progress is evident is some areas, greater efforts are needed to align agricultural policies with emerging needs of the sector. There is scope for improvement through improved policy coherence, reduced distortions and stronger focus on general services that facilitate a more productive and sustainable development of the sector ensuring long-temps competitiveness.

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[45] World Bank (2019), World Bank Databank (database), https://data.worldbank.org/indicator/NV.AGR.TOTL.ZS.

[6] World Bank Group (2019), Commodity Markets Outlook, October 2018, World Bank, https://openknowledge.worldbank.org/handle/10986/30614.

[18] WTO (1995), Agreement on the Application of Sanitary and Phytosanitary Measures, https://www.wto.org/english/docs_e/legal_e/15-sps.pdf.

Annex 1.A. Definition of OECD indicators of agricultural support

Nominal indicators used in this report

Producer Support Estimate (PSE): The annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, measured at the farm gate level, arising from policy measures that support agriculture, regardless of their nature, objectives or impacts on farm production or income. It includes market price support, budgetary payments and budget revenue foregone, i.e. gross transfers from consumers and taxpayers to agricultural producers arising from policy measures based on: current output, input use, area planted/animal numbers/receipts/incomes (current, non-current), and non-commodity criteria. PSE categories are defined in Annex Box 1.A.1.

Market Price Support (MPS): The annual monetary value of gross transfers from consumers and taxpayers to agricultural producers arising from policy measures that create a gap between domestic market prices and border prices of a specific agricultural commodity, measured at the farm gate level. MPS is available by commodity, and sums of negative and positive components are reported separately where relevant along with the total MPS.

Producer Single Commodity Transfers (producer SCT): The annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, measured at the farm gate level, arising from policies linked to the production of a single commodity such that the producer must produce the designated commodity in order to receive the payment. This includes broader policies where transfers are specified on a per-commodity basis. Producer SCT is also available by commodity.

Group Commodity Transfers (GCT): The annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, measured at the farm gate level, arising from policies whose payments are made on the basis that one or more of a designated list of commodities is produced, i.e. a producer may produce from a set of allowable commodities and receive a transfer that does not vary with respect to this decision.

All Commodity Transfers (ACT): The annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, measured at the farm gate level, arising from policies that place no restrictions on the commodity produced but require the recipient to produce some commodity of their choice.

Other Transfers to Producers (OTP): The annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, measured at the farm gate level, arising from policies that do not require any commodity production at all.

Consumer Single Commodity Transfers (consumer SCT): The annual monetary value of gross transfers from (to) consumers of agricultural commodities, measured at the farm gate level, arising from policies linked to the production of a single commodity. Consumer SCT is also available by commodity.

Consumer Support Estimate (CSE): The annual monetary value of gross transfers from (to) consumers of agricultural commodities, measured at the farm gate level, arising from policy measures that support agriculture, regardless of their nature, objectives or impacts on consumption of farm products. If negative, the CSE measures the burden (implicit tax) on consumers through market price support (higher prices), that more than offsets consumer subsidies that lower prices to consumers.

General Services Support Estimate (GSSE): The annual monetary value of gross transfers arising from policy measures that create enabling conditions for the primary agricultural sector through development of private or public services, institutions and infrastructure, regardless of their objectives and impacts on farm production and income, or consumption of farm products. The GSSE includes policies where primary agriculture is the main beneficiary, but does not include any payments to individual producers. GSSE transfers do not directly alter producer receipts or costs or consumption expenditures. GSSE categories are defined below.

Total Support Estimate (TSE): The annual monetary value of all gross transfers from taxpayers and consumers arising from policy measures that support agriculture, net of the associated budgetary receipts, regardless of their objectives and impacts on farm production and income, or consumption of farm products.

Total Budgetary Support Estimate (TBSE): The annual monetary value of all gross budgetary transfers from taxpayers arising from policy measures that support agriculture, regardless of their objectives and impacts on farm production and income, or consumption of farm products.

Ratio indicators and percentage indicators

Percentage PSE (%PSE): PSE transfers as a share of gross farm receipts (including support in the denominator).

Percentage SCT (%SCT): Single Commodity Transfers as a share of gross farm receipts for the specific commodity (including support in the denominator).

Share of SCT in total PSE (%): Share of Single Commodity Transfers in the total PSE. This indicator is also calculated by commodity.

Producer Nominal Protection Coefficient (producer NPC): The ratio between the average price received by producers (at farm gate), including payments per tonne of current output, and the border price (measured at farm gate). The Producer NPC is also available by commodity.

Producer Nominal Assistance Coefficient (producer NAC): The ratio between the value of gross farm receipts including support and gross farm receipts (at farm gate) valued at border prices (measured at farm gate).

Percentage CSE (%CSE): CSE transfers as a share of consumption expenditure on agricultural commodities (at farm gate prices), net of taxpayer transfers to consumers. The %CSE measures the implicit tax (or subsidy, if CSE is positive) placed on consumers by agricultural price policies.

Consumer Nominal Protection Coefficient (consumer NPC): The ratio between the average price paid by consumers (at farm gate) and the border price (measured at farm gate). The Consumer NPC is also available by commodity.

Consumer Nominal Assistance Coefficient (consumer NAC): The ratio between the value of consumption expenditure on agricultural commodities (at farm gate) and that valued at border prices.

Percentage TSE (%TSE): TSE transfers as a percentage of GDP.

Percentage TBSE (%TBSE): TBSE transfers as a percentage of GDP.

Percentage GSSE (%GSSE): Share of expenditures on general services in the Total Support Estimate (TSE).

Share of potentially most distorting transfers in cumulated gross producer transfers (%): represents the sum of positive MPS, the absolute value of negative MPS, payments based on output and payments based on unconstrained use of variable inputs, relative to the sum of positive MPS, the absolute value of negative MPS, and all budgetary payments to producers.

Annex Box 1.A.1. Definitions of categories in the PSE classification

Definitions of categories

Category A1, Market price support (MPS): Transfers from consumers and taxpayers to agricultural producers from policy measures that create a gap between domestic market prices and border prices of a specific agricultural commodity, measured at the farm gate level.

Category A2, Payments based on output: Transfers from taxpayers to agricultural producers from policy measures based on current output of a specific agricultural commodity.

Category B, Payments based on input use: Transfers from taxpayers to agricultural producers arising from policy measures based on on-farm use of inputs:

  • Variable input use that reduces the on-farm cost of a specific variable input or a mix of variable inputs.

  • Fixed capital formation that reduces the on-farm investment cost of farm buildings, equipment, plantations, irrigation, drainage, and soil improvements.

  • On-farm services that reduce the cost of technical, accounting, commercial, sanitary and phyto-sanitary assistance and training provided to individual farmers.

Category C, Payments based on current A/An/R/I, production required: Transfers from taxpayers to agricultural producers arising from policy measures based on current area, animal numbers, revenue, or income, and requiring production.

Category D, Payments based on non-current A/An/R/I, production required: Transfers from taxpayers to agricultural producers arising from policy measures based on non-current (i.e. historical or fixed) area, animal numbers, revenue, or income, with current production of any commodity required.

Category E, Payments based on non-current A/An/R/I, production not required: Transfers from taxpayers to agricultural producers arising from policy measures based on non-current (i.e. historical or fixed) area, animal numbers, revenue, or income, with current production of any commodity not required but optional.

Category F, Payments based on non-commodity criteria: Transfers from taxpayers to agricultural producers arising from policy measures based on:

  • Long-term resource retirement: Transfers for the long-term retirement of factors of production from commodity production. The payments in this subcategory are distinguished from those requiring short-term resource retirement, which are based on commodity production criteria.

  • A specific non-commodity output: Transfers for the use of farm resources to produce specific non-commodity outputs of goods and services, which are not required by regulations.

  • Other non-commodity criteria: Transfers provided equally to all farmers, such as a flat rate or lump sum payment.

Category G, Miscellaneous payments: Transfers from taxpayers to farmers for which there is a lack of information to allocate them among the appropriate categories.

Note: A (area), An (animal numbers), R (receipts) or I (income).

Definitions of labels

With or without current commodity production limits and/or limit to payments: Defines whether or not there is a specific limitation on current commodity production (output) associated with a policy providing transfers to agriculture and whether or not there are limits to payments in the form of limits to area or animal numbers eligible for those payments. Applied in categories A – F.

With variable or fixed payment rates: Any payments is defined as subject to a variable rate where the formula determining the level of payment is triggered by a change in price, yield, net revenue or income or a change in production cost. Applied in categories A – E.

With or without input constraints: defines whether or not there are specific requirements concerning farming practices related to the programme in terms of the reduction, replacement, or withdrawal in the use of inputs or a restriction of farming practices allowed. Applied in categories A – F. The payments with input constrains are further broken down to:

  • Payments conditional on compliance with basic requirements that are mandatory (with mandatory);

  • Payments requiring specific practices going beyond basic requirements and voluntary (with voluntary).

    • Specific practices related to environmental issues.

    • Specific practices related to animal welfare.

    • Other specific practices.

With or without commodity exceptions: defines whether or not there are prohibitions upon the production of certain commodities as a condition of eligibility for payments based on non-current A/An/R/I of commodity(ies). Applied in Category E.

Based on area, animal numbers, receipts or income: defines the specific attribute (i.e. area, animal numbers, receipts or income) on which the payment is based. Applied in categories C – E.

Based on a single commodity, a group of commodities or all commodities: defines whether the payment is granted for production of a single commodity, a group of commodities or all commodities. Applied in categories A – D.

Drivers of the change in PSE

Decomposition of PSE

Per cent change in PSE: Per cent change in the nominal value of the PSE expressed in national currency. The per cent change is calculated using the two most recent years in the series.

Contribution of MPS to per cent change in PSE: Per cent change in nominal PSE if all variables other than MPS are held constant.

Contribution of price gap to per cent change in the PSE: Per cent change in nominal PSE if all variables other than gap between domestic market prices and border prices are held constant.

Contribution of quantity produced to per cent change in the PSE: Per cent change in nominal PSE if all variables other than quantity produced are held constant.

Contribution of budgetary payments (BP) to per cent change in PSE: Per cent change in nominal PSE if all variables other than BP are held constant.

Contribution of BP elements to per cent change in PSE: Per cent change in nominal PSE if all variables other than a given BP element are held constant. BP elements include Payments based on output, Payments based on input use, Payments based on current A/An/R/I, production required, Payments based on non-current A/An/R/I, production required, Payments based on non-current A/An/R/I, production not required, Payments based on non-commodity criteria and Miscellaneous payments.

Change in Producer Price

Per cent change in Producer Price: Per cent change in Producer Price (at farm gate) expressed in national currency. The per cent change is calculated using the two most recent years in the series.

Decomposition of the change in the Border Price

Per cent change in Border Price: Per cent change in Border Price (at farm gate) expressed in national currency. The per cent change is calculated using the two most recent years in the series.

Contribution of Exchange Rate to per cent change in Border Price: Per cent change in the Border Price (at farm gate) expressed in national currency if all variables other than Exchange Rate between national currency and USD are held constant.

Contribution of Border Price expressed in USD to per cent change in Border Price: Per cent change in the Border Price (at farm gate) expressed in national currency if all variables other than Border Price (at farm gate) expressed in USD are held constant.

Definition of GSSE categories

Agricultural knowledge and innovation system

  • Agricultural knowledge generation: Budgetary expenditure financing research and development (R&D) activities related to agriculture, and associated data dissemination, irrespective of the institution (private or public, ministry, university, research centre or producer groups) where they take place, the nature of research (scientific, institutional, etc.), or its purpose.

  • Agricultural knowledge transfer: Budgetary expenditure financing agricultural vocational schools and agricultural programmes in high-level education, training and advice to farmers that is generic (e.g. accounting rules, pesticide application), not specific to individual situations, and data collection and information dissemination networks related to agricultural production and marketing.

Inspection and control

  • Agricultural product safety and inspection: Budgetary expenditure financing activities related to agricultural product safety and inspection. This includes only expenditures on inspection of domestically produced commodities at first level of processing and border inspection for exported commodities.

  • Pest and disease inspection and control: Budgetary expenditure financing pest and disease control of agricultural inputs and outputs (control at primary agriculture level) and public funding of veterinary services (for the farming sector) and phytosanitary services.

  • Input control: Budgetary expenditure financing the institutions providing control activities and certification of industrial inputs used in agriculture (e.g. machinery, industrial fertilisers, pesticides, etc.) and biological inputs (e.g. seed certification and control).

Development and maintenance of infrastructure

  • Hydrological infrastructure: Budgetary expenditure financing public investments into hydrological infrastructure (irrigation and drainage networks).

  • Storage, marketing and other physical infrastructure: Budgetary expenditure financing investments to off-farm storage and other market infrastructure facilities related to handling and marketing primary agricultural products (silos, harbour facilities – docks, elevators; wholesale markets, futures markets), as well as other physical infrastructure related to agriculture, when agriculture is the main beneficiary.

  • Institutional infrastructure: Budgetary expenditure financing investments to build and maintain institutional infrastructure related to the farming sector (e.g. land cadastres; machinery user groups, seed and species registries; development of rural finance networks; support to farm organisations, etc.).

  • Farm restructuring: Budgetary payments related to reform of farm structures financing entry, exit or diversification (outside agriculture) strategies.

Marketing and promotion

  • Collective schemes for processing and marketing: Budgetary expenditure financing investment in collective, mainly primary, processing, marketing schemes and marketing facilities, designed to improve marketing environment for agriculture.

  • Promotion of agricultural products: Budgetary expenditure financing assistance to collective promotion of agro-food products (e.g. promotion campaigns, participation on international fairs).

  • Cost of public stockholding: Budgetary expenditure covering the costs of storage, depreciation and disposal of public storage of agricultural products.

  • Miscellaneous: Budgetary expenditure financing other general services that cannot be disaggregated and allocated to the above categories, often due to a lack of information.

More detailed information on the indicators, their use and limitations is available in the OECD’s Producer Support Estimate and Related Indicators of Agricultural Support: Concepts, Calculation, Interpretation and Use (the PSE Manual) available on the OECD public website (http://www.oecd.org/tad/agricultural-policies/psemanual.htm).

OECD indicators of support

ACT

All Commodity Transfers

CSE

Consumer Support Estimate

GCT

Group Commodity Transfers

GSSE

General Services Support Estimate

MPS

Market Price Support

NAC

Nominal Assistance Coefficient

NPC

Nominal Protection Coefficient

OTP

Other Transfers to Producers

PEM

Policy Evaluation Model

PSE

Producer Support Estimate

SCT

Single Commodity Transfers

TSE

Total Support Estimate

Currencies

ARS

Argentinian peso

AUD

Australian dollar

BRL

Brazilian real

CAD

Canadian dollar

CLP

Chilean peso

COP

Colombian peso

CHF

Swiss frank

CNY

Chinese yuan renminbi

CRC

Costa Rican colon

EUR

Euro

INR

Indian rupee

ILS

Israeli shekel

ISK

Icelandic krona

JPY

Japanese yen

KRW

Korean wong

KZT

Kazakh tenge

MXN

Mexican peso

NOK

Norwegian krone

NZD

New Zealand dollar

PHP

Philippines peso

RUR

Russian rouble

TRY

New Turkish lira

UAH

Ukrainian hryvnia

USD

United States dollar

VND

Vietnamese dong

ZAR

South African rand

Notes

← 1. Kazakhstan, Ukraine, and Viet Nam also have negative PSE, but small enough not to significantly affect %PSE for emerging and developing countries.

← 2. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production (World Bank, 2019[45]).

← 3. Labour productivity is defined as the value of output per farm worker.

← 4. Water use refers to water abstraction. Water consumption is the fraction of water used that is not returned to the water system. Some technologies such as pressurised irrigation systems can decrease water use but increase water consumption by the plants (OECD, 2016[46]).

← 5. Water stress is defined as the fraction of total freshwater abstractions to total renewable water resources in a country.

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