This chapter presents developments in agriculture policy based on information and support estimates gathered for 54 countries covered in OECD’s Agricultural Policy Monitoring and Evaluation 2025. It provides an overview of recent economic and market developments relevant to the implementation of agricultural policies. It then presents an analysis of developments in the level and structure of support to agriculture. A concluding section summarises key findings and provides recommendations for policy reform.
Agricultural Policy Monitoring and Evaluation 2025
Making the Most of the Trade and Environment Nexus in Agriculture
Abstract
Agricultural support policies generated on average USD 842 billion per year in transfers towards agriculture in 2022-24 across the 54 countries covered in this report, with most support provided to individual producers and smaller shares going to the sector collectively or to consumers. Estimates suggest that nominal transfers in the last five years (post pandemic) are about 20% above the levels seen prior to 2020.
Market price support (MPS) is still the dominant form of support to producers. MPS policies generated transfers of USD 334 billion per year. At the same time, several countries use policies which caused negative market price support (lowering domestic prices) which cost producers USD 179 billion per year during the same period.
Despite international commitments to reform including through WTO and OECD declarations, the share of MPS and other potentially most distorting forms of support in overall positive producer support has declined by only 5 percentage points over the last 20 years to 66% in 2022-24.
The growth in the value of agricultural production has outpaced growth in support such that positive producer support as a share of gross farm receipts (GFR) was at historic lows in 2022‑24. The %PSE declined from 20% of gross farm receipts in 2000-02 to 12.6% in 2022-24, on average across all 54 countries. Over the same period, positive MPS has also fallen from 11.4% of gross farm receipts to 6.7%.
As agriculture tends to make up a smaller share of the overall economy over time, total support towards agriculture as a percentage of GDP has also declined since 2000. It averaged 1.1% of GDP in 2000-02 but was only 0.89% of GDP in 2022-24. However, across the emerging economies covered in this report, transfers to the sector still accounted for more than 1.6% of GDP in 2022-24, implying a more important economic burden of agricultural support.
Declining support rates as a share of the value of production have made potentially most distorting forms of support less important in the farming economy. However, spending on general services that underpin the functioning of the sector is undergoing a similar decline, which may pose risks for the longer term.
Investing in the Agriculture Knowledge and Innovation System (AKIS) will be important to boost productivity growth which has been slowing in many countries in this report. Spending on AKIS was estimated to be 0.54% of the value of production in the OECD in 2022‑24, but only 0.28% in the emerging economies. Reorienting budgetary support towards general services is one way countries can invest in the future of their agricultural sectors while maintaining the benefits of global trade.
Most support to (or from) consumers is generated by market price support policies. MPS policies transferred USD 249 billion away from consumers on average in 2022-24, while budgetary support to consumers (such as nutrition assistance) totalled USD 105 billion. Budgetary support to consumers can be more effective than market price support measures as it can be better targeted to low-income consumers or other groups in need.
Agriculture production in 2024 and 2025 was conducted in dynamic policy environment as many countries adjusted tariff rates for agricultural products, often in retaliation for other trade actions. Supply chain logistics also remained difficult, though with signs of improvement. Despite the challenges, the sector performed well globally, setting a new production record and some regions, like the European Union, also set trade records in 2024. Overall, the agriculture and food system demonstrated resilience to the usual challenges of weather, pests and volatile markets.
This chapter provides an overview of some of the macroeconomic drivers of agricultural policies and a description of overall developments of global support to agriculture based on the latest data available. Chapter 3 takes a finer look at some of the events affecting policy and how governments have responded, reporting on a country-by country basis.
Inflationary pressures continued in 2024 and 2025 while GDP growth and labour markets were sound but slowing
Conditions in agricultural markets are strongly influenced by macro-economic factors such as economic growth (measured by gross domestic product, GDP), which drives demand for agricultural and food products, as well as by prices for crude oil, natural gas, and other energy sources that underpin many production inputs in agriculture, notably fuel, chemicals and fertiliser. Energy prices also affect the demand for cereals, sugar crops, and oilseeds through the market for biofuels produced from these feedstocks.
Inflationary pressures persist in many economies, with headline inflation recently turning up after being mainly flat in 2023 and 2024 (Figure 2.1, upper graph). Food prices have been steadier, though the prices for some commodities like dairy have seen notable increases in the last several quarters (Figure 2.1, lower graph). Higher food prices have drawn public attention in many places, notably in Japan, Spain and Korea, and in the United States where high egg prices have drawn particular attention. Households have been experiencing higher inflation in a few economies, including in the United States and the United Kingdom (OECD, 2025[1]).
Global GDP growth is projected to slow from 3.3% in 2024 to 3.2% in 2025 and 2.9% in 2026, as higher tariffs and ongoing policy uncertainty slow down investment and trade. Global growth was more resilient than anticipated in the first half of 2025, especially in many emerging-market economies (OECD, 2025[2]).
Labour markets generally remained in solid health. Median annualised employment growth in the final quarter of 2024 was 0.3% in the OECD, down from 0.8% in the first half of the year. Employment growth had also started to slow in some large non-OECD economies. Nonetheless, employment as a share of the working-age population was generally high compared with the pre-pandemic period, reflecting both relatively low unemployment and increased participation rates (OECD, 2025[1]).
A challenging environment for agricultural trade in 2024 and 2025
Overall, trade has been resilient while global trade remains a critical component of food supply and security. Global shipping of bulk commodities was still complicated in 2024 and 2025, with shipping rates volatile. Shipping of grain in the Black Sea improved and the tariff landscape saw some rapid changes.
Many of the challenges faced in 2023 continued to disrupt ocean shipping in 2024. Houthi attacks in the Red Sea forced vessels to lengthen their routes, and low water levels in the Panama Canal restricted vessel transits during the first half of the year. The average yearly ocean freight rate for shipping bulk grain from the United States to Asian ports was up 8% in 2024 compared with 2023, but below the prior 4-year average (USDA, 2025[3]). Rates declined in 2025 as the situation in both the Panama Canal and in the Red Sea improved as well as on lower demand from the People’s Republic of China (hereafter “China”).
Ukraine reopened key Black Sea ports, including Odesa, Chernomorsk, and Pivdenne, in September 2023. Despite the expiration of the Black Sea Grain Initiative, Ukraine's grain shipments doubled in early 2024 and totalled 13 million tonnes in the 2024/25 marketing season, compared to 8 million in the previous season.1 This brought down the price of wheat compared with previous years.
The tariff landscape has been evolving rapidly in 2025. This has affected the timing and destination of trade in agricultural products in some cases. The United States increased tariffs on many trade partners, which resulted in a round of responses, including from China, Canada and the European Union that targeted some US agricultural exports. In all cases, these responses were put on hold to allow for negotiations.
Separately, the preferential trade agreement between Ukraine and the European Union, which allowed duty-free access for agricultural products expired in June 2025, returning to the previous system of TRQs. The European Union had already imposed on imports from Russia a flat tariff of EUR 95 (USD 103) per tonne of cereals and a 50% tariff on oilseeds and some other products. In May 2025, the European Union established an escalating schedule of tariffs on Russian fertiliser imports, set to reach 100% in three years. India, a major rice exporter, experienced high rice yields and subsequently eliminated export controls on rice, significantly increasing market availability of that grain.
The harvest in the 2024/25 season was generally good, but weather troubled some regions
Global cereals production remained high at 2 853 million tonnes in 2024/25, matching the record levels set in 2023/24. Trade in cereals was down in 2024 at 478 million tonnes but is expected to rebound in 2025. Ending stocks were also down, but the stock-to-use ratio at 30% remained comfortable. Global oilseed production is expected to hit a record of 696 million tonnes, led by soybeans with good conditions seen in Brazil (FAO, 2025[4]).
World meat production was 378 million tonnes in 2024 and is expected to increase in 2025. Poultry is the main driver, and production is expected to see steady expansion due to strong consumer demand. Meat prices were elevated through the end of 2024 and remained strong in 2025. Trade continues to expand year over year, though the pace of growth is slower in 2025, with trade restrictions and animal diseases having an impact. Milk production is forecasted to rise by 1% year-on-year, to reach 993 million tonnes in 2025. As noted earlier, dairy prices have been growing strongly since late 2023, led by high prices for butter and cheese (FAO, 2025[4]).
Extreme weather events can reduce production, lower farm income and threaten food security. Over the course of 2024 and 2025, Brazil and Argentina faced prolonged droughts, severely impacting soybean and maize production. This led to reduced exports and increased global prices for these commodities. Thailand and Viet Nam, two of the world's largest rice exporters, experienced devastating floods. This disrupted rice planting and harvesting, causing a significant drop in global rice supply. France and Spain recorded record-breaking temperatures, which affected wheat and grape yields. This not only impacted food production but also the wine industry, with lower-quality harvests. France also experienced excessive rainfall in some regions that disrupted planting and harvesting schedules, resulting in a 30% to 40% drop in winter crop production.
The 2023-2024 El Niño event, recognised as the fifth-most powerful on record, led to widespread droughts and floods, adversely affecting agricultural yields globally. For instance, severe droughts and floods affected production of nuts, fruit and grapes in Spain, Similarly, extreme weather conditions impacted cocoa production in Ghana and Ivory Coast. The Philippines experienced several natural disasters that significantly impacted its agricultural sector. The El Niño drought caused below-normal rainfall and severe drought conditions across the country, leading to major agricultural losses. Additionally, the Philippines was struck by several typhoons and volcanic eruptions further exacerbating food production challenges. Cyclone Biparjoy struck India and Bangladesh, destroying vast areas of farmland. This affected the production of tea, jute, and other crops, disrupting exports.
This section provides an overview on developments in policy support in agriculture, building on the OECD estimates of agricultural policy support that are comparable across countries and time. These show the diversity of support measures implemented across different countries and focus on different dimensions of these policies. Complete definitions are shown in Annex 2.A.
The Total Support Estimate (TSE) is the broadest of the OECD support indicators. It combines three distinct elements: a) transfers to or from agricultural producers individually; b) policy expenditures for the primary agricultural sector collectively; and c) budgetary support to consumers of agricultural commodities (Figure 2.2).
The Producer Support Estimate (PSE) measures all transfers to agricultural producers individually. Two major types of transfers can be distinguished: Market Price Support (MPS) represents transfers from taxpayers and consumers to agricultural producers through domestic prices that are higher than their international reference prices due to domestic and trade policies. MPS can also be negative, representing transfers from producers to consumers through domestic prices that are lower than references prices. Budgetary support is financed by taxpayers and comes in many forms (Box 2.1). The PSE indicator is expressed as a net transfer, including both positive and negative elements.
The General Services Support Estimate (GSSE) measures policy expenditures that benefit the primary agricultural sector as a whole, rather than going directly to individual producers. Different types of expenditures are represented in specific categories of the GSSE.
Similar to the PSE, the Consumer Support Estimate (CSE), which reports support to (or implicit taxation of) consumers of agricultural commodities, distinguishes between market transfers that mirror the MPS, and budgetary support. To avoid double-counting, only the budgetary part of the CSE is included in the TSE.
Note: *Market Price Support (MPS) is net of producer levies and excess feed cost.
Source: Annex 2.A.
The PSE is composed of MPS and budgetary support. Budgetary support is delivered in many different forms and allocated to different categories according to the PSE classification system. These budgetary categories identify the following distinctions in the way policies are implemented:
Payments based on current output of a specific agricultural commodity.
Payments based on-farm use of inputs. These either reduce the cost of purchased inputs like fertiliser or chemicals, fixed capital like farm buildings and equipment, or on-farm services that reduce the cost of technical, accounting, commercial, sanitary and phytosanitary assistance and training provided to individual farmers.
Payments based on current area, animals, revenue or income (A/An/R/I) that require production.
Payments based on non-current (i.e. historical or fixed) A/An/R/I, with current production of any commodity required.
Payments based on non-current A/An/R/I, with current production of any commodity not required but optional.
Payments based either on the long-term retirement of factors of production from commodity production, for the use of farm resources to produce specific non-commodity outputs of goods and services, or transfers provided equally to all farmers, such as a flat rate or lump sum payment.
Payments for which there is a lack of information to allocate them among the appropriate categories have their own miscellaneous category.
More information on the PSE classification system and the indicators used in this chapter can be found in Annex 2A.
Total support to agriculture is higher in nominal terms in the post-pandemic era…
The 54 countries covered in this report collectively provided USD 842 billion in positive support to the sector per year on average over 2022-24 (Figure 2.3). Of these USD 842 billion, 74% (USD 624 billion) went to producers individually. This was mainly in the form of market price support (MPS) policies that increase the domestic price of agricultural commodities, as well as budgetary support. Further, 12.5% of positive support went to consumers of agricultural products (budgetary part of the CSE) and 13.3% went to general services that benefit the sector overall (GSSE). In addition, some countries (mainly India and Argentina) implicitly taxed their farmers (resulting in negative MPS) by lowering the price of agricultural commodities to benefit consumers. This tax amounted to USD 179 billion per year on average. The net producer support (PSE), which includes negative MPS, thus amounted to USD 445 billion per year in 2022‑24, and the net Total Support Estimate (TSE) to USD 663 billion.2 The OECD carries out analysis on the effects of the support policies in the PSE database to determine their impacts and to propose avenues for reform (Box 2.2).
The level of support has been consistently higher after the COVID pandemic (after 2020). Nominal support averaged USD 845 billion in the past five years (2020-2024), 21% above the average of the decade before COVID (USD 697 billion). Higher consumer subsides make up a notable share of this increase, though support to producers is also higher in the post-pandemic period. This difference in support levels since 2020 is more pronounced in the emerging economies (37% higher) than it is in OECD countries (5% higher).
…but support has been declining as a share of production value
While nominal support levels are higher, total support as a share of the value of production has been consistently falling as the sector grows at a faster pace. Total positive support as a share of the value of production (VP) amounted to 18% in 2022-24, down from the 20% average share seen in the decade before COVID (2010-19).
The PSE is made up of many different policy categories, some of which are potentially more distorting of production and trade than others (Box 2.2). The potentially most distorting forms of support accounted for 66% of the positive producer support (USD 410 billion) on average over 2022-24 while less distorting forms made up 34% (USD 214 billion). These shares have been relatively stable since 2000; as most distorting forms of support accounted for 70% of the positive PSE in 2000-02.
The OECD has worked to investigate the nature of agricultural support policies and their impacts in order to make recommendations to policy makers for several decades. The term “potentially most distorting forms of support” used in this report comes from this research. Specifically, the OECD has used quantitative models to estimate the relative effects of different support policies (Martini, 2011[5]; OECD, 2001[6]). These analyses have concluded that MPS, support based on output payments and on the unconstrained use of variable inputs potentially have the most distorting effect on production and trade, and as a result this group of policies are collectively referred to in the context of this report as “potentially most distorting forms of support”.
This same research has concluded that policies that are most distorting also tend to have low income benefits to farmers. This is because market distortions tend to shift some of the benefits of the government transfer to other recipients, like the companies that sell fuel, seeds and fertiliser. How well funds flow from governments or consumers to producers is termed “transfer efficiency”. Input support was estimated to have the lowest transfer efficiency; only 25% of the transfers of this form made to producers actually accrue as additional income (Dewbre, Antón and Thompson, 2001[7]; OECD, 2001[6]). The body of research in this era was brought together to create “a positive reform agenda” (OECD, 2002[8]). This positive reform agenda calls for countries to identify and reform their most distorting policies, finding better alternatives when needed.
More recently, OECD work has considered how to encourage better food systems. This is the “triple challenge” of ensuring food security and nutrition for all, providing opportunities for livelihoods and promoting rural development, and ensuring environmental sustainability (OECD, 2021[9]). This idea was reinforced in the 2022 Ministerial Declaration on Transformative Solutions for Sustainable Agriculture and Food Systems.
OECD work has shown that the effects of policies considered potentially most distorting of production and trade have less clear-cut effects on the environment (Henderson and Lankoski, 2019[10]; Lankoski, Nales and Valin, 2025[11]). Policies whose benefits are linked to production appear to have the most potential to generate environmentally harmful impacts, although these impacts vary depending on the type of production or input being targeted, and possible environmental conditions attached to the support. In contrast, agri-environmental payments, and more particularly performance- or results-based payments directly tied to environmental outcomes are the most likely to deliver benefits. Local conditions, trade-offs between environmental dimensions and scales of analysis of the impacts (domestic or global level) need to be considered for a complete determination of the impacts of support instruments. Reforming or reorienting support policies can improve environmental outcomes and, in the case of budgetary support, can provide additional resources for investment in targeted and beneficial measures (Valin, Henderson and Lankoski, 2023[12]).
OECD work on risk management is centred around a holistic framework that evolved from focusing on agricultural risk management tools to a much broader agricultural resilience lens. The initial framework provided the building foundation of that work, by recognising the need to make risk management interventions commensurate to the type of risks considered (OECD, 2009[13]). In particular, it distinguished normal, market and catastrophic risks, each with consequences for farming, and corresponding policy interventions.
Some of the recommendations coming from this research include:
Governments should reform and reorient the most distorting forms of support and measures that reduce the capacity of the international trading system to fulfil its role in balancing food supplies between surplus and deficit regions.
Governments should promote broad approaches to resilience that ensure preparedness and risk management systems that respond to OECD’s established risk management framework.
Governments should reduce income support measures with low transfer efficiencies.
Governments should move towards more sustainability and resilience to address the triple challenge facing agriculture and food systems of ensuring food security and nutrition for a growing global population, addressing environmental challenges, including climate change and biodiversity loss, and providing opportunities for livelihoods for all farmers, including family farmers, and others employed along food supply chains (the “triple challenge”).
The global landscape of support has shifted towards large emerging economies
Four economies – China, Japan, the European Union, and the United States – accounted for roughly 69% of all positive producer support in 2022-24. However, the relative shares among these economies have changed dramatically over the past decades (Figure 2.4). In 2000-02, the European Union3 accounted for the largest share with 30% of all positive producer support, followed by Japan (17%), the United States (17%) and China (7%). In 2022-24, support provided by China has overtaken the United States and European Union combined and represented about 44% of positive producer support, while the European Union (16%), the United States (6%) and Japan (4%) collectively accounted for about 26%. India’s share of negative producer support (through implicit taxation) has grown from 61% in 2000-02 to 83% in 2022-24.
The policy mix and support intensity vary considerably between OECD countries and emerging economies
The share of support in farm revenue, expressed as a percentage of gross farm receipts (GFR), has been declining steadily in OECD countries (Figure 2.5). That is, sector growth is reducing the role of support in farm income over time. The picture in emerging economies is more mixed, as levels of support (driven by China) have been growing at a rate closer to the rate of increase in GFR (Figure 2.5).
The %PSE in the OECD averaged 13% over 2022-24, down from 18% in 2010-12 and 28% in 2000-02. The average %PSE in emerging economies averaged 6.7% in 2022-24, up from 3.8% in 2000‑02. Further, these figures for average support to producers include the effects of negative MPS. Excluding this, the %PSE among emerging economies was 12.2% in 2022-24, close to (but still below) the OECD average.
MPS is the largest category of support in both OECD and emerging economies. However, OECD countries tend to make more use of budgetary support based on land while emerging economies make more use of input support as well as negative MPS. In OECD countries, MPS has declined as a share of total support between 2000 and 2024. Positive MPS has been increasing in emerging economies, mostly in China. The use of budgetary support in emerging economies has become less dominated by input support (considered one of the potentially most distorting forms of support) over time.
In 2022-24, USD 410 billion per year, or two-thirds of the USD 624 billion in positive support to producers across the 54 countries covered in this report, was in forms considered to be the potentially most distorting to production and trade (8.3% of gross farm receipts). Across the OECD, such support amounted to USD 95 billion or 5.7% of GFR, while for the 11 emerging economies such transfers to producers totalled to USD 314 billion per year (10%). Policies reducing domestic prices additionally gave rise to USD 179 billion in implicit taxation in 2022-24 (3.6% of GFR) and, while benefitting consumers, these also have a distorting effect.
Government policies can increase or reduce food prices for consumers
Consumer policies can have varied objectives, and the overall effect of agricultural support on consumers is strongly linked to policies aimed at producers. These policies can increase food costs (taxing consumers) or reduce them (supporting consumers) (Box 2.3). In net terms over all the countries in this report, policies increased the cost of agricultural commodities to consumers by 3.2% of gross consumer expenditures measured at farm gate prices (%CSE) on average between 2022-24 (Figure 2.6).4
The consumer support estimate is composed of three elements. These are defined by the source and destination of the transfer generated by the policy.
Transfers from Consumers to Producers. The largest component of the CSE in most countries, this is MPS that raises domestic prices. Consumers pay a higher price for food, and farmers receive a higher price for their production, therefore the direction of transfer is from consumers to producers (i.e. an implicit taxation of consumers). This can also be reversed when policies keep domestic prices low – this negative MPS is a transfer from producers to consumers (i.e. support to consumers). Some countries use a mix of positive and negative MPS, though it is more common in OECD countries for MPS policies to only make transfers from consumers to producers.
Other Transfers from Consumers. This is also a result of MPS policies. When a country uses MPS to raise the domestic price of a commodity, and the country is also a net importer of that commodity, the government is the beneficiary of the transfer in the form of tariff revenue earned on the imported product.
Transfers from Taxpayers to Consumers. This is a result of budgetary policies (which are funded by taxpayers) that make transfers to consumers, such as in the form of reduced cost for school lunches or nutrition assistance programmes. In most countries, this is the smallest component of the CSE.
Transfers from consumers to producers averaged USD 77 billion in OECD countries in 2022-24, and USD 117 billion in the 11 emerging economies. Other transfers from consumers to taxpayers (essentially tariff revenue for imports for consumption) totalled USD 22 billion in the OECD and USD 53 billion in the emerging economies.
Budgetary consumer support rose dramatically following the outbreak of the COVID-19 pandemic, it was 57% higher in 2020-24 compared with the decade prior (USD 109 billion vs USD 69 billion). This support declined in 2024. Budgetary support to consumers was USD 96 billion in 2024 in total for all countries in this report, down from USD 101 billion in 2023. As is the case for overall support, the increase in the post-COVID era is more pronounced in the emerging economies (up 85%) than in OECD countries (up 45%) India represents about 91% of the budgetary support to consumers in the emerging economics group. In the OECD, the United States is the largest provider of food assistance to low-income consumers (accounting for 98.6% of OECD budgetary transfers to consumers).
Many emerging economies seek to find a balance between supporting producers or consumers. The emerging economies are a diverse grouping, some of whom offer mainly positive MPS benefitting producers (China) and others mainly negative MPS benefitting consumers (India and Argentina), some use a mix of positive and negative MPS for different commodities (Kazakhstan and Indonesia) and others make almost no use of MPS at all (Brazil). Some countries aim to keep consumer prices within a certain range, using budgetary transfers, preferential distribution of food or other interventions. For example, India has an important programme for public distribution of food grains.
In OECD countries, the implicit taxation of consumers has decreased significantly. The %CSE was ‑18.1% in the early 2000s but only ‑1.9% in 2022-24, a substantial reduction in the effect of policy on consumer prices. Conversely, consumers in emerging economies have seen the %CSE move from near zero 20 years ago to an average ‑4.1% in 2022-24. This is largely the result of increasing MPS as of 2012 (when MPS in China approximately doubled).
Improving infrastructure is a major government objective
Policies aimed to benefit the agricultural sector as a whole and which are not directed at producers or consumers individually are termed “general services”. Investments in general services can help the agricultural sector to become more productive, sustainable and resilient. For example, infrastructure spending can be used to maintain irrigation canals or reservoirs, or to provide rail or port storage which makes transport and marketing of products easier and reduces wastage. General services also include inspection services to ensure food quality and safety or the efficient control and handling of pests and diseases, investments in knowledge and innovation and institutional investments that support farm organisations or help farmers sell their products at home and abroad, among others. Public funding of agricultural R&D can underpin knowledge infrastructure, strengthen the research with public good aspects, and complement private research efforts (OECD, 2019[14]).
Countries provided USD 112 billion in support for general services to the agricultural sector (GSSE) on average over 2022-24. This is about 2.4% of the value of production of the sector, a decline from 4.7% in 2000-02. In OECD countries, GSSE equalled 3.5% of the value of production, down 2 percentage points from 2000-02 and in emerging economies it was 1.9%, down by 1.7 percentage points (Figure 2.7).
Spending on infrastructure is the largest component of the GSSE, though this share is decreasing in the OECD (37% in 2022-24) and increasing in emerging economies (56% in 2022-24). Public stockholding is important in emerging economies (21%), but little used in the OECD area since the mid-2000s (1.2%).5 OECD countries dedicate a larger share of GSSE spending to marketing and promotion (about 18%) while emerging economies spend only about 1.4% of their general support in this area. Spending on agricultural knowledge and innovation systems (AKIS) was USD 25 billion, 30% of the OECD GSSE but only 15% in the emerging economies, where this spending share peaked at 26% of the GSSE in 2013 and has been declining since then. AKIS spending as a share of the sector’s value of production was 1.1% in the OECD but only 0.3% in the emerging economies in 2022-24.
Positive and negative MPS both increased in 2024
Preliminary estimates indicate that net market price support declined in 2024. Positive MPS increased by an estimated USD 21 billion and negative MPS became USD 31 billion more negative (Figure 2.8). Market price support reflects trade and domestic market policies in place but can change in response to world price movements or changes in production, so a change in MPS need not imply a change in the underlying policy (Box 2.4). Negative MPS became more negative in most countries that make important use of it, though India as the largest user drives the total. Overall, the gap between domestic prices and world prices has narrowed over the past 20 years. On average over all countries effective prices received by farmers were 4% higher than world prices in 2022-24, down 9 percentage points from the 13% higher prices in 2000-02.
Market price support (MPS) estimates the benefit or loss farmers receive when there is a difference between domestic prices and world prices. This price gap is calculated by measuring the difference between the actual domestic market price and price farmers would have received were there no price-distorting policies in place (OECD, 2016[15]).
The price gap for a specific commodity measures the difference between two prices: the average domestic price and a reference price calculated at the same level in the value chain (generally at the farm gate). This reference price corresponds to the country’s border price, i.e. the import price (for net-imported commodities) or the export price (for net-exported commodities). The reference price can be observed directly, estimated based on prices in similar or neighbouring countries or in rare cases using tariff or export tax data.
If the price gap is such that the domestic price is twice the reference price, the MPS as a share of commodity gross receipts should be 50% and producers receive double the revenue they would have otherwise (assuming there were no other forms of support offered). If domestic prices are five times border prices, the MPS as a share of commodity gross receipts would be 80%. For negative MPS, if the domestic price is half the world price (such as would result from a 50% tax), MPS as a share of commodity gross receipts would be -100%. Market developments (such as exchange rate movements affecting world prices expressed in local currencies) may influence the price gap, so changes in MPS do not always mean that a policy has changed.
The price gap is calculated only if policies exist that could cause such a gap, such as border measures that restrict or promote imports or exports, and government purchases, sales and intervention prices in the domestic market. If countries do not implement such policies, the price gap is assumed to be zero. The price gap for individual commodities is adjusted for differences in product qualities, processing and transportation margins, to compare like with like.
MPS 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.
Source: OECD (2020[16]).
Measures lifting domestic prices above reference levels provided USD 334 billion per year in positive MPS to producers on average between 2022-24 across all covered economies (6.7% of annual gross farm receipts). Negative MPS caused by policies which reduce domestic prices was worth USD 179 billion or 3.6% of gross farm receipts over that time. Import tariffs, tariff rate quotas and minimum support prices are the most frequently applied policies which give rise to positive MPS, whereas export restrictions, quotas, bans or export taxes are most frequent for negative MPS.
Only a quarter of support is provided subject to specific requirements
Payments made to producers are often subject to conditionality that sets out obligations that farmers must meet to be eligible. These conditions involve actions that may be “mandatory” or “voluntary”. The mandatory input constraints include requirements to comply with prevailing laws or regulations, while voluntary constraints go beyond legal requirements where farmers adopt or refrain from certain practices in exchange for receiving the payment. Within the voluntary input constraint label, a further distinction is introduced to identify the character of constraint, i.e. whether it concerns (i) environmental practices, (ii) animal welfare, or (iii) other practices. For example, in Switzerland there is a payment per head of animal raised in housing systems that provide a certain amount of space for free movement, in addition to other benefits for the animal (Systèmes de stabulation particulièrement respectueux des animaux). Market price support cannot be made conditional, as beneficiaries cannot be excluded from higher prices in the domestic market. Budgetary payments however can be, and often are, subject to mandatory or voluntary input constraints.
In 2022-24, 23% of support to all countries covered in this report was delivered subject to constraints, with the majority of these being mandatory input constraints (17% of support). This is an increase from 12% in 2000-02. Voluntary environmental constraints apply to 5% of all transfers to producers, the same share as in 2000-02, and other constraints account for about 1% (Figure 2.9). Constraints are almost always applied to support that is based on non-commodity criteria. More than half of support based on area, animal numbers, revenue or income have some conditions attached. Payments based on input use are less often subject to input constraints (about 11%).
Certain commodities are singled out for support
Policies are often designed to affect specific commodities. For example, a tariff put on imports of wheat results in market price support which advantages domestic producers of wheat to the exclusion of producers of other commodities. By their construction, policies providing MPS and payments for outputs are commodity specific, while other budgetary payments may or may not be targeted to a specific commodity. For example, payments based on inputs or other production factors often stipulate terms that make them commodity specific such as when a fertiliser subsidy is granted only for the production of maize, or a payment that is made per head of livestock. The total value of such payments taken together with MPS are reported for each commodity as single-commodity transfers (SCT).
SCTs are highest for sugar, maize and rice, for which they each represented over 15% of the gross receipts for the respective commodity in 2022-24 (Figure 2.10). However, there is significant variation in the level of commodity support among the covered countries. For sugar and maize, almost all SCT support is positive, indicating that most countries’ objectives for these policies centre on the producers of these commodities. Support for rice is more mixed. While the preponderance of support benefits producers (positive SCT for rice is 18% of commodity gross receipts), there is significant support for consumers also observed in the negative MPS, which is equal to about 6% of commodity gross receipts. Rice and sugar are two of the so-called “white commodities” that historically have received particular policy attention (Box 2.5).
For some commodities, there are clear difference in policy objectives in different countries. At an aggregate level, over the 54 countries and economies covered in the report, net SCT for wheat, eggs, sunflower and soybeans are all near zero, but this is as a result of both substantial amounts of positive and negative MPS (along with other SCT support). In 2022-24, positive and negative SCT for wheat combined amounted to 13% of GFR. For sunflower it was 11%, eggs 5%, and soybeans 8%. Looked at in this way, the commodities that receive the most overall policy attention are (in order), rice, milk, sugar, maize, wheat and poultry. Some countries act to raise the prices of these commodities, others lower them.
The “white commodities”, sugar, rice, milk and cotton, have historically shared a propensity for high rates of government support in many countries. For example, in the period between 2002 and 2005, cotton accounted for 2% of the US value of production, but received 22% of government payments (Sumner and Buck, 2007[17]). Rice and sugar are still near the top of the list of commodities receiving the most SCT as a percentage of commodity receipts, but milk finds itself at the other end of the spectrum with a large amount of negative MPS, making it one of the most highly “taxed” commodities. Does it still make sense to think of these commodities as an important grouping for agricultural policy makers?
In the 1980s at the height of the agricultural trade war, support for rice, milk and sugar were between 70% and 80% of receipts (Figure 2.11). In 1986, 4 out of every 5 dollars received by rice producers came from support policies. Cotton was not yet in the support picture to the same degree, but support trended upwards until the 2000s, where it has remained relatively stable at around 25% of receipts ever since. The high levels of support for sugar, milk and rice were not sustainable and successive rounds of trade negotiations and reforms has reduced the support for these commodities substantially. The addition of new producers less inclined to offer support in the PSE is also a factor in the trend; the earliest years of the database contain only OECD countries.
The most dramatic change happened for milk. Milk was never a highly traded commodity, a function of both the limited transportability of the product and the high barriers to trade in place. Changing market conditions over time reduced MPS in those countries that traditionally provided it, and other countries expanded consumer support for milk such that periodically since 2007 and consistently since 2018, overall SCT support for milk has been negative.
These commodities can still be considered sensitive in many countries, but it is no longer the case that they receive unusual amounts of support. Perhaps it is time for the idea of “white commodities” to fade to black.
Note: For a background on the history of the so-called trade wars, see https://ers.usda.gov/sites/default/files/_laserfiche/publications/41764/54007_ages8923.pdf?v=32146.
Commodity-specific support can influence production choices by changing the relative returns of commodities or groups of commodities. For example, a payment per bale of cotton produced can lead to more area being planted to cotton instead of other alternatives. In this way, support that is targeted to a few specific commodities can be more distorting of production than the same level of support that is distributed evenly across commodities or that is not commodity specific. This can hinder the adaptive capacity of farmers when commodity-specific support makes producers less likely to move away from a commodity when growing conditions change.
Overall support remains above pre-pandemic levels in nominal terms. Potentially most distorting measures continue to dominate
Over the past five years, overall support to agriculture at current prices has remained above levels seen prior to the COVID-19 pandemic, and the distribution of support has changed only little. Average annual support to the sector reached approximately USD 842 billion over 2022–24. The majority of this support continues to be delivered through policy instruments considered potentially most market- and trade-distorting and the share of this kind of support has remained stable. Governments should reform and reorient, including phasing out where possible, the most distorting forms of support, especially MPS and support based on the unconstrained use of variable inputs. OECD research suggests that less-distorting forms of support that are targeted and tailored to their objectives are a more efficient use of public resources. Positive directions for reform include towards policies with demonstrated benefits for sustainability, while ensuring the capacity of the international trading system to balance food supplies between surplus and deficit regions.
Producer support is declining relative to the value of agricultural production
Although support levels (not adjusted for inflation) have been trending higher, producer support as a share of GFR has declined as the value of agricultural production has increased. In 2024, producer support accounted for 9% of GFR, down from 18% in 2000-02. This is a positive development for global trade, as potentially most distorting forms of support are less important in the farming economy, improving conditions for global trade competition. Nevertheless, certain commodities such as rice, sugar, maize, and milk continue to receive significant market price support, contributing to enduring distortions in global trade flows. OECD research suggests that support focussed on a small number of commodities has a more distortionary effect than non-commodity specific support. Moreover, commodity specific support makes structural adjustments to the sector more difficult, thus reducing the sector’s capacity to adapt to changing conditions. Governments should reorient product-specific support to allow for greater market responsiveness and more broadly support resilience and ensure preparedness, including risk management systems following OECD’s established risk management framework.
Market price support policies create trade-offs between consumers and producers
Most support to (or from) consumers is generated by market price support policies. Such mechanisms introduce trade-offs between consumer and producer welfare, often constraining policy reform due to distributional impacts. Transitioning from MPS (which is paid for mostly by consumers) to targeted budgetary support (which is financed from taxpayers’ money) could mitigate these trade-offs and enhance the effectiveness of assistance. This is particularly helpful for vulnerable or low-income consumer groups. Reforming MPS policies can also benefit producers. MPS typically has lower income transfer efficiencies for producers and can make structural adjustments of the sector more difficult, such that alternatives could provide greater benefits.
The majority of producer support continues to be provided without specific environmental conditions
Just one-quarter of producer support is delivered subject to constraints, with the majority of these being mandatory input constraints, while voluntary environmental constraints only apply to 5% of all transfers to producers. Such constraints can help improve the sector’s environmental performance, although details in the programme implementation matter. In designing such policies, governments should align environmental protection and the mitigation of negative environmental impacts with promoting open and transparent agro-food trade and addressing the triple challenge facing agriculture and food systems.
More investments in innovation are needed
The estimated amount of general services support – investment in sector-enabling infrastructure and services – declined to 2.4% of the value of agricultural production in 2022-24. Of particular concern is lower reported investment in agricultural knowledge and innovation systems relative to the sector’s size, especially in emerging economies, where it averaged just 0.3% of the sectoral production value in 2022‑24. This trend poses risks to longer-term productivity improvements and the sectors’ preparedness for future challenges. OECD work finds that public funding of agricultural R&D is crucial. It should provide stable funds for knowledge infrastructure, strengthen the research with public good aspects, and complement private research efforts. In this regard, government should redirect fiscal resources to targeted innovation for sustainable productivity growth.
Slow reform has implications for productivity and food security
The combination of low public investment in innovation and persistent market distortions increases pressure on global food systems. Slowing productivity growth in many OECD countries hampers progress toward shared policy objectives, including enhancing farm income, improving environmental performance, and strengthening food security. Public investment in innovation remains a critical lever for reviving productivity growth. The total amount of positive support provided in 2022-24, USD 842 billion per year, shows that governments are willing to provide substantial resources to aid their agricultural sectors. Redirecting and optimising this support could foster a more productive, resilient, and sustainable agricultural sector.
References
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[10] Henderson, B. and J. Lankoski (2019), “Evaluating the environmental impact of agricultural policies”, OECD Food, Agriculture and Fisheries Papers, No. 130, OECD Publishing, Paris, https://doi.org/10.1787/add0f27c-en.
[11] Lankoski, J., E. Nales and H. Valin (2025), “Assessing the impacts of agricultural support policies on the environment: Economic analysis, literature findings and synthesis”, OECD Food, Agriculture and Fisheries Papers, No. 223, OECD Publishing, Paris, https://doi.org/10.1787/808f110c-en.
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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 Box 2 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.
Gross Farm Receipts (GFR): The annual monetary value of production, to which budgetary transfers to individual producers are added (i.e. VP + PSE – MPS).
Commodity Gross Receipts: The annual monetary value of production for an individual commodity, to which budgetary transfers to producers of that commodity are added (i.e. VP + producer SCT – MPS).
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 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 aggregated 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.
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 phytosanitary 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.
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.
Note: The change in Producer Support Estimate (PSE) is not decomposed when PSE is negative for the current and/or previous year. The producer price change and the border price change are not calculated when both negative and positive market price support (MPS) occur at the commodity level for the previous year. Note that negative MPS estimates for livestock products may arise in cases of aligned product prices if there is positive MPS for feed commodities.
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 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.
Million USD
Note: p: provisional. NPC: Nominal Protection Coefficient. NAC: Nominal Assistance Coefficient. A/An/R/I: Area planted/Animal numbers/Receipts/Income. The OECD total for 1986-88 includes all 38 OECD member countries except Chile, Colombia, Costa Rica, Israel, Latvia, Lithuania and Slovenia, for which data are not available. The OECD total for 2000-02 includes all 38 OECD member countries except Latvia and Lithuania. TSE as a share of GDP for 1986-88 for the OECD is an estimate based on available data. 1. Market Price Support (MPS) is net of producer levies and excess feed cost. MPS commodities: see notes to individual country tables.
Source: OECD (2025), “Producer and Consumer Support Estimates”, OECD Agricultural policy monitoring (database), https://data-explorer.oecd.org/.
Million USD
Note: p: provisional. NPC: Nominal Protection Coefficient. NAC: Nominal Assistance Coefficient. A/An/R/I: Area planted/Animal numbers/Receipts/Income. The Emerging Economies include Argentina, Brazil, China, India, Indonesia, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam. 1. Market Price Support (MPS) is net of producer levies and excess feed cost. MPS commodities: see notes to individual country tables.
Source: OECD (2025), “Producer and Consumer Support Estimates”, OECD Agricultural policy monitoring (database), https://data-explorer.oecd.org/.
Million USD
Note: p: provisional. NPC: Nominal Protection Coefficient. NAC: Nominal Assistance Coefficient. A/An/R/I: Area planted/Animal numbers/Receipts/Income. The All countries total includes all OECD countries, non-OECD EU Member States, and the Emerging Economies: Argentina, Brazil, China, India, Indonesia, Kazakhstan, the Philippines, Russian Federation, South Africa, Ukraine and Viet Nam. The All countries total for 2000-02 includes data for all countries except Latvia and Lithuania, for which data are not available. 1. Market Price Support (MPS) is net of producer levies and excess feed cost. MPS commodities: see notes to individual country tables.
Source: OECD (2025), “Producer and Consumer Support Estimates”, OECD Agricultural policy monitoring (database), https://data-explorer.oecd.org/.
← 1. Ukraine’s trade in 2024: restoration of logistical routes, see https://www.osw.waw.pl/en/publikacje/analyses/2025-01-17/ukraines-trade-2024-restoration-logistical-routes.
← 2. Tables with the breakdown of the Total Support Estimates for the three regional aggregates used in this report, including OECD, Emerging Economies, and All Countries, can be found in Annex 2.B.
← 3. Included 15 countries.
← 4. Consumer support includes support to both final consumers of agricultural products as well as industry consumers who transform agricultural commodities into processed products (first-stage buyers).
← 5. Cost of public stockholding are expenditures to cover the cost of storage or disposal of agricultural commodities, as well as their depreciation.
← 6. Data shown in the OECD database on agricultural support are based on submissions from the covered countries.