United States Department of Agriculture

Economic

Research

Service

Economic

Brief

Number 30

November 2020

Economic and Food Security Impacts 

of Agricultural Input Reduction Under 

the European Union Green Deal’s Farm 

to Fork and Biodiversity Strategies

Jayson Beckman, Maros Ivanic, Jeremy L. Jelliffe,

Felix G. Baquedano, and Sara G. Scott
United States Department of Agriculture

Economic Research Service 

www.ers.usda.gov

Recommended citation format for this publication:

Beckman, Jayson, Maros Ivanic, Jeremy L. Jelliffe, Felix G. Baquedano, and Sara G. 

Scott. November 2020. Economic and Food Security Impacts of Agricultural Input 

Reduc-tion Under the European Union Green Deal’s Farm to Fork and Biodiversity 

Strategies, EB-30, U.S. Department of Agriculture, Economic Research Service.

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United States Department of Agriculture

Economic

Research

Service

Economic

Brief

Number 30

November 2020

Jayson Beckman, Maros Ivanic, Jeremy L. Jelliffe,

Felix G. Baquedano, and Sara G. Scott

Abstract

The European Commission (EC) unveiled its Farm to Fork and Biodiversity Strategies that 

would impose restrictions on European Union (EU) agriculture through targeted reductions 

in the use of land, fertilizers, antimicrobials, and pesticides. The proposal also pledges to use 

EC trade policies and other international efforts to support this vision of sustainable agri-food 

systems, suggesting intentions to expand the reach of the policy beyond the EU. To examine the 

economic implications of the proposal, we performed a range of policy simulations on several 

of the proposed targets using three progressively broader adoption scenarios of the EC’s initiative. Under all these scenarios, we found that the proposed input reductions affect EU farmers 

by reducing their agricultural production by 7 to 12 percent and diminishing their competitiveness in both domestic and export markets. Moreover, we found that adoption of these strategies 

would have impacts that stretch beyond the EU, driving up worldwide food prices by 9 (EU 

only adoption) to 89 percent (global adoption), negatively affecting consumer budgets, and ultimately reducing worldwide societal welfare by $96 billion to $1.1 trillion, depending on how 

widely other countries adopt the strategies. We estimate that the higher food prices under these 

scenarios would increase the number of food-insecure people in the world’s most vulnerable 

regions by 22 million (EU only adoption) to 185 million (global adoption).

Keywords: European Union, EU, international trade, global markets, production systems, 

research and development, R&D, exports, food prices, food security, Farm to Fork, biodiversity, 

land, fertilizers, pesticides, pest control, antimicrobials, agriculture productivity, commodities, 

labeling, USDA, U.S. Department of Agriculture, ERS, Economic Research Service.

Acknowledgments

The authors thank Andrew Muhammad (University of Tennessee), Jason Grant (Virginia 

Polytechnic Institute and State University), Michael Adjemian (University of Georgia); and 

Utpal Vasavada, Anne Effland, and Philip Jarrell (USDA, Economic Research Service (ERS)) 

for their reviews and comments. They would also like to acknowledge comments and feedback 

received during presentations and interagency reviews. Thanks also to ERS editors Grant Wall, 

Angela Brees, and Elaine Symanski, and Chris Sanguinett (ERS) for design assistance.

Economic and Food Security Impacts of 

Agricultural Input Reduction Under the 

European Union Green Deal’s Farm to Fork 

and Biodiversity Strategies
ii

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

Trends in Agricultural Input Use and Food Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Model and Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

Scenarios ....................................................................6

Results ......................................................................7

Impacts on Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Impacts on Market Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

Impacts on Trade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

Economywide Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17

Welfare ..................................................................... 17

GDP .......................................................................20

Land use ....................................................................22

Gross farm income ............................................................22

Impacts on Food Expenditures ...................................................23

Impacts on Food Security ......................................................25

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28

Appendix 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31

Appendix 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34

Contents

Errata

On February 23, 2021, the Summary table was revised to correct errors that occurred in data 

transmission. No other components of the report were affected by the error.
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providing timely information on economic and policy 

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United States Department of Agriculture

A report summary from the Economic Research Service November 2020

Economic and Food Security Impacts of 

Agricultural Input Reduction Under the 

European Union Green Deal’s Farm to Fork 

and Biodiversity Strategies

Jayson Beckman, Maros Ivanic, Jeremy L. Jelliffe,

Felix G. Baquedano, and Sara G. Scott

What Is the Issue?

The European Commission (EC) has unveiled its Farm to Fork and Biodiversity Strategies that would 

impose restrictions on European Union (EU) agriculture through targeted reductions in the use of land, 

fertilizers, antimicrobials, and pesticides. The Farm to Fork and Biodiversity Strategies (European 

Commission, 2020) and which we refer to as “the Strategies,” represents a fundamental shift in EU food 

and agriculture policy, with correspondingly fundamental implications for the structure and productivity 

of the EU food and agriculture industry. As the EU is a major agricultural producer and participant in 

international agricultural trade, this policy shift is likely to affect international markets for agricultural 

commodities and, consequently, the broader food and agriculture system.

What Did the Study Find?

Our analysis, which examines three adoption scenarios—EU-only, middle (adoption by some countries, 

and including explicit EU trade restrictions against non-adopters), and global adoption—suggests that 

the EC’s 10-year plan of targeted reductions in the use of land, antimicrobials, fertilizers, and pesticides 

would lead to a reduction in EU agricultural production and reduce its competitiveness in domestic and 

export markets. If the plan were adopted beyond the EU, those impacts would also expand with consequences for worldwide welfare and food insecurity. In summary, we found that by 2030:

• The decline in agricultural production in the EU, as shown in the summary table, would range

from 7 percent (global adoption) to 12 percent (EU-only). Impacts on production would be

smaller worldwide, except in the case of global adoption, when production would decline by 11

percent.

• The decline in agricultural production would tighten the EU food supply, resulting in price

increases that impact consumer budgets. Prices and per capita food costs would increase the most

for the EU, across each of the three scenarios. However, price and food cost increases would be

significant for most regions if Strategies are adopted globally. For the United States, price and

food costs would remain relatively unchanged except in the case of global adoption.

• Production declines in the EU and elsewhere would lead to reduced trade, although some regions

would benefit depending on changes in import demand. However, if trade is restricted as a result

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United States Department of Agriculture

Economic 

Research 

Service

Economic 

Brief 

Number 30

November 2020

Economic and Food Security 

Impacts of the European Union 

Green Deal’s Farm to Fork and 

Biodiversity Strategies

Jayson Beckman, Maros Ivanic, Jeremy Jelliffe, 

Felix Baquedano, and Sara Scott

Summary
of the imposition of the proposed measures, the negative impacts are concentrated in regions with the world’s most 

food-insecure populations. 

• The declines in production and trade, coupled with the projected increases in food commodity prices, would significantly reduce the EU’s gross domestic product (GDP), especially if adoption was limited to the EU. In that case,

the EU’s decline in GDP would represent 76 percent of the decline in the worldwide GDP. If the Strategies were

adopted beyond the EU, however, the EU’s share in decline of worldwide GDP would drop to 49 percent in the

middle scenario and as low as 12 percent if globally adopted. The effects on the GDP of the United States would be

smaller than for the EU and worldwide under all adoption scenarios.

• Food insecurity, measured as the number of people who lack access to a diet of at least 2,100 calories a day,

increases significantly in the 76 low- and middle-income countries covered in our analysis due to increases in food

commodity prices and declines in income, particularly in Africa. By 2030, the number of food-insecure people

in the case of EU-only adoption would increase by an additional 22 million more than projected without the EC’s

proposed Strategies. The number would climb to 103 million under the middle scenario and 185 million under

global adoption.

How Was the Study Conducted?

To examine the prospective market and food security impacts of the EC proposal, we focused on several selected agricultural input reductions specified in the Strategies: reduction of pesticide use by 50 percent, reduction of fertilizer use 

by 20 percent, reduction of antimicrobial use for livestock by 50 percent, and removal of 10 percent of existing farmland 

from agricultural use. To capture the potential impacts of not only EU adoption of the Strategies but also “the global transition to sustainable agri-food systems through its trade policies and international cooperation instruments” (European 

Commission, 2020), we used the three different adoption scenarios noted above. 

The first scenario assumes the EU alone implements the Strategies and trade is permitted normally—the EU-only 

scenario. The second scenario, a “middle scenario,” extends the restrictions on agricultural inputs to those EU trade 

partners who depend on food and agricultural exports to the EU. This scenario simultaneously assumes the EU restricts 

50 percent of imports from regions that do not adopt the Strategies to simulate the use of trade policies to support the 

Strategies. In the third scenario, the “global scenario,” the study considers the impacts of the extreme case of global adoption of the Strategies, as suggested by the EC’s pledge to support a global transition. 

In the first phase of our study, we used a specific Computable General Equilibrium (CGE) model, the Global Trade 

Analysis Project–AgroEcological Zones (GTAP-AEZ) model, to examine the potential market and economywide impacts 

from the adoption of the Strategies. GTAP-AEZ divides the world into 18 agroecological zones and explicitly accounts 

for land use by allowing cropland to compete with other land applications. We assumed a medium-run horizon; thus, the 

results could be interpreted as to impacts that might occur over 8–10 years. To examine potential food security impacts 

from the adoption of the Strategies, in the second phase of our study, we used the estimated changes in gross domestic 

product (GDP) and food prices from the CGE model as inputs into the USDA, Economic Research Service’s International 

Food Security Assessment (IFSA) model, which estimates changes in food consumption in developing countries.

Our study was limited to an analysis of agricultural input reductions under the Strategies and does not consider other 

important aspects of the EC’s proposal, for example, increased land in organic production or reductions of food waste and 

greenhouse gas emissions. In addition, while our results indicate the potential market and food security impacts from the 

Strategies stemming from proposed input reductions, they do not provide any information about the potential benefits and 

costs to the environment and human health. Evaluation of environmental and human health (benefits and costs) under the 

Strategies is subject to ongoing debate. However, estimation of the market impacts of the Strategies can serve as an important tool to assess policy aims.

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Summary of the main impacts of the Strategies under the three scenarios1

European Union United States Worldwide

-12 0 -1

17 5 9

2 -3

-2

-20 6

-16 6 2

153 59 51

na1 na 22

-71 -2 -94

-11 0 -4

60 1 21

-10 -7

-9

-10 -2

8 1 4

651 16 159

na na 103

-186 <-1 -381

-7 -9 -11

53 62 89

-5 -15

-4

2 3

15 34 17

602 512 450

na na 185

Scenario: EU adoption only

Production (percent change)

Prices (percent change)

Imports (percent change)

Exports (percent change)

Gross farm income (percent change)

Increase in food cost (annual per capita change in U.S. dollars)

Increase in food insecurity2 (millions of people)

GDP (change, in billions of U.S. dollars)

Scenario: middle3

Production (percent change)

Prices (percent change)

Imports (percent change)

Exports (percent change)

Gross farm income (percent change)

Increase in food cost (annual per capita change in U.S. dollars)

Increase in food insecurity (millions of people)

GDP (change, in billions of U.S. dollars)

Scenario: global adoption

Production (percent change)

Prices (percent change)

Imports (percent change)

Exports (percent change)

Gross farm income (percent change)

Increase in food cost (annual per capita change in U.S. dollars)

Increase in food insecurity (millions of people)

GDP (change, billions of U.S. dollars) -133 -74 -1,144

Notes: 1na = not applicable; 2Food insecurity is estimated for 76 low- and middle-income countries and not the full set of 

countries in the Global Trade Analysis Project – AgroEcological Zones (GTAP-AEZ) model; 3In the middle scenario, we 

assume that trade partners who depend on food and agricultural exports to the EU or that have close colonial ties adopt 

the Strategies to maintain their trading relationship with the EU. The regions that we assumed adopt the Strategies in this 

scenario are European Free Trade Association (EFTA) countries (Iceland, Liechtenstein, Norway, and Switzerland); other 

European countries; Turkey; Ukraine; the Middle East and North Africa; and Africa.

The gross farm income calculation is based on the returns to agriculture from changes in prices and quantities. Those 

returns are not going to all farmers, but probably those that own land.

Source: USDA, Economic Research Service calculations using the GTAP-AEZ model and USDA, ERS’s International 

Food Security Assessment Model.

1Percent change represents a one-time change from the counterfactual values (i.e., no policy change); all annual changes 

expressed in U.S. dollars represent the impacts evaluated over the period of a year after the changes have occurred.
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Economic and Food Security Impacts of the 

European Union Green Deal’s Farm to Fork 

and Biodiversity Strategies

Introduction

Agricultural productivity gains during the 20th century can be credited with meeting many of the 

global population’s food and fiber needs, and these benefits accrued even as the global population 

grew. These gains can be largely attributed to public and private investment in agricultural research 

and development (R&D), spurring innovation in the field by farmers worldwide (Fuglie, 2018; 

USDA, International Agricultural Productivity Data Set). At the same time, intensive modern agricultural production systems, such as conventional tillage and chemical inputs, are associated with 

environmental spillovers. Unmitigated environmental spillovers can increase the cost of farming 

to society. Thus, significant efforts have been made to foster sustainable intensification in modern 

farming systems, aiming to minimize the environmental footprint while maintaining farm productivity (Garnett et al., 2013). 

The European Commission (EC) presented its vision to achieve these goals in its Farm to Fork 

and Biodiversity Strategies (henceforth referred to as “the Strategies”) released in May 2020 under 

the Commission’s larger European Union (EU) Green Deal (European Commission, 2020). The 

Strategies take a broad approach to promoting sustainability in agriculture in four areas for improvement. These include (1) sustainable food production, (2) sustainable food consumption, (3) sustainable food processing and distribution, and (4) food loss and waste prevention. The Strategies focus 

on EU agricultural sector stewardship of the environment, as well as food security and human health 

outcomes, by setting policy targets for 2030. Ultimately, the Strategies’ proposal represents a fundamental shift in the EU food and agriculture industry and has, therefore, been the subject of wide 

debate (Schebesta and Candel, 2020). 

In principle, the costs to society from the Strategies must be offset by the prospective gains (e.g., 

environmental and human health) from implementing such a policy (Bullock and Salhofer, 2003). 

This paper focuses on the former and considers the impacts of the specific reductions listed in the 

Strategies (i.e., land, antimicrobials, pesticides, and fertilizer) on agricultural production, food 

prices, and societal welfare. In the latter case, evaluation (benefits and costs) of environmental and 

human health under the Strategies is subject to considerable debate. However, estimation of the 

market impacts of the Strategies can serve as an important tool to assess policy aims. To this end, 

we are the first to examine the prospective impacts of the Strategies in their current form. Here, we 

considered the prospective market and food security impacts of agricultural input reductions—(1) 

sustainable food production—that are clearly specified in the Strategies (figure 1). 
2

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Figure 1

European Commission Farm to Fork and Biodiversity Strategies: agricultural input

reductions 

• Pesticide use by 50 percent;2

• Fertilizer use by 20 percent;

• Antimicrobials for livestock by 50 percent;3

• Land in agriculture by 10 percent.

In focusing on the Strategies’ proposed reductions of agricultural inputs (figure 1), we expect that 

additional inputs, such as labor, could be used as a replacement. This will have a large impact on 

agricultural production, relying on shifts to new (or older) practices that require different labor 

supply and allocation of resources throughout the growing season. A primary constraint to adopting 

alternatives to chemical inputs is the unavailability of qualified managers and insufficient labor at 

critical times during the growing season (Bastiaans et al., 2008; Chikowo et al., 2009; Rossi et al., 

2012). Furthermore, these methods are largely crop and scale dependent, which means that while 

some crops may readily transition to alternative production systems that are less chemically dependent, others may face catastrophic decline by doing so. For example, sugar beet farmers in France 

lobbied successfully for special chemical use to prevent crop losses from pest pressure (Mallet, 

2020). Furthermore, agrochemical rates in the environment can be highly localized and driven by 

crop value, as evidenced by two recent studies (Maggi et al., 2019; Skevas and Oude Lansink, 2020). 

While the Strategies appear to presume that research and innovation can adequately maintain agricultural productivity through these shifts, considering the factors in play, this may not be feasible 

under the proposed timeframe.

Accordingly, we assumed that agricultural productivity is essentially fixed during the 8- to 10-year 

horizon of the Strategies for this analysis. This assumption is based on studies on investment in agricultural research and development (R&D) over recent decades and the technology treadmill effect 

(Fuglie, 2018; Levins and Cochrane, 1996).4 The foundation of this treadmill is well-funded R&D; 

evidence suggests that investments over recent decades are inadequate to maintain current productivity levels. Consequently, this assumption about future technologies and innovation given current 

R&D stocks is conservative, and without additional investments in R&D, producers face declining 

productivity in the future. In addition, lags between investments in agricultural R&D and productivity increases are more than two decades (Baldos et al., 2019). Thus, a concern for agricultural 

markets could be that implementing restrictions on input use will outpace innovation, resulting in 

regressive food and agricultural production trends and, ultimately, shortages. As the EU is a major 

agricultural producer and participant in international agricultural trade, these Strategies could affect 

global markets for agricultural commodities.

2The Strategies also specify the reduction of pesticide risk by 50 percent, but the Strategies do not specify the risk criteria—hence, we were unable to include it in our model. 

3The EU also proposes to reduce antimicrobials in aquaculture by 50 percent, but we do not examine this. 

4The observed pattern of perpetual adoption of innovative technologies by farmers to maintain productivity over time is 

referred to as the agricultural technology treadmill effect (Levins and Cochrane, 1996). 
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Trends in Agricultural Input Use and Food Production

To cultivate crops and other primary agricultural products, farmers use land, labor, capital (in the 

form of tractors and other machinery),5 and other inputs such as seed, fertilizer, and pesticides. 

Trends for selected inputs used on a global scale and in the EU are shown in figure 2(a) for pesticide 

and fertilizer use, and land in agriculture in figure 2(b) (United Nations, 2020). EU application of 

fertilizers has remained steady after two decades of declining usage linked to agriculture policy 

reform (European Commission, 2019). While EU use of fertilizer and pesticides has been relatively 

stable since 1990, worldwide application increased from 1990-2018, stabilizing around 2010. Land 

usage in agriculture (figure 2(b)) both worldwide and in the EU decreased at similar rates from the 

mid-2000s until present.

Agricultural production per capita (figure 3), as measured by the United Nations’ gross per capita 

Production Index Number (PIN), declined slightly in the EU from 1990 to 2018, while the measure 

increased steadily worldwide over the same period (United Nations, 2020).6 Trends in agricultural 

production are similar for fertilizer and pesticide use over the period from 1990 to 2018, with slight 

declines in the EU and general increases worldwide. While input use and food production has 

increased over the previous quarter-century worldwide, EU levels have been relatively stable over the 

same period. Thus, a concern is that the Strategies’ proposed input reductions (figure 1) will result in 

corresponding declines in food and agricultural production, as well as impacts to prices, gross farm 

incomes, trade, food security, and societal welfare.

5These are often referred to as endowments, as is the case in our computable general equilibrium (CGE) model. 

6The PIN is indexed to agricultural production levels during the period from 2014-16 (i.e., 2014-16=100). 
4

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Figure 2

Selected agricultural inputs world and European Union 28 from 1990-2018: (a) fertilizer and 

pesticide, and (b) land in agriculture

Note: Kg/Ha refers to kilograms per hectare.

Source: United Nations, 2020.

 
5

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Figure 3

United Nations’ Food and Agriculture Organization: Gross per capita production index 

number, world and European Union 28, 1990-2018

Note: FAO is the Food and Agriculture Organization of the United Nations. Agricultural production is indexed to the period 

from 2014-16 (i.e., 2014-16 = 100). PIN is the production index number.

Source: United Nations, 2020.

 
6

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Model and Scenarios

Computable General Equilibrium (CGE) models are often used to evaluate the potential impacts 

of a policy, as they provide economywide and commodity-specific effects while considering interindustry linkages. These models are often used to examine policy targets under alternative implementation scenarios, such as regulations, taxation, subsidies, and combinations thereof.7 A benefit 

of the CGE model is that it captures the economic effects of regulations related to land being taken 

out of use. In the first phase of our study, we used a specific CGE model, the Global Trade Analysis 

Project–AgroEcological Zones (GTAP-AEZ) model, which divides the world into 18 agroecological 

zones and explicitly accounts for land use by allowing cropland to compete with other land applications. We assumed a medium-run horizon; thus, the results could be interpreted as to impacts that 

occur over 8-10 years. See appendix 1 for the regions and commodities used in the model and our 

work to update the model to 2020. 

For these reasons, CGE models are well-suited to estimate market impacts of the Strategies; 

however, the Strategies could also lead to changes in international food security as prices for food 

and other goods rise. To consider potential food security impacts, we then used the estimated 

changes in gross domestic product (GDP) and food prices from the CGE model as inputs into the 

USDA, Economic Research Service’s (ERS) International Food Security Assessment (IFSA) model, 

which estimates changes in food consumption in developing countries.

Scenarios

We considered three different implementation scenarios to assess the potential impacts of the policies encompassing EC’s intent to “support the global transition to sustainable agri-food systems 

through its trade policies and international cooperation instruments” with all its partners (European 

Commission, 2020). 

In the first scenario, we assumed the EU alone implements the Strategies and does not impose any 

restrictions on trade—the EU-only scenario (see box, “Implementing the Scenarios: Methodology”). 

The second scenario (which we denote as the “middle scenario”) extends the restrictions of agricultural inputs to the EU’s trade partners who depend on food and agricultural exports to the EU.8 At 

the same time, we assumed the EU restricts 50 percent of imports from regions that do not adopt 

the Strategies. The third scenario, the “global scenario,” considers the impacts resulting from global 

adoption of the Strategies, assuming all regions in the world adopt the reduction in agricultural 

production inputs listed in figure 1. 

7Further examples of using CGE models to consider changes in agricultural input use are Bareille and Gohin (2018); 

Bartelings et al. (2016); Bellora and Bureau (2014); Nadoveza Jelić and Šimurina (2020); and Rendleman et al. (1995). 

8In the middle scenario, we assume that trade partners who depend on food and agricultural exports to the EU or that have 

close colonial ties adopt the Strategies to maintain their trading relationship with the EU. The regions that we assumed adopt 

the Strategies in this scenario are European Free Trade Association (EFTA) countries (Iceland, Liechtenstein, Norway, and 

Switzerland); other European countries; Turkey; Ukraine; the Middle East & North Africa; and Africa. 
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The impacts estimated across the scenarios indicate significant price increases for agricultural 

commodities and decreased GDP in numerous countries.9 Given these large changes to commodity 

prices, the final phase of the analysis examines potential impacts on international food security 

using the IFSA model. 

Results

We present results across the three scenarios at the same time to facilitate comparison. Results are 

first presented for market impacts from the CGE model (production, prices, trade, and economywide 

impacts), then we present the food security results from the IFSA model.10

9As a reviewer points out, the EU proposals lead to large changes estimated by the CGE model, but the model is dependent on parameters that might not be well designed for very large structural transformations that affect production, input 

substitution, and trade. 

10See appendix table A-3 for the definition of agriculture in our model. 

Implementing the Scenarios: Methodology

To incorporate the impact of the Strategies in the model, all components in figure 1 are conducted 

simultaneously. They are applied as a reduction in each targeted value across primary agriculture as a whole; e.g., we target a reduction in fertilizer use by 20 percent for all crops. This 

approach allows the model to solve for the most economically efficient use of the components 

while still achieving the policy target. To achieve the required reductions in inputs such as 

fertilizer, pesticide, and antimicrobial use, we introduce a tax on their use, which brings the 

total use to the lower application level. To achieve a reduction in the available land across 18 

agroecological zones (AEZs), we adjust the available area by land type so the returns to each 

type of land are constant, and the total area is reduced by the 10-percent reduction in land 

specified in the Strategies. To minimize distortions from policy-related government revenue, 

we distribute all tax revenue generated by the input taxes back to producers in the form of a 

uniform tax reduction on farm output. While the model assumes the most economically efficient means to implement the Strategies, real-world application is likely to result in considerable 

deviation from this efficient implementation.

To properly model the substitution between fertilizers, pesticides, and antimicrobials with land, 

labor, and capital, we set the elasticity to -0.13 (previously, the elasticity is 0—hence, no substitution), which is half of the value of the substitution between land, labor, and capital (see 

Dissanayake et al. (2017) for a visual of the Global Trade Analysis Project GTAP-AEZ model 

production structure). The assumed elasticity is similar to that used for developed countries in 

Bartelings et al. (2016), which assumes a value of -0.15.

For the middle scenario, the 50 percent reduction in imports is introduced directly in the model. 

The model then solves for the tariff that would be necessary to restrict trade by that amount—

acting as a non-tariff measure (see Beckman and Arita (2017) for more information on these 

trade barriers). By not completely banning trade, we assume that some farmers in regions that 

do not adopt the Strategies still produce products that are allowed into the EU (e.g., processed 

food and animal products). If the reduction in imports was more than 50 percent or completely 

banned, the market impacts in the middle scenario would be more significant.
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Impacts on Production

In the EU-only scenario, worldwide agricultural production decreases by 1 percent, precipitated by 

a decline in agricultural production in the EU of 12 percent. All other regions in our model—none 

of which impose the production changes required by the Strategies—realize an increase in agricultural production, as they seek to replace the lost EU production (and trade). Results by commodity/

region are shown in appendix table B-1. These results show the largest declines in production by 

product for the EU: oilseeds (61 percent), wheat (49 percent), and other crops (44 percent).11 The 

projected decreases in the production volume of EU oilseeds are driven by strong worldwide competition (and EU price increases). For wheat, production decreases are driven by reduced fertilizer and 

land use (fertilizer and land make up a relatively large proportion of production costs for wheat). 

For other crops, the decreases result from reduced land use (land makes up 21 percent of production 

costs—the highest share for any agricultural product category). The two regions in which overall 

agricultural production declines in this scenario, the European Free Trade Association (EFTA) and 

Ukraine, are closely tied to agricultural trade with the EU in general. Their agricultural production 

declines as they are not able to compete with other regions for the rest of the international market. 

In addition, these regions could have a reduction in agricultural production from cross-commodity 

effects (land moving out of one commodity to another). Agricultural production in Oceania12 is 

projected to increase by the greatest percent (2 percent), as they have increases in the production of 

oilseeds, sugar, vegetable oil, and wheat. Production volumes of meats increase by the fastest rate in 

Canada, but because Canada is a relatively small producer, the decline in EU production is filled by 

a larger international producer, Brazil. 

In the middle scenario, worldwide agricultural production declines by 4 percent as regions that adopt 

the Strategies, along with the EU, also see a decrease in agricultural production. As noted in figure 

4, some regions have large production declines. Agricultural production in Ukraine is reduced by 

33 percent, with double-digit decreases in production for almost every commodity (appendix table 

B-2). Production in the Middle East and North Africa region and the EFTA region both decline by 

15 percent, again with many commodities undergoing double-digit production losses. In addition to 

those regional declines, other regions that do not adopt the Strategies also observe decreased agricultural production. However, those changes tend to be smaller than in countries where the Strategies 

are adopted. This decrease may occur because those regions (Argentina, Brazil, India, other Asia, 

and other South America) tend to rely more on trade with those adopting the Strategies and, therefore, scale back production as a result of diminished overseas demand. For example, 37 percent of 

Brazil’s agricultural exports were to regions assumed in this scenario as adopting the Strategies, 

versus only 16 percent of U.S. exports. In the middle scenario, Canada realizes the highest increase 

in agricultural production, mainly through increased pork production (appendix table B-2).

11Other crops include products such as herbs, spices, and cut flowers.

12Oceania includes Australia, New Zealand, and the islands in the Pacific. 
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Figure 4Changes in agricultural/food output volumes for the three scenariosNote: EU-only is defined as only the European Union (EU) implementing the Strategies; in the middle scenario, trade partners who depend on food and adopt the Strategies; and global is defined as all regions adopting the Strategies. EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ model.

 
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Finally, the global scenario leads to the greatest reduction in worldwide agricultural production (11 

percent). Figure 4 indicates that total agricultural production volumes would fall in every region, 

with half of the regions incurring a double-digit decrease. Those regions where total agricultural 

production volumes would fall by the greatest percentages are Ukraine (from oilseeds production), 

Argentina (from oilseeds and beef production), and Brazil (from oilseeds production) (appendix 

table B-3). Most other major agricultural producers incur a decrease in agricultural production, including the United States (9 percent) and China (17 percent). Oceania is the region with 

the smallest decrease (3 percent), as production of oilseeds and vegetable oil increases, despite a 

decrease in almost every other commodity. 
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Impacts on Market Prices

Large-scale reductions in EU agricultural output, as observed in the EU-only scenario, would 

tighten market availability of agricultural commodities in the EU, leading to increased prices (figure 

5). Appendix table B-4 indicates prices increasing across all agricultural commodities in the EU, 

with most commodity prices climbing by double digits. Agricultural prices increase across all 

regions (figure 5) due to the increase in EU prices (affecting imports) and an increase in competition 

for domestically produced goods (i.e., exports). Agricultural prices in Ukraine increase mainly as a 

result of their close trade with the EU.

The middle scenario highlights differences in prices between those who join the EU’s initiative to 

reduce agricultural inputs targeted in the Strategies and those who do not join. The 6 regions that 

adopt the Strategies all see an increase in the price of agricultural products by more than 50 percent. 

In the middle scenario, regions adopting the Strategies have the same increase in prices from the 

reduction in input use; but they also have higher prices as trade restrictions increase the prices of 

agricultural products. As a result, prices in these regions are high—most commodities incur a tripledigit increase in these regions (appendix table B-5). In particular, commodities that are primary 

products (crops) undergo triple-digit increases in response to restrictions under the Strategies in all 

regions with few minor exceptions. These increases lead to higher prices for meats as well, given 

that there are higher prices for the feed input (and the decrease in antimicrobial use). Conversely, 

regions that retain traditional production practices but are constrained in their trade to the EU see 

little change in prices. 

Larger production changes in the global scenario lead to larger changes in prices across all regions, 

with double-digit increases for total agriculture for all regions and triple-digit increases for many 

regions. The price of most crops increases by triple digits in every region (appendix table B-6). 

Figure 5 indicates that the increase in the price of agricultural products is dampened for those 

regions adopting the Strategies in the middle scenario. However, these regions would still see a 

larger increase than non-adopters in the scenario. A move toward equalizing agricultural prices 

worldwide occurs as trade is not hindered under the global scenario; however, prices are the highest 

in this scenario since all regions are implementing the Strategies.
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Impacts on Trade

The decrease in EU agricultural production impacts international trade with a 2-percent decrease 

across all regions. Although many regions fill some of the lost EU trade, the EU is a major trade 

market, and their decrease outweighs the gains for the other regions. For the EU, the EU-only 

scenario would lead to an increase in the volume of agricultural imports in the EU (figure 6) and a 

decrease in exports (figure 7). The largest expected increase in bilateral EU imports by commodity 

and source are for other crops (31 percent), wheat (18 percent), and milk (raw) (19 percent) 

(appendix table B-7). The EU is a major importer of other crops; its largest source is Africa (35 

percent of EU imports). Africa’s exports to the EU would increase by 103 percent. Canada is the 

EU’s main source of wheat imports in our model (44 percent); Canadian exports of wheat to the EU 

grow by 177 percent under this scenario. Finally, as the EU imports most of its oilseeds from Brazil 

and the United States, both of those regions increase exports of oilseeds to the EU. All other regions 

other than Brazil and Ukraine undergo a decrease in their agricultural imports.

Agricultural exports in the EU-only scenario increase across all non-EU regions in the model, with 

several regions registering double-digit increases in crop exports (appendix table B-10). India’s 

exports of other crops and wheat grow by 64 and 50 percent; Africa’s exports of beef and other crops 

increase 36 and 37 percent, respectively, and exports of many crops in the former USSR and rest of 

Europe increase. Other major agricultural exporters such as Argentina, Brazil, and the United States 

increase exports of crops and their total agricultural exports, but the increase tends to be smaller 

than other regions as they are not major exporters of other crops. 

Under the middle scenario, worldwide agricultural trade decreases by 9 percent—the largest 

decrease across all three scenarios. Imports fall in most regions with double-digit decreases in 

imports in 9 of the 20 regions (figure 6). Imports in all regions decrease, except Ukraine, which is a 

major importer of agricultural products from the EU, particularly fruits and vegetables and all meat 

products (appendix table B-8). Imports in all other regions decrease due to restrictions on exports to 

the regions adopting the Strategies—the CGE model results indicate that the non-adopting regions 

also reduce their imports from regions where the Strategies are adopted. 

Similar results occur for exports (figure 7), where the reduction in trade to the regions adopting 

the Strategies is greater than the trade occurring between regions that do not adopt. Canada and 

Japan are the only regions where agricultural exports increase; Japan is a very small exporter, while 

Canada benefits from an increase in pork exports (appendix table B-11). 

Worldwide, agricultural trade decreases by 4 percent if the Strategies are adopted by every region 

(global scenario). Changes in production and prices cause changes in the mix of agricultural imports 

(appendix table B-9). Production for most crops increases in most regions but decreases in 8 of 

the 20 regions. Similarly, in 10 of the 20 regions, milk and meat imports fall. For total agriculture, 

imports decrease in most regions. Japan is a major agricultural importer; however, its imports fall by 

4 percent. This reduction is mainly because of lower imports of processed agriculture—in particular, 

vegetable oil. Brazil, a major agricultural exporter, increases overall imports relative to current low 

levels due to an increase in processed agriculture. 
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Like imports, agricultural exports by region are also mixed (appendix table B-12). As mentioned, 

Brazil is a major agricultural exporter, and its exports are estimated to decrease by 45 percent. In 

particular, Brazil’s oilseeds exports decrease by about 50 percent. In this scenario, India’s exports 

increase due mainly to rice exports. Note that Africa has an increase in agricultural exports under 

all three scenarios; thus, the model likely assumes that African producers adopt and meet the 

Strategies. This would likely involve a significant investment and transformation of its production 

practices to follow the policy as written. This is perhaps possible as technological innovations that 

are compliant with the strategy catch up. However, the initial fixed costs may prove too difficult to 

overcome in the time frame, considering the unique circumstances applicable to lower income developing countries.
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Figure 5Change in agricultural/food market prices for the three scenarios

 

Note: EU-only is defined as only the European Union (EU) implementing the Strategies; in the middle scenario, trade partners who depend on food and 

adopt the Strategies; and global is defined as all regions adopting the Strategies. EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
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Figure 6Change in agricultural/food import volumes for the three scenarios

 

Note: EU-only is defined as only the European Union (EU) implementing the Strategies; in the middle scenario, trade partners who depend on food and adopt the Strategies; and global is defined as all regions adopting the Strategies. EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
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Figure 7Change in agricultural/food export volumes for the three scenarios

 

Note: EU-only is defined as only the European Union (EU) implementing the Strategies; in the middle scenario, trade partners who depend on food and adopt the Strategies; and global is defined as all regions adopting the Strategies. EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
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Economywide Impacts

The changes created by the Strategies ultimately lead to economywide changes. This section 

discusses the impacts on societal welfare, GDP, land use, gross farm income, and food expenditures.

Welfare

Societal welfare, or consumer well-being, is measured in the GTAP model by the equivalent variation (EV) (see box, “Equivalent Variation in the GTAP: A Measurement of Welfare”), which allows 

for the decomposition of changes in welfare into several activities—allocative efficiency, terms of 

trade, endowments, and other. Using this measure, welfare would be reduced worldwide by $95.9 

billion in the EU-only scenario. As noted in appendix table B-13, most ($80.1 billion) is due to 

allocative efficiency (AE)—the redistribution of resources from a more productive sector to a less 

productive one. Figure 8 indicates that the EU is the region with the largest reduction in welfare; 

$84.2 billion of the total worldwide reduction in welfare originates from the EU, mostly due to AE 

(67 percent). In addition, the loss of endowments ($14.5 billion) and terms of trade ($10.7 billion) 

further reduce welfare in the EU (appendix table B-13). Conversely, several regions in the EU-only 

scenario benefit from an increase in welfare, as they gain from the reduction in the EU terms of 

trade. 

Worldwide welfare is reduced by more in the middle scenario, with a $396 billion decline. The EU 

again has the largest reduction in welfare at $206 billion. Trade loss in the EU declines by a smaller 

amount, but the loss in AE is greater in this scenario as more resources are pulled from relatively 

efficient production. In the EU-only scenario, welfare increases in half of the regions; however, it 

increases in only five regions in the middle scenario.
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Figure 8Welfare change by region for the three scenarios

 

Note: EU-only is defined as only the European Union (EU) implementing the Strategies; in the middle scenario, trade partners who depend on food and adopt the Strategies; and global is defined as all regions adopting the Strategies. EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
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Considering that the projected impacts are larger under the global adoption scenario, it is not 

surprising that estimated welfare impacts are also comparatively greater than the other scenarios 

(figure 8). If these Strategies are adopted globally, welfare falls by $1.1 trillion. Welfare would 

increase in some regions—these are primarily larger agricultural exporters who gain from higher 

prices and trade terms. For the EU, although their agricultural production decreases by a smaller 

scale relative to others under the global scenario, they experience a greater loss in welfare relative to 

the EU-only scenario. Welfare decreases from endowments and terms of trade, but the reduction in 

welfare from the AE component is greater under the global scenario than the total welfare change in 

the EU-only scenario (appendix table B-15). The model also generates details on contributions by 

commodity to AE. For the EU, AE losses stem mainly from the worldwide trade decline in 

processed food and pesticides. It is noted that the EU is the world’s largest exporter (by value) of 

pesticides (WTO, 2020). Reducing international demand leads to a reduction in EU exports and the 

movement of resources out of pesticide production. China realizes the greatest welfare loss worldwide, with large losses in AE and trade terms (appendix table B-15). The reduction in AE is due to 

the movement of resources out of pesticide use—data from the United Nations (2020) indicate that 

China uses four times the value of any other country of pesticides in agricultural production. China’s 

terms of trade losses are largely from paying higher prices for agricultural products on the international market.

Equivalent Variation in GTAP: A Measurement of Welfare 

The equivalent variation (EV), as used in the Global Trade Analysis Project (GTAP) model, is 

the change in income at current prices that would have the same impact on consumer welfare as 

would the change in prices with income unchanged. The results provide a decomposition of the 

total economywide welfare measure, allocating the change in welfare to four activities (which 

can be summed to equal total welfare change). 

• The first welfare change is allocative efficiency, which involves the redistribution of

resources to other sectors. That is, if a policy change occurs, resources such as labor will move

based on the relative profitability of each sector. A move from a less efficient to a more efficient

sector will generate an increase in welfare based on allocative efficiency.

• The second component involves the terms of trade, which is the relative price of imports

in terms of exports for a region. If a region undergoes an increase in the price they receive for

their exports on the international market, relative to the price of products that they import, they

experience a gain in welfare from terms of trade.

• The third component involves endowments and is the change in total factor productivity

calculated as the ratio of aggregate inputs to aggregate outputs.

• The final activity is deemed “other” and largely involves how well a region is able to

attract foreign investment based on the profitability of a region given the change in scenario.

Welfare is different from gross domestic product (GDP), as noted in Dynan and Sheiner (2018), 

as it is primarily a calculation of consumer well-being, while GDP measures production and 

investment.
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GDP

Figure 9 presents information on changes in real GDP (GDP adjusted for inflation). For the EU-only 

implementation of the Strategies, GDP increases in only two regions, Argentina and Ukraine. Most 

regions, like the EU, incur decreases in GDP. The EU undergoes the largest decrease in GDP at 0.3 

percent, which based on actual GDP leads to a decrease of $71 billion.

Under the middle scenario, larger decreases occur to both EU and worldwide GDP. EU GDP 

decreases by 0.8 percent, or $186 billion, based on actual GDP. In this scenario, however, regions 

where agriculture plays a more important role in the economy experience larger GDP decreases if 

they adopt the Strategies than does the EU. Those regions tend to be the developing regions (note 

that the EFTA, a developed region with a relatively high share of the economy in agriculture, has a 

smaller decrease in GDP than the EU). For example, Ukraine has a reduction in GDP of 6.2 percent, 

and Africa has a 3.7-percent reduction. Worldwide GDP decreases by 0.4 percent. 

The impacts to real GDP are also much larger under the global scenario (figure 9). In the EU-only 

scenario, worldwide real GDP decreases by 0.1 percent; however, if these Strategies are implemented globally, real GDP would decrease worldwide by over 1 percent ($1.1 trillion). In certain 

regions dependent upon agricultural exports, projected impacts are relatively large. In Ukraine, 

GDP decreases by nearly 6 percent; in Africa, it decreases by 3 percent; and in Brazil, by almost 3 

percent. The EU also sees a larger decrease in GDP under the global scenario as compared to when 

they implement the Strategies on their own; as the largest exporter of pesticides, a reduction in international demand leads to a reduction in GDP.
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Figure 9Change in GDP for the three scenarios

 

Note: EU-only is defined as only the European Union (EU) implementing the Strategies; in the middle scenario, trade partners who depend on food and adopt the Strategies; and global is defined as all regions adopting the Strategies. EFTA refers to the European Free Trade Association. GDP = gross domSource: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
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Land use

One measure prescribed by the EC calls for the removal of 10 percent of existing farmland from 

production (figure 1). The class of land use (forestry, cropland, and pastureland) from which that 

area is removed is determined within our model. Under the EU-only scenario, the EU reduction 

in land use is mostly cropland, an outcome caused by reducing pesticide and fertilizer use—and a 

subsequent decline in production (appendix table B-16). In addition, pastureland is more affected 

than forestry because of the reduction in antimicrobials, which reduces the number of live animals 

that use that type of land. In most other regions, cropland increases with a concurrent reduction in 

other land uses, as agricultural production increases in those regions. 

Under the middle scenario, more regions reduce their overall land use, with the EU again reducing 

cropland. Other regions implementing the Strategies also see a reduction in cropland (appendix table 

B-17). In most regions, overall land use decreases by more than 10 percent.

Finally, under the global scenario, land use is reduced across all regions (appendix table B-18). In 

many regions, cropland use decreases by greater than 10 percent--beyond what the EC first proposed 

in the Strategies. Generally, this is because the decrease in crop production tends to be greater than 

10 percent—as a result of the larger than 10-percent decrease in fertilizer and pesticide use.13

Gross farm income

We also estimate the change in gross farm income based on the returns to agriculture from changes 

in prices and quantities (Beckman et al., 2018).14 In the EU-only scenario, gross farm income in 

the EU falls by 16 percent, as decreased productivity prevents farmers from benefiting from higher 

prices (table 1). Gross farm income increases in all other regions, led by a 26-percent increase in the 

EFTA region from increased agricultural exports to the EU. Thus, farmers worldwide benefit from 

higher prices and a decrease in EU production, but food consumers instead pay those higher prices. 

Results for the middle scenario indicate that more regions see overall decreases in gross farm 

income (Oceania, Argentina, Brazil, other South America,15 and Russia) since price increases are 

relatively muted in these regions. Conversely, gross farm income rises in regions that adopt the 

Strategies due to the large resulting increase in agricultural prices. 

In the global scenario, gross farm income decreases in only two regions, China and Brazil, which 

are also two of the regions in which agricultural production falls. Gross farm income increases in all 

other regions with some large increases, particularly EFTA and developed Asia,16 where producers 

can take advantage of higher prices that result from the worldwide decline in production. Note that 

13Given that this result occurs, the model essentially is treating inputs into production as complements more than substitutes.

14Our measure of gross farm income represents aggregate returns on all factors employed in agriculture (primary and 

processing), such as rents to landowners, wages to laborers, and dividends to capital owners. Because the aggregate ownership of resources need not correspond to the typical ownership by individual farmers (e.g., some farmers may lease land or 

hire off-farm labor), this measure does not reflect the changes in total net incomes that producers may experience through 

implementation of the Strategies. This would be especially true for those farmers who do not own land, the resource whose 

return is expected to increase most substantially.

15As noted in appendix table A-3, other South America includes Chile, Costa Rica, Falkland Islands, French Guiana, 

Guyana, Panama, Paraguay, South Georgia and the South Sandwich Islands, Suriname, Uruguay, and Venezuela. 

16As noted in appendix table A-3, developed Asia includes Korea, Singapore, and Taiwan. 
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model results indicate that the price of labor and capital will increase; however, since land is the 

only fixed factor (capital and labor are mobile across sectors in the medium-run CGE setup), all 

extra revenues are assigned to land by the model. This is essentially a demand story—food faces 

extremely inelastic demand, prices go up when output falls, and land is assigned the extra revenue as 

the fixed factor. 

Table 1

Changes in gross farm income for the three scenarios (percent changes)

EU-only Middle Global

EU -16.4 7.5 14.6

Africa 3.7 11.3 16.6

Argentina 5.9 -4.7 16.9

Brazil 3.4 -2.3 -5.1

Canada 4.1 1.0 25.0

China 1.0 0.9 -4.6

Developed Asia 9.0 1.9 66.5

EFTA 25.8 131.5 111.9

Former USSR and rest of Europe 6.0 3.5 15.9

India 5.3 0.1 48.2

Japan 1.5 1.3 9.6

Mexico and Central America 6.9 0.1 18.8

Middle East and North Africa 2.6 3.7 4.4

Oceania 5.9 -0.1 27.7

Other Asia 6.7 0.1 35.8

Other South America 4.9 -2.1 15.8

Russia 7.9 -3.4 27.6

Turkey 3.7 16.9 18.1

Ukraine 8.8 14.0 6.1

United States 6.2 0.5 34.2

World 2.0 3.6 17.1

Note: EU-only is defined as only the European Union (EU) implementing the Strategies; in the middle scenario, trade partners 

who depend on food and agricultural exports to the EU also adopt the Strategies; and global is defined as all regions adopting the Strategies. EFTA refers to the European Free Trade Association. The gross farm income calculation is based on the 

returns to agriculture from changes in prices and quantities.

Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones 

(GTAP-AEZ) model.

Impacts on Food Expenditures

The final piece of economywide change is annual changes in food expenditures by consumers in 

each region, calculated as the change in purchases of agricultural products (both domestic and 

imported) due to the Strategies (table 2). In the EU-only scenario, the average annual food expenditure increases by $51 per capita worldwide. Food expenditures increase the most in the EU, as they 

are the only region adopting the Strategies. 

In the middle scenario, annual food expenditures per capita increase by $159 worldwide, led by large 

increases in regions that adopt the Strategies. Most regions undergo increases greater than $500 
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(Africa is the only exception at $413). Annual food expenditures per capita increase by $651 in the 

EU, but they decrease in several regions that do not adopt the Strategies.

Finally, global adoption of the Strategies leads to an increase in annual food expenditures of $450 

per capita. All regions in the model observe a triple-digit increase in food expenditures per capita, 

with the smallest increase of $214 in India and the highest increase of $919 in developed Asia. 

Table 2

Changes in annual food expenditures per capita for the three scenarios (dollars)

EU Only Middle Global

153.2 650.5 601.9

47.0 412.8 381.7

56.0 -14.6 501.3

76.0 -7.2 665.0

86.4 24.0 709.7

32.5 6.9 542.0

78.8 23.5 919.2

131.2 680.3 648.0

82.5 26.7 660.0

19.6 1.2 213.7

56.0 19.1 767.4

58.3 4.4 546.4

70.8 673.7 539.6

71.8 11.0 484.7

32.0 2.0 341.3

61.2 -3.0 582.5

69.4 13.2 527.4

75.9 777.5 704.6

109.6 934.1 760.5

58.6 16.2 512.2

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

European Free Trade Association 

Former USSR and rest of Europe

India

Japan

Mexico and Central America

Middle East and North Africa

Oceania

Other Asia

Other South America

Russia

Turkey

Ukraine

United States

World 50.6 159.3 450.1

Note: EU-only is defined as only the European Union (EU) implementing the Strategies; in the middle scenario, trade partners 

who depend on food and agricultural exports to the EU also adopt the Strategies; and global is defined as all regions adopting the Strategies. EFTA refers to the European Free Trade Association. 

Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones 

(GTAP-AEZ) model.

As a developed region, the EU has a small number of food-insecure people (i.e., people unable 

to access 2,100 calories a day). We estimate that the average share of income spent by European 

consumers on food will increase from 11.1 percent to 13.3 (middle scenario) or 12.9 percent (global 

scenario) after the Strategies have been adopted. Thus, it is likely that poorer households whose 

food consumption represents a larger share of total expenditure may see a reduction in their overall 

purchasing power.
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How Food Security Is Assessed: Method and Definitions 

The International Food Security Assessment (IFSA) model, as detailed in Baquedano et al. 

(2020), first generates food insecurity estimates in their current state as a baseline to measure 

the potential impact of the Strategies on food insecurity. 

Each country model comprises a price-independent demand system for each of the four food 

groups (Muellbauer, 1975). The demand system is calibrated on a 3-year-average of prices and 

incomes (2017–19), observed consumption levels, a measure of inequality, and income and 

price elasticities. Demand projections are based on projected prices and incomes; the model 

implicitly assumes that both the preferences represented by the demand system and the income 

distributions embedded in the calibration and projections are constant over time.

Impacts on Food Security

Given the impact of significant price increases for agricultural commodities and the decreases of 

GDP in numerous countries from the Strategies, we would expect impacts on food security in other 

regions. The final piece of our analysis examines the potential impacts of the Strategies on international food security. We use USDA, ERS’s IFSA model (see box, “How Food Security Is Assessed: 

Method and Definitions”) to project food demand for 76 low- and middle- income countries.17 The 

country and regional coverage in our analysis of food security impacts reflects the availability of 

demand estimates in the IFSA model database, which covers a smaller number of countries than 

the GTAP database. The IFSA model analyzes the gap between projected food demand, which is a 

function of per capita income and food prices, and a nutritional target of 2,100 calories per capita 

per day.18 Food insecurity occurs when estimated per capita food consumption for a consumer at a 

certain income level falls short of that nutritional target.

Illustrating the impact of the Strategies on international food security, figure 10 shows the increase 

in the number of food-insecure people from the status quo (our baseline) that would occur by 2030 

with adoption of the Strategies across the three scenarios. Under the EU-only scenario, food price 

increases resulting from adoption of the Strategies by the EU increases the number of food-insecure 

people by 22 million (or 0.5 percentage points in the prevalence of food insecurity). Most of the 

increase is in Africa and other Asia regions, which see an absolute increase in the number of foodinsecure people of 8 million and 10 million, respectively. Moreover, the prevalence of food insecurity increases by 0.4 percentage point and 1 percentage point in Africa and other Asia regions, 

respectively.

Under the middle scenario, the prevalence of food insecurity increases by 2.2 percentage points. The 

increase in food insecurity in Africa (94 million) and the Middle East and North Africa (10 million) 

is due to significant food price increases. In all other regions, the number of food-insecure people in 

2030 remains unchanged or marginally declines, reflecting lower price levels as countries in these 

regions shift away from trading with the EU. When the Strategies are adopted at the global level, the 

17Twelve in other Asia and India, 7 in Mexico and Central America, 4 in other South America, 8 in the former USSR and 

rest of Europe, 5 in the Middle East and North Africa, and 39 in Africa.

18The 2,100 kcal/per capita/per day threshold is an internationally agreed-upon level set by the United Nations as the 

recommended dietary energy intake level for a healthy, well-nourished individual (United Nations, 2004).
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number of food-insecure people increases to 185 million and the prevalence of food insecurity to 3.9 

percentage points. The increase in food security is spread across all regions, but Africa (80 million) 

and other Asia (72 million) continue to be the most impacted. This is because they could experience 

the largest increase in commodity prices and the largest GDP declines.

Figure 10

Net increase in food-insecure people by 2030 for the three scenarios

 

Note: EU-only is defined as only the European Union (EU) implementing the Strategies; in the middle scenario, trade partners 

who depend on food and agricultural exports to the EU also adopt the Strategies; and global is defined as all regions adopting the Strategies. 

Source: USDA, Economic Research Service calculations using the International Food Security Assessment Model. 
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Conclusions

Based on our analysis, the food and agricultural sustainability measures proposed by the EC in 

their 10-year plan to reduce the use of traditional agricultural inputs of land, fertilizers, antimicrobials, and pesticides in the EU would lead to a reduction in both EU agricultural production and 

their competitiveness in export markets. Furthermore, the tightening of the EU food supply would 

likely result in price increases that affect consumer budgets, reduce food security, and decrease 

GDPs worldwide. In the three scenarios modeled in this study, the estimated impacts of adopting the 

EC’s Farm to Fork and Biodiversity Strategies include: reduced agricultural output for the regions 

adopting the Strategies; increased agricultural commodities prices; and decreased GDP and welfare 

worldwide, with the largest impacts to prices and GDP in the regions adopting the Strategies. Our 

models find that the more widespread EC’s measures limiting usage of agricultural inputs, the more 

marked these impacts become, with consequences for international food insecurity. Likewise, we 

find that when trade is restricted as a result of the imposition of the EC’s proposed measures, the 

impacts are concentrated in regions with the world’s most food-insecure populations. We also find 

that EU-specific implications of the Strategies will depend on the degree to which others adopt this 

or similarly compliant strategies. For example, the EU’s share of welfare loss is 88 percent when the 

EU alone adopts the Strategies but is 18 percent when the Strategies are adopted globally. 

Prospective gains to environmental and human health from the Strategies is a subject of ongoing 

debate. Therefore, we do not include measurement of the associated costs and benefits from the 

Strategies in this analysis. Furthermore, we exclude some components of the Strategies that could be 

expected to add to adoption costs due to a lack of detailed information (e.g., animal welfare regulations and organic production). In addition, while the model assumes the most economically efficient 

means to implement the Strategies, real-world application is likely to result in considerable deviation from efficient implementation. We also note that the changes estimated here are based on large 

structural policy shocks; as such, further work could be done to investigate the aspects mentioned 

here. 

The framers of the Strategies include incentives for the adoption of new technologies and innovations. Presumably, adopting these technologies will help curb the productivity impacts from the 

Strategies’ input reductions. While details on these aims are not fully defined, they deserve more 

consideration. Further discourse and refinement of the Strategies can help identify the best path to 

achieving the overarching aims of this policy of a “fair, healthy, and environmentally friendly food 

system” (European Commission, 2020). However, the current cutting-edge technologies are likely 

insufficient to mitigate the production losses and their cascading impacts on the worldwide economy 

and food security from the magnitude of the Strategies’ agricultural inputs reduction targets. The 

effective treadmill of agricultural technology adoption, along with insufficient research and development (R&D) stocks and spending, poses distinct challenges to generate future productivity 

growth and feed an expanding population. This leads to concerns over the feasibility of the EC’s 

Strategies over the proposed timeline, as well as consideration of the steps needed to generate a more 

sustainable food and agriculture system. Ultimately, a robust and resilient food system may benefit 

from greater investment in innovative agricultural R&D, where sustainability is achieved through 

perpetual adaptation to new and distinct challenges through science, innovation, and adoption by 

farmers in their fields throughout the world. Future economic research can evaluate the merits of 

alternative approaches to generating sustainability outcomes. 
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Appendix 1

The latest Global Trade Analysis Project (GTAP) database is set to 2014. Given that the EU 

Strategies are in reference to changes from 2020, we updated the database using inputs to the model 

for GDP, population, labor, capital, and productivity (appendix table A-1).

Appendix Table A-1

Shocks to update the CGE model (percent changes)

Population Labor Capital GDP Productivity

Africa 15.3 19.1 32.6 15.9 13.7

Argentina 5.6 6.0 24.3 9.9 8.1

Brazil 4.5 6.7 22.8 -0.3 7.6

Canada 4.5 2.2 17.4 11.8 9.5

China 2.4 -0.2 56.5 45.7 33.0

Developed Asia 3.0 4.9 33.8 16.5 15.3

EFTA 5.1 4.0 16.2 10.3 6.4

European Union 1.0 -1.7 12.2 13.6 8.6

Former USSR and rest of Europe 4.4 4.4 31.8 19.6 20.2

India 7.3 10.5 35.6 53.0 20.6

Japan -1.3 -2.4 10.7 7.0 8.0

Mexico and Central America 6.3 10.9 25.0 14.4 7.5

Middle East and North Africa 11.5 10.2 27.2 17.0 2.4

Oceania 7.4 7.2 18.5 16.8 10.5

Other Asia 6.8 10.4 30.3 35.3 10.4

Other South America 6.6 9.1 25.3 -10.3 6.4

Russia -0.5 -4.8 22.8 3.9 27.6

Turkey 4.6 9.0 33.7 30.1 14.4

Ukraine -2.3 -6.7 17.7 4.3 41.7

United States 4.7 3.0 15.5 15.4 5.6

Note: CGE refers to the computable general equilibrium model. GDP is gross domestic product. EFTA refers to the European 

Free Trade Association. 

Source: Population and GDP are from USDA, Economic Research Service (International Macroeconomic Data Set) and 

labor, capital, and productivity are from Foure et al. (2016). 

The GTAP database has 65 sectors and 141 regions, which can be aggregated into broader categories. There are 20 agricultural commodities in the database which are kept mostly disaggregated in 

this simulation (appendix table A-2). However, commodities vital to this work (fertilizers, pesticides, 

and antimicrobials) are aggregated into larger sectors in the original GTAP database. To model these 

properly, we split these from their aggregated sector (known as “chemicals”). There are 141 regions 

in the model. We aggregated the EU countries together, and we kept major agricultural producers 

disaggregated. Finally, we also kept regions that are dependent on trade with the EU disaggregated. 

In total, our model has 20 regions, noted in appendix table A-3. 
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Appendix Table A-2

Sectoral aggregation

Name Description GTAP sector code

Paddy rice1 Paddy rice Paddy rice (pdr)

Wheat1 Wheat Wheat (wht) 

Coarse grains1 Cereal grains Cereal grains nec (gro)

Fruits and vegetables1 Fruits and vegetables* Vegetables, fruit, nuts (v_f)

Nuts1 Nuts* Vegetables, fruit, nuts (v_f)

Oilseeds1 Oilseeds Oil seeds (osd)

Sugar1 Sugar Sugar cane, sugar beet (c_b)

Other crops1 Other crops Plant-based fibers (pfb), Crops nec (ocr)

Cattle1 Cattle Bovine cattle, sheep and goats (ctl)

Hogs1 Hogs* Animal products nec (oap)

Other animals1 Other live animals* Animal products nec (oap), Wool, silk-worm cocoons (wol)

Milk1 Raw milk Raw milk (rmk)

Natural resources Natural resources Forestry (frs), Fishing (fsh)

Energy/mines Energy and mining activities

Coal (coa), Oil (oil), Gas (gas), Minerals nec (oxt), Petroleum, coal 

products (p_c), Mineral products nec (nmm), Ferrous metals (i_s), 

Electricity (ely), Gas manufacture, distribution (gdt)

Beef1 Beef Bovine meat products (cmt)

Pork1 Pork* Meat products nec (omt)

Other meat1 Poultry and other meat* Meat products nec (omt)

Vegetable oil1 Vegetable oil and fats Vegetable oils and fats (vol)

Milk products1 Milk products Dairy products (mil)

Processed rice1 Processed rice Processed rice (pcr)

Sugar1 Sugar Sugar (sgr)

Processed foods1 Processed foods, beverages and tobacco Food products nec (ofd), Beverages and tobacco products (b_t)

Labor manu Labor intensive manufacturing

Textiles (tex), Wearing apparel (wap), Leather products (lea), Wood 

products (lum), Paper products, publishing (ppp)

Other chemicals Other chemical products* Chemical products (chm)

Fertilizers Fertilizers* Chemical products (chm)

Pesticides Pesticides* Chemical products (chm)

Capital manu Capital intensive manufacturing

Basic pharmaceutical products (bph), Rubber and plastic products 

(rpp), Metals nec (nfm), Metal products (fmp), Computer, electronic and 

optic (ele), Electrical equipment (eeq), Machinery and equipment nec 

(ome), Motor vehicles and parts (mvh), Transport equipment nec (otn), 

Manufactures nec (omf)

Services Services

Water (wtr), Construction (cns), Trade (trd), Accommodation, Food and 

servic (afs), Transport nec (otp), Water transport (wtp), Air transport 

(atp), Warehousing and support activi (whs), Communication (cmn), 

Financial services nec (ofi), Insurance (ins), Real estate activities (rsa), 

Business services nec (obs), Recreational and other service (ros), 

Public Administration and defe (osg), Education (edu), Human health 

and social work a (hht), Dwellings (dwe)

Note: 1 indicates a sector we consider as agriculture. * indicates a sector that has been disaggregated. Nec means not elsewhere classified.

Source: USDA, Economic Research Service using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) 

model.
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Appendix Table A-3

Regional aggregation

Country/region Included Global Trade Analysis Project (GTAP) country/regions

EU Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, 

Germany, Greece, Guadeloupe, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, 

Martinique, Netherlands, Poland, Portugal, Reunion, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom

Africa* Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Congo DR-Kinshasa, Congo-Brazzaville, Cote d’Ivoire, Djibouti, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, 

Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Mozambique, Namibia, Niger, 

Nigeria, Rwanda, Sao Tome/Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, 

Sudan, Swaziland, Tanzania, Togo, Uganda, Zambia, Zimbabwe

Argentina Argentina

Brazil Brazil

Canada Canada

China China, Hong Kong

Developed Asia Singapore, South Korea, Taiwan

EFTA* Iceland, Liechtenstein, Norway, Switzerland

Former USSR and 

Rest of Europe

Albania, Andorra, Armenia, Azerbaijan, Belarus, Bosnia/Herzegovina, Faroe Islands, Georgia, 

Gibraltar, Kazakhstan, Kyrgyzstan, Macedonia, Moldova, Monaco, San Marino, Serbia and Montenegro, Tajikistan, Turkmenistan, Uzbekistan

India India

Japan Japan

Mexico and Central 

America

Anguilla, Antigua/Barbuda, Aruba, Bahamas, Barbados, Belize, Bermuda, Bolivia, Cayman 

Islands, Colombia, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Greenland, 

Grenada, Guatemala, Haiti, Honduras, Jamaica, Mexico, Montserrat, Netherlands Antilles, 

Nicaragua, Peru, Puerto Rico, Saint Kitts/Nevis, Saint Lucia, Saint Pierre/Miquelon, Saint Vincent/

Grenadines, Trinidad and Tobago, Turks/Caicos, Virgin Islands British, Virgin Islands U.S.

Middle East and North 

Africa*

Algeria, Bahrain, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Libya, Morocco, Occupied 

Palestine, Oman, Qatar, Saudi Arabia, Syria, Tunisia, United Arab Emirates, Yemen

Oceania American Samoa, Antarctica, Australia, Cook Islands, Fiji, French Polynesia, Guam, Kiribati, Marshall Islands, Micronesia Federated States, Nauru, New Caledonia, New Zealand, Niue, Norfolk 

Island, Northern Mariana Islands, Palau, Papua New Guinea, Saint Helena, Samoa, Solomon 

Islands, Tokelau, Tonga, Tuvalu, Vanuatu, Wallis and Futuna

Other Asia Afghanistan, Bangladesh, Bhutan, Brunei Darussalam, Burma, Cambodia, Indonesia, Laos, 

Macau, Malaysia, Maldives, Mongolia, Nepal, North Korea, Pakistan, Philippines, Sri Lanka, 

Thailand, Timor Leste, Vietnam

Other South America Chile, Costa Rica, Falkland Islands (Malvinas), French Guiana, Guyana, Panama, Paraguay, 

Suriname, Uruguay, Venezuela

Russia Russian Federation

Turkey* Turkey

Ukraine* Ukraine

United States United States of America

*Note: * indicates a region which we assume adopts the Strategies in the middle scenario. EFTA refers to the European Free

Trade Association.

Source: USDA, Economic Research Service using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) 

model.
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Appendix Table B-1Production changes from EU-only scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA 

Former USSR and 

rest of Europe

India

Japan

Mexico and Central 

America

Middle East and 

North Africa

Oceania

Other Asia

Other South 

America

Rice -13.2 -0.9 18.1 -1.2 0.8 -0.3 -0.6 -7.8 -0.5 1.2 -0.4 -2.3 -2.8 -0.9 -1.2 -0.4 

Wheat -48.5 0.8 7 -3 18.6 0.8 5.8 18.2 12.7 0.9 9.4 12 15.4 8.5 8.4 -1.8 

Coarse grains -20 -0.4 4.5 1.3 1.1 0.4 3.9 5.7 1.1 0.2 6 1.1 1.5 -1.9 0.5 3.1 

Fruits and vegetables -5.2 -0.2 0 -1.1 -6.1 -0.1 -0.5 -2.4 -0.8 0 0.2 -1.8 -0.5 -2 -0.9 0.3 

Nuts -9.2 0 -1.4 -2.7 -4.8 0.7 -0.2 -7.2 -2.4 3.3 0.7 -2.9 -1.3 -3.8 0 -0.3 

Oil seeds -60.7 5.4 -0.5 0 -6.2 2.8 2.3 2.4 6 2.4 13.5 2.9 4.2 37.3 2.8 3.4 

Sugar crops -20.5 0.9 0.3 -2.3 -0.7 -0.3 8.4 0.8 1.8 1.1 0.2 -0.1 -0.1 4.6 -0.4 3.8 

Other crops -44 13 3.2 14.1 10.9 4.1 15.6 3.4 5.7 4.7 5 13.3 2.3 -4.4 6.9 6 

Cattle -14.8 0.9 0.3 0.9 3.1 0.3 -1.2 -0.2 -0.1 2.1 2.6 -0.1 1.9 2 -0.5 0.4 

Hogs -8.4 0.4 0.4 2.8 2.2 -0.2 -0.3 -0.5 -0.3 -0.2 1.4 -0.4 -0.3 0.1 0.3 0.2 

Other animals -18.9 2.1 2.1 3 12 1.2 0.6 7.6 1 0.2 2.2 0.4 -0.1 0.8 1.2 2.4 

Milk -11.6 1 0.4 -0.5 0 1.4 0.4 -0.4 0.1 -0.3 0.2 0.3 0.8 1.1 0.9 0.5 

Forestry 5.6 -0.8 -2.5 -1.4 -1.5 -0.1 -0.5 -7.7 -3.3 -0.7 0.2 -1.3 -1.8 -3.5 -0.6 -0.5 

Energy, mining 1.1 -1.2 -1.3 -1.1 -0.5 0.1 0.1 0.6 -0.3 -0.4 0 -0.3 0.1 -1.2 0.2 -0.2 

Beef -13.5 0.5 0.3 0.7 1 3.4 -1.3 -2.5 0 4.2 1.6 -0.5 -0.1 0.9 -0.6 1.1 

Pork -6.9 1.9 -0.2 4 5.4 -0.2 1.6 -1.2 1.5 2.5 4.7 -0.2 8.1 3.4 0.3 0.5 

Other meat -12.5 1 -0.3 5.8 2 1.4 -0.2 1.8 -1 -0.2 0.5 -0.5 -0.3 1.7 3.4 0.1 

Vegetable oil -16.2 8.5 -3.7 -1.2 -5.5 -0.4 -1.4 0 -4.6 1.6 5.7 -0.3 2.6 39.8 3.8 7.2 

Milk products -10.6 3.2 0.5 -0.3 0 2 0.7 -0.3 0.3 0.2 0.5 0.3 1 1 1.2 0.7 

Processed rice -4.3 -3.3 1.7 -0.6 0.5 -0.3 -0.7 -19.3 -0.8 1.4 -0.5 -1.8 -5.4 -0.3 -1.3 -0.8 

Sugar -16.3 2.7 0.4 -2.6 4.9 -0.3 15.8 -1.2 -3 1.6 -0.3 0 -1.4 7.8 -0.3 1.9 

Processed food -4.5 0.1 0.2 -1.1 0.7 -0.2 -1.9 -0.2 -0.3 -1 -0.5 -0.3 -1.7 0.9 0 -0.2 Labor intensive manufactures 3 -2.4 -1.1 -1.2 -1.1 -0.7 1.2 0 -3.4 -1.5 1 -0.5 -1.6 -0.5 -2.9 0 

Other chemicals 1.3 -2.6 -2 -2.2 -1 -0.6 0.7 -0.6 -0.8 -1.1 0.4 -0.5 0.4 -1.9 -0.5 -0.5 

Fertilizers -5.9 -1.8 -0.9 -0.6 -0.9 -0.3 0.5 -1 -0.5 -0.3 0.3 -0.5 0.1 -1.2 0.1 -0.9 

Pesticides -16.1 -2.1 -1.1 -0.2 -1.2 -0.3 0.6 -14.9 -0.8 -2.1 -1.1 -0.5 -7.3 -2.1 -0.2 -0.9 

Capital intensive manufacturing 1.7 -3.4 -3.2 -1.1 -1.4 0.1 0 -0.2 -2.4 -1.1 -0.1 -0.8 -0.3 -1.9 -0.5 -1 

Services 0.2 -0.2 0.3 0.1 0.1 -0.1 -0.1 0 0 0 0 0.1 -0.2 0.1 0 0 

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
35

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-2Production changes from Farm to Fork regions adoption of Strategies (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA 

Former USSR and 

rest of Europe

India

Japan

Mexico and Central America

Middle East and 

North Africa

Oceania

Other Asia

Other South 

America

Rice 69.5 -2.5 -1.4 -0.6 0.6 0 -0.3 -9 0.9 -3.9 0.1 -0.1 -9.2 -3.6 -2.2 

Wheat -24.7 -85.1 3.1 0.2 -13.6 0.2 0.3 0.4 -8.2 -1.1 -2.3 -3.3 16 -6.1 0.1 -0Coarse grains -17.2 -12.5 -13.4 -5 1.7 1 7.7 -9.4 0.5 -0.8 3.7 0.3 -1.1 7.2 -0.1 -0Fruits and vegetables 7.4 -9.6 1.1 -1.2 -2 0.3 0.1 -43.1 5.2 0.1 0.5 -1 -18.7 -1.1 0.6 -3

Nuts 78 -39.8 -4.4 3.7 17.5 3.1 11.2 -61.2 -8.5 11.7 8.1 4.3 -15.3 15.9 12.8 -4Oil seeds -37.8 22.6 -4.7 -2.2 -0.4 -0.9 0.1 -3.6 -7.1 -0.2 2.6 -1.4 13.4 -11.1 -2.9 -6Sugar crops -18.2 -4.6 -0.2 -5.6 0.5 -0.2 -0.1 -31 0.6 -3 1.6 -1.1 -12.7 0.9 -0.6 0Other crops -20.6 -1.3 0.7 -0.6 8.6 1.9 2.8 12.9 1.3 1.9 3 1.4 -25.2 12.4 3.4 3Cattle -11.7 -5 -0.8 -1.6 1.7 0.1 -0.8 -24.1 0.3 -0.9 -0.6 0.3 -13 -2.4 -0.1 -0Hogs -11.4 -7.6 0.3 -4.9 2.6 0.4 0.6 -18.8 1.1 0 2.2 0.3 -11 2 -0.1 0

Other animals -12.3 -13.1 0.9 -4.7 7.6 1 1.4 -16.1 1.5 0 2.9 0 -11.9 10.6 0.3 1

Milk -12 -11.6 0.8 0 0.9 1.1 1.2 -26 1 0 0.7 0.6 -22.2 1.4 0.7 0

Forestry -4.4 -8.9 2.7 1 1.2 0.7 1 -20.1 3.3 0.3 0.9 0.9 -15.2 1.2 0.9 1

Energy, mining 0.4 0 0.4 0.3 -1 -0.7 -0.8 1.9 -0.7 -0.6 -1 -1 3.1 -1.2 -1 -0Beef -11.7 -3.2 -1.3 -1.7 0.3 -0.7 -1.1 -27.7 -0.3 -8.7 -1 -0.2 -3.6 -3.1 -0.5 -1Pork -13.3 -5.8 0.3 7.7 8.9 0.5 3.9 -18.4 5.7 7.2 7.7 2.1 2.1 10 1.1 2

Other meat -8.2 -4.1 0.5 -11.4 2 1.6 0.2 -20.7 1.6 0.1 -0.6 0 1.4 0.2 -1.9 -0

Vegetable oil -14.8 84.7 -9.8 -6.3 8.2 0 -2 -8.8 -2.6 -0.5 1.8 -1.2 17.8 -9.6 -7.2 -4

Milk products -7.2 -9.7 0.8 -0.1 0.9 1.5 1.3 -25.7 2 0 0.9 0.8 -26.8 1.7 1.3 0Processed rice 118.2 37.2 -3.2 -0.8 0.4 0 -0.6 119.8 -1.7 -5 0 -0.3 0.7 -5.6 -2.7 -3

Sugar -16.1 4.6 0.4 -8.1 -0.8 -0.6 -0.3 -42.4 -9.1 -4 1.4 -1.7 -12.4 0.7 -0.9 -0Processed food -11.1 -6.4 -0.6 -1 3.2 0.3 0 -6.2 2.9 -0.6 0.8 0.5 -21.9 1.3 0.4 0Labor intensive manufactures

0.2 -17.9 1.3 1.6 0.3 1 1.3 0.3 1.3 1.6 0.4 0.7 -20.5 0.7 1.6 1

Other chemicals -1.3 -11.6 2.3 1.2 0.3 -0.5 0.6 -6 0.9 0.6 0 0.1 2.7 0.4 0.4 0Fertilizers -10.2 -24.9 -4.3 -2.4 -1.5 -0.1 0.1 -9 -1.3 -0.2 0.3 -0.6 -2.9 0.2 -0.4 -1

Pesticides -27.5 -48 -3.4 -2.5 -2.4 -2.3 0.1 -27.6 -4.5 -11.1 -3.2 -1.4 -24.8 -1.3 -1 -1

Capital intensivemanufacturing

1.2 -10.9 2.4 1.1 -0.2 -0.5 -0.1 1.3 -0.5 0.2 -0.5 0.1 4.7 0.4 0.3 0

Services 0.1 0.4 0 0.1 0.1 0.1 0 0.1 -0.1 0.1 0.1 0.1 -1.3 0.1 0.1 0

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
36

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-3Production changes from global scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA 

Former USSR and 

rest of Europe

India

Japan

Mexico and Central America

Middle East and 

North Africa

Oceania

Other Asia

Other South 

America

Rice 48.4 -8.5 241.6 -15.1 7.7 -15.8 -16.3 7.1 -11.3 10 -16.9 -36 -26.7 15.5 -20.7 -15.2 

Wheat -33.5 -93.1 55.3 -55.2 -25 -32.9 -21.8 -11.1 16.8 -20.7 -33.8 27.9 9.4 -12 43 -77.1 

Coarse grains -13.7 -10.9 0.1 -14.4 -22.8 -12.4 -4.1 -7.6 -29 -10.3 0.8 -0.6 -6.9 -36.3 -4.8 -4 Fruits and vegetables 27 -6.4 -13.9 -19.4 -34.8 -16.3 -23.8 -40 -15.5 -3.7 -15.1 -33.8 -12.9 -1.6 -9.5 -4.6 

Nuts 72.1 18.1 -27.4 -36.9 -30.3 -24.6 -55.7 -59.9 -27.8 27.3 -51.9 -40.1 -8.3 -19.7 -22.7 -17.6 

Oil seeds -43.4 51.7 -51.6 -44.6 -38.9 -34.2 -3.6 -10.4 -47.6 -0.6 24.4 9.1 24.5 184 1.9 -60 

Sugar crops -15.1 -6.8 -6.7 -28.8 -4.4 -31.7 128.2 -29.7 -42.2 -3.4 -21.2 -9.8 -13.5 45.2 -20.1 6.4 Other crops -26.7 -17.5 0.3 -20.1 88.3 -26.8 61.8 10 5 10.2 -33.8 6.9 -29.1 -63.7 -2.1 -22.1 Cattle -10.8 -5.6 -16 -14.3 -3.9 -5.1 -17.8 -22 -16.2 6.2 3.7 -13.5 -12.3 -3.5 -16.6 -18.4 Hogs -8.3 -8.5 -11.8 -16.8 1.5 -11.8 -13.8 -18.6 -12.2 -4.2 -6.9 -11.2 -9.8 -12.4 -6.8 -11 

Other animals -6 -11.1 -20.8 -18.4 27.4 -11.9 -12.1 -19.6 -13.9 -3.3 -3.1 -11.9 -10.3 -47.3 -6.5 -9.9 

Milk -7 -11.3 -12.5 -23.7 -16.9 -12.4 -16.1 -23.8 -16.9 -7.3 -10.6 -14.2 -17.9 -30.8 -14.2 -14.8 

Forestry 1.3 -8.1 -3.7 1 -5.3 -6 -9.5 -6.8 -3.8 -9.4 0 -3.6 -11.4 -16.2 -5.7 -1.8 

Energy, mining -3.4 -2.9 -7.2 1.4 -4.4 6 -0.4 -0.7 1.2 -2.5 -0.7 -0.9 1.3 -8.6 3.9 1.4 

Beef -12.4 -3.8 -18.1 -17.3 -2.8 7.2 -17.9 -26.1 -17 22 3.3 -12.1 -5.5 -13.7 -15.2 -18.1 

Pork -8.9 -7.1 -5.7 -18.5 9.9 -12 -10.5 -18.1 -19.6 -16.5 -7.8 -14.7 6.8 -8.7 -5.5 -14.5 

Other meat -6.4 -6.9 -9.8 -17.9 11.8 -14.8 -10.7 -21 -19.3 -6.2 -3.1 -11.5 -4.1 -6.7 -3.1 -12.6 

Vegetable oil 0.5 93.2 -76.6 -34.9 -46.7 -32.6 -31.8 13.2 -73.2 -1.5 57.3 -13.2 33.9 406.6 6 32.4 

Milk products 0.7 -8.9 -12.9 -20.2 -15.6 -11 -15.9 -23.3 -19.1 -3.6 -6.9 -14.5 -21.5 -40.9 -19.1 -16.9 

Processed rice 65.6 -13 25.9 -6.2 7.5 -15.6 -16.2 32.6 33.7 13.4 -17.3 -22.7 -44.6 35.7 -22 -16.5 

Sugar -11.2 -0.7 -4.6 -35.9 36.5 -50.2 257.8 -39.6 -72.3 -1.1 -18 -10.8 -16.8 101.4 -23 1.9 Processed food -5.9 -5.3 -3.2 -20.5 -1.1 -14.4 -27 2.5 -13.6 -20.2 -10 -7.7 -18.8 6.3 -7.1 -10.7 

Labor intensive manufactures 14.7 -6.5 -3.7 7 3.9 -13.8 20.2 12.2 -8.7 -10 16 5.2 -3.9 5.5 -20.3 12.7 Other chemicals 1.2 -8.4 -4.9 -13.2 -2.1 -8.6 10.9 -0.8 7.4 -4.3 8.7 1.7 12.5 -11.2 2 0.7 

Fertilizers -11.3 -22.8 -22.4 -22.7 -17.6 -21.8 -1.4 -12.3 -8.6 -19.1 -5 -11.7 -1.5 -23.7 -14 -14.1 

Pesticides -35.9 -44.1 -50.9 -50.5 -45.1 -48.1 -17.6 -39.3 -46.9 -39.4 -23.9 -35.6 -28.6 -45.5 -30.7 -40.3 Capital intensive manufacturing

-3.9 -13 -17.2 -2.3 -7.6 8.9 -0.5 -3 -6.2 -6.1 -0.9 0 3.5 -9.8 2 -2.6 

Services 0.3 0.2 3.3 1.9 1.3 -1.2 -0.3 0.5 0.9 0.2 0.1 0.6 -0.9 1.3 0.3 0.2 Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
37

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-4Market price changes from EU-only scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA 

Former USSR and 

rest of Europe

India

Japan

Mexico and Central America

Middle East and 

North Africa

Oceania

Other Asia

Other South 

America

Rice 29.5 11.6 11.1 27.4 14.5 10.4 14.3 19 23.3 11 11.9 28.5 14.6 30.7 14.7 17.8 

Wheat 71 46.2 17.2 23.5 27.2 19.6 14.9 34 21.9 17.3 14.9 22 16.3 24 11.8 36 

Coarse grains 96.3 15.6 20.5 22.2 41 13.6 13.1 36.2 47.4 12.5 14.8 21.1 15.8 34.7 13.3 23.3 

Fruits and vegetables 15.7 9.6 17.8 25.7 19.2 8.9 15.6 24.5 16.4 6.4 12.4 21.4 11.5 15.6 11.9 15.2 

Nuts 14.9 9.8 17.2 25.4 19.5 9 14.6 22.4 15.7 8.4 12.3 21 11.5 15.2 12 14.9 

Oil seeds 93.3 10.7 18.9 25.4 27.1 10.2 13.1 28.4 30.5 12.2 10.3 18.7 10.9 17.7 14.9 29.6 

Sugar crops 107.8 23.4 21.2 25.9 23.6 12.7 14.1 28.8 38.7 11.7 31.1 18.8 16.4 17.2 13.1 10.2 

Other crops 73.8 22.3 15.6 21.6 15.3 11.3 13.7 32.9 17 11.5 12.5 20.6 19.8 24.6 15.1 21.4 

Cattle 53.1 4.6 7.4 5.6 6.8 2.2 8.1 13.5 8.8 6.9 4.2 7.2 6.6 6.8 6.7 5.7 

Hogs 19.8 4.4 4.5 4 1.8 1.8 3.2 4.9 4.4 2.9 1.8 3.2 4.3 7.7 2.8 2.6 

Other animals 19.6 4.4 4.5 4.1 1.8 1.8 3.2 5 4.5 2.8 1.8 3.2 4.3 7.2 2.7 2.6 

Milk 40.9 10.6 9.7 11.1 7.7 3.6 11.6 15 8.2 3.3 5.5 8.6 7.2 13 7.9 8.2 

Forestry -8.9 5.1 6.9 6.2 4.3 1.2 2.2 2.9 3.2 4.9 1.6 5.5 2.8 6.5 2.8 4.1 Energy, mining -0.4 0.1 0.8 0.4 0.2 -0.2 0 -0.2 0 0.2 0 0.1 -0.1 0.2 -0.1 0 

Beef 17.1 2.3 5.8 3.6 3.2 1.1 4.5 7.1 4.9 2.4 2.1 4 3.6 4.3 3.4 3.4 Pork 9.5 2.7 3.7 2.2 1.6 1.4 2.2 3.7 3.1 2.7 1.5 2.3 2.6 2.8 1.6 2.3 

Other meat 9.5 2.7 3.7 2.1 1.6 1.4 2.2 3.8 3.1 2.7 1.5 2.3 2.2 2.8 1.6 2.3 Vegetable oil 15.2 4.2 13.4 11.8 13.6 9.4 9.2 9.6 15.2 6.6 3.6 9.9 6.9 3.7 7.4 6.7 

Milk products 11.6 3.3 4.7 4.9 3.5 2.1 4.2 4.3 4 2.1 1.5 3.4 5.2 6.2 4.3 3.6 Processed rice 6.4 8.9 4.5 8.8 3.5 8 12.7 13 7.1 4.1 10.7 12.5 12.8 6.3 11.2 9.5 Sugar 20.1 7.4 6.6 12.8 2.5 12.6 2.6 16.5 17.6 5.4 4.7 7 10.3 2.7 7.1 5.3 

Processed food 6.6 4.1 4 8.8 2.6 3.1 6.1 3.9 4.8 6.9 2.3 3.2 6.3 2.3 3.3 3.9 Labor intensive manufactures -0.5 1.8 1.9 1.3 1 0.8 0.3 0 1.1 1.4 0.1 0.8 0.9 1 1.3 0.6 Other chemicals -0.2 0.8 1 1.4 0.4 0.5 0 0.1 0.2 0.4 0 0.4 0 0.8 0.2 0.4 Fertilizers -0.2 0.8 1 1.4 0.4 0.5 0 0.1 0.2 0.4 0 0.4 0 0.8 0.2 0.4 

Pesticides -0.2 0.8 1 1.4 0.4 0.5 0 0.1 0.2 0.4 0 0.4 0 0.8 0.2 0.4 

Capital intensive manufacturing -0.5 0.8 1.2 0.7 0.3 -0.1 0 -0.1 0.4 0.4 0 0.2 0 0.5 0.1 0.2 

Services -0.5 0.9 1.4 0.7 0.4 -0.1 0 -0.1 0.2 0.5 0 0.3 0.1 0.6 0.1 0.3 

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
38

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-5Market price changes from middle scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA 

Former USSR and 

rest of Europe

India

Japan

Mexico and Central America

Middle East and 

North Africa

Oceania

Other Asia

Other South 

America

Rice 175.7 130 -2.6 -1.7 2.4 0.7 1.3 149.7 8.6 -1.1 0.7 0 206.2 -0.7 -1 -2.2 Wheat 321.1 562.2 -3.1 -1.8 -0.6 0.6 1.6 281.5 0.3 -0.3 0.4 -1.4 194 -1.4 0.4 -1.3 

Coarse grains 401.5 177.2 -5.1 -2.3 0.3 0.8 3.4 325.8 1.6 -0.2 1.3 0 214 0.3 -0.2 -1.7 Fruits and vegetables 95.8 98.1 -3 -1.8 0.1 0.8 1.2 247 3.1 0.1 0.7 -0.2 150.1 -0.4 0.1 -2.3 Nuts 104.1 90.2 -3.9 -1.3 1.6 1.2 3.8 235.4 0.7 3.4 1.2 0.9 151.2 1.3 4.3 -2.6 

Oil seeds 395.7 104.1 -3.8 -2 0.2 0.5 0.8 297.3 0.8 0 1 -0.3 136.3 -1.9 -1.4 -2.7 

Sugar crops 440.9 261 -3.7 -2.6 0.2 0.6 2.4 291.9 1.9 -0.8 0.7 -0.5 181.5 -0.2 -0.3 -1.3 

Other crops 302.9 242.2 -3.5 -1.8 1.9 1 1.9 202.7 2.2 0.4 0.9 0.3 272.7 0.9 1.3 -0.8 

Cattle 77.3 51.7 -3.1 -1.6 1 1 1.4 94 2.6 -0.3 1 0.5 63.5 -0.7 0 -1.2 

Hogs 43.1 53.3 -1.1 -0.7 0.6 0.6 1.7 44.1 1.5 0.2 0.9 0.4 49.9 0.3 0.5 0 

Other animals 43.1 53.2 -1.1 -0.7 0.7 0.6 1.8 44.1 1.5 0.2 0.9 0.4 49.7 0.8 0.5 0 

Milk 63.7 162 -2.3 -1 0.9 1.6 3.2 126.2 3.4 0.2 1.1 0.7 70.6 0.8 1.3 -0.4 

Forestry 15.4 27.1 1.3 -0.6 2.5 1.2 2.2 27.8 5.5 0.7 2.3 1.1 27.7 2.6 0.9 0.8 

Energy, mining -0.5 -0.6 -0.4 -0.4 0 0.2 -0.2 -0.8 -0.2 -0.1 0 0 -1 -0.1 -0.1 -0.1 

Beef 28.8 18.5 -2.3 -1.1 0.7 0.7 1.3 43.9 1.9 0.3 0.8 0.5 28.1 -0.3 0.1 -0.6 

Pork 22.9 26.2 -1.2 -0.5 0.5 0.6 1.2 27.1 1.7 0.3 0.8 0.4 25.6 0.4 0.4 0 

Other meat 23 26.2 -1.2 -0.5 0.5 0.6 1.2 27.1 1.7 0.3 0.8 0.4 24 0.3 0.3 0 Vegetable oil 104.6 36.8 -2.8 -1 0.5 0.5 1.4 89.4 2.6 0.3 0.9 0.1 76.7 0.5 -0.4 -0.4 

Milk products 21.2 32.1 -1.3 -0.7 0.6 1 1.6 34.3 1.8 0.4 0.7 0.4 51 0.5 0.8 -0.1 Processed rice 40.1 98.2 -1.1 -0.8 0.8 0.6 1.3 80.8 2.8 -0.3 0.7 0.3 161.8 0.1 -0.7 -0.9 Sugar 86.7 75.9 -1.4 -1.4 0.6 0.6 0.7 146.2 3.9 -0.3 0.7 0 110.2 0.2 -0.1 -0.5 Processed food 33.5 36.7 -1 -0.9 0.8 0.6 2.7 26.3 1.7 0.1 0.8 0.3 69.8 0.4 0.4 0 Labor intensive manufactures 0.9 10.5 -0.6 -0.4 0.6 0.5 0.4 0.7 0.7 0.2 0.4 0.3 8.8 0.3 0.4 0.1 Other chemicals 0.5 3.1 -0.5 -0.4 0.2 0.4 0.1 1.3 0 0 0.2 0.2 -0.7 0.2 0.1 0.1 Fertilizers 0.5 3.1 -0.5 -0.4 0.2 0.4 0.1 1.3 0 0 0.2 0.2 -0.7 0.2 0.1 0.1 Pesticides 0.5 3.1 -0.5 -0.4 0.2 0.4 0.1 1.3 0 0 0.2 0.2 -0.7 0.2 0.1 0.1 

Capital intensive manufacturing

-0.2 2.6 -0.5 -0.4 0.3 0.3 0.2 -0.2 0.1 0.1 0.3 0.2 -1.2 0.1 0.1 0 

Services -0.2 1.5 -0.6 -0.5 0.3 0.4 0.3 -0.5 0.1 0.1 0.4 0.2 -0.2 0.2 0.1 0.1 

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
39

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-6Market price changes from global scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA 

Former USSR and 

rest of Europe

India

Japan

Mexico and Central 

America

Middle East and 

North Africa

Oceania

Other Asia

Other South America

Rice 146.3 120.8 116.1 311.5 131.6 269.2 263.9 165.2 165.5 142.2 245.8 346.5 169.5 337.7 212.5 206Wheat 260.5 495.6 185.9 262.9 248.7 513.3 210.6 239.4 202.9 241.7 261.3 191.6 161.4 242.7 126.3 45Coarse grains 327 163.4 230.9 246 384.1 359.2 200.7 284.2 530.6 170.3 277 236 177.8 378.6 165.9 262Fruits and vegetables 84.7 94.2 194.9 288.8 191.1 225.6 286.2 218.2 166.1 76.4 255.7 250.9 126.4 164 161.1 17

Nuts 90.2 99.7 190.7 286 192.8 222.1 260.8 206.3 160.7 94.9 250.8 248.8 127.5 160.4 152.4 167Oil seeds 319.8 104.3 219.2 279.2 256.4 240.3 187.6 257.3 313.4 158 173.9 195.2 116 150.3 187.1 355

Sugar crops 357.3 240.6 244.8 285.4 229.8 331.3 141.8 257.6 421.9 153 652.8 201.1 153.4 161.6 177.6 108Other crops 246.8 218.7 165 220.4 148.1 267.6 162.3 175.6 159.9 139 246.2 188.6 225.9 258.7 174.2 233Cattle 90.2 53.6 87.1 76.7 80.6 34.7 86 94.2 86.7 74.5 61.6 95.2 58.5 64.8 75.2 83Hogs 43 52.7 66.5 67.6 26.7 44.8 40.4 47.3 54.7 36 28.1 47.4 44.9 82.9 41.5 42

Other animals 43 52.4 63.8 67.4 26.8 44.8 39.2 47.3 54.5 35.1 28.1 47.4 44.9 75.7 41.2 42

Milk 76.1 168.2 130.1 206.6 97.1 60.3 105.8 136.4 98.7 51.1 92.4 138.3 71.6 130.9 117.8 136

Forestry 23.6 35.5 26 11.4 35.5 8.6 21.3 29.9 19.9 52.2 15 23.7 24.9 40.4 20.5 23

Energy, mining 0.9 -0.3 4.2 -1.1 1.2 -4.8 -0.5 0.2 -0.4 0.5 -0.2 0.4 -0.8 0.7 -2.2 -0

Beef 33.3 20.3 66.5 45.7 37.4 16 49.4 44.9 42.6 25.1 28.8 48.8 25.8 40 37.5 47Pork 23.7 26.6 40 29.3 18.6 30 26.9 28.8 29.6 33.3 22.9 30.5 22.9 26.7 22.1 33

Other meat 23.7 26.6 40 29.3 18.6 30 26.9 28.7 29.6 33.3 22.9 30.5 21.7 26.8 22.1 33

Vegetable oil 78.7 37.2 152.5 124.7 131.4 189 113.1 70.2 138.6 83.2 39.5 104.2 64.8 33.2 89.3 76

Milk products 25.4 34.9 56.6 82.7 42.1 34.8 39.1 37.3 40.7 25.5 22.3 49.7 46.3 61.1 57.8 53

Processed rice 35.1 90.3 42.7 94.6 32.1 184.9 232.6 70 49.6 50.6 219.8 143.6 127.9 66.4 161.4 110

Sugar 71.4 71.1 69.2 136.7 24.2 326.8 31.8 128 166.9 69.5 76.5 73.5 92.3 23.4 95.5 55

Processed food 28.9 33.1 36.9 91.9 24.4 66.1 69 23.9 42.3 90.4 29.1 32.4 54.4 20.3 37.4 

Labor intensive manufactures 3.4 12.3 12.7 3.7 7.9 14.7 4 2.4 9.7 13.7 1.9 5.8 8.4 6.6 14.3 3

Other chemicals 2.2 4.4 5.6 10.1 3.4 8.2 0.9 2.7 1 3.3 0.8 2.6 -0.1 6.3 1.9 3

Fertilizers 2.2 4.4 5.6 10.1 3.4 8.2 0.9 2.7 1 3.3 0.8 2.6 -0.1 6.3 1.9 3

Pesticides 2.2 4.4 5.6 10.1 3.4 8.2 0.9 2.7 1 3.3 0.8 2.6 -0.1 6.3 1.9 3

Capital intensive manufacturing 

1.5 3.6 6.1 1.1 2.3 -2.6 0.2 1.2 1.9 2.7 0.4 0.9 -0.4 3.1 -0.3 0

Services 1.8 3 7.8 -0.4 3.1 -4.1 1.3 0.9 0.2 2.6 0.6 1.3 0.4 3.9 -0.5 0

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
40

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-7Import volume changes from EU-only scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA

Former USSR and 

rest of Europe

India

Japan

Mexico and Central 

America

Middle East and 

North Africa

Oceania

Other Asia

Other South America

Rice 31.5 3.3 -1.3 161.1 9.3 -73.9 -29.3 6.7 37 -5.8 -43.9 11.9 1.9 174.8 9.1 3.5 

Wheat 18.4 -1.7 -13.7 1.7 10.4 -95.2 -9.1 -21.3 -0.7 -16.3 -1 -1.3 -18.3 4.2 -6.3 0.8 

Coarse grains 3.8 -1.5 -1.7 -0.5 2.4 -9 -0.7 -16.6 -7.6 -5 -0.6 -1.7 -4.9 -1.1 -1.7 0.3 

Fruits and vegetables -0.5 0.2 1 4.3 1 -5.7 -0.8 2.6 0.3 -3.9 -2.2 3.3 -1.4 2.7 1.2 0.4 

Nuts -1.7 0.9 1.5 3 1 -4.5 -0.6 0.3 -0.1 -1.3 -0.3 2 -0.4 1.9 0.1 0.5 Oil seeds 6.6 -0.5 -3.8 -0.9 2.2 -3 -3.7 -0.2 -10.8 -0.5 0 -1.2 -3.5 15 -3.1 5.9 

Sugar crops 1 9.2 7.1 8.1 5.3 -54.4 5.9 -15.8 -75.4 -16.6 -45.9 -1.7 -46.4 -16.1 -6.1 -38.5 Other crops 31.4 0.8 -6.4 -3.4 -1.2 -15.5 -1.3 -9.4 -16.5 -8.4 -6.3 2 -7.3 0.2 -2.9 -1.8 

Cattle 8.3 2.3 -3.5 -3.6 -11.6 -4.1 -4 -44.7 -19.4 -16.3 -9.6 -10.2 -10 -4.8 2.6 3.6 

Hogs -6.1 2.1 3.2 2.8 5.2 -0.1 -3.5 -6.7 -15.6 1.8 -2.6 1.3 2 4.8 0.6 0.6 

Other animals -3.5 -3.3 -0.2 -0.6 -3.5 -5.1 -0.3 -6.9 -9.5 -1.9 -1.3 -0.4 -4.3 4.7 -2.2 -1.7 

Milk 18.8 -74.6 -60.4 -24.1 -39.1 -11.2 -11.2 -49.9 -39.6 -46.3 -33.5 -72 -33.2 -25.7 -64.8 -70.8 

Forestry -4.7 4.9 8.9 3.3 -0.2 -3.2 -0.5 10.5 2.1 1.6 -2 5.4 2.6 5.1 -0.6 2.5 

Energy, mining 0.3 -0.5 1.3 -0.2 -0.3 -0.5 0.1 0.2 -0.2 0.1 0 -0.2 -0.1 0 -0.2 -0.4 Beef -1.9 -5.7 -22.9 -3 -1.7 -5.9 -0.5 -10.5 -13.9 -11.2 -3.1 -0.8 -0.4 -2.1 0.1 -1.5 

Pork -4.1 -10.7 4.1 -12.5 -2.1 -16.1 -11.6 -18.2 -7.7 -5.8 -4.8 0.9 -2 -7.4 -14.2 -3.8 

Other meat -3.6 -5.5 -1.9 -14.4 -0.8 -8.9 -1.5 -9.4 -1.3 -7.6 -0.8 0.8 -1.8 -3.6 -6 -1 

Vegetable oil -2 -1.9 8.5 -1 0.6 -4.2 -1.2 -3.1 -0.2 -4 -4.6 -1.1 -2.6 -2.4 -0.8 -1.3 

Milk products -6.1 -14.3 -9 -6.6 -12.5 -13.4 -7.3 -21.8 -8.5 -19.9 -11.6 -6.3 -9.6 -8.4 -8.3 -3.8 

Processed rice -1.6 1.5 -2.8 2.9 -0.8 -5.9 4.8 0.7 -0.4 -3.7 12.3 10.9 4.2 0.9 6 4.3 

Sugar -3.1 -0.9 -3.2 13.6 -4 2.2 -1.7 -9.7 -0.2 -6.6 -1.1 3.2 -2 -4.3 -0.4 -2.6 

Processed food -2.5 -1.1 -1.2 3.8 -0.9 -2.3 0 -3.7 -1.3 2.3 -2.3 -0.6 -0.5 -1.8 -0.7 -0.6 

Labor intensive manufactures

-0.3 2 3.1 1.4 0.4 0.5 -0.4 0.5 0 1.8 -1.1 0.2 0.2 0.8 -0.4 -0.2 

Other chemicals 0.4 0 0.8 1.8 -0.4 0.9 0.1 -0.2 -0.5 -0.4 -0.2 -0.2 -0.2 0.7 -0.4 -0.1 Fertilizers -8.6 0.7 1.4 0.5 0.7 1.1 -0.1 -0.8 0.2 0.1 -0.2 -0.2 0 0 -0.3 0.3 

Pesticides -33.8 0.2 0.8 0.3 0.5 0.7 0.1 -0.4 0.1 -0.1 0 -0.1 0 -0.2 -0.1 0.2 

Capital intensive manufacturing

0.2 1 1.9 1.5 0 -0.1 0 0.1 0.3 0.9 0.2 0.1 0 1 -0.1 0.2 

Services -0.5 1.7 3.2 1.4 1 -0.2 0.1 0.2 0.5 1 0.1 0.7 0 1.4 0.3 0.6 

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
41

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-8Import volume changes from middle scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA

Former USSR and 

rest of Europe

India

Japan

Mexico and Central 

America

Middle East and 

North Africa

Oceania

Other Asia

Other South America

Russia

Rice 158.5 24 -49.2 -4.6 -43.1 -31.1 -60 16.6 18.9 -65.3 -62.8 0.5 105.7 -45.7 -7.6 -3.3 -67.Wheat 18.5 45.1 -45.4 -1.7 -23.1 3.7 -0.6 -4.4 11.2 -12 0.8 -1.6 -53.1 0.1 0.3 -0.2 -40.

Coarse grains -4.6 -9.7 -17.9 -4.3 0.3 -8.9 6.5 -12.1 -22.4 -16.3 0.6 -0.2 -39.8 -13.2 0.5 0.2 -46.

Fruits and vegetables -0.4 3.9 -8.3 -9.3 -0.2 -0.5 -2.1 45.5 -24.3 -11 -1.7 -3.4 7.7 -5.5 -3.8 -6.5 -18.

Nuts 3.6 4 -4.9 -12.2 -3.1 -16.4 -1.6 1.1 -19.2 -30.1 -1.2 -2.3 -15.6 -1.7 -26.4 -4.8 -4.

Oil seeds 10 12.3 -12 -7.3 3.3 0.7 2.9 26 -27 -57.8 0.9 -1.2 -16.3 -11.4 -10.8 -3.4 -10.

Sugar crops -2.7 -6.8 -21.1 -23.6 -2.7 -51.8 -1.6 -29.9 -72.4 -30.6 -18.9 -17 -81.7 -27.5 -17.6 -60.8 -80.

Other crops 8.2 -7.1 -16.5 -45.2 -2.3 -6.9 -1.1 -28.7 -35.2 -29.5 -3 -6.1 -14 -3.2 -12.8 -3.3 1.

Cattle 10.5 28.5 -13.2 -11 -12 -1.9 -6.9 -8.7 -28 -37.2 -10.1 -9.4 -1.5 -14 0.3 -1.6 -1

Hogs -7.9 -13.5 -0.9 -4 4.3 -0.1 -6 -17.2 -31.4 -0.4 -3.1 0.4 -20 8.1 -0.8 0.2 -18.

Other animals -9.7 -3.5 -5.2 -7.9 -4.4 -6.2 -0.3 -15.5 -21 -7.6 -1.3 -1.4 -9.2 -2 -3.3 -1.2 -1Milk -25.5 275.8 -45.2 -20.3 -34.1 -11.1 -13.5 83.7 -26.2 -39.9 -28.1 -36.8 -23.9 -24 -36.8 -40.2 -23.

Forestry -5.8 18.4 -6 -3.1 1.3 -5.3 -1.8 8.2 -14.8 -2.7 -1.5 -6.7 4.6 -1.3 -5.5 -11.9 -14.

Energy, mining 0 -1.6 -0.5 0 -0.5 1.3 0 -0.6 -0.4 0.7 0.3 -0.4 -0.7 -0.1 0.2 -0.5 -1.

Beef -12.9 -25.5 -35.7 -5.9 1.9 1.4 2.5 7.9 -19 -20.6 1.1 -0.9 -32.1 -3.1 -0.7 1 -0.Pork -9.9 -5.8 -6.1 -27.5 -2.8 -20.7 -18.9 -1.8 -20.2 -16.1 -6.3 -1.3 -13.8 -17.6 -24.1 -6.3 -2.

Other meat -10.3 -14.2 -16.1 -25.8 -0.5 -9.7 -0.4 -6 -11.3 -19.8 1.8 -1.3 -32 -8.7 -9.6 0.9 -2.Vegetable oil -14.6 -19.2 -13.7 -21.9 -2 -2.7 0.6 -10.6 -8.1 -9.1 -1.9 -0.5 -31.2 -1.9 -0.8 -0.9 -19.Milk products -8.4 6.6 -20.9 -5.3 -18.6 -8.6 -6.4 12.7 -21 -34.9 -9.1 -5.1 22.9 -12.2 -6.5 -0.9 -1

Processed rice -4.4 -34.2 -5.4 -0.9 1.5 2.9 2 7.5 -0.4 -12.3 1.5 0.6 -9.8 0.9 -1 -1 3.Sugar -14.6 -20.4 -18.4 -15.1 2.2 2 -0.2 -9.2 0.3 -0.1 -3.4 -1.9 -16.4 -9.3 -1.1 -0.1 1.

Processed food -12.7 -9.1 -7.2 -12.1 -4.6 -9.1 -4.1 -20.5 -13.2 -10.7 -6 -4.8 2.3 -8.4 -4.2 -5.1 -16.Labor intensive manufactures -0.8 14.4 -2.2 -2.3 0 0.1 0.1 -1 -0.6 -1.6 -0.2 -0.2 7.3 -0.6 0.5 -0.5 -0.Other chemicals -0.6 -1.5 -0.7 -1 -0.2 0.6 0 -1.7 -0.3 0.2 -0.3 -0.2 -3.1 0 0.1 0 -1.Fertilizers -9.7 -17 -6.2 -0.9 -2.4 1.2 0.2 -9.7 1 -0.4 0.5 -0.5 -19.3 0.7 -0.7 -2.6 -2.

Pesticides -34.5 -48.6 -6.4 -1.8 -3.5 0.8 0.2 -31.8 1.1 -0.6 0.4 -0.5 -48.2 0.3 -0.7 -3 -1.

Capital intensive manufacturing

0 0.8 -0.5 -0.6 0.2 0.5 0.2 0.1 0.2 0.2 0.5 0.3 -2.1 0.2 0.2 0.3 -0.

Services -0.5 3 -1.5 -0.9 0.4 0.6 0.4 -1.1 -0.1 0.2 0.7 0.3 -2 0.1 0.1 0.1 -0.

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
42

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-9Import volume changes from global scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA

Former USSR and 

rest of Europe

India

Japan

Mexico and Central 

America

Middle East and 

North Africa

Oceania

Other Asia

Other South 

America

Rice 67.4 6.8 -22.8 2,010.5 4 689.2 838.3 32.2 60.9 43.3 578.9 190.9 53.7 2,245.3 77.1 39.5 

Wheat 22.1 27.2 41.1 22.4 144.2 854.7 -24.1 10.9 19.4 94.7 -7.7 -18.3 -42.2 26.1 -49.9 27.3 

Coarse grains -1.3 -15 -26.6 -13.9 1 -12.4 -28.3 -3.8 23.3 -34.3 -9.8 -28 -28.2 20.6 -19.3 -6.5 

Fruits and vegetables -1.9 1.8 7.6 44.2 5.2 46.2 80.9 39.9 26.2 -41.9 69.4 42.5 0.9 21.9 -4.2 -1.1 

Nuts -2.5 3.6 12.7 18 5 36.5 21.5 -2.3 5.2 -11.3 15.7 26.1 -5.8 5.2 9.5 5 

Oil seeds 17.7 9.9 -60.8 -32.5 -9.6 -14.3 -27.7 12.9 -19.3 50 2.7 -25.1 -32.5 62.2 -12.2 46.7 

Sugar crops 8.3 2.7 8.3 -1.1 11.8 21.2 1.1 -21.7 20.6 -50.6 460.2 -26.7 -76.2 -31 -41.2 -81.8 

Other crops 17.2 12.9 -34.7 22.6 -11.5 75.5 -6.6 -14.2 -34.2 -49.6 31.8 8.7 7.7 6.5 -10.8 20.6 

Cattle 13.8 28.7 -10.7 -4.5 -13.5 -11.7 3.8 -14.9 35.9 15.9 -9 5.5 -4.7 72 37 28.3 

Hogs -5.1 0.7 6.6 11 2.4 3.3 -3.7 -14.3 7.4 -9.9 -14.4 2.9 -7.1 -18.2 -4.8 3.7 

Other animals -6.4 1.3 11.2 16.6 -12.2 -9.7 -1.2 -10.9 3.4 -17.1 -12.2 4.6 -8.9 42 -9.9 -6.9 

Milk -8.2 342.4 138.4 92 13.1 -20.2 37.7 106.9 32.8 -53.1 15.7 162.5 -14.3 80.2 103.8 146.5 

Forestry -3 10.8 3.7 -13.5 1.2 -29.2 2.2 0.8 -13.1 36.5 -14.4 -6.3 -5 20.3 -12.4 -6.3 

Energy, mining -0.9 -2.3 7.2 -5.1 -3.3 -8 0.9 -1.3 -1.2 -0.2 0.5 -1.1 -1.3 -0.5 -0.4 -1.5 

Beef -10.3 -24.4 109.1 8.4 -22.6 -48.4 1.1 6.9 17 -27.1 -24.8 -3.9 -23 -9.3 8.3 -10.8 

Pork -8.4 -1.1 40.3 4 -18.6 9.1 2.9 3.6 12.4 15 -6.6 12.7 -11.6 0.6 -11.6 15.1 

Other meat -9.3 -2.4 48.1 0.6 -17.6 2.7 -1.8 -1.4 3.6 25.3 -12.9 11.6 -21.1 -3.3 -13.3 1.3 

Vegetable oil -11.9 -26.8 93.1 43.4 1.4 206.2 -9.6 -9.6 2.5 -21.4 -55.7 -14.7 -28 -29.8 -13.1 -24.3 

Milk products -6 0.2 42.8 79.4 1.5 -23.3 -16.3 9.7 37.7 -20.1 -44.1 4.7 5.6 31.5 19.2 -11.2 

Processed rice -9.8 -5 -62.3 23.7 -31.8 31.3 136.8 0.8 -21 -50.4 435.6 123.8 29 -7.8 91.3 41.9 

Sugar -9.8 -20.3 16.8 175.6 -49.6 547.6 -13.6 -2.3 -0.7 -49.7 35.5 30.1 -17.1 -37 6.9 -35.3 

Processed food -9.9 -7.3 -14.8 48.6 -9.9 25 5.6 -15.5 -4.5 54.9 -19.6 -3.9 1.4 -16.5 -10 -3.8 

Labor intensive manufactures

-2.1 0 18.4 -15.3 -1.2 18.6 -6 -2.8 -2.6 8.6 -16.6 -1.2 -4.7 -6.3 -4.4 -10.7 

Other chemicals -0.2 -2.7 0.5 9.8 -2.2 15.6 1.6 -1.7 -3 -4.1 -3.2 -1.9 -3.2 1.7 -3 -2.2 

Fertilizers -8.8 -17.8 -14.1 -6.2 -12.2 -2.6 -5.5 -6.2 -18.2 -17.8 -15 -19 -20.1 -12.5 -20 -22.6 

Pesticides -34 -49.1 -47.6 -24.2 -43.2 -38.7 -22.2 -29.9 -48.6 -41.7 -39.8 -47.2 -48.4 -36.1 -45 -49 

Capital intensive manufacturing

0.5 3.1 11.6 -0.9 0.8 -7.3 0.9 -1.1 0 6.1 3.8 1.3 -1.9 5.8 0.6 -1.7 

Services 0.7 2.8 14.6 -2 3.7 -10.8 0.3 -0.7 -1.8 2 -0.9 0.1 -3.2 6 -3.9 -0.9 

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
43

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-10Export volume changes from EU-only scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA

Former USSR and 

rest of Europe

India

Japan

Mexico and Central 

America

Middle East and 

North Africa

Oceania

Other Asia

Rice -82.2 63.6 159 -6.4 484.7 8.3 21.8 -10.1 -9.5 21 74.9 -1.1 18.6 -13.2 12.2 

Wheat -82.4 7.6 21 7.9 21 13.3 83.2 -6.8 58.2 50.4 58 84 245.7 11.4 554.4 

Coarse grains -34.2 23.3 7.5 4.6 2.5 18.2 28.5 1.5 15.5 11 19.4 22.2 34.3 -3.6 11.9 

Fruits and vegetables -5.3 9.5 0.5 -2.5 -7.3 7.8 1.1 -10.2 2.5 17.7 3.7 -2.9 6.8 -5.9 -0.3 

Nuts -9.5 0.6 -1.9 -6.2 -9.5 6.8 0.7 -9.6 -3.3 8.6 1.6 -5 -0.9 -4.8 1.3 

Oil seeds -84.6 57.5 7.7 0.6 -6.6 35.4 25 9.4 18.7 47.5 74.4 21.8 119.1 71.7 16 

Sugar crops -54.4 143 111.6 35.4 78.6 91.2 246.4 118.5 102.8 127.6 10.8 146.1 349.1 159.6 305.3 Other crops -84.7 37 22.3 30.3 17.8 27.1 31.1 6.9 40.1 64.1 28.7 33.8 38.8 -4.8 47.2 

Cattle -28.7 21.2 19.5 9.8 8.3 25.3 3.4 43.1 24.8 6.9 85.4 5.3 23.1 7.8 16 Hogs -9.3 2.4 1.6 3 2.2 10.8 -0.6 33.8 22.5 16.6 5 7 -6.3 -6.1 2.3 Other animals -34.6 13.7 8.6 8.4 27.3 22.8 6.5 27 20.7 22.9 17 17.4 14.2 1.2 16.6 

Milk -157 24.4 26 12.8 56.1 139.9 22.6 10.6 39.5 120.8 67.2 23.5 77.6 16.1 26.4 

Forestry 13 -7 -22.6 -16.2 -4 2.9 1.6 -16 -12.6 -6.5 2.8 -9.7 -9.1 -8 0.2 

Energy, mining 2.6 -1.2 -5.8 -3 -1 1.5 0.1 0.9 -0.5 -2.1 -0.1 -0.7 0.3 -1.7 0.8 

Beef -28 36.3 6 5.5 4.9 84.9 -1.5 6.6 -1.1 6.1 16.6 0.5 45.4 1.9 9.4 

Pork -14.2 13.6 2.9 8.3 12.7 14.8 17.5 23 -0.7 5.6 25.1 7 12.7 13 17 

Other meat -20.7 11.1 -2.9 9.9 7 10.2 3.7 15.5 -2.9 -0.2 11.9 6.7 6.5 8.2 23.7 Vegetable oil -22.8 29.6 -3.9 -0.7 -7.7 2.6 -0.6 2.8 -4.1 13.5 82 2.6 11.5 91.3 6.4 Milk products -20.5 21 4 3.9 17.5 28.4 9.2 19.6 5.2 39.9 45.5 10.5 9.8 1.8 8.7 

Processed rice -4.8 -7.3 13.8 -3.8 23.3 2.3 -1.2 -34.7 0.5 13.5 0.3 -7.1 -10.8 -0.8 -3.7 Sugar -27.2 16 7.5 -5 35.9 0.8 72.6 -9.7 -3.6 18.9 12.7 4.5 0.5 37.5 1.2 Processed food -5.8 1.4 1.3 -4.7 1.7 2.4 -3.5 1.4 0.7 -2.5 4.3 1.1 -2.5 4 1.5 

Labor intensive manufactures 5.2 -6.9 -7.6 -5.6 -1.9 -1.6 2.5 1.5 -5.1 -4.9 4 -0.9 -3.4 -2.4 -4.4 

Other chemicals 1.6 -3.9 -4.2 -5.9 -1.2 -1.8 0.8 -0.6 -0.8 -1.8 0.8 -0.8 0.7 -3.6 -0.5 Fertilizers -3.2 -2.4 -3.6 -4.6 -1 -1.3 0.7 -1 -0.5 -1.3 0.8 -1.8 0.2 -3.2 -0.2 

Pesticides -15.1 -2.7 -3 -4.4 -1.4 -1.5 0.5 -15 -2.8 -2.7 -3.4 -1 -9.4 -3.3 -0.3 

Capital intensive manufacturing 2.4 -5.8 -6.5 -4.5 -1.8 0.4 0 -0.1 -3.6 -3 -0.3 -1.1 -0.5 -3.7 -0.7 

Services 1.4 -3.3 -4.9 -2.8 -1.5 0.2 -0.3 -0.1 -1 -1.8 -0.3 -1.2 -0.6 -2.4 -0.5 

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
44

Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-11Export volume changes from middle scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA

Former USSR and 

rest of Europe

India

Japan

Mexico and Central 

America

Middle East and 

North Africa

Oceania

Other Asia

Other South America

Ri

Rice 118.3 173.4 9.8 5.3 -20 -10.3 -9.1 -23 -34.1 -6.5 -7.3 27.2 -86.1 20.7 13 9.8 -48

Wheat -29.9 -95.8 11.7 10.8 -15.9 -42.8 -20 -11 -30.1 -16.7 -24.2 -41.3 867.5 -8.9 -24.3 -5.3 -32

Coarse grains -18.5 20 -20.1 -12.8 0.8 7.1 -5.6 -21.1 -9.2 -9.5 -7.8 -2.6 61.6 7.8 4.1 -4.4 -31

Fruits and vegetables 20.7 4.4 2.3 -34 -4.4 3 -1 -91.4 41.3 -15.9 -0.7 -3.4 -37.2 -6.7 -0.5 -8.4 -3

Nuts 88 -54.2 -18.5 8.5 20.9 4.4 31.9 -70.3 -21.9 -18.7 36.6 9.7 -34.6 22.9 7.6 -7.3 28

Oil seeds -49.1 282.2 8.3 -0.2 -4.5 -20 12.9 -36.4 -32.9 -14.4 -17.9 -8.6 723.2 -22.8 4.1 -7.9 -30

Sugar crops -40.6 174.2 23.5 23.5 10.8 1.6 11.8 74.1 -2.7 21.8 7.3 16.6 988.6 24.9 4.7 4.9 200

Other crops -30.5 19.9 23.7 -3.4 10.4 3.6 4.1 211.2 -7.8 9.7 12.2 1.2 -15.7 16 -3.4 9.3 13

Cattle 1.9 22.1 1.5 -10.3 4.7 0.3 -4.5 -54.8 -13.1 -35.5 -22.6 5 -10.1 -2.7 -7.3 -2.1 

Hogs -7.1 37.3 -0.2 -1.1 2.4 -7.3 -10.6 -40.2 110.9 -8 1.1 -7.4 -42.3 5.7 2.9 -20.7 159

Other animals -14.9 -52.4 2.7 -0.1 13.6 -6.1 5.7 -8.5 0.3 -13.4 11.6 -8.4 -29.6 15.3 4.1 6.2 -5Milk -1 -97.3 49.7 50.2 40.8 18.8 24.3 -92.3 7.7 45.8 37.2 27.3 -36.5 39.2 22.6 33.5 10

Forestry -6.2 -46.4 29.2 21.8 4.3 13.8 9 -32.5 20.4 28.6 6.3 14 -29 2.5 8.9 7.4 3Energy, mining 0.9 1.5 1.6 0.4 -2.1 -5.2 -1.5 2.8 -1.2 -2.8 -3.3 -2.6 5.1 -2.3 -2.9 -1.9 -0

Beef -7.4 90.7 -15.1 -10 -3.7 -27.2 -10.5 -67 -15.5 -12.6 -5 -3.9 0.1 -4.9 -29.1 -8.6 -

Pork -21.5 -9.5 15.8 16.1 20.1 27.9 1.2 -12 2.4 10.5 4.6 26 -3 32.6 27.2 26.5 

Other meat -6.4 -11.9 3.9 -19.6 6.2 -1.1 5.6 -36.7 -5.2 -7.6 6.2 -6.9 35.8 -5.4 -19.9 -0.5 Vegetable oil -14.5 290.6 -11 -23.2 10.1 -4.9 -11 22.4 -19.7 -18 -6.8 -7.2 49.6 -26.1 -12 -16.5 -15

Milk products -1.2 -24.5 4.3 -9.9 10.1 -4.7 0.1 -60.2 11.2 -9.8 8.8 8 -53.6 2.2 -2.2 6 32

Processed rice 229 237.2 -25.4 -24.9 -11 -16.7 -19.4 330.9 -10.8 -42.7 -25.9 -18.4 19.2 -26.6 -28 -18.6 -1

Sugar -6.2 24.6 1.2 -21.8 -6.1 -7.4 -3.9 -76.2 -16.4 -41.9 -7 -10.2 -3.2 -1 -6.4 -13.8 -43Processed food -12.1 -13.1 -4.2 -14.6 6 -3 -2.5 -1.2 -7.7 -7.6 4.5 0 -45.3 1.4 -2.2 0.2 5Labor intensive manufactures 0.8 -43 8.6 8.1 0.3 3 2.9 1.4 2 6.1 2.3 2.1 -39.1 2.9 2.9 3.9 2

Other chemicals -1.6 -15.7 4.2 3.9 0.4 -1.2 0.7 -6.5 1.2 1.1 0 0.3 5.3 0.4 0.6 1.2 2

Fertilizers -9.1 -27.1 1.3 0.3 -0.8 -3.8 -2.2 -8.7 -2.3 -3.9 -0.7 -2.1 1.9 -1 -0.8 -1.9 -3

Pesticides -27.8 -49.7 1.8 -1.7 -2.3 -19.2 -0.3 -27.6 -31 -16.2 -9.2 -2.7 -22.9 -3.5 -1.7 -2.3 -29

Capital intensive manufacturing 1.8 -16.9 4.8 3.7 -0.4 -1.5 -0.3 1.8 -0.7 0.1 -1.2 0 9.7 0.4 0.2 1 1

Services 0.7 -5.1 2.5 1.9 -0.8 -1.2 -0.9 1.8 -0.2 -0.3 -1.2 -0.6 0.9 -0.3 -0.3 -0.1 0

Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
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Appendix Table B-12Export volume changes from global scenario (percent change)

EU

Africa

Argentina

Brazil

Canada

China

Developed Asia

EFTA

Former USSR and 

rest of Europe

India

Japan

Mexico and Central 

America

Middle East and 

North Africa

Oceania

Other Asia

Rice 252.1 756.7 2,109.3 -85.2 9,319.2 -84.6 -43.7 948.1 249.5 538.1 69.2 -97.2 65.8 -89.2 -62.3 Wheat -47.5 -99.2 172.1 -57.3 -26.5 -99.6 89.9 -15.8 146 -51.5 -46.6 177.9 620.8 -17.7 2,575.7 

Coarse grains -13.5 83.2 15.7 -3.9 -33.9 -38.8 105.9 -12.3 -69.6 37.3 19.9 57.4 92.2 -38.2 86.4 

Fruits and vegetables 55.1 69.6 -35.9 -83.9 -39.8 -47 -59.2 -62.7 -13.3 223.7 -56.9 -60.9 10.3 -0.6 15.6 

Nuts 81.5 34 -49.2 -78.3 -48.6 -64.3 -69.8 -69.2 -33.9 84.9 -69.4 -69.7 22.1 -28.5 -22.2 

Oil seeds -58.1 575.1 8.9 -49.9 -37.7 -26.7 59.3 -25.7 -62.5 169.5 171.5 73.6 526.4 363.8 41.4 

Sugar crops -37.3 92.4 62.3 -39.1 74.6 -42 1,438.9 51.2 -63.7 291.1 -98.6 241 864.1 382.9 507.2 

Other crops -42.7 -24.4 75.7 -30.6 159 -68.4 133.1 111.9 117.9 236.5 -58.3 35.9 -34.3 -71.6 66.1 

Cattle 6.9 14.6 -24.8 35.7 -6.5 97.9 -27.9 -31 -20.4 -42 52.5 -27.2 3 30 -1.7 

Hogs -3.2 -11.3 -59 -16.3 5.1 -4.7 -4.3 -4.4 -41 11.5 50 -7.6 -23.6 -68.8 10.7 

Other animals -0.6 -27.5 -54.4 -51.8 70.4 -11.6 0.3 -20.2 -35.4 24.7 54.9 -19.3 -6.7 -66.1 3 

Milk 22.7 -94.4 -82.9 -97.9 -46 156.4 -62.7 -86.4 -49.7 262.7 -38.3 -86.6 47 -83.4 -74.2 

Forestry 1.4 -31.6 -7.5 55.5 -29.8 51.4 5.2 -11 21.2 -52.9 23.3 8.2 0.4 -39.7 16.5 

Energy, mining -8.4 -2.3 -31 5.6 -8.5 43.8 -4.4 -1.3 2.1 -8.8 -6.6 -3.5 1.9 -13.6 11 

Beef -7.4 91.2 -80.7 -46.2 13.7 194.3 -61.3 -44 -47.1 33.5 37.4 -35.5 48.9 -15.6 -27.6 

Pork -5 -9.2 -62.6 -31.3 28.4 -32.3 -17.8 -15.3 -47.7 -47.4 14.6 -41 13.3 -19.3 15.8 

Other meat -1.3 -11.4 -55.9 -25.8 41.8 -31.7 -13.4 -30.6 -43.1 -45.9 17.6 -33.1 21 -16.5 10.9 

Vegetable oil 12.3 304 -82.8 -63.7 -59 -92.7 -50 66.6 -81.1 54.9 771.9 -10.9 138.9 919.8 14.5 Milk products 24.1 -7.3 -41.3 -79.9 -11.6 16.9 -4.1 -30.9 -54.8 141.4 141.2 -33.1 -35.3 -62.4 -51.6 

Processed rice 110.3 2.5 218 -15.2 487.8 -73.6 -88.2 91.5 140 162.7 -86.8 -68.7 -69.4 137.5 -66.5 

Sugar 1.8 9.6 21.2 -64 260.9 -98.6 1,233.2 -68 -81.3 60.5 32 4.8 -11.2 494.4 -32.4 

Processed food 0.9 -3.2 -2.7 -71 9.6 -50.6 -51.4 19.7 -18.3 -70.5 21.4 -6.7 -34.2 36.8 -7.5 Labor intensive manufactures 25.8 -17.2 -24.2 36 6.9 -31.4 41.2 36.8 -13.4 -29.1 61.7 18.9 -4 19.8 -31.1 

Other chemicals 1.9 -9.6 -11.4 -32.8 -1.8 -27.7 14.2 -0.6 11.4 -3.8 15 4.1 19 -18.1 6.2 

Fertilizers -11.6 -24.7 -29.7 -46.8 -16.2 -38 -6.6 -12.2 -4.5 -19.2 -0.8 -14.3 3.1 -32.5 -9.5 

Pesticides -37.7 -46.6 -50.8 -63.6 -31.6 -57.4 -32 -39.5 -43.3 -42.3 -30.4 -39.9 -29.2 -47.1 -36.6 

Capital intensive manufacturing -5.6 -20.3 -33.1 -2 -10.3 26.5 -0.5 -4.5 -8.5 -15.2 -1.5 0.4 7.6 -18.6 4 

Services -1.5 -6.1 -20.8 6.3 -6.2 19.1 -0.4 1.3 3.5 -4.5 1.2 -0.3 3.1 -9.6 6.6 Note: EFTA refers to the European Free Trade Association.Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones (GTAP-AEZ) model.
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Appendix Table B-13

Welfare changes from EU-only scenario (billions of U.S. dollars, over a period of a year)

Allocative 

efficiency Endowments Terms of trade Other Total

EU -56.8 -14.5 -10.7 -2.3 -84.2

Africa -0.7 0.0 4.8 0.0 4.1

Argentina 0.1 0.0 4.3 -0.1 4.3

Brazil -1.5 0.0 9.3 0.0 7.8

Canada -0.4 0.0 4.6 -0.2 4.1

China -6.8 0.0 -22.3 4.7 -24.4

Developed Asia -0.9 0.0 -5.4 1.5 -4.8

EFTA -1.2 0.0 -2.0 0.8 -2.4

Former USSR and rest of 

Europe

-0.6 0.0 0.6 -0.1 0.0

India -0.9 0.0 5.6 -0.4 4.3

Japan -1.4 0.0 -6.0 0.0 -7.4

Mexico and Central America -0.9 -0.1 1.7 -0.1 0.6

Middle East and North Africa -2.0 0.0 -17.6 1.0 -18.5

Oceania 0.1 0.0 6.3 0.0 6.5

Other Asia -1.9 0.1 1.1 -0.2 -0.9

Other South America -0.2 0.0 1.0 0.1 0.9

Russia -1.6 0.0 0.3 0.9 -0.4

Turkey -0.8 0.0 0.7 -0.3 -0.5

Ukraine 0.2 0.0 4.3 0.0 4.4

United States -2.0 0.0 17.9 -5.1 10.8

Note: EFTA refers to the European Free Trade Association.

Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones 

(GTAP-AEZ) model.
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Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-14

Welfare changes from middle scenario (billions of U.S. dollars, over a period of a year)

Allocative

efficiency Endowments Terms of trade Other Total

EU -172.6 -14.2 -17.5 -1.6 -205.9

Africa -68.7 -11.5 59.2 0.0 -20.9

Argentina -0.3 0.0 -1.9 0.4 -1.8

Brazil 0.3 0.0 -5.4 2.4 -2.7

Canada -0.3 0.0 -0.8 -0.7 -1.7

China 0.0 0.0 -5.0 10.5 5.5

Developed Asia -0.3 0.0 -3.8 4.9 0.8

EFTA -6.3 -2.8 -10.5 2.6 -17.0

Former USSR and rest of Europe -0.9 0.0 -2.5 -0.9 -4.3

India 0.6 0.0 2.7 -2.8 0.5

Japan -1.5 0.0 0.4 0.4 -0.7

Mexico and Central America -0.9 0.0 -0.8 -0.5 -2.3

Middle East and North Africa -70.7 -4.2 -75.0 1.5 -148.4

Oceania -0.1 0.0 -2.0 0.3 -1.8

Other Asia -0.9 0.0 -2.2 -1.0 -4.1

Other South America -0.2 0.0 -2.2 1.2 -1.1

Russia -1.9 0.0 -12.2 4.2 -9.8

Turkey -18.0 -1.2 11.0 -0.2 -8.4

Ukraine -10.3 -0.5 39.6 -0.4 28.4

United States -0.1 0.0 20.7 -20.5 0.2

Note: EFTA refers to the European Free Trade Association.

Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones 

(GTAP-AEZ) model.
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Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

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Appendix Table B-15

Welfare changes from global scenario (billions of U.S. dollars, over a period of a year)

Allocative 

efficiency Endowments Terms of trade Other Total

EU -119.1 -14.4 -54.9 -14.9 -203.4

Africa -59.9 -11.9 36.6 0.4 -34.9

Argentina -11.7 -1.2 45.2 -0.7 31.7

Brazil -63.6 -3.6 83.6 4.4 20.8

Canada -13.3 -1.4 35.6 -2.1 18.8

China -326.4 -32.7 -238.0 44.5 -552.6

Developed Asia -17.4 -2.2 -47.8 10.2 -57.2

EFTA -3.8 -2.7 -15.4 4.6 -17.4

Former USSR and rest of Europe -17.2 -2.8 5.0 -1.1 -16.1

India -33.2 -30.1 56.5 -6.7 -13.5

Japan -21.2 -1.4 -63.1 -0.9 -86.6

Mexico and Central America -38.2 -6.1 7.4 -1.9 -38.7

Middle East and North Africa -44.6 -4.0 -150.5 8.5 -190.6

Oceania -11.9 -2.0 53.6 -0.7 39.1

Other Asia -67.4 -26.0 7.5 -3.8 -89.6

Other South America -15.0 -2.2 9.3 1.3 -6.6

Russia -22.3 -3.0 -6.4 7.3 -24.4

Turkey -13.5 -1.2 5.6 -2.5 -11.6

Ukraine -8.8 -0.5 30.6 0.0 21.3

United States -65.1 -8.8 185.8 -44.6 67.3

Note: EFTA refers to the European Free Trade Association.

Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones 

(GTAP-AEZ) model.
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Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-16

Land use changes from EU-only scenario (percent change)

Forestry Cropland Pastureland

EU 9.8 -10.5 -6.1

Africa -2.1 1.0 -2.5

Argentina -0.9 1.5 -3.1

Brazil -2.0 0.3 -0.7

Canada -0.3 4.6 4.4

China -0.1 0.9 -0.2

Developed Asia -2.9 0.5 -1.6

EFTA -14.7 -0.5 -0.8

Former USSR and rest of Europe -1.8 0.5 -2.1

India -5.4 1.5 -12.0

Japan -0.3 0.0 0.9

Mexico and Central America -2.3 -0.3 -1.2

Middle East and North Africa -5.0 1.5 -0.2

Oceania -3.5 10.1 -5.2

Other Asia -0.9 -0.7 0.8

Other South America 1.1 1.8 -0.8

Russia -3.6 3.3 1.7

Turkey 0.1 1.9 -2.4

Ukraine -3.0 4.2 0.0

United States -5.1 1.4 -2.4

Note: EFTA refers to the European Free Trade Association.

Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones 

(GTAP-AEZ) model.
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Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-17

Land use changes from middle scenario (percent change)

Forestry Cropland Pastureland

EU -7.8 -6.8 -11.0

Africa -12.5 -9.8 -13.5

Argentina 2.3 -1.0 0.1

Brazil 0.6 -0.9 -0.3

Canada 0.3 -0.9 0.3

China 0.2 -0.1 0.0

Developed Asia 0.0 0.0 -0.5

EFTA -31.8 -20.7 -27.1

Former USSR and rest of Europe 0.8 0.1 -0.1

India 0.9 -0.1 0.5

Japan 0.1 -0.1 -0.4

Mexico and Central America 0.3 -0.3 -0.1

Middle East and North Africa -25.7 -10.1 -9.5

Oceania 1.3 -0.5 0.0

Other Asia 0.3 -0.3 0.0

Other South America 0.6 -1.1 -0.1

Russia 0.5 -0.6 -0.5

Turkey -9.2 -3.3 -22.6

Ukraine -7.4 -9.3 -16.5

United States 0.4 -0.3 -0.1

Note: EFTA refers to the European Free Trade Association.

Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones 

(GTAP-AEZ) model.
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Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-18

Land use changes from global scenario (percent change)

Forestry Cropland Pastureland

EU -3.2 -3.7 -10.2

Africa -10.9 -7.9 -13.7

Argentina -16.0 -11.0 -15.4

Brazil 0.3 -22.3 -8.5

Canada -8.0 -23.8 -17.9

China -6.0 -22.8 -6.0

Developed Asia -28.0 -15.5 -20.6

EFTA -13.9 -20.5 -27.0

Former USSR and rest of Europe -6.9 -11.1 -18.4

India 1.3 -11.0 -3.8

Japan -8.6 -10.5 -8.6

Mexico and Central America -11.3 -13.0 -18.6

Middle East and North Africa -21.5 -9.4 -11.6

Oceania -17.1 37.1 -44.3

Other Asia -8.2 -15.9 -15.9

Other South America 1.3 -27.2 -14.5

Russia -13.0 -2.8 -11.9

Turkey -7.3 -5.8 -21.1

Ukraine 2.0 -16.3 -12.9

United States -26.9 -8.9 -34.8

Note: EFTA refers to the European Free Trade Association.

Source: USDA, Economic Research Service calculations using the Global Trade Analysis Project–AgroEcological Zones 

(GTAP-AEZ) model
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Economic and Food Security Impacts of Agricultural Input Reduction Under the European Union Green Deal’s Farm to Fork and Biodiversity Strategies, EB-30

USDA, Economic Research Service

Appendix Table B-19Food security changes across the three scenarios

Share of the population food-insecure Difference from Baseline Number of people food-insecure D

B

2020 2030 2020 2030 2020 2030 

(percent) (percent) 

Africa baseline 29.4 18.8 431.5 342.2 

Farm to Fork (EU) 29.4 19.3 -0.1 0.4 430.6 350.1 

Farm to Fork (Middle Scenario) 30.3 24.0 0.8 5.2 443.6 436.2 

Farm to Fork (Global) 30.2 23.3 0.8 4.4 443.0 422.5 

Former USSR and rest of Europe baseline 30.2 13.8 7.9 3.8 

Farm to Fork (EU) 30.7 15.9 0.5 2.1 8.0 4.3 

Farm to Fork (Middle Scenario) 30.2 13.9 0.0 0.1 7.9 3.8 

Farm to Fork (Global) 33.0 24.2 2.8 10.4 8.6 6.6 

India baseline 14.0 1.1 185.1 15.7 

Farm to Fork (EU) 14.0 1.1 0.1 0.01 186.2 15.9 

Farm to Fork (Middle Scenario) 13.9 1.1 0 0 184.9 15.5 

Farm to Fork (Global) 14.8 2.3 0.8 1.2 195.6 33.1 

Mexico and Central America baseline 30.2 18.7 19.1 13.2 

Farm to Fork (EU) 30.3 19.8 0.2 1.1 19.2 13.9 

Farm to Fork (Middle Scenario) 30.2 18.7 0.0 0.0 19.1 13.2 

Farm to Fork (Global) 31.2 23.8 1.0 5.1 19.8 16.7 

Middle East and North Africa baseline 25.3 18.2 38.2 32.1 

Farm to Fork (EU) 25.5 19.4 0.1 1.2 38.4 34.2 

Farm to Fork (Middle Scenario) 26.2 23.8 0.8 5.6 39.5 41.9 

Farm to Fork (Global) 26.1 20.6 0.7 2.4 39.3 36.4 

Other Asia baseline 23.2 9.4 217.0 96.3 

Farm to Fork (EU) 23.3 10.4 0.1 1.0 217.8 106.4 

Farm to Fork (Middle Scenario) 23.2 9.3 0 0 216.9 95.8 

Farm to Fork (Global) 24.8 16.4 1.6 7.0 231.8 168.3 

Other South America baseline 19.9 8.5 21.8 10.2 

Farm to Fork (EU) 20.0 9.2 0.1 0.7 21.9 11.0 

Farm to Fork (Middle Scenario) 19.9 8.5 0.0 0.0 21.8 10.1 

Farm to Fork (Global) 20.8 12.3 0.8 3.7 22.7 14.7 

Total baseline 22.6 10.9 920.6 513.4 

Farm to Fork (EU) 22.6 11.4 0.0 0.5 922.2 535.8 

Farm to Fork (Middle Scenario) 22.9 13.1 0.3 2.2 933.8 616.5 

Farm to Fork (Global) 23.6 14.9 1.0 3.9 960.9 698.4 

Note: Food security estimates are for 76 low- and middle-income countries and do not include China, high-income countries in Asia, and Mexico. Source: USDA, Economic Research Service calculations using the International Food Security Assessment Model.