Report Coordinator

Shahla Shapouri

Stacey Rosen

Principal Contributors 

Birgit Meade

Stacey Rosen

Shahla Shapouri

Abebayehu Tegene

Michael Trueblood

Keith Wiebe

Technical Editor

Lindsay Mann

Production/Design

Wynnice Pointer-Napper

Victor Phillips, Jr.

Cover Photo

FAO

Niger, by P. Cenini

Approved by the World

Agricultural Outlook Board.

Summary released December 7,

2000. Summary and full report

may be accessed electronically via

the ERS web site at

http://www.ers.usda.gov

FOOD SECURITY

ASSESSMENT

Situation and Outlook Series

Contents

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Global Food Security: Overview . . . . . . . . . . . . . . . . . . . . . . . . .4

Regional Summaries:

North Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

Sub-Saharan Africa (SSA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17

Latin America and the Caribbean (LAC) . . . . . . . . . . . . . . . . . . .20

New Independent States (NIS) . . . . . . . . . . . . . . . . . . . . . . . . . . .22

Special Articles:

Resource Quality, Agricultural Productivity, and Food Security 

in Developing Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24

Vulnerability to HIV/AIDS in Sub-Saharan Africa . . . . . . . . . . . .30

Boxes:

How Food Security Is Assessed . . . . . . . . . . . . . . . . . . . . . . . . . . .9

Data and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28

Country Statistical Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35

Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .76

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78
 ✺ 

				
 
	



Preface

This report continues the series of food assessments begun in the late 1970s. Global Food Assessments were done from 1990

to 1992, hence the GFA series. In 1993, the title was changed to Food Aid Needs Assessment to more accurately reflect the

contents of the report, which focuses on selected developing countries with past or continuing food deficits. In 1997, we

widened our analysis beyond the assessment of aggregate food availability to include more aspects of food security. We therefore changed the title to Food Security Assessment.

Acknowledgments

Appreciation is extended to Neil Conklin, Director of the Market and Trade Economics Division, for his support of the food security work, and to Cheryl Christensen, for valuable comments on the articles. We would also like to thank the reviewers, especially

Mary Bohman, Joy Harwood, Carol Goodloe, Jerry Rector, and Bill Hawkins, for their comments. Special thanks are extended to

Lindsay Mann, Martha R. Evans, Wynnice Pointer-Napper, and Victor Phillips, Jr., for editorial and design assistance.

	

	


	











	









 
	

		
	

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USDA’s Economic Research Service (ERS) projects that

average per capita food consumption for 67 low-income

countries will increase in the next decade. ERS also projects

that the number of people failing to meet their nutritional

requirements will decline from 774 million in 2000 to 694

million in 2010, providing an improved outlook for global

food security. But the gains are not uniform across countries

and in many food insecurity will probably intensify. SubSaharan Africa, as the most vulnerable region, accounts for

only 24 percent of the population of these 67 countries, but

it is projected to account for 63 percent of these “hungry”

people in 2010. HIV/AIDS is expected to reduce the

region’s agricultural productivity, and constraints in financial resources will limit commercial imports, thus leading to

declining per capita consumption.

ERS evaluated the food security position of low-income

countries by projecting the gaps between food consumption

(domestic production, plus commercial imports, minus nonfood use) and consumption targets through the next decade.

The consumption targets are (1) maintaining per capita

food consumption at 1997-99 levels (also referred to as

“status quo”) and (2) meeting minimum recommended

nutritional requirements.

In 2000, the food gap to maintain per capita consumption at

1997-99 levels in 67 low-income developing countries is

estimated at about 7 million tons. The gap to meet minimum

nutritional requirements is estimated to be higher at 17 million tons. The food gaps with respect to both consumption

targets are projected to widen during the next decade. The

gap to maintain per capita consumption will increase 80 percent to 12.7 million tons in 2010, while the nutritional gap

will expand 30 percent to more than 22 million tons. For the

67 countries as a whole, the “distribution gap” (the amount

of food needed to raise consumption of each income group

to the minimum nutritional requirement) is expected to

widen by 21 percent and exceed 31 million tons in 2010.

The growth of food gaps stands in contrast to the projected

trend in the number of hungry people. In fact, the number of

people failing to meet nutritional requirements is projected

to decline in the next decade, implying that hunger in the

food insecure and lower income groups will intensify.

ERS has identified Sub-Saharan Africa as the region most

vulnerable to food insecurity. The high incidence of

HIV/AIDS in Sub-Saharan Africa is expected to reduce

agricultural productivity, and constraints in financial

resources will limit commercial imports, thus leading to

declining per capita consumption. Sub-Saharan Africa is the

only region that shows increases in all indicators of food

insecurity, such as food gaps and growth in the number of

hungry people.

Depending upon the future availability of food aid, a portion

or all of the projected food gaps can be eliminated. For

example, in 1999 roughly 12 million tons of food aid was

distributed globally. If the same amount were provided in

2000, it would fill the entire calculated gap to maintain per

capita consumption (status quo) and about 66 percent of the

nutritional gap. However, all of the available food aid is not

going to low-income, food-deficit countries. In 1999, only

7.5 million tons of food aid, or 63 percent of the total, was

given to the study countries, and that is about 40 percent of

the estimated nutritional gap in 2000.


	

 

				


✺ 

Summary


 

The lower food prices in recent years were welcome news

for highly import-dependent countries, helping to improve

food affordability and security. The low prices also did not

reduce production incentives for those countries that have

managed to improve their productivity and reduce their

costs. Even among the lowest income developing countries,

there are definite signs of rising living standards. At the

forefront are some lower income Asian countries, e.g.

Vietnam, that have shown steady increases in their food supplies and several indicators supporting the continuation of

this trend. This achievement is very important because of

the number of people who are at stake—more than 60 percent of the population of the countries covered in this report.

The food situation in the lower income Latin American

countries such as Bolivia and Guatemala is also improving,

a credit to their improved economic and trade policies that

have led to steady increases in their export earnings that

finance imports. Similarly in the North African and New

Independent States (NIS) countries, several of which are oil

exporters, the oil price hike should provide a stronger basis

on which to expand food imports. 

Sub-Saharan Africa, however, is almost entirely dependent on

domestic production, which in most countries is projected to

grow at too slow a pace to allow increases in per capita consumption. The region’s nutritional food gap is projected to

increase 40 percent, exceeding 17 million tons in 2010.

Despite all the reasons for optimism in four of the five

regions, the unequal distribution of food, both at the international and national levels, remains a major obstacle to

improving food security among the poor. Even among the

prosperous regions, some countries are lagging behind.

Although some of these countries have inadequate

resources, both physical and financial, the most severe foodinsecure countries are the ones that have internal political

instability. The situations in Haiti and Afghanistan are clear

examples of dysfunctional economies and food insecurity.

The future food security position of the 67 developing countries included in this study is evaluated by projecting the

gaps between food consumption (domestic production, plus

commercial imports, minus nonfood use) and two different

consumption targets through the next decade. Food aid,

although a part of the historical food supply, is excluded in

the projections presenting the food gaps that countries face

when left to their own resources. The two consumption targets are (1) maintaining per capita consumption at the

1997-99 level (also referred to as status quo) and (2) meeting minimum recommended nutritional requirements (see

box 1). The estimated nutritional gap only measures the gap

in calorie consumption and does not consider other factors

such as poor utilization of food due to inadequate consumption of micronutrients and lack of health and sanitary facilities. Because the national level estimates represent the average food gaps and mask the impact of unequal incomes on

food security, we also estimate a “distribution gap.” This

gap is defined as the amount of food needed to raise food

consumption for each income group to the level that meets

nutritional requirements. This indicator captures the impacts

of unequal purchasing power or food access.

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This report is an updated version of the 1999 report, with all

historical and projected data updated. The food production

estimates for the year 2000 are based on USDA data as of

September/October 2000. The financial and macroeconomic

data are updated based on the latest World Bank data. The

projected macroeconomic variables are either extrapolations

based on calculated growth rates for 1980-98 or are World

Bank projections/estimations. 

In this report, we have included a scenario that examines the

impact of slower growth in crop area on food security. In

most food insecure countries, increases in food production

are mainly due to the expansion of cropland. Our projections confirm that there will be a need for a substantial

increase in food production over the next decade to meet

nutritional requirements in the lower income countries,

mostly in Sub-Saharan Africa. The existing conditions for

food production and prospects for expansion vary greatly.

However, there are ample studies suggesting that the

increased food supply will have to come from the intensification of production. This applies to Asia and to a lesser

extent to Latin America and Africa. In the latter regions,

opportunities to expand the production area exist, but unrestrained expansion can lead to long-term damage to natural

resources and the environment. The analysis of the scenario

of slower growth in production area confirms and quantifies

 ✺ 

				
 
	



Global Food Security: Overview 

	


	





	
	



	

	


	










	

 








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what common sense suggests: without any increase in

investment in production intensification, lower income

countries tend to become more food insecure. 

This report also includes two special articles. The first article

is entitled “Factors Affecting Agricultural Productivity of

Developing Countries” and concludes that agricultural productivity is important for food security both through its

impact on food supplies and prices, and through its impact

on the incomes and purchasing power of farmers. In this context, land quality is related to both food availability and food

access. Land quality is, on average, lower in low-income

food-deficit countries than it is in high-income countries.

This has important implications for policymakers concerned

with improving food security, both through protection and/or

improvement of land quality itself and through recognition of

the distinct roles played by more conventional agricultural

inputs in areas that differ in land quality. 

The second article is entitled “HIV/AIDS and the SubSaharan African Food Market.” The article concludes that

the HIV/AIDS epidemic will reduce labor quality and productivity and will have long-term implications on the performance of the agricultural sector of the highly affected countries. The projected long-term food outlook for these countries shows a steady increase in food gaps in part due to the

impact of HIV/AIDS, and indicates that the situation will

worsen if productivity declines further. This means that to

minimize the impact of HIV/AIDS, policies should combine

educational messages to prevent the spread of the disease

and economic assistance and investment in areas such as

introducing labor-saving technologies. 

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Food gaps based on status quo and nutritional targets and

distribution gaps are projected to grow (tables 1 and 2). In

contrast, a decline in the number of people failing to meet

the nutritional target is estimated. This means that nutritional disparity among and within countries will intensify

more than food deficits will spread. In other words, the

hunger problem will get more severe in the vulnerable countries and/or among the lower income groups. 

The status quo food gaps (or food needed to maintain per

capita consumption at the 1997-99 base level) are estimated

at 7 million tons for 2000, much lower than the projected

12.7 million tons for 1999 (table 1 and fig. 1). This drop can

be attributed to the lower per capita consumption target.

This is a moving average, which fell significantly due to last

year’s drought in North Africa. The food gaps to meet minimum nutritional requirements are estimated at 17 million

tons, higher than last year’s estimate of 15 million tons. 

When the impact of unequal incomes is taken into account, as

we do in the distribution gap the estimated results for the 67

countries show that food gaps increased significantly relative

to the national average (table 2). In 2000, the distribution gap

is estimated to be more than 25 million tons, 33 percent larger

than the national average nutritional gap. Based on the estimated distribution gaps, we calculated the number of people

(in each income quintile) whose consumption falls short of

the minimum nutritional requirement in each country. For the


	

 

				


✺ !

Table 1--Food availability and food gaps for 67 countries

Grain Root Commercial Food aid Aggregate Population

Year production production imports receipts availability

(grain equiv.) (grain equiv.) (grains) of all food

---1,000 tons --- Million

1991 369,198 53,828 30,309 11,123 571,862 2,188

1992 373,263 56,360 42,471 9,916 599,004 2,262

1993 380,772 58,799 43,808 7,975 610,979 2,310

1994 391,859 59,197 46,623 8,003 628,165 2,358

1995 396,966 60,938 54,089 6,212 657,794 2,406

1996 420,083 62,385 50,144 4,695 665,122 2,454

1997 407,457 62,122 59,025 5,337 669,734 2,503

1998 427,151 64,270 61,270 7,847 686,466 2,552

1999 433,093 67,553 61,358 5,068 715,439 2,600

Projections Food gap*

SQ NR (w/o food aid)

2000 434,843 67,121 63,868 7,026 17,054 710,448 2,650

2005 481,858 73,292 68,397 7,602 16,875 784,538 2,896

2010 525,478 79,944 76,710 12,709 22,072 859,932 3,138

*SQ stands for status quo and describes the amount of grain equivalent needed to support 1997-99 levels of per capita consumption

 and NR stands for nutritional requirements and describes the amount needed to support minimum nutritional standards.
67 countries, the number of people failing to meet the nutritional target is projected to decline from 771 million in 2000

to 695 million by 2010. 

Overall, the long-term food gaps for the 67 countries are

lower than those reported in last year’s assessment, principally due to the assumptions of higher economic growth

rates for the Asian and Latin American countries. For the

same reason, in the 1999 Food Security Assessment report,

we projected the number of people failing to meet the nutritional target to grow and for 2009 our projection was higher

than the current projection.

-#"##*#%#"

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Of the 37 countries in Sub-Saharan Africa, per capita consumption is projected to rise in only 7 countries. Even in those

countries, the growth is not expected to be particularly strong.

In 2010, consumption for 60 percent of the region’s population

is projected to fall short of nutritional requirements. In addition, the region is projected to account for nearly two-thirds of

the hungry people in the 67 countries, but it accounts for only

about one-fourth of the population (fig. 2). The region’s nutritional gap is estimated to account for 65 percent of the nutritional gap for the 67 countries in total in 2000. This number is

projected to jump to 76 percent in 2010. The region accounts

for only 24 percent of the population of the 67 countries, thus

indicating the severity of the region’s food security situation. 

In Sub-Saharan Africa, domestic food production accounts

for about 80 percent of consumption. During the next

decade, production growth is projected to fall short of historical rates and average 2.1 percent per year versus 2.4 percent

during 1980-99. The reason for the expected lower production growth is twofold. First, nearly 90 percent of the

region’s historical grain production growth stemmed from

area expansion. This trend is not expected to continue in the

future, as much of the region’s remaining land area is marginal for agricultural purposes. Second, the decline in population growth due to spread of HIV/AIDS is expected to

reduce labor productivity. Labor remains the essential factor

of production and lack of labor-saving technologies will lead

to a decline in food production (see “Vulnerability to

HIV/AIDS in Sub-Saharan Africa”). In the Food Security

model, the marginal productivity of labor is assumed constant over the projection period. For the Sub-Saharan countries, this may be an overestimation because the decline in

population growth is in part due to the spread of HIV/AIDS,

which affects the most productive segment of the population. 

The distribution gap, which incorporates the impact of skewed

income distribution, is projected to rise from 15.3 million tons

in 2000 to 22.5 million tons in 2010, 10 percent higher than

the national average nutrition gap. The number of people in

different income quintiles who fail to meet their nutritional

requirement is projected to increase from 344 million to 435

million in 2010. Sub-Saharan Africa is the only region where

food security, both in terms of the size of the gaps and the

number of undernourished people is expected to rise. 

*##
#

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Per capita consumption in the 10 Asian countries covered

in this report is projected to increase, on average, in the

next decade. There are problem areas, however.

Afghanistan and North Korea, and to a lesser extent,

Bangladesh, account for most of the region’s nutrition gaps

during the projection period. The region’s distribution gap

is projected to decrease during the next decade, as is the

number of people who cannot meet their nutritional

requirement. The region has about 65 percent of the population of countries covered in the report, but is projected to

account for only 26 percent of the people who cannot meet

their nutritional requirement in 2010. 

Per capita food consumption in most of the lower income

Latin American and Caribbean countries (11 countries) is

expected to improve. Even with a relatively slow increase in

" ✺ 

				
 
	



Table 2--Number of people with inadequate food and 

 the size of food deficit 

Number of people with Distribution gap (due to

insufficient food inadequate access to food)

2000 2010 2000 2010

--Million people-- --1,000 tons--

Total 774 694 25,315 30,874

Asia 307 177 5,489 5,294

Sub-Saharan

Africa 344 435 15,294 22,496

Latin America 62 47 1,897 1,813

North Africa 48 31 1,970 1,131

NIS 13 6 664 141

Source: Own calculations using Food Security Assessment model.

2000 2002 2004 2006 2008 2010

25

20

15

10

5

0 0

5

10

15

20

25

Figure 1

Food gaps in all 67 countries, 2000-2010

Mil. tons

Nutritional gap

Gap to maintain consumption

	

 

				


✺ #

Asia

Latin America

NIS

North Africa

SS-Africa Population in 2010

2000--774 million are hungry 2010--694 million will be hungry

Figure 2

While total number of hungry people is projected to decline, Sub-Saharan Africa's 

share is rising sharply

24%

65%

5%

1% 5%

44%

40%

8%

2%

6%

63%

26%

6%

1% 4%

76%

16%

4% 4%

65%

17%

4%

9%

5%

2000--Nutritional gap 2010--Nutritional gap
food production, strong commercial import growth will raise

food supplies sufficiently to keep up with population growth.

Another positive sign is the projected decline in the number

of people with inadequate food supplies. Despite this bright

picture at the aggregate level, food insecurity is growing in a

few countries and highly skewed purchasing power aggravates the problem. In 2000, the estimated distribution gap

(that captures inequality in food access) is about six fold

higher than of the national average nutritional gap. Nutritional

gaps both at the national average and disaggregated levels

(distribution gap) are projected to increase, indicating growth

in intensity of hunger in countries such as Haiti. 

$"*##$#0"#	

#	


Food imports make up about 42 percent of North Africa’s

consumption needs, and this level is projected to continue

through 2010. Financing this level of imports in the next

decade is the critical element to ensure food security. The

region’s two largest food importers, Egypt and Algeria, to

varying degrees, depend on oil and gas revenues. With the

real prices of oil and gas recovering, these countries should

be able to cover their import needs. 

Short-term production variability creates a challenge to food

security in Algeria, Morocco, and Tunisia. Morocco is the

extreme case because it has one of the highest levels of production variability in the world (app. 3). In Algeria, political

difficulties are the main threat to food security. This year,

because of the expected windfall in oil export revenues,

imports are likely to increase to fill these gaps. The longterm food security of the country is threatened because of

low investment that has led to slow growth in agricultural

production and increased food-import dependency of the

country; about 70 percent of grain consumption was

imported during 1997-99. The ability to finance imports will

be the critical factor to ensure food security. 

We project positive growth for agricultural productivity and

import capacity of the NIS countries, but political uncertainty remains a major issue. The drought in 2000 has led to

food gaps in Armenia, Azerbaijan, Georgia, and Tajikistan.

Although Georgia experienced the largest percentage production shock in 2000, the food gaps are expected to be relatively more severe in Armenia and Tajikistan. Tajikistan is

the only country where food gaps are expected to continue

over the next decade. Access to food by lower income

groups in a few of these countries is a problem now, but

should improve as the economies of these countries grow.

$ ✺ 

				
 
	



How Food Security Is Assessed

The commodity coverage in this report includes grains, root crops, and a group called “other.” The three commodity groups

in total, account for 100 percent of all calories consumed in the study countries. This report projects food consumption and

access in 67 lower income developing countries: 37 in Sub-Saharan Africa, 4 in North Africa, 11 in Latin America and the

Caribbean, 10 in Asia, and 5 in the NIS (see app. 1 for a detailed description of the methodology and app. 2 for a list of

countries). The projections are based on 1997-99 data. The periods covered are 2000, 2005 (5 years out), and 2010 (10

years out). Projections of food gaps for the countries through 2010 are based on differences between consumption targets

and estimates of food availability, which is domestic supply (production plus commercial imports) minus nonfood use. The

estimated gaps are used to evaluate food security of the countries.

The food gaps are calculated using two consumption targets: (1) maintaining base per capita consumption or status quo

(SQ), which is the amount of food needed to support 1997-99 levels of per capita consumption, and (2) meeting nutritional

requirements (NR), which is the gap between available food and food needed to support a minimum per capita nutritional

standard (for definitions of terms used see “Methodology” in app. 1). Comparison of the two measures either for countries,

regions, or the aggregate, indicates the two different aspects of food security: consumption stability and meeting the nutritional standard. 

The aggregate food availability projections do not take into account food insecurity problems due to food distribution difficulties within a country. Although lack of data is a major problem, an attempt was made in this report to project food consumption by different income groups based on income distribution data for each country. The concept of the income-consumption relationship was used to allocate the projected level of food availability among different income groups. The estimated “distribution gap” measures the food needed to raise food consumption of each income quintile to the minimum

nutritional requirement. Finally, based on the projected population, the number of people who cannot meet their nutritional

requirements is projected. 

The following common terms are used in the reports: domestic food supply, which is the sum of domestic production and

commercial imports; food availability, which is food supply minus nonfood use such as feed and waste; import

dependency, which is the ratio of food imports to food supply; and food consumption, which is equal to food availability.
*+#*#	

Depending upon the future availability of food aid, a portion

or all of the projected food gaps can be eliminated. For

example, in 1999 roughly 11.9 million tons of food aid were

distributed globally (fig. 3). If the same amount were provided in 2000, it would fill the entire calculated gap to maintain per capita consumption (status quo) and about 66 percent of the nutritional gap. However, all of the available food

aid is not going to low-income, food-deficit countries. In

1999, only 7.5 million tons, or 63 percent of total food aid

were given to the countries studied in this report, and the aid

would cover about 40 percent of their estimated nutritional

gap in 2000. 

Food aid shipments for 1999 grew significantly from the

1996 level of 6.6 million tons. The main source of the hike

in donations was the United States, while the European

Union and Japan reduced their allocations. Although the

amount of food aid donations was virtually unchanged from

1998 to 1999, allocations to the study countries declined by

20 percent. Allocations to Asian and Latin American countries declined, while those to Sub-Saharan countries

remained roughly the same at 2.8 million tons. 

Allocations of available food aid are not necessarily based

on nutritional needs. Other factors such as political instability leading to the collapse of internal marketing systems and

financial difficulties that disrupt commercial imports can

play an important role in food aid allocations among countries. For example, in 1999, the bulk of the increase in U.S.

food aid was allocated to Russia. In 1998, Indonesia was the

third largest recipient of food aid after Bangladesh because

of serious food deficits caused by the financial crisis and

internal problems. The share of food aid going to SubSaharan Africa—the most food insecure region according to


	

 

				


✺ %

1990 91 92 93 94 95 96 97 98 99

0

2

4

6

8

10

12

14

16

18

1990 91 92 93 94 95 96 97 98 99

0

2

4

6

8

10

12

14

16

18

Figure 3

Food aid: Donors and recipients

Food aid donors

Million tons

Food aid recipients

Million tons

Japan

United States

Canada

Other

EU

Asia Dvng

LAC

Other

SSA
our estimates—was only 24 percent in 1999. If this level of

food aid is continued, it will cover only 23 percent of the

estimated nutritional gap for the region in 2000.

0#1'
#	

*	#*#

In many low-income countries, increases in agricultural output mainly have stemmed from area expansion. In SubSaharan Africa, area expansion accounted for more than 80

percent of grain output growth between 1980-99. This

means that yield growth contributed to less than 20 percent

of the growth. In Latin America, area expansion accounted

for 68 percent of the growth in grain production. In Asia, the

reverse was true—area expansion accounted for less than 5

percent of the growth in grain output. 

The long-term prospects for acreage expansion are not

bright, because, in most countries, a large part of land that

could be used for farming is unfit to cultivate without major

investment. In Latin America and Sub-Saharan Africa, continued expansion of cropland means converting range and

forestland to crop production, a process with high economic

and environmental costs. According to FAO estimates, about

half of the land that could be used to produce food in SubSaharan Africa has poor quality soil. Sub-Saharan Africa has

a vast and diverse land area, but the region faces a number

of resource constraints (such as lack of water) to sustainable

agricultural growth. 

Land quality as defined by soil quality, climate, and rainfall

is a crucial factor determining agricultural productivity, as is

discussed in more detail in the special article “Resource

Quality, Agricultural Productivity, and Food Security in

Developing Countries.” Cross-country analysis confirms that

low quality in cropland is significantly associated with low

agricultural productivity. Loss of land available to agriculture—due to land degradation or expansion of urban areas—

is a reality in many areas, especially in developing coun-

 ✺ 

				
 
	



North Africa Sub-Saharan Africa Asia Latin America & Caribbean New Independent 

States

0

5

10

15

20

25

North Africa Sub-Saharan Africa Asia Latin America & Caribbean New Independent 

States

0

5

10

15

20

25

Status quo gap in 2010

Nutritional gap in 2010

Figure 4

Food gaps by region

Million tons

Million tons

Base scenario Reduced area scenario
tries. While new technology has been successful in providing data on the existing quality of land, limited data are

available on changes of land quality over time. In the

absence of precise projections, we analyze a scenario where

area expansion is half the rate used in the base model for

Sub-Saharan Africa, Latin America, NIS, and North Africa.

In Asia, where annual area growth between 1980 and 1999

was less than 0.1 of a percent, we assumed area to remain

constant during the entire projection period. 

In Sub-Saharan Africa, production in the baseline scenario

was projected to grow at a rate of 2.1 percent per year;

under the reduced area growth scenario, this rate is projected to fall to 1.7 percent. As a result of the slower production growth, the region’s nutritional gap in 2010 jumps

by 34 percent to more than 22 million tons (fig. 4). In other

regions, the cut in area is much less significant either

because of high import capacity such as the case of North

Africa or potential for yields to be the main contributor to

production growth, i.e. Asia. 

The results indicate that for food-insecure countries, in particular countries in Sub-Saharan Africa, the only option to

sustain production growth is to increase yields. Yields highly

depend on the use of improved inputs. Data show that SubSaharan Africa has the lowest labor productivity and that it

is declining. Similarly, the region’s fertilizer use is the lowest and on a declining trend. Even with an increase in fertilizer use, yields may not increase much. A cross-country

estimate for developing countries showed that a 1-percent

increase in fertilizer use results only in a 0.1- to 0.3-percent

increase in yield. The principal factor limiting yield

response to fertilizer use is the inadequate supply of water

during the growing season. Irrigation can be a solution, but

is too costly and in Sub-Saharan Africa only 4.2 percent of

cropland is irrigated. Although water availability varies considerably across regions, it has been a serious problem in

many countries. In addition, the agricultural sector consumes over half of the fresh water in most countries and

could face increased competing demands from urban consumers and industrial uses in the future. 

Overall, farm management practices, in particular improved

efficiency in the use of water, can be the first step to

improving food security in the vulnerable countries. To

increase yields, high-yielding varieties appropriate for specific agroclimatic conditions are essential. The success,

however, depends on the investment in supportive institutions for research and extension to diffuse the new varieties

to farmers. For the resource-poor countries, the long-term

strategy should aim at diversifying the sources of income of

the farmers. In these countries, the agricultural sector alone

cannot generate adequate incomes and food to support their

growing populations. Policies to promote rural development

not only would improve income distribution, they would

allow the poor the means to buy the food they need and

would also reduce pressure on land. 

%

Cleaver, Kevin, Gotz Schreiber. Reversing the Spiral: The

Population, Agricultural, and Environment Nexus in SubSaharan Africa. Washington, DC: The World Bank, 1994.

Delgado, Christopher. “Africa’s Changing Agricultural

Development Strategies: Past and Present Paradigms as

a Guide to the Future.” Washington, DC: IFPRI, 1995.

Harold, Courtney; Bruce Larson; Linda Scott. “Fertilizer

Consumption Remains Low,” International Agricultural

and Trade Reports: Africa and Middle East Situation and

Outlook Series, WRS-94-3; U.S. Dept. of Agri., Econ.

Res. Ser., 1994.

Ingram, Kevin; George Frisvold. “Productivity in African

Agriculture: Sources of Growth and Stagnation,”

International Agricultural and Trade Reports: Africa and

Middle East Situation and Outlook Series. WRS-94-3;

U.S. Dept. of Agri., Econ. Res. Ser., 1994. 

Rosegrant, Mark L. “Water Resources in the twenty-first

Century: Challenges and Implications for Action.”

Washington, DC: International Food Policy Research

Institute, 1997. 

Seckler, D.; D. Gollin; P. Antoine. Agricultural Potential of

“Mid-Africa”: A Technological Assessment. World Bank

Discussion Papers 126, Washington, DC, 1991.

United Nations, Food and Agriculture Organization.

Agriculture: Towards 2010. Rome, 1993.

Wiebe, Keith D.; Meredith J. Soule; David E.

Schimmelpfennig. “Agricultural Productivity and Food

Security in Sub-Saharan Africa.” Food Security

Assessment, GFA-10; U.S. Dept. of Agri., Econ. Res.

Ser., 1999. 


	

 

				


✺ 
Algeria, Morocco, and Tunisia have experienced a serious

drought in 2000 leading to production deviations that

range from 48 percent to 64 percent below trend. In the

case of Morocco, a country with one of the highest levels

of production variability in the world, the shortfall is even

more severe than last year’s deficit, compounding a 

difficult situation. 

These significant production shocks translate into relatively

modest food gaps. All of these countries are middle income

countries with relatively high per capita consumption levels

compared to other countries in this report. Tunisia had the

smallest shock and appears able to compensate for the shortfall with commercial imports. For Morocco, there is no food

gap in 2000 based upon recent per capita consumption

trends, but there is a nutrition-based food gap of 1 million

tons. Morocco represents an extreme case in which the

recent per capita consumption target can change dramatically

each year. Because of last year’s drought, the per capita consumption target—a 3-year moving average—dropped from

398 kg/cap to 241 kg/cap. Given this lower consumption target, assuming trend level of commercial imports, the target

can be met despite the second year of drought. Using last

year’s consumption target (i.e. average consumption of the

years 1996-98) would translate into a food gap of 4.1 million

tons under the same assumptions.

Algeria shows a food gap of 361,000 tons to maintain recent

per capita consumption levels and a food gap of 518,000

tons to meet nutritional requirements. However, these gaps

will probably be fully met this year because of Algeria’s

expected windfall in oil and gas export revenues from high

world prices, which will allow for higher imports. Analysis

of the ratio of food import costs to export revenues suggests

that even an above-average level of imports could be easily

afforded compared with many previous years.

Analyzing the distribution of food consumption, the lower

income groups in Algeria are the most vulnerable in the short

and longrun: the four lowest income quintiles are projected

not to meet minimum nutrition requirements, both in 2000

and 2010. For Morocco, the impact of the consecutive

droughts in 1999 and 2000 is such that all income groups are

projected to be unable to meet nutrition requirements in 2000.

However, by 2010, this situation should be turned around

with all income groups meeting these requirements. In Egypt

and Tunisia, all income groups are estimated to have nutritionally adequate food supplies in both 2000 and 2010.

The four countries in North Africa examined in this report

will continue to face limited land and water resources and

become more reliant on food imports over time. The primary economic question is whether they will be able to

afford these imports to sustain their current consumption

levels (holding aside the issue of production volatility).

However, another question is, would food gaps develop if

area expansion were constrained?

For the first question, only Algeria is projected to show 

longrun food gaps (718,000 tons by 2010 to maintain current

per capita consumption levels, which is about 7 percent of

total food supplies). This is a somewhat tenuous projection in

the case of Algeria, given its high dependency on oil and gas

revenues, because of the great uncertainty of petroleum

prices. If oil prices are sustained at recent levels, these food

gaps could easily be eliminated. As for the second question,

assuming that crop land grows half as rapidly, the gaps only

increase for Algeria, and even then only slightly (up to

758,000 tons by 2010). This can be explained by the small

impact that crop land growth has in the base case (less than 1

percent growth per year, which is reduced to 0.5 percent

growth in the modified scenario). A similar explanation

applies to the other North African countries in this report. 

 ✺ 

				
 
	



North Africa


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✺ 

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grains) of all food

---1,000 tons ---

1991 26,890 1,162 13,254 1,345 39,211

1992 20,765 1,085 15,109 831 38,740

1993 19,082 1,053 16,854 418 39,804

1994 24,645 945 19,131 239 41,955

1995 19,881 1,353 19,739 221 46,839

1996 33,267 1,465 16,312 190 44,178

1997 22,439 1,192 20,565 94 46,340

1998 26,699 1,261 21,745 50 45,769

1999 24,449 1,211 21,895 63 49,071

Projections Food gap

SQ NR (w/o food aid)

2000 20,628 1,277 22,274 361 1,563 43,701

2005 27,752 1,396 22,686 180 354 50,858

2010 30,492 1,521 24,039 718 909 55,071

Table 3--Food availability and food gaps for North Africa

North Africa

138 million people in 2000

A second year of drought in North

Africa has severely reduced 

production. Morocco could face 

the most severe nutritional food

gaps. Algeria shows modest food

gaps, but may avoid them due to

imports financed by rising oil and

gas prices.

Food supplies for the lowest

income groups in Algeria and

Morocco may not be adequate in

2000, but should be sufficient in

the long run.

Algeria is the only country in the

region to face longrun food gaps,

but this will depend on oil and gas

price projections.

North Africa's production shocks have

led to differently sized food gaps

Nutrition gap Status quo gap Production shock

Tunisia

Morocco

Algeria

-80 -60 -40 -20 0

Percent of target/trend

North Africa: Land use

Change (ha per capita) Annual rate of

Region/ Share of cropland Arable land in arable land between change in

country irrigated 1995-97 1979-81 and 1995-97 deforestation

1979-81 1995-97 1990-95

Percent Hectare per capita Percent

North Africa 52.2 52.7 0.18 -20 0.9

Algeria 3.4 6.9 .26 -30 1.2

Egypt 100.0 99.8 .05 -17 .0

Morocco 15.2 13.1 .33 -13 .3

Tunisia 4.9 7.6 .32 -37 .5

* Aggregate for Middle East and North Africa.

Source: World Development Report 2000/2001, World Bank.

*

North Africa's grain output variability is

relatively high

Coefficient of variation, percent, 1980-99

North Africa

S.S. Africa

Asia

Latin America

NIS

0 10 20 30 40
Food security in Sub-Saharan Africa is almost entirely

dependent on domestic production. Imports, as a share of

the region’s total food supplies, averaged around 10 percent

in the late 1990s despite strong growth in commercial

imports. The food aid share of imports peaked in the late

1980s at roughly 40 percent. In more recent years, that share

has averaged less than 20 percent of imports.

Sub-Saharan Africa’s agricultural productivity—as measured

by output relative to agricultural land area—has accelerated

over time. Between 1990-98, this productivity indicator rose

2.3 percent per year. This compares quite favorably to the

success stories among the East and Southeast Asian countries

where growth measured just under 2.5 percent during the

same time period. However, Sub-Saharan Africa’s population

growth averaged 2.7 percent per year since 1990, meaning

that productivity declined on a per capita basis. Moreover,

the region’s absolute level of productivity measured only

about 65 percent of that of the Asian countries. This low

level of productivity is directly attributable to low input use.

Fertilizer use, the lowest rates in the world, actually declined

between 1990 and 1998. Irrigated area as a share of total

agricultural area stagnated during the 1990s and measured

only about 3 percent in 1998. In Latin America, this share

exceeded 11 percent and in Asia 20 percent.

Nearly 90 percent of the region’s historical grain production

growth stemmed from area expansion. This trend is not

expected to continue in the future, as much of the region’s

remaining land area is marginal for agricultural purposes. 

Production growth during the next decade is projected to fall

short of historical rates and average 2.1 percent per year. To

close the nutritional food gap, production would need to rise

2.9 percent per year. Given the region’s limitations to

expanding land area, achieving this growth rate would

require investment in research and extension activities,

improved infrastructure, and increased input use. Similar to

the historical period, imports will not be a significant factor

in the food security equation. Commercial imports are projected to account for less than 8 percent of food supplies in

2010 as slow export earnings growth is expected to constrain import capacity. Food aid allocations to the region

may rise, but that has not been the case in recent years.

Political and financial instability have been deciding factors

in global food aid allocations. Sub-Saharan Africa, the most

vulnerable region according to our analysis, received only a

quarter of global food aid in 1999.

This slow production and import growth is expected to

result in a continuation in the declining trend in per capita

consumption. Of the 37 countries in the region, per capita

consumption is projected to rise in only 7 countries—

Ethiopia, Kenya, Sudan, Mozambique, Zimbabwe, Chad,

and Togo. Even in these countries, the growth is not

expected to be particularly strong. For example, Sudan is

expected to experience the highest growth, but still only 1.4

percent per year. For Sudan, growth in grain output is not

projected to match that of the historical period, but it will

still outpace population growth by more than 1 percent per

year. The same is true for Ethiopia and Mozambique. Slow

population growth projections, due to the HIV/AIDS epidemic, is the primary factor behind the positive per capita

consumption growth as production growth is projected to be

quite slow—even falling short of the regional average. For

Kenya, Chad, and Togo, the growth is negligible.

The region’s food gap to maintain consumption is projected

to rise about 65 percent during the next 10 years to 8.3 million tons in 2010. The nutritional food gap is projected to

increase 40 percent, nearing 17 million tons in 2010. In

other words, the region would need more than two times the

amount of food to achieve nutritionally adequate diets as

compared with simply maintaining the recent standard. The

region’s nutritional gap is estimated to account for 65 percent of the nutritional gap for the 67 countries in total in

2000. This number is projected to jump to 76 percent in

2010. The region accounts for only 24 percent of the population of the 67 countries, thus indicating the severity of the

region’s food security situation. 

The situation appears even more desperate when examining

projected consumption by income group. The distribution

gap—the amount of food needed to raise consumption in

each income group to the nutritional target—is projected to

increase 40 percent during the next decade, reaching almost

23 million tons in 2010. At the same time, the number of

people in the region consuming inadequate diets is projected

to rise 25 percent during the next decade. The fact that this

gap is projected to rise at a faster rate than the number of

 ✺ 

				
 
	



Sub-Saharan Africa (SSA)

)*	




 	
	




	



	



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✺ !

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grains) of all food

---1,000 tons ---

1991 59,185 35,394 5,262 5,140 113,750

1992 57,345 36,993 6,858 5,514 124,658

1993 61,108 39,479 7,717 3,236 125,908

1994 64,401 39,768 7,864 3,295 130,818

1995 64,872 41,029 7,179 2,269 137,916

1996 69,804 41,542 7,526 1,846 137,016

1997 63,597 40,945 9,860 2,140 136,878

1998 69,295 44,772 11,940 2,598 148,628

1999 68,792 45,763 10,466 1,700 148,117

Projections Food gap

SQ NR (w/o food aid)

2000 69,734 45,600 11,152 3,287 10,999 147,217

2005 81,354 49,996 11,344 4,687 12,812 165,527

2010 90,756 54,753 12,055 8,295 16,574 182,620

Table 4--Food availability and food gaps for Sub-Saharan Africa

Sub-Saharan Africa

589 million people in 2000.

Only 7 of the 37 countries are 

projected to have rising per capita

consumption trends through the

next decade.

While Sub-Saharan Africa will have

only 24 percent of the population

of the study countries in 2010, it 

is projected to account for 76 

percent of the total nutrition gap.

Sixty percent of the region's 

population is projected to consume

at levels below the minimum 

nutritional requirement in 2010.

2000 2005 2010

0

5

10

15

20

25

Slow area growth scenario

Baseline

Nutritional food gap in Sub-Saharan Africa

Mil. tons

Sub-Saharan Africa: Land use

Change (ha per capita) Annual rate of

Region/ Share of cropland Arable land in arable land between change in

country irrigated 1995-97 1979-81 and 1995-97 deforestation

1979-81 1995-97 1990-95

Percent Hectare per capita Percent

SSA

Kenya 0.9 1.5 0.14 -39 0.3

Rwanda .4 .3 .12 -20 .2

Angola 2.2 2.1 .27 -34 1.0

Madagascar 21.5 35.0 .19 -32 .8

Mozambique 2.1 3.4 .18 -25 .7

Congo, Dem. Rep. .1 .1 .15 -40 --

Source: World Development Report 2000/2001, World Bank.

2010

2005

2000

0 25 50 75 100 125 150

Nutritional gap as share of imports

Percent
hungry people is an indicator that the food security problems in this region will not only spread, they will intensify.

In 2010, consumption for 60 percent of the region’s population is projected to fall short of nutritional requirements. In

addition, the region is projected to account for nearly twothirds of the hungry people in the 67 countries, while

accounting for only 24 percent of the total population (see

fig. 2 in the Overview). 

Given the region’s land constraints, we ran a scenario of

reduced area growth. In the base scenario, agricultural area

was projected to rise 1.2 percent per year. For the scenario,

this growth was cut in half. As a result of these changes, the

nutritional gap is projected at more than 22 million tons—

30 percent above that under the base scenario (see fig. 4 in

the Overview). Given the precarious food security position

of the region, the implications of lower domestic production

growth rates are particularly acute for the lower income

groups. The number of people with inadequate diets jumps

15 percent relative to the base scenario to 435 million as

consumption in only the highest income group is projected

to exceed the minimum nutritional requirement. 

While policy reform in the region has had some positive

effects (i.e., market-determined prices, private sector

involvement in food marketing), there is considerable room

for improvement. Investment is needed to improve rural

infrastructure to facilitate the transport of agricultural inputs

and products. Policies are needed to promote the continued

participation of the private sector in distributing inputs and

marketing output. The HIV/AIDS crisis, which has already

reduced the supply and productivity of labor in many countries, must be addressed through education efforts. Countries

in this region need to participate in international trade negotiations to improve their trade and market access.

The discussion of debt forgiveness within the international

community is welcome news for these countries and should

open opportunities for increased investment. Gross domestic

investment in the region declined from 23 percent of GDP

in 1980 to 18 percent in 1997. The new U.S. initiative—The

African Growth and Opportunity Act—was signed into law

on May 18, 2000. It provides preferential access to U.S.

markets for eligible products from designated countries

within the region as well as improved access to U.S. credit

and technical expertise. 

" ✺ 

				
 
	


The Asia region in this report includes Afghanistan,

Bangladesh, India, Indonesia, Nepal, the Democratic

People’s Republic of Korea (North Korea), Pakistan, the

Philippines, Sri Lanka, and Vietnam. Fewer people in the

region are expected to be hungry in 2010 than in 2000. The

aggregate food security situation for the region is projected

to improve during the next decade, as a larger number of

people will consume nutritionally adequate diets. The

region’s achievements in agricultural growth during the last

two decades were largely a result of rapid growth in input

use and productivity. Investment in public research and

extension, expansion of irrigated area, and improvements in

rural infrastructure and human capital contributed greatly to

the productivity growth. Concerns are growing, however, as

population growth is placing pressure on natural resources.

Already, nearly 80 percent of the region’s potentially arable

land is cultivated. In addition, there is increasing competition for water from household and industrial uses that will

invariably raise costs. 

Grain output in the region rose roughly 2.5 percent per year

during the historical period (1980-99) due to strong yield

growth. This growth was supported by steady increases in

irrigated land area and fertilizer use. In 1998, 36 percent of

the region’s cultivated land was irrigated—twice the world

average. Fertilizer use jumped more than 5 percent per year

and averaged 130 kilograms per hectare, roughly 10 percent

above the world average. The strong production growth,

coupled with rapid commercial import growth, resulted in

an increase in per capita consumption and will continue to

sustain it through the next decade. 

Improvements in food security are also reflected in food

consumption by income group. In 2000, consumption in all

income groups, with the exception of the lowest 20 percent,

is estimated to exceed the minimum nutritional requirement.

In 2000, 17 percent of the region’s population are estimated

to be hungry. By 2010, we project that this share will fall to

9 percent, or 177 million people. 

Most of the region’s improvements can be attributed to India

whose population of more than 1 billion is by far the largest

in the region and therefore influences the performance of the

region on the whole. Agricultural output per hectare, a measure of land productivity, grew at an annual rate of 3.3 percent—twice the U.S. and world average rates. This growth

was supported by high rates of input use. Roughly 35 percent

of cultivated land is irrigated, twice the world average. The

country is estimated to have no status quo or nutritional food

gaps in 2000. Per capita consumption is projected to continue its upward trend during the next decade, ensuring that

by 2010, consumption in all income groups, on average, will

exceed the nutritional requirement. However, within the lowest income group, there will be people who cannot afford to

purchase enough food for an adequate diet. 

Indonesia is beginning to recover from the international

financial crisis that hit in 1997 and continued through early

1999. The country’s real GDP declined nearly 14 percent in

1998 and a further 4 percent in 1999. The currency depreciation resulted in an inflation rate of 70 percent which, in

turn, led to a decline in consumption. For example, wheat

consumption declined 50 percent from the 1996 peak to

1998. Food aid shipments of 1 million tons in 1998 and

500,000 tons in 1999 were crucial in preventing famine. The

situation began to stabilize in 1999 and real GDP growth for

2000 is estimated at around 2 percent. The projections indicate that the country’s nutritional food requirements were

being met as of 1999 and that the food security situation is

expected to improve through the next decade. 

Political uncertainty makes projections for North Korea and

Afghanistan difficult. North Korea has been characterized

by a stagnating economy that has reduced both commercial

import capacity and the supply of agricultural inputs. Per

capita consumption fell 25 percent during the 1990s. North

Korea is estimated to account for a third of Asia’s nutritional

food gap in 2000. While the situation is projected to

improve, it is still desperate. By 2010, consumption in only

the top income group is expected to exceed the minimum

target, meaning that roughly 80 percent of the population

will have inadequate diets.

Afghanistan is estimated to account for the other two-thirds

of the region’s nutritional gap in 2000. Production, although

rebounding from the lowest points of the early 1990s, has

not recovered to the levels achieved in the 1980s. Per capita

consumption in 1999 was roughly half of the mid-1980s

level; it is projected to fall more than 1 percent per year

through 2010. Consumption will fall short of nutritional

requirements in all income groups; in even the highest


	

 

				


✺ #

Asia



/

	





	



	





	








.	


,---
2	
,-.-'



/

	

+


$%	1
&
income group consumption is projected at only 80 percent

of the nutritional target in 2010. 

Considering the land constraints facing the region—primarily attributable to population pressures—we ran a scenario

for Asia assuming zero area growth. In the base scenario,

total area was projected to rise 0.3 percent per year. Under

the reduced area scenario, consumption for 23 percent of the

population—or 459 million people—will fall short of the

nutritional requirement in 2010. In the base scenario, only 9

percent of the population was projected to consume an inadequate diet. The region’s per capita consumption growth is

cut by more than half—from 0.5 percent per year to 0.2 percent. While this lower area growth adversely affected all

countries in the region, the implications varied. For example, the food security position of Indonesia, Sri Lanka, and

Vietnam was so strong, that even with lower production

growth, nutritional requirements will continue to be met

across all income groups. Conversely, in India and Pakistan,

the drop in output results in inadequate diets for the lowest

income group. In Afghanistan and North Korea, even consumption in the top income group is projected to fall below

the nutritional target. Therefore, what seems to be a very

small change in one variable can have severe implications

for consumption, particularly for the poorest segments of the

population, in many countries in the region.

$ ✺ 

				
 
	



	

 

				


✺ %

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grains) of all food

---1,000 tons ---

1991 269,734 14,804 7,485 2,811 391,293

1992 280,809 15,669 11,461 1,769 399,324

1993 286,011 15,298 11,296 1,792 409,558

1994 289,925 15,431 10,971 1,942 418,601

1995 299,303 15,295 17,824 2,106 435,076

1996 303,206 16,016 15,899 1,722 445,101

1997 307,064 16,621 16,947 2,054 446,522

1998 316,929 14,916 15,220 4,193 450,664

1999 324,982 16,768 16,991 2,534 475,894

Projections Food gap

SQ NR (w/o food aid)

2000 330,470 16,616 17,403 2,627 2,925 479,938

2005 356,138 17,944 19,463 2,445 2,783 519,832

2010 386,322 19,362 22,699 3,218 3,454 566,771

Table 5--Food availability and food gaps for Asia

Asia

1,678 million people in 2000

By 2010, Asia's population—65

percent of the total of the 67 study

countries—is projected to account

for 17 percent of the nutritional

food deficit.

The share of the region's population consuming nutritionally inadequate diets is projected to fall from

an estimated 17 percent in 2000 to

9 percent in 2010.

Serious land constraints face 

the region. In a zero area growth

scenario, the region's per capita

consumption growth was cut in

half—from 0.5 percent per year 

to 0.2 percent.

Status quo gaps in selected Asian countries

Mil. tons

Nepal

North Korea

Afghanistan

0 0.5 1.0 1.5 2.0

2005

2010

2000

Asia: Land use

Change (ha per capita) Annual rate of

Region/ Share of cropland Arable land in arable land between change in

country irrigated 1995-97 1979-81 and 1995-97 deforestation

1979-81 1995-97 1990-95

Percent Hectare per capita Percent

Asia

Bangladesh 17.1 43.4 0.06 -40 0.8

India 22.8 32.4 .17 -29 .0

Indonesia 16.2 15.5 .09 -25 1.0

N. Korea 59.6 60.6 .04 -20 .2

Pakistan 72.7 80.8 .17 -29 2.9

Philippines 14.0 16.3 .07 -22 3.5

Source: World Development Report 2000/2001, World Bank.

2000 2005 2010

0

1,000

2,000

3,000

4,000

5,000

Zero area growth scenario

Baseline scenario

Status quo food gap in Asia

1,000 tons
Food security in most of the 11 countries in this region1 is

improving as increases in food production combined with

food imports will grow at a faster rate than population.

Regional per capita consumption is projected to increase

roughly 1 percent per year over the next 10 years. Despite

this positive trend there remain four countries with insufficient food supplies to meet consumption requirements. 

Compared to the 1999 projections, this year’s results show

considerably lower food gaps by the end of this decade,

thanks to a more optimistic economic outlook. The region is

expected to import almost half of its grain consumption.

High import dependency for staple foods means that the

financial situation of the countries will be a crucial factor in

maintaining food security. 

The nutritional food gap is projected to reach 900,000 tons

by 2010. This projection is 36 percent lower than last year’s

projection for 2009 which illustrates growing optimism for

the region based on agricultural and economic performance

in recent years.

At the country level, food insecurity continues to be of concern in Bolivia, Haiti, Honduras, and Nicaragua. Bolivia and

Honduras are projected to improve over time. Bolivia is

expected to eliminate its food gaps by 2005 if projected production increases can indeed be realized. Honduras is still

recovering from Hurricane Mitch, but is projected to raise

per capita consumption above the base level during the next

10 years. Despite this positive trend, hunger will still remain

a problem in Honduras where the nutritional gap is projected at 6 percent of total food availability in 2010. 

Haiti and Nicaragua, the two poorest countries in the Western

Hemisphere, have not been able to achieve adequate production to eliminate food gaps, which amount to one-third of

grain and root crop requirements. Commercial imports are not

expected to be able to compensate for the production shortfalls

because of insufficient foreign exchange. Both countries are

projected to rely on food aid receipts over the next decade.

While Haiti’s political deadlock offers little hope for dramatic economic improvements, Nicaragua has enjoyed

steady economic growth and fast increasing export earnings

of 11 percent annually for the last few years. However, the

country will need foreign investment to further expand its

export sectors. In December, Nicaragua will find out if it is

included in the Highly Indebted Poor Countries Initiative.

Criteria include good economic performance, improved governance and more openness. If Nicaragua qualifies for relief

on its debt of $6.3 billion it will be in a much better position

to improve infrastructure and attract international investors. 

Highly skewed income distribution remains the root cause

of food insecurity in the region. The size of the distribution

gap in 2000 is about 2.6 times the average nutrition gap.

The good news is, however, that an increase in food availability and economic prosperity is expected to improve the

food situation of the poor in the longrun. By 2010, the number of hungry people is projected to decline by 30 percent to

44 million and 2010 project the distribution gap projected to

decline slightly, by 4 percent. More than 80 percent of the

population of Haiti and Nicaragua is projected to fail to meet

their nutritional requirements by 2010. On the other hand,

Colombia, the Dominican Republic, Jamaica, and Peru are

expected to limit food deficits to less than 20 percent of their

populations.

The overall progress towards food security in the last two

decades was mainly due to improvements in the performance of the export sector. Production growth of the staple

food crops has been slow and most of the growth was due to

area expansion. This pattern of growth is not sustainable

over the next decade.While Latin America has the world’s

largest reserves of cultivable land—the agricultural potential

of the region is estimated at 576 million hectares—more

than half of this land has been adversely affected by land

degradation, mostly soil erosion, but also loss of nutrients. 

In order to examine the impact of resource constraints, in

particular land degradation, a scenario of slower area expansion was analyzed for all regions. Area growth in Latin

America and the Caribbean was assumed to be half the

baseline rate. In this scenario, the average nutritional food

gap increased by 30 percent and the status quo gap

increased by more than 50 percent relative to the baseline

scenario. In addition, the number of people vulnerable to

food insecurity would be higher. This means, again, that in

the absence of investment in improved technologies that

raise land productivity, food security in the poorer countries

will be critically dependent upon area expansion.

 ✺ 

				
 
	



Latin America and the Caribbean (LAC)

3

	





	


	
	


	






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1 The countries studied here are four Central American countries: El

Salvador, Guatemala, Honduras, and Nicaragua; three Caribbean countries:

the Dominican Republic, Haiti, and Jamaica; and four South American

countries: Bolivia, Colombia, Ecuador, and Peru.

	

 

				


✺ 

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grains) of all food

---1,000 tons ---

1991 9,575 2,468 4,308 1,828 27,608

1992 10,539 2,376 6,159 1,324 29,284

1993 11,036 2,723 6,052 1,371 29,153

1994 9,960 2,802 7,814 1,002 30,524

1995 10,088 2,970 8,619 520 31,861

1996 9,911 3,040 9,308 556 32,579

1997 9,736 3,028 10,145 476 32,572

1998 10,081 2,946 10,726 847 34,251

1999 10,625 3,369 10,611 493 35,148

Projections Food gap

SQ NR (w/o food aid)

2000 10,713 3,225 11,417 287 735 35,569

2005 11,465 3,508 13,260 286 726 39,964

2010 12,382 3,810 16,173 470 894 46,470

Table 6--Food availability and food gaps for Latin America and the Caribbean (LAC)

Latin America and the Caribbean

137 million people in 2000

Food security in the region is 

projected to improve over the next

10 years. Despite recent economic

difficulties in South America long

term projections indicate rising 

per capita consumption for 

most countries.

Haiti and Nicaragua, however, the

poorest countries in the region, do

not share this optimistic outlook.

Their situation is expected to

worsen unless drastic political and

infrastructural improvements can

be achieved.

2000 2005 2010

0

200

400

600

800

1,000

Status quo Nutritional gap

Food gaps in Latin America and the Caribbean

1,000 tons

Latin America and the Caribbean: Land use

Change (ha per capita) Annual rate of

Region/ Share of cropland Arable land in arable land between change in

country irrigated 1995-97 1979-81 and 1995-97 deforestation

1979-81 1995-97 1990-95

Percent Hectare per capita Percent

LAC 11.6 13.5 0.28 -13 0.6

Bolivia 6.6 4.1 .23 -34 1.2

Guatemala 5.0 6.6 .13 -32 2.0

Haiti 7.9 9.9 .08 -20 3.4

Honduras 4.1 3.6 .29 -34 2.3

Nicaragua 6.0 3.2 .54 -39 2.5

Source: World Development Report 2000/2001, World Bank.

LAC's grain supply

Mil. tons Tons/ha

1980 82 84 86 88 90 92 94 96 98

0

5

10

15

20

25

1.35

1.45

1.55

1.65

1.75

1.85

Yields (right axis)

Production

Total imports
Severe droughts in Georgia and Tajikistan in 2000 have

affected output and are estimated to lead to food gaps in

these countries. Based upon recent per capita consumption

levels, the food gap in Georgia is estimated to be 68,000

tons (7 percent of total supplies) and 208,000 tons in

Tajikistan (15 percent of total food supplies). Using a nutrition standard, the food gaps are estimated to be 242,000

tons and 253,000 tons, respectively (21 percent and 17 percent of total supplies). Of the five NIS countries examined

in this report, only Tajikistan is projected to have longrun

food gaps (the nutrition-based food gap is projected at

70,000 tons by 2010, 4 percent of supplies). 

Over the last 10-15 years, one common pattern among these

five countries is that area sown has increased, especially

after independence, offsetting declining yields. In many

transition economies, yields declined after subsidies on

inputs like fertilizer and plant protection agents were

removed and their application levels declined. Future projections assume that the growth in land sown will slow (from

3-4 percent per year to 1-2 percent per year) and that yields

will resume moderately positive growth rates ranging from

0.6 percent to 1.0 percent per year. The assumption about

yield growth may be too optimistic, which may possibly

understate future food gaps. Of course, any resumption of

hostilities would dramatically affect these projections.

With the exception of Kyrgyzstan, these NIS countries depend

on imports for a sizeable share of their total food supplies

(ranging from about 30 percent to 60 percent). The share of

imports in total food supplies is expected to increase. To

finance these imports, these five countries will need to show

steady growth in real export earnings. These countries’ trade is

highly open compared with many regions around the world.

However, these five countries continue to depend on Russia

and other former Soviet republics for trade (ranging from 40

percent to 80 percent of exports in 1999). After the Russian

ruble devaluation in 1998, several of these countries devalued

their own currencies to stay competitive, forcing a short-term

contraction in imports and economic growth. Preliminary data

suggest that the devaluation stimulated domestic output in

Russia and the other NIS countries, which in the medium term

may indirectly improve these countries’ economies. 

The World Bank has projected that overall real GDP growth

in the transition economies will average about 5 percent per

year in the coming decade. Azerbaijan in particular is projected to grow quite rapidly. Over the past year, there have

been a few key developments regarding the oil and gas sector in this region. A new oil pipeline went online connecting

Baku, Azerbaijan, to Suspa, Georgia, on the Black Sea. A

pipeline agreement was signed by Azerbaijan, Georgia, and

Turkey that will allow oil to be delivered from Baku to the

Mediterranean port of Ceyhan, Turkey, within 3 years.

However, the economic viability of this deal remains questionable and may be determined by external oil and gas

developments in several neighboring countries.

Except for Tajikistan, recent national average per capita consumption levels in these NIS countries have been above

nutrition requirements. In Azerbaijan and Kyrgyzstan, all

income groups are estimated to have adequate food supplies

in the short and longrun to meet the minimum nutritional

requirements. Although Georgia’s recent national average

per capita consumption level exceeds nutrition requirements,

the 2000 drought has led to projections in which food supplies are nutritionally inadequate for each quintile group.

However, this problem is expected to be resolved within a

few years as production recovers. In Armenia, the two lowest income quintiles in 2000 are estimated to have inadequate food supplies to sustain minimum nutrition levels.

However, by 2010, all income groups in Armenia are projected to have nutritionally adequate food supplies. 

In Tajikistan, the recent national average per capita consumption levels are below nutrition requirements by about 5

percentage points. In 2000, every quintile group is projected

to fall below nutrition requirements. This situation should

improve slightly by 2010 with the top income quintile

reaching the nutritional requirement. 

We considered a scenario that hypothetically examined the

effect of land degradation, assuming that the growth in land

area is cut in half. Under this scenario, only Tajikistan

would display food gaps. To maintain recent per capita food

consumption levels, the gap would increase from 58,000

tons in 2010 in the base case to 67,000 tons; nutrition-based

food gaps would increase from 70,000 tons to 118,000 tons.

These relatively small changes in the food gaps reflect the

already low growth rates assumed for future land area sown. 

 ✺ 

				
 
	



New Independent States (NIS)

5

6


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7


	



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✺ 

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grains) of all food

---1,000 tons ---

1991 3,814 --- --- --- ---

1992 3,805 --- 2,885 --- ---

1993 3,535 246 1,889 1,159 6,556

1994 2,928 250 843 1,526 6,267

1995 2,822 291 728 1,097 6,101

1996 3,895 322 1,100 381 6,248

1997 4,621 337 1,507 573 7,422

1998 4,147 375 1,639 158 7,154

1999 4,245 442 1,395 277 7,210

Projections Food gap

SQ NR (w/o food aid)

2000 3,298 404 1,623 426 832 6,216

2005 5,107 449 1,645 0 243 8,227

2010 5,482 498 1,746 0 285 8,862

Table 7--Food availability and food gaps for New Independent States (NIS)

NIS

27 million people in 2000

This year's drought has affected

output in several countries.

Shortrun food gaps may occur in

four countries. The most severe

gaps will be in Armenia and

Tajikistan, which already faced

food consumption levels that were

low in absolute terms. Tajikistan is

the only country in the region to

face longrun food gaps.

Almost all income groups may

have inadequate access to food in

Armenia and Georgia in 2000, but

this situation should improve with

time. In Tajikistan, access will

remain a problem.

NIS production shocks in 2000 translate into

differently sized food gaps

Nutrition gap Status quo gap Production shock

Tajikistan

Georgia

Azerbaijan

Armenia

-50 -40 -30 -20 -10 0

Percent of target/trend

New Independent States: Land use

Annual rate of

Region/ Share of cropland Arable land change in

country irrigated 1995-97 deforestation

1975-97 1990-95

Percent Hectare per capita Percent

NIS 67.0 0.18 0.1

Armenia 51.5 .13 -2.7

Azerbaijan 74.9 .21 .0

Georgia 43.3 .14 .0

Kyrgyzstan 77.3 .29 .0

Tajikistan 79.7 .13 .0

* Aggregate for Europe and Central Asia.

Source: World Development Report 2000/2001, World Bank.

*

NIS countries have increased area sown but

yields declined in the 1990s

Area Yield

Percent

Tajikistan

Kyrgyzstan

Georgia

Azerbaijan

Armenia

-6 -4 -2 0 2 4 6 8
%2#
#*	#




Sustained growth in agricultural productivity is critical to

improving food security for two reasons. First, growth in

agricultural productivity translates into increased food supplies and lower food prices for consumers. Second, growth

in agricultural productivity means higher incomes and thus

improved ability to purchase food and other basic necessities, for many food-insecure people who earn their livelihoods through agricultural production.

Agricultural productivity depends in turn on a variety of factors. Recent studies (e.g. Craig, Pardey, and Roseboom,

1997, and Frisvold and Ingram, 1995) indicate that most differences in agricultural productivity, whether across households or countries or over time, can be attributed to differences in the quantity of conventional inputs used in agricultural production, such as land, labor, fertilizer, and machinery. But agricultural productivity also depends critically on

the quality of inputs used, including the quality of natural

resources such as land. As simple as this statement seems,

the influence of resource quality on agricultural productivity

has received insufficient attention in the past because appropriate data have been scarce. However, recent advances in

data and analytical methods (see box, “Data and Methods”)

allow improved understanding of the ways in which agricultural productivity and food security are affected by differences in the quality of resources. Distinguishing the relative

impacts of input quantity and quality is important in determining appropriate policy measures to improve agricultural

productivity and food security.

#0#

Land—embodying soils, climate, and other characteristics—

is one of the most basic resources used in agricultural production. Figure A-1 illustrates global differences in land

quality, based on assessments by USDA’s Natural Resources

Conservation Service of the suitability of soils and climate

for agricultural production. Extensive areas of high-quality

land are evident in North America and Europe. Land is of

lower quality, on average, in Latin America, Asia, and SubSaharan Africa, and is poorest of all in North Africa, the

Middle East, and Central Asia. 

Figure A-2 illustrates global differences in average annual

rainfall. Rainfall may be more equitably distributed on a

global scale than is high-quality land, but substantial variations remain within regions and countries. Latin America

receives abundant rainfall, on average, with the exception of

northern Mexico, northeastern Brazil, and the western coast

of South America. Western and central Africa receive more

rain than northern, eastern, and southern parts of the continent, while southeast Asia and adjoining areas receive more

rain than northern and western portions of India and China.

 ✺ 

				
 
	



	


Resource Quality, Agricultural Productivity, and 

Food Security in Developing Countries

Keith Wiebe and Abebayehu Tegene1

Abstract: Raising agricultural productivity improves food security both through increased

incomes for farmers and through increased food supplies for consumers. Productivity

depends in turn on a variety of factors, including the quantities of fertilizer, water, and other

inputs used in agricultural production. Recent advances in data and analysis show how productivity also depends critically on the quality of inputs used, including the quality of natural resources such as land. Within Sub-Saharan Africa, the productivity of agricultural land is

found to be 28 percent higher in countries with favorable soils and climate than it is in countries with poor land quality, everything else being equal, and in Asia the difference is 34 percent. Productivity is especially responsive to increases in the use of fertilizer and irrigation

in countries with poor land, while productivity in countries with good land is more responsive to improvements in labor quality and transportation infrastructure. Reductions in the

incidence of armed conflict are important in both sets of countries.

Keywords: land quality, agricultural productivity, food security.

1 Agricultural economists with the Resource Economics Division,

Economic Research Service, USDA.

	

 

				


✺ !

Figure A-1

Global land quality

Note: Land quality class 1 represents the land most suitable for agricultural production, i.e. having

the fewest inherent soil and climate constraints.

Source: NRCS/USDA.

Figure A-2

Global mean precipitation, 1961-96

Source: Climatic Research Unit, University of East Anglia.
Poor soils and climate do not make agricultural production

impossible, but they do mean that costs of production are

likely to be higher and/or that yields and net returns are

likely to be lower than they would be under more favorable

conditions. (In other words, agricultural productivity is

likely to be lower.) Figure A-3 illustrates where crop production actually dominates the landscape, based in part on

land quality and rainfall patterns, along with other physical

and economic characteristics. Large concentrations occur in

North America, Europe, India, China, Brazil, and Argentina;

cropland is more sparsely distributed in Africa and the

Middle East.

Combining this information on soils, climate, and land cover

allows us to compare the quality of cropland by country and

region. While the quality of all land is, on average, lowest in

the Middle East and North Africa, the quality of cropland is

lowest in Sub-Saharan Africa. In 12 of 38 Sub-Saharan

African countries studied, less than 1 percent of cropland is

classified in the top three land-quality classes, and the

median share of cropland that is classified in the top three

land-quality classes in Sub-Saharan African countries is

about 6 percent (fig.A- 4). This compares with a median of

16 percent in Asia (where 7 of 17 countries studied have

more than a quarter of their land in the top three classes), 19

percent in the Middle East and North Africa (where 3 of 8

countries studied have more than a quarter of their land in

the top three classes, and 27 percent in Latin America

(where 12 of 19 countries studied have more than a quarter

of their land in the top three classes). By contrast, the

median share of high-quality cropland was 29 percent in the

high-income countries, as defined by the World Bank

(where 13 of 22 countries studied have more than a quarter

of their land in the top three classes) and over 50 percent in

Eastern Europe (where all six countries studied have more

than a quarter of their cropland in the top three classes).

Not surprisingly, econometric analysis of 110 countries during 1961-97 (see box, “Data and Methods”) reveals that

after taking into account other factors such as input levels,

differences in the quality of cropland soils and climate are

significantly related to differences in agricultural productivity. Within Sub-Saharan Africa, the productivity of agricultural land is 28 percent higher, on average, in countries with

high land quality than it is in countries with poor land quality. The productivity difference attributable to high land

quality is 34 percent in Asia, and 22 percent in the highincome countries. (In Latin America, where most countries

lie above the global median in terms of land quality, only

the best soils and climate are significantly associated with

increased agricultural productivity.)

These findings confirm our expectations and provide for the

first time an empirical estimate of the significance that differences in the inherent physical quality of soils and climate

have on agricultural productivity. Perhaps more important,

however, are the insights they provide into the impact on

agricultural productivity of more conventional inputs, such

as quantities of land, labor, fertilizer, and machinery.

" ✺ 

				
 
	



Figure A-3

Global distribution of cropland

Source: USGS/UNL/JRC Global Land Cover Characterization.

	

 

				


✺ #

0#
#"#

To capture these impacts, we included in our econometric

analysis country-level measures of conventional agricultural

inputs like agricultural land, labor, tractors, livestock, and

fertilizer. We also included factors such as annual rainfall on

cropland, the percentage of each country’s agricultural land

that is classified as arable land or permanent cropland, the

percentage of arable land or permanent cropland land that is

not irrigated, life expectancy and illiteracy rates (as measures of labor quality), an indicator of the occurrence of

armed conflict (as a measure of institutional stability), and

road density and cumulative agricultural research and development expenditures (as measures of infrastructure). (Data

on agricultural research and development expenditures were

available only for 1961 through 1985, but they revealed a

significant and positive association with agricultural productivity during that time.)

Within each region, countries were classified according to

the share of their cropland that is highly suitable for agricultural production (see box, “Data and Methods”). Countries

where this share exceeds the median value for their region

were identified as having good soils and climate; those with

less than the median were identified as having poor soils

and climate. Each group of countries was then analyzed separately to compare the impacts of individual factors on agricultural productivity by region and land-quality class.

In Sub-Saharan African countries with good soils and climate, agricultural land productivity rises significantly with

increases in quantities of labor, livestock, tractors, fertilizer,

and annual rainfall. Productivity also improves with irrigation, labor quality (in the form of longer life expectancy and

higher literacy rates), and transportation infrastucture and

falls significantly with the occurrence of armed conflict. In

Sub-Saharan African countries with poor soils and climate,

productivity responds even more strongly to fertilizer application, irrigation, and political instability, but it is not sensitive to improvements in tractors, labor quality, or infrastructure. Overall, the results suggest a land quality-related hierarchy of constraints limiting agricultural productivity in

Sub-Saharan Africa. In countries poorly endowed with soils

and climate, basic inputs such as fertilizer, water (in the

form of irrigation), and institutional stability are more

important than they are in countries that are relatively well

endowed. The evidence suggests that only when these constraints have been overcome do factors such as labor quality,

road density, and mechanization become significantly associated with improvements in agricultural productivity—as

they are in countries with better soils and climate.

Similar patterns characterize other developing regions. In

Latin America, increases in labor, fertilizer, and irrigation

are associated with increased productivity of agricultural

land in countries with poor soils and adverse climate but not

in countries with good soils and beneficial climate.

Improvements in literacy and transportation infrastructure

are associated with increased productivity in countries with

good soils and climate but not in those that are poorly

endowed. In Asia, additional land, labor, and roads increase

agricultural productivity in counties with good soils and climate but not in those that are poorly endowed, where productivity is relatively more sensitive to increased irrigation.

(Specifically, productivity is positively related to an increase

in irrigated area, but some authors (e.g. Rosegrant 1997)

have noted that degradation of irrigated areas through waterlogging and salinization is also a significant and growing

problem.) In the Middle East and North Africa, agricultural

productivity is sensitive to levels of labor, tractors, and literacy in well-endowed countries but not in countries with

poor soils and climate, where (as in Asia) productivity is relatively more sensitive to increased irrigation. 

Analysis of inherent land quality thus improves our understanding of the impacts on agricultural productivity of factors

over which policy makers exercise at least some influence.

The policy implications of these findings will be discussed

further below. Analysis of differences in land quality across

countries and regions also provides an initial indication of

the potential impact on agricultural productivity of changes

in land quality (i.e. land degradation) over time. Data on land

degradation rates and impacts remain even more scarce than

data on land quality, but most studies to date have found that

global average productivity losses due to processes such as

soil erosion, nutrient depletion, and salinization are small (on

the order of 0.1 - 0.2 percent per year) in relation to historic

gains in productivity (on the order of 2 percent per year) due

to improvements in technology and input use (den Biggelaar

et al. forthcoming, Crosson 1997; Byerlee, Heisey, and

Pingali 1999; Pinstrup-Andersen, Pandya-Lorch, and

Rosegrant 1999). Nevertheless, in some areas with poor or

fragile soils and inappropriate agricultural management practices, productivity losses could be significantly higher

Figure A-4

Cropland quality

High-quality cropland (median %)

High-Income

Countries

Eastern Europe

Middle East & 

North Africa

Latin America

Asia

Sub-Saharan

Africa

0 10 20 30 40 50 60 70
(Scherr 1999, Lal 1998). That such conditions are found in

parts of Sub-Saharan Africa, where productivity levels are

already low and the need for growth is correspondingly high

is cause for concern.


#
#


As noted earlier, agricultural productivity is important for

food security both through its impact on food supplies and

prices and through its impact on the incomes and purchasing

power of those whose livelihoods depend on agricultural

production. Through its effect on agricultural productivity,

land quality is thus related directly to both food availability

and food access. Land quality is, on average, lower in lowincome, food-deficit countries than it is in high-income

countries, and agricultural productivity is more sensitive to

differences in land quality. These relationships have important implications for policymakers concerned with improving food security, both through protection and/or improvement of land quality itself and through recognition of the

distinct roles played by more conventional agricultural

inputs in areas that differ in land quality.

In Sub-Saharan African countries with relatively poor soils

and adverse climate, for example, the policy-sensitive variable most strongly associated with agricultural productivity

is irrigation, followed by armed conflict and fertilizer use.

Among the policy measures most important for increased

agricultural productivity in those countries are thus investments in the efficient delivery and use of water and fertilizer, combined with efforts to improve institutional stability

through the cessation of armed conflict. In Sub-Saharan

African countries with good soils and climate, these factors

remain important, but agricultural productivity becomes relatively more sensitive to improvements in labor quality and

infrastructure. Policymakers in those countries may need to

focus additional resources on investment in education,

health, extension services, and transportation.

Similar conclusions apply in other regions as well. In Latin

American countries with relatively poor soils and climate,

agricultural productivity and thus food security are likely to

respond most strongly to policy measures to improve efficiency in the use of fertilizer and water and to reduce the

occurrence of armed conflict. In Latin American countries

with better land, productivity responds much more strongly

to improvements in labor quality, infrastructure, and mechanization, suggesting the need for investments in education,

transportation, and capital. Improvements in irrigation, education, and conflict reduction are important in Asian countries with poor land, while improved transportation remains

important in Asian countries with good land. Increased

application of fertilizer is not associated with improved agricultural productivity in Asia, regardless of land quality,

reflecting the relatively high levels of use already observed

there. In the Middle East and North Africa, not surprisingly,

improvements in irrigation offer the greatest potential gains

in agricultural productivity. 

$ ✺ 

				
 
	



Data and Methods

We examined the impact of resource quality on the productivity of agricultural land, using for the first time recent global

data on soils, climate, and land cover. We began with data developed by Eswaran et al. (1997), who combined FAO’s

Digital Soil Map of the World and associated soil characteristics (e.g. slope, depth, and salinity) with spatially referenced

longrun average temperature and precipitation data to establish nine land quality classes in terms of their suitability for

agricultural production (fig. 1). Wiebe et al. (2000) then overlaid these land quality classes with political boundaries and

global land-cover data generated from satellite imagery with a resolution of 1 kilometer United States Geological

Survey/University of Nebraska-Lincoln/Joint Research Centre of the European Commission (USGS/UNL/JRC, 1999). They

focused on cropland identified according to the International Geosphere-Biosphere Programme land cover classification

scheme (fig. 2). The result is a dummy variable based on the share of each country’s cropland that is found in the three best

quality classes. Countries where this share exceeds the median value for their region are identified as having good soils and

climate; those with less than the median are identified as having poor soils and climate.

This static measure, based on cross-country differences in inherent soil and climate characteristics, supplements existing

time-variant quality indicators such as the percentage of agricultural land that is cropped (or irrigated) and long-term average

or annual rainfall. To better capture this last effect, we also developed a high-resolution measure of annual rainfall by aggregating and overlaying monthly precipitation data on a 0.5-degree grid (fig. 3; Climatic Research Unit 1998) with national

boundaries and cropland as described above. The result is a country-specific, time-variant measure of rainfall on cropland.

The dependent variable in our analysis is the productivity of agricultural land, measured as the value of total agricultural

production (the sum of price-weighted quantities of all agricultural commodities, expressed in international dollars, after

deductions for feed and seed) per hectare of agricultural land (the sum of arable land, permanent cropland, and permanent

pasture). Other variables include country-level indicators of agricultural labor, tractors, livestock, and fertilizer, as well as

measures of the quality of labor, the institutional environment, and infrastructure. The data are combined in an econometric

analysis of 110 countries during 1961-97. Additional detail is provided in Wiebe et al. (2000).
Results and implications are generally consistent with the

expectation that the greatest improvements in agricultural

productivity will be realized by relaxing the constraints that

bind most tightly and those constraints will vary from region

to region according to differences in resource endowments

and other factors. Neither is it surprising that the quality of

soils and climate should play a key role in defining these

differences. Yet only recently, with improvements in spatial

data and methods, has characterizing these differences with

increased precision at the multi-country scale become possible. Analysis to date supports the conclusion that policymakers in low-income, food-deficit countries face a hierarchy of priorities that depends critically on the quality of

soils and climate but that is broadly consistent across

regions. Continued research will be needed to further refine

our understanding of the relationships of resource quality,

agricultural productivity, and food security.

%

Byerlee, Derek, Paul Heisey, and Prabhu Pingali (1999).

“Realizing Yield Gains for Food Staples in Developing

Countries in the Early 21st Century: Prospects and

Challenges.” Presented to the Study Week on Food Needs of

the Developing World in the Early 21st Century, the Vatican,

January 27-30.

Climatic Research Unit (1998). Climate Impacts LINK

Project (U.K. Department of the Environment Contract EPG

1/1/16), Climatic Research Unit, University of East Anglia.

Craig, Barbara, Philip G. Pardey, and Johannes Roseboom

(1997). “International Productivity Patterns: Accounting for

Input Quality, Infrastructure, and Research.” American

Journal of Agricultural Economics, Vol. 79, pp. 1064-76.

Crosson, Pierre (1997). “Will Erosion Threaten Agricultural

Productivity?” Environment, Vol. 39, No. 8, pp. 4-31

(October).

den Biggelaar, Christoffel, Rattan Lal, Keith Wiebe, and

Vince Breneman (2001). “Soil Erosion Impacts on Crop

Yields in North America.” Advances in Agronomy, Vol. 72,

No. 1, pp. 1-52, 2001.

Eswaran, Hari, Russell Almarez, Evert van den Berg, and

Paul Reich (1997). “An Assessment of the Soil Resources of

Africa in Relation to Productivity.” Geoderma, Vol. 77,

pp. 1-18.

Frisvold, George, and Kevin Ingram (1995). “Sources of

Agricultural Productivity Growth and Stagnation in SubSaharan Africa.” Agricultural Economics Vol. 13, pp. 51-61.

Lal, Rattan (1998). “Soil Erosion Impact on Agronomic

Productivity and Environmental Quality.” Critical Reviews

in Plant Sciences Vol. 17, No. 4, pp. 319-464.

Pinstrup-Andersen, Per, Rajul Pandya-Lorch, and Mark W.

Rosegrant (1999). World Food Prospects: Critical Issues for

the Twenty-First Century. Food Policy Report, International

Food Policy Research Institute, Washington, DC.

Rosegrant, Mark W. (1997). Water Resources in the TwentyFirst Century: Challenges and Implications for Action.

Food, Agriculture, and the Environment Discussion Paper

No. 20. International Food Policy Research Institute,

Washington, DC. March.

Scherr, Sara J. (1999). Soil Degradation: A Threat to

Developing-Country Food Security by 2020? Food,

Agriculture, and the Environment Discussion Paper No. 27.

International Food Policy Research Institute, Washington,

DC. February.

United States Geological Survey/University of NebraskaLincoln/Joint Research Centre of the European

Commission. (1999). “Global Land Cover Characterization.

U.S. Geological Survey, University of Nebraska-Lincoln,

and European Commission’s Joint Research Center

<http://edcwww.cr.usgs/landdaac/glcc/glcc.html>.

Wiebe, Keith, Meredith Soule, Clare Narrod, and Vince

Breneman (2000). “Resource Quality and Agricultural

Productivity: A Multi-Country Comparison.” Selected

Paper presented at the Annual Meeting of the American

Agricultural Economics Association, Tampa, FL, July 31,

2000 <http://agecon.lib.umn.edu/aaea00/sp00wi01.pdf>.


	

 

				


✺ %


The projections of food gaps reveal the intensity of the current as well as the future food security problems in SubSaharan Africa. By 2010, this region is projected to account

for 65 percent of the total (all 67 countries covered in this

report) gap to maintain consumption and 75 percent of the

gap to meet nutritional needs even though the region’s population constitutes only 25 percent of the 67-country total.

The region’s nutrition gap, as a share of consumption (total

available food supplies), is projected to exceed 10 percent

by 2010. Added to the food problem is the prevalence of

HIV/AIDS in the region. The future impact of the

HIV/AIDS disease on food systems is of major concern

because of the already low and declining per capita food

consumption and the low level of agricultural productivity in

the region. Also, coping with and combating the disease in

rural areas where poverty is at its highest and education is at

its lowest level is the biggest challenge facing both individual countries and the international community. This article

reviews the historical role of population (and the labor

force) in food markets in Sub-Saharan Africa and the

expected impact of HIV/AIDS on the structure of the population. It also examines the likely implications of the disease

on food security in highly infected countries. The final section reviews the coping mechanism and response capacity.

3#4	(0"#	
#

)"#

Sub-Saharan Africa’s population growth during the 1980s was

the highest in the world—about 3 percent per year. Since

then, it has declined to 2.7 percent and is projected to decline

further during this decade. The high population growth in

Sub-Saharan Africa resulted from sharp mortality declines in

the 1950s due to improved health services. Rapid population

growth occurred in industrial countries between 1890 and

1920 and was supported by strong income growth and

improvements in education and health. Their experience also

shows that high population growth, when accompanied by

appropriate and adequate investments in agricultural technology and supportive government policies, can have a positive

impact on agricultural development. In Sub-Saharan Africa,

however, fertility rates have remained high, incomes have

stagnated, and low education levels have persisted. Although

the high population growth put additional pressure on the

demand side of the food market, it has remained the key

source of productivity on the production side. In most SubSaharan countries, modernization of the agricultural sector

has not yet occurred. Limited uses of new technology and

poor market infrastructures are the two characteristics that

have precluded an increase in agricultural productivity (see

“Resource Quality, Agricultural Productivity, and Food

Security in Developing Countries” p. 24.)

Now, after a long period of dealing with the burden of growing populations, the region is facing a sharp decline in population growth rates. The problem, however, is that the decline

is not a natural progression of development, but a result of the

rapid spread of HIV/AIDS. The disease has major implications for the economies and agricultural sectors of Africa. 

The two severely affected regions are Southern and Eastern

Africa. In Southern Africa, seven countries—Botswana,

Lesotho, Namibia, South Africa, Swaziland, Zambia, and

Zimbabwe—are reported to have adult HIV prevalence of

 ✺ 

				
 
	



	


Vulnerability to HIV/AIDS in Sub-Saharan Africa

Shahla Shapouri and Stacey Rosen1

Abstract: Labor is the vital component of agricultural production in Sub-Saharan Africa. If

size and structure are changed productivity of the labor force will directly affect food production and consumption in the region. Sub-Saharan Africa, with 11 percent of global population, has an estimated 73 percent of global HIV/AIDS—related infections. Little is known

about the net affect of HIV/AIDS on the agricultural economy, but vulnerability to food insecurity will certainly increase in the severely affected countries. The estimated health and productivity costs of the epidemic will have long-term implications on the economic growth of

the countries. 

Keywords: Sub-Saharan-Africa, AIDS, HIV, population growth, food production, food 

consumption, labor productivity.

1 Agricultural economists with the Market and Trade Economics Division,

Economic Research Service, USDA.
more than 20 percent. In most East African countries, HIV

prevalence is more than 10 percent. In these countries, life

expectancy is projected to decline to 30-40 years instead of

60-70 years (an estimate used prior to the spread of

HIV/AIDS). According to a UN report, about 55 percent of

all HIV infections in Sub-Saharan Africa are among women.

Peak HIV prevalence among women is at age 25, that is 10

to15 years earlier than for men, changing the structure of the

population. Thus, the most productive age cohort, 15-45, is

dying the fastest from HIV/AIDS. This age cohort is nearly

50 percent of the population in highly HIV/AIDS affected

countries. HIV prevalence among the relatively educated as

well as high-income urban population is as high or higher

than among low-income and rural groups. In Rwanda, Congo,

and Zambia, the level of HIV infection in the highest socioeconomic strata is two to four times higher than among those

in the lowest category.

.5*+#


In the countries mostly affect by HIV/AIDS, slow growth in

agricultural productivity and overall economic growth that

limited purchasing power resulted in growing food insecurity

over the last two decades. Even in countries such as Uganda

where food supplies are projected to be nutritionally adequate, food insecurity remains a major concern because of the

low and wide disparity in purchasing power. Table B-1 shows

the projected nutritional vulnerability in selected countries

that are highly affected by HIV/AIDS. These projections

include the decline in population growth and productivity of

labor, as well as can be estimated. Most of the available studies have focused on the medical costs, and there is limited

information on long-term economic costs of HIV/AIDS and

the variation of the effects on different groups within countries. By the same token, any quantification of the net effect

of HIV/AIDS on the food system is preliminary. However, the

food system will be certainly subjected to shocks that could

amplify the food insecurity of many countries. 

"4*	#
#


.5*+

The size of the supply shock depends on the extent to which

HIV/AIDS reduces the productivity of the agricultural labor

in rural areas. The agricultural sector plays a crucial role in

the economy of African countries in terms of both sources

of food and exports to finance food imports. A review of the

statistics of selected countries in table B-2 shows that with

the exception of Kenya, the agricultural sector provides 80

percent of grain consumption in these countries. Grains contribute as much as 80 percent of per capita calorie consumption in these countries. The share of the agricultural sector

in GDP for the same set of countries is in the range of 11

percent in Zambia to 47 percent in Tanzania. 

With labor as the prime component of agricultural production, the implication of the HIV/AIDS epidemic on food

security of the countries could be staggering. In projecting

crop production for these countries, we use an elasticity of

0.3, meaning that with a 1-percent decline in labor availability, production will decline by 0.3 percent. However, we did

not account for a change in the quality of labor. In the Food

Security model, the marginal productivity of labor is

assumed to remain constant over the projection period. For

the Sub-Saharan countries, this may be an overestimation

because the decline in population growth is in part due to

the spread of HIV/AIDS, which affects the most productive

segment of the population. A decline in healthiness of rural

populations is expected to reduce labor productivity in rural

areas. The World Health Organization estimates that local

losses in agricultural productivity from HIV/AIDS at the

household or village level range from 10 to 50 percent in

about 10 Sub-Saharan African countries. 

The high rate of infection among women will, in particular,

have enormous implications on nutrition and poverty. Many

farms are headed by women and on other farms women provide a large portion of total labor. For example, a study of two

towns in Tanzania found that women provide 48 percent of

agricultural labor including land preparation, planting, weeding, and harvesting while men did most of the marketing.

Economic consequences will be compounded by the fact that

women are barred from owning land in many countries. If a

husband dies, the wife’s lack of collateral limits her ability to

obtain credit to keep the farm in operation or to purchase

labor-saving technology. Also, an increase in the number of

orphans places a burden on healthy women in the community


	

 

				


✺ 

Table B-1--Grain market performance profile for selected countries

Region/ Ratio of nutritional gap in 

country Annual production growth grain equivalent in year 2010 to:

1980-99 1989-99 Production Imports

Percent

East Africa:

Kenya 0.44 -1.04 12.12 25.21

Tanzania 2.03 0.00 33.57 353.67

Uganda 2.18 1.29 .00 .00

Southern Africa:

Malawi 1.83 4.14 18.11 213.54

Zambia -1.22 -3.63 69.91 356.20

Zimbabwe -1.06 -.10 2.41 21.75

Source: Economic Research Service, USDA.
who must care for the sick and dying, while simultaneously

increasing their child care responsibilities. This dilemma

compounds the effect of HIV/AIDS on agriculture because

healthy women will have less time for farming activities. 

Another factor that can worsen the situation is the likely

change in cropping patterns. For example, farmers are

expected to move away from labor-intensive export crops to

more subsistence crops that use less labor. Among food

crops, a switch from corn to cassava would conserve considerable labor. However, cassava is less nutritious than corn.

Nutritional intake is already below minimum standards in

several countries, including those highly affected by

HIV/AIDS. In 14 of the 17 countries in East and Southern

Africa, per capita daily caloric intake is below the level

required to attain a minimum nutritional standard (the calories required to sustain life with minimum activity). The

nutritional vulnerability of the countries is projected to grow

by 30 percent in the next decade. A domino effect follows:

food supply deficits and decreased healthiness impair agricultural productivity through reduced food availability, which

further reduces agricultural productivity and may hasten the

onset of HIV/AIDS in weakened HIV-positive people. 

1.5*+#4+#

One of the effects of HIV/AIDS is declining living standards and, consequently, a reduction in food demand

through lower population and income growth. The bleakest

economic outlook is for GDP growth to decline from its

already meager pace (table B-3). In Kenya, for example,

GDP will probably be 14.5 percent lower than projections

that do not account for the effects of HIV/AIDS. In

Tanzania, the annual direct medical costs and losses in labor

productivity are projected to be 2 percent to 4 percent of

GDP. These costs are very troublesome because public and

private incomes in these countries have stagnated or

declined in the last 20 years and any increase in public and

private outlays on health care must come at the expense of

investment in economic development. More immediately,

many health care needs are likely to be unmet due to prohibitive costs. To put this in perspective, the average public

health expenditure for the region was 1.7 percent of GDP

during 1990-97 and the region’s per capita GNP in 1997

was $308; thus, annual health care spending was $5 per

capita. Even in a country such as Zimbabwe that is on the

high end of the region’s income, the per capita expenditure

was not much more than $10 per person. According to available reports, the life-extending drugs costs $11,000 a year in

the United States. Even at a discounted rate, their costs far

outstrip health expenditures in these countries.

The implication of HIV/AIDS on the demand for food is

clear. As incomes decline due to the spread of HIV, demand

for food will decline, but as expected, the impact is more

damaging to the lower income countries than the higher

incomes. Low-income countries spend more than half of

their income on food. In Africa, this share is in the range of

40 percent to 70 percent. The average income-calorie elasticity for Sub-Saharan Africa is estimated at 0.14 percent

(using cross-country data). Thus, a 10-percent decline in

income over the projected period will reduce calorie consumption by 1.4 percent. While this kind of decline would

not affect the nutritional well being of high income countries such as the United States where per capita calorie

availability is about 3,700 per day, it can have serious implication for the countries that live on the margin of the minimum calorie requirement. In Sub-Saharan Africa the average per capita calorie availability was about 2,200 per day in

1998, the lowest of all developing regions of the world.

Added to the low level of calorie consumption is the quality

of food consumed in the region. Cereals and starchy roots

and pulses, low-cost foods, comprise 70 percent of the

region’s calorie consumption, while higher cost foods such

as meat and dairy products that are good sources of vitamins

and minerals are consumed at the lowest rates in the world. 

The decline in income will have varying implications for the

entire population. Skewed income distribution in these

countries exacerbates the problems for the poor. In most

countries, the poorest 20 percent of the population holds

only 4 percent to 8 percent of total national income, while

the richest 20 percent holds nearly 50 percent. This disparity

in purchasing power could worsen with the spread of

HIV/AIDS. The food security estimates for the year 2000

indicate that food consumption by 60 percent of SubSaharan Africans falls short of meeting their nutritional

requirements. More alarming, however, is the depth of the

problem. Food consumption of the lowest income group is

estimated to be 20 percent less than the nutritional requirement in year 2000. If the income distribution worsens, the

implication will be serious. In African countries, most of the

poor live in rural areas. In rural areas, most farmers are subsistence producers and have limited assets to bear the reduction or loss in their productivity. For the rural landless

laborer, HIV/AIDS means a severe cut in purchasing power.

Also, there is no formal safety-net program to provide support for the sick and unemployed in these countries.

Therefore, the family network must provide the support. 

 ✺ 

				
 
	



Table B-2--Agricultural indicators for selected countries

Grain import Agricultural Agricultural 

Region/ share in share in share in

country consumption GDP exports

1997-99 1997 1997

Percent

East Africa:

Kenya 32.2 24.4 56.2

Tanzania 9.0 47.4 63.3

Uganda 5.2 41.4 76.0

Southern Africa:

Malawi 12.9 44.6 76.8

Zambia 19.6 11.1 4.6

Zimbabwe 10.6 13.9 46.2

Sources: Economic Research Service, USDA and World Bank data.
Overall, any reduction in agricultural output and/or demand

for food below the current low levels will have serious consequences for food security of the severely affected countries. Even without taking into account the side effects of

HIV/AIDS, a continuation of present trends in food consumption is projected to lead to deteriorating food security

in these countries. Investment and a concerted policy

response by the affected governments must occur if these

losses are to be minimized.

0
	"##

%
0#
#


To identify coping options in dealing with the impact of

HIV/AIDS on food security, one should examine forces

that shape the food markets of these countries. One

important characteristic of the market is that the agriculture sector is the main source of both food production and

exports to finance food imports. Agricultural sectors in

Sub-Saharan Africa have performed poorly and are generally characterized by (1) low productivity that is now

compounded by the spread of HIV/AIDS, (2) a lack of

resources and affordable technology to increase productivity, and (3) a low literacy rate that limits access to knowhow and technology as well as access to knowledge for

essential behavioral change. These factors reinforce each

other, and altering the situation requires attacking all three

problems simultaneously. 

To reduce the economic costs of HIV/AIDS, African countries must design an economic strategy in which health

policy is a major component. Public policy should aim at

providing information wherein health is a precondition of

economic wellbeing. Currently, there are success stories in

the region. Uganda has launched major preventive efforts

during the last decade and has managed to reduce the rate

of infection. Now, the growing awareness by officials at

the international level has led to an increase in financial

aid to improve and expand the preventive measures to

reduce the rate of infection. This should ease costs and

support national programs.

Educational messages to prevent the spread of disease, if

combined with economic assistance to cope with the situation, are the most efficient ways of using new resources. For

example, in response to the reduction in food supplies,

nutritional education, particularly the mother’s education, is

important to provide information on food processing and

nutritional conservation. To promote self-reliance and more

sustainable responses in highly affected HIV areas, governments should encourage communities to diversify their economic activities. Many communities in Africa have started

income-generating activities such as raising poultry or gardening to improve their financial situation and to help families affected by HIV/AIDS. In Malawi and Uganda, village

banks give small loans to households to start their own

enterprise such as market trading and honey production. In

Uganda, 75 percent of households who received loans

recently reported that they were caring for orphans (U.S.

Agency of International Development (USAID)-Impact on

HIV, June 2000). 

In sum, the projected long-term food outlook for these

countries shows a steady increase in food gaps, both to

maintain per capita consumption and to meet nutritional

requirements. Sub-Saharan Africa historically has shown

the smallest improvement in average daily per capita calorie consumption. The HIV/AIDS crisis, which has already

reduced the supply of labor in many countries, is projected

to deepen the food insecurity problems of the region. Our

projections, however, do not capture the full economic

implications of HIV/AIDS, such as the decline in labor

quality, medical/care costs, and costs associated with

change in population structure. The challenge is new and

has no simple remedy. As for the agriculture sector, strategies should aim at promoting domestic production. Unless

urgent steps are taken to reverse the technological stagnation in the agricultural sector, HIV/AIDS will further deteriorate the food security problem of the region. The

process, however, will be long and require consistent policies and credible institutional bodies. Given current economic and resource constraints, governments will have to


	

 

				


✺ 

Table B-3--Social indicators in selected countries

Public Life 

Region/ Adult HIV Per capita Population expenditure on expectancy

country infection rate GNP below poverty health, share of GDP at birth

in Dec. 1999 1998 line 1990-97 1997

Percent US Dollars Percent

East Africa:

Kenya 14.0 330 42.0 1.9 51

Tanzania 12.0 210 51.1 1.1 49

Uganda 8.0 320 55.0 1.9 42

Southern Africa:

Malawi 16.0 200 54.0 2.3 43

Zambia 20.0 330 68.0 2.9 43

Zimbabwe 25.1 610 25.5 1.7 51

Source: World Development Report, World Bank, 1999.

Years
make difficult choices about HIV/AIDS care, prevention,

and revitalization of their economies. 

%

African Development Bank (1993). “AIDS (HIV) and

Development,” Annual meeting symposium, Abidjan, Côte

d’Ivoire, May 11.

Becker, Charles (1990). “The Demo-Economic Impact of

the AIDS Pandemic in Sub-Saharan Africa,” World

Development Report, Vol.18. Elmsford, NY: Pergamon

Press, pp. 1599-1619.

Chenery, H., and T.N. Srinivasan, eds., (1988). Handbook of

Development Economics, Vol. 1. Amsterdam: Elsevier

Science Publisher.

Cuddington, John T. (1993). “Modeling the Macroeconomic

Effects of AIDS, with an Application to Tanzania,” The

World Bank Economic Review, Vol. 7, No. 2, May, p. 173.

Food and Agriculture Organization of the United Nations

and Joint United Nations Programme on HIV/AIDS

(UNAIDS) (1999). Sustainable Agriculture/Rural

Development and Vulnerability to the AIDS Epidemic.

Geneva, Switzerland, December.

Gellman, Barton (2000). “DeathWatch: The Global

Response to AIDS in Africa,” Washington Post, June 5, pp.

A1, 12-13.

Guerny, J. (1999). “AIDS and Agriculture in Africa: Can

Policy Make a Difference?,” Food, Nutrition, and

Agriculture, Food and Agriculture Organization of the

United Nations, Vol. 25.

International Labor Office (2000). HIV/AIDS: A Threat to

Decent Work, Productivity, and Development, Geneva,

Switzerland, June 2. 

Kambou, Gerard, Shatayanan Deverajan, and Mead Over

(1993). “The Economic Impact of AIDS in an African

Country: Simulations with a Computable General

Equilibrium Model of Cameroon,” Journal of African

Economies, Vol. 1, No. 1.

Karen A. Stanecki (2000). “The AIDS Pandemic in the 21st

Century: The Demographic Impact in Developing

Countries,” World Population Profile 2000, U.S. Census

Bureau, in press.

Lorch, Donatella (1993). “Uganda, Scarred by AIDS, Turns to

its Youth,” front page story, New York Times, February 23. p. 1.

National Intelligence Council (2000). The Global Infectious

Disease Threat and its Implications for the United States,

Environmental Change and Security Report, Washington,

D.C.: Woodrow Wilson Center.

Way, Francis, and Mead Over (1992). “The Projected

Economic Impact of an AIDS Epidemic,” paper presented at

the annual meeting of Population Association of America,

Denver, Co, April 28-May 2.

 ✺ 

				
 
	



	

 

				


✺ !

Statistical table 1--Algeria (North Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 3,730 275 4,190 19 8,309

1992 3,348 295 4,689 15 8,600

1993 1,563 272 5,483 18 8,339

1994 959 183 6,939 24 9,434

1995 2,137 306 5,724 13 11,541

1996 4,883 294 3,653 36 8,871

1997 883 242 5,778 13 9,199

1998 3,023 281 5,861 27 9,692

1999 2,172 254 5,745 0 9,653

Projections Food gap

SQ NR (w/o food aid)

2000 772 280 6,025 361 518 8,467

2005 2,043 309 6,079 180 354 9,629

2010 2,208 339 6,340 718 909 10,027

Algeria's 2000 drought led to a

severe production shock and food

gaps, but the windfall from petroleum revenues might over-come

this shortfall. Algeria will become

more dependent on food imports.

Longrun food gaps are projected,

but could be eliminated if petroleum

prices continue at recent levels.

1980 83 86 89 92 95 98

0

2

4

6

8

10

12

14

Percent

Algeria's share of grain imports

to total imports

Data are estimated for 1999 and 2000.

Statistical table 2--Egypt (North Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 12,016 508 6,456 1,026 17,701

1992 12,329 460 6,573 482 17,529

1993 13,205 466 6,764 230 18,301

1994 13,510 398 8,895 180 20,265

1995 14,578 721 7,701 190 20,989

1996 15,485 731 8,507 145 21,306

1997 16,304 522 10,037 59 23,396

1998 15,289 572 10,558 13 22,987

1999 16,676 542 10,072 63 24,922

Projections Food gap

SQ NR (w/o food aid)

2000 16,820 560 10,666 0 0 24,914

2005 17,551 599 10,996 0 0 25,512

2010 18,615 640 11,798 0 0 27,110

Egypt does not show any food

gaps in the short or longrun.

Annual grain output continues to

grow steadily and impressively, but

yield growth appears to be slowing

down. Almost all income groups

appear to consume well above

nutrition requirements, but this

might erode slightly over time.

1980 83 86 89 92 95 98

0

2

4

6

8

10

12

14

16

Percent

The share of food aid in total grain 

supplies has declined in Egypt
" ✺ 

				
 
	



Statistical table 3--Morocco (North Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 8,636 325 1,768 203 9,593

1992 2,933 276 2,923 234 8,869

1993 2,753 265 3,593 124 9,898

1994 9,530 312 1,711 13 9,245

1995 1,800 267 3,620 0 9,922

1996 10,037 373 2,912 4 10,479

1997 4,101 357 2,780 10 10,049

1998 6,733 335 3,358 10 9,157

1999 3,785 341 4,515 0 10,633

Projections Food gap

SQ NR (w/o food aid)

2000 2,185 361 3,669 0 1,045 7,138

2005 6,401 405 3,639 0 0 11,553

2010 7,755 453 3,779 0 0 13,406

Morocco has experienced two consecutive major droughts. Last year,

the country was able to absorb the

production shock, but not this year.

For most income groups, average

consumption levels may fall below

nutrition requirements in the short

run, but recover in the long run.

1980 84 88 92 96 2000

-80

-60

-40

-20

0

20

40

60

80

100

Percent of trend

Morocco experiences another large 

deviation from production trend

Statistical table 4--Tunisia (North Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 2,508 55 839 96 3,608

1992 2,155 54 925 100 3,743

1993 1,561 49 1,014 46 3,267

1994 646 52 1,585 22 3,011

1995 1,366 58 2,694 18 4,387

1996 2,862 67 1,239 4 3,522

1997 1,151 72 1,971 12 3,695

1998 1,654 73 1,969 0 3,933

1999 1,816 74 1,562 0 3,862

Projections Food gap

SQ NR (w/o food aid)

2000 851 76 1,914 0 0 3,182

2005 1,757 83 1,972 0 0 4,164

2010 1,914 90 2,122 0 0 4,527

Tunisia's production in 2000 is

almost 50 percent below trend due

to the drought. However, the country should be able to compensate

for the shortfall with commercial

imports. Consumption levels

should be above nutrition requirements for all income groups in both

the short run and long run.

1990 92 94 96 98 2000 0

100

200

300

400

500

600

Kg per capita

Tunisia's imports should offset

low production

Commercial imports

Production

	

 

				


✺ #

Statistical table 5--Cameroon (Central Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 950 747 253 13 2,979

1992 868 755 434 1 3,129

1993 878 784 307 2 3,097

1994 892 778 417 2 3,235

1995 1,140 749 314 4 3,366

1996 1,240 892 122 0 3,449

1997 1,065 927 360 5 3,588

1998 1,155 833 432 11 3,671

1999 1,215 835 288 3 3,643

Projections Food gap

SQ NR (w/o food aid)

2000 1,215 906 395 0 0 3,833

2005 1,280 987 457 162 0 4,177

2010 1,402 1,075 546 237 0 4,642

Production is projected to grow 

at an annual rate of 1.8 percent

through 2010, marking a slight

slowdown from the historical trend.

A 2.6-percent growth rate would be

required to maintain per capita

consumption at base levels and

eliminate the status quo gap.

1st 2nd 3rd 4th 5th 0

20

40

60

80

100

120

Percent

Consumption by income quintile

in 2010

Share of nutritional requirements

Statistical table 6--Central African Republic (Central Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 129 270 22 3 691

1992 93 281 25 5 673

1993 93 279 25 6 682

1994 85 271 43 1 710

1995 105 281 28 0 722

1996 110 298 14 0 747

1997 120 315 29 3 794

1998 120 333 23 10 821

1999 120 318 29 1 813

Projections Food gap

SQ NR (w/o food aid)

2000 120 328 29 23 56 819

2005 127 347 29 58 94 863

2010 134 366 30 98 137 912

The nutritional situation is 

projected to deteriorate during 

the next decade. Annual production

growth of just over 1 percent will

be insufficient to fill nutritional

requirements, and imports will 

continue to play a minimal role 

in contributing to domestic 

food supplies.

2000 2005 2010

0

20

40

60

80

100

120

140

1,000 tons

Grain imports and food gaps

Commercial imports

Nutritional gap
$ ✺ 

				
 
	



Statistical table 7--Congo, Democratic Republic (Central Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,229 6,826 164 129 9,130

1992 1,408 6,968 238 27 9,550

1993 1,567 6,668 246 31 9,929

1994 1,545 6,744 218 91 9,929

1995 1,452 6,841 336 33 10,070

1996 1,465 5,998 260 24 9,418

1997 1,305 6,029 511 10 9,491

1998 1,585 6,044 464 13 9,862

1999 1,445 5,841 240 10 9,408

Projections Food gap

SQ NR (w/o food aid)

2000 1,470 6,176 405 156 2,141 9,872

2005 1,770 6,769 377 718 3,021 10,915

2010 1,964 7,409 367 1,551 4,218 11,920

Per capita consumption is 

projected to decline more than 

1.1 percent per year through 2010.

Population growth is projected 

to average roughly 2.8 percent

annually. Consumption in each

income group will fall short of 

that needed to fulfill minimum 

nutritional requirements.

2000 2005 2010 0

10

20

30

40

Percent

Food gaps as a share of total

availability

Status quo gap

Nutritional gap

Statistical table 8--Burundi (East Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 385 389 33 1 1,328

1992 258 399 18 6 1,214

1993 249 389 0 59 1,189

1994 185 339 62 49 1,108

1995 225 356 45 5 1,140

1996 220 366 13 1 1,132

1997 225 389 16 0 1,152

1998 215 355 26 0 1,143

1999 220 397 69 1 1,252

Projections Food gap

SQ NR (w/o food aid)

2000 220 389 39 28 412 1,200

2005 227 422 38 116 553 1,280

2010 269 456 39 142 629 1,417

Even though projected production

growth far outstrips the historical

trend, food supplies will not be sufficient to meet nutritional requirements through the next decade.

Consumption in even the highest

income group is projected at only

82 percent of the nutritional target

in 2010.

2000 2005 2010

0

10

20

30

40

50

60

Percent

Food gaps as a share of total

availability

Status quo gap

Nutritional gap

	

 

				


✺ %

Statistical table 9--Eritrea (East Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 72 -- 0 253 72

1992 198 -- 0 39 198

1993 73 26 0 246 291

1994 298 26 102 153 677

1995 153 25 26 65 366

1996 84 25 232 9 447

1997 99 26 254 63 553

1998 458 27 218 103 908

1999 270 26 237 53 699

Projections Food gap

SQ NR (w/o food aid)

2000 280 28 243 89 236 659

2005 290 30 243 174 340 673

2010 316 33 253 237 424 717

Production growth would need to

double from the projected rate of

1.8 percent per year to eliminate

the nutrition gap by 2010. Per

capita consumption is projected to

decline 1.4 percent annually.

2000 2005 2010

0

10

20

30

40

50

60

Percent

Food gaps as a share of total

availability

Status quo gap

Nutritional gap

Statistical table 10--Ethiopia (East Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 4,876 0 0 1,046 4,876

1992 5,342 0 0 543 5,342

1993 5,276 1,354 0 652 8,656

1994 5,702 1,431 236 787 9,637

1995 6,922 1,510 122 525 10,793

1996 9,116 1,551 116 297 12,875

1997 6,901 1,587 5 655 10,854

1998 7,867 1,592 22 696 12,053

1999 7,805 1,615 17 823 12,261

Projections Food gap

SQ NR (w/o food aid)

2000 7,745 1,672 14 793 3,479 11,380

2005 10,182 1,850 14 0 2,365 14,374

2010 11,745 2,046 15 0 2,525 16,461

Despite a projected slowing of the

production growth rate relative to

the historical period, per capita

consumption will rise nearly 1 percent per year through 2010.

However, food supplies will 

fall short of meeting nutritional

requirements.

2000 2005 2010 0

5.0

10.0

15.0

20.0

25.0

Mil. tons

All food availability versus

requirement

Nutritional requirement
  ✺ 

				
 
	



Statistical table 11--Kenya (East Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 3,033 480 136 186 5,910

1992 3,085 500 360 288 6,047

1993 2,220 525 313 236 4,907

1994 3,554 520 1,004 111 6,878

1995 3,227 571 298 42 6,320

1996 2,778 606 365 59 5,456

1997 2,930 644 1,470 112 7,520

1998 3,030 651 855 80 6,852

1999 2,715 642 1,542 49 7,343

Projections Food gap

SQ NR (w/o food aid)

2000 2,915 664 1,363 0 191 7,289

2005 3,102 727 1,442 0 357 7,759

2010 3,297 795 1,584 0 399 8,355

Production growth is projected to

be quite slow through the next

decade—1.3 percent per year.

However, a continued slowdown in

the population growth rate, principally due to the impact of AIDS,

will preclude a deterioration in per

capita consumption through 2010.

1990 1995 2000 2005 2010

0

1,000

2,000

3,000

4,000

5,000

6,000

Sources of grain

1,000 tons

Food aid

Commercial imports

Production

Statistical table 12--Rwanda (East Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 254 749 19 11 1,597

1992 267 695 0 90 1,631

1993 188 583 46 90 1,463

1994 149 346 0 282 1,131

1995 154 347 0 258 1,159

1996 174 450 0 349 1,328

1997 214 490 0 177 1,434

1998 214 474 57 153 1,537

1999 194 565 133 77 1,704

Projections Food gap

SQ NR (w/o food aid)

2000 214 499 20 443 436 1,378

2005 255 551 19 499 491 1,525

2010 271 609 19 595 585 1,651

Although production returns to prewar levels before the end of the

projection period, growth is slow

and commercial imports are negligible. As a result, food supplies will

fall well short of those required to

maintain base per capita consumption levels and to meet minimum

nutritional requirements.

2000 2005 2010

29

30

31

32

33

34

35

36

37

Percent

Food gaps as a share of total

availability

Status quo gap

Nutritional gap

	

 

				


✺ 

Statistical table 13--Somalia (East Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 257 16 77 132 1,093

1992 202 14 38 312 1,181

1993 162 14 125 75 1,126

1994 228 13 115 13 1,186

1995 293 16 80 13 1,268

1996 313 18 93 3 1,341

1997 320 19 83 22 1,394

1998 254 21 88 34 1,402

1999 204 23 68 55 1,414

Projections Food gap

SQ NR (w/o food aid)

2000 229 21 81 159 939 1,367

2005 298 23 78 327 1,261 1,501

2010 321 25 79 548 1,640 1,587

Production growth is projected at

1.8 percent per year through 2010.

This growth rate would need to

nearly triple in order to eliminate

the nutritional food gap.

Consumption in even the highest

income group is projected at only

60 percent of nutritional requirements in 2010.

1st 2nd 3rd 4th 5th 0

10

20

30

40

50

60

70

Percent

Consumption by income quintile

in 2010

Share of nutritional requirements

Statistical table 14--Sudan (East Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 4,488 49 489 711 7,396

1992 5,307 49 333 286 7,794

1993 3,087 47 93 293 6,071

1994 5,152 50 677 138 8,145

1995 3,307 51 325 58 6,595

1996 5,207 52 282 120 8,418

1997 4,507 52 555 99 8,540

1998 5,842 53 400 294 9,139

1999 4,507 54 623 71 8,621

Projections Food gap

SQ NR (w/o food aid)

2000 5,382 53 536 0 0 9,057

2005 6,244 56 526 0 0 10,347

2010 6,976 59 540 0 0 11,482

Prospects for the 2000 coarse

grain crop are good due to high

producer prices and export opportunities to Eritrea and Ethiopia. The

government has also delivered

inputs such as seeds, fertilizer,

fuel, and pesticides to facilitate

agricultural activities.

1980 84 88 92 96 2000

0

1

2

3

4

5

6

7

Mil. tons

Grain production is very volatile

in Sudan
  ✺ 

				
 
	



Statistical table 15--Tanzania (East Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 3,540 1,736 111 18 6,648

1992 3,390 1,648 154 36 6,476

1993 3,700 1,593 150 47 6,520

1994 3,305 1,671 223 114 6,443

1995 4,355 1,451 184 35 6,822

1996 4,180 1,450 148 20 6,799

1997 3,355 1,436 217 96 6,481

1998 3,905 1,477 340 42 6,917

1999 3,585 1,728 361 22 7,134

Projections Food gap

SQ NR (w/o food aid)

2000 3,685 1,560 319 0 838 6,948

2005 4,281 1,684 328 0 930 7,812

2010 4,730 1,817 354 55 1,252 8,559

Although production growth rates

are projected to exceed those of

the historical period, they will not

keep pace with the annual population growth rate of 2.3 percent.

As a result, the nutritional situation

is expected to deteriorate through

2010.

2000 2005 2010

0

2.0

4.0

6.0

8.0

10.0

12.0

Mil. tons

All food availability versus

requirement

Nutritional requirement

Statistical table 16--Uganda (East Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,460 1,834 0 30 5,120

1992 1,666 1,765 0 40 5,304

1993 1,794 1,886 36 46 5,539

1994 1,900 1,593 0 63 5,553

1995 2,020 1,688 0 44 5,843

1996 1,750 1,431 0 49 5,484

1997 1,550 1,582 43 82 5,475

1998 1,680 2,007 80 53 5,958

1999 1,670 2,217 0 0 6,225

Projections Food gap

SQ NR (w/o food aid)

2000 1,670 1,975 19 274 0 5,995

2005 2,088 2,194 21 416 0 6,944

2010 2,354 2,436 23 830 0 7,758

While the projected production

growth rate of 2.5 percent per year

is adequate to provide enough

food to meet nutritional requirements, it falls more than 1 percentage point short of that needed to

maintain base per capita consumption levels.

2000 2005 2010

0

2.0

4.0

6.0

8.0

10.0

Mil. tons

All food availability versus

requirement

Status quo requirement

	

 

				


✺ 

Statistical table 17--Angola (Southern Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 346 633 164 142 2,074

1992 452 714 207 116 2,057

1993 317 707 107 222 1,944

1994 261 887 176 229 2,254

1995 302 948 192 218 2,545

1996 473 932 315 190 2,654

1997 513 871 232 132 2,413

1998 443 1,175 259 146 2,887

1999 603 1,143 368 138 2,907

Projections Food gap

SQ NR (w/o food aid)

2000 513 1,113 298 231 440 2,698

2005 609 1,195 308 502 746 2,915

2010 661 1,282 331 785 1,065 3,135

Corn production for 2000 was

adversely affected by several factors: the late start of the rainy season which was followed by excessive rainfall, scarcity of inputs, poor

seed quality, and displacement of

population due to civil strife.

2000 2005 2010

0

1.0

2.0

3.0

4.0

5.0

Mil. tons

All food availability versus

requirement

Nutritional requirement

Statistical table 18--Lesotho (Southern Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 148 14 197 37 348

1992 75 16 175 45 448

1993 151 17 189 32 541

1994 243 20 174 15 312

1995 106 20 301 47 689

1996 261 20 304 15 512

1997 210 22 306 13 448

1998 135 23 313 6 585

1999 175 25 202 3 453

Projections Food gap

SQ NR (w/o food aid)

2000 170 24 282 25 34 506

2005 197 25 281 57 66 528

2010 213 27 292 87 97 556

Production growth is projected at

1.75 percent per year through

2010. This is about half the rate

necessary to eliminate the status

quo and nutritional food gaps.

1990 1995 2000 2005 2010

0

100

200

300

400

500

600

700

Sources of grain 

1,000 tons

Food aid

Commercial imports

Production
 ✺ 

				
 
	



Statistical table 19--Madagascar (Southern Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,553 932 28 54 2,842

1992 1,715 916 73 59 3,057

1993 1,812 953 77 34 3,138

1994 1,670 972 123 20 3,057

1995 1,780 956 127 24 3,205

1996 1,830 962 48 43 3,238

1997 1,830 986 103 13 3,319

1998 1,700 981 126 25 3,274

1999 1,875 996 145 6 3,505

Projections Food gap

SQ NR (w/o food aid)

2000 1,875 1,019 128 92 146 3,459

2005 2,013 1,105 127 346 407 3,716

2010 2,181 1,197 131 591 661 4,018

Per capita consumption is projected to drop more than 1 percent

per year as food production

remains just above the historical

trend of 1.5 percent. Production

would need to grow nearly 3 

percent per year to preclude 

this decline.

2000 2005 2010

0

100

200

300

400

500

600

700

Food gaps 

1,000 tons

Status quo gap

Nutritional gap

Statistical table 20--Malawi (Southern Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,629 116 0 285 1,358

1992 670 105 0 605 3,057

1993 2,016 128 498 62 1,586

1994 1,093 118 220 284 2,902

1995 1,628 124 182 117 2,493

1996 1,833 125 85 51 1,839

1997 1,270 127 67 27 2,570

1998 1,795 128 121 84 3,062

1999 2,445 128 58 63 2,315

Projections Food gap

SQ NR (w/o food aid)

2000 2,245 130 176 0 0 2,876

2005 2,048 142 180 0 281 2,706

2010 2,264 156 192 14 401 2,977

Good rains and agricultural inputs

supplied at no cost or at highly

subsidized rates have resulted in

two consecutive above average

harvests. As a result, it is estimated that food supplies will be

adequate and there will be no food

gaps, on the aggregate level, 

in 2000.

2000 2005 2010

0

1.0

2.0

3.0

4.0

Mil. tons

All food availability versus

requirement

Nutritional requirement

	

 

				


✺ !

Statistical table 21--Mozambique (Southern Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 544 1,355 0 664 2,860

1992 278 1,193 130 929 3,348

1993 715 1,292 309 351 3,232

1994 756 1,238 217 305 3,558

1995 1,080 1,528 263 266 4,019

1996 1,313 1,727 257 91 3,915

1997 1,453 1,941 145 183 4,290

1998 1,573 2,049 362 159 4,626

1999 1,673 2,054 369 64 4,378

Projections Food gap

SQ NR (w/o food aid)

2000 1,423 2,082 297 132 558 4,281

2005 2,013 2,232 295 0 231 5,046

2010 2,327 2,391 307 0 95 5,589

Severe flooding in February and

March resulted in a small decline

in foodcrop plantings, on the

aggregate level. However, successive years of good harvests have

raised onfarm stocks and boosted

food supplies.

1994 95 96 97 98 99 2000

0

1,000

2,000

3,000

4,000

Sources of grain and tubers 

1,000 tons

Food aid

Commercial imports

Root prod.

Grain prod.

Statistical table 22--Swaziland (Southern Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 158 2 91 5 217

1992 59 2 59 40 260

1993 78 2 80 10 275

1994 104 2 102 1 267

1995 81 2 62 12 297

1996 140 2 64 0 250

1997 105 2 78 0 257

1998 105 2 64 10 243

1999 105 2 76 0 251

Projections Food gap

SQ NR (w/o food aid)

2000 105 2 76 10 0 263

2005 115 2 82 28 7 285

2010 121 2 92 45 21 310

Growth in grain production and

imports will be sufficient to provide

enough food to meet nearly all of

the nutritional requirements

through the next decade. However,

consumption in only the top

income groups will exceed the minimum nutritional target in 2010.

1st 2nd 3rd 4th 5th

0

20

40

60

80

100

120

Percent

Consumption by income quintile

in 2010

Share of nutritional requirements
 " ✺ 

				
 
	



Statistical table 23--Zambia (Southern Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,309 234 0 342 1,316

1992 597 227 188 535 2,947

1993 1,759 252 342 11 1,593

1994 1,195 243 55 12 1,576

1995 929 239 80 73 2,378

1996 1,563 251 138 8 1,420

1997 1,157 280 101 8 1,493

1998 702 322 338 39 2,033

1999 1,015 335 222 5 1,945

Projections Food gap

SQ NR (w/o food aid)

2000 1,142 321 228 0 479 1,914

2005 1,109 351 230 15 719 1,932

2010 1,233 383 243 70 862 2,120

Production would need to grow

nearly 1 percentage point faster

than the projected growth rate to

achieve the growth necessary to

close the nutritional food gap.

Consumption in all income groups

is projected to fall short of the minimum nutritional requirement 

in 2010.

2000 2005 2010

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Mil. tons

All food availability versus

requirement

Nutritional requirement

Statistical table 24--Zimbabwe (Southern Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 2,139 47 0 87 992

1992 675 52 583 896 4,189

1993 2,249 57 586 16 2,956

1994 2,622 58 86 5 1,210

1995 1,225 64 118 3 3,801

1996 2,900 65 457 1 2,757

1997 2,417 68 216 0 2,137

1998 1,870 69 214 82 2,489

1999 1,945 72 201 0 2,976

Projections Food gap

SQ NR (w/o food aid)

2000 2,175 73 216 0 373 2,707

2005 2,412 82 243 0 168 3,064

2010 2,576 91 287 0 62 3,333

Per capita consumption is projected to grow more than 1 percent

per year through the next decade.

Production is projected to rise

nearly 2 percent per year while

population growth will continue its

slowdown, equaling just 1 percent

in 2010.

2000 2005 2010

0

1.0

2.0

3.0

4.0

5.0

Mil. tons

All food availability versus

requirement

Nutritional requirement

	

 

				


✺ #

Statistical table 25--Benin (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 524 802 138 7 1,469

1992 602 782 161 19 1,560

1993 635 843 106 26 1,619

1994 635 868 85 15 1,611

1995 746 914 94 9 1,765

1996 651 1,018 81 12 1,701

1997 805 1,244 86 31 1,966

1998 795 1,284 111 11 1,900

1999 835 1,497 106 9 2,164

Projections Food gap

SQ NR (w/o food aid)

2000 800 1,414 107 105 0 2,060

2005 953 1,570 114 150 0 2,320

2010 1,065 1,741 127 227 0 2,581

Production growth averaged nearly

5 percent per year between 1980-

98. Although this is projected to

slow to just over 2 percent by

2010, food supplies will be 

adequate to meet minimum nutritional requirements.

1991 93 95 97 99

0

200

400

600

800

1,000

1,200

1,400

1,600

Grain production

Root prod. (in grain equiv.)

Crop production 

1,000 tons

Statistical table 26--Burkina Faso (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 2,220 21 108 101 2,668

1992 2,438 31 122 31 2,868

1993 2,515 22 114 27 2,997

1994 2,453 19 104 19 2,879

1995 2,265 22 101 26 2,727

1996 2,425 21 104 31 2,895

1997 1,965 18 141 27 2,440

1998 2,640 20 134 75 3,116

1999 2,590 20 145 10 3,133

Projections Food gap

SQ NR (w/o food aid)

2000 2,590 19 142 0 28 3,031

2005 2,922 20 137 0 117 3,391

2010 3,270 21 137 129 264 3,773

The projected production growth

rate of 2.4 percent per year

through the next decade marks a

significant slowdown relative to 

the historical period. However, 

food gaps in the long term will

remain small.

2000 2005 2010

0

1.0

2.0

3.0

4.0

5.0

Mil. tons

All food availability versus

requirement

Nutritional requirement
 $ ✺ 

				
 
	



Statistical table 27--Cape Verde (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 4 3 0 76 128

1992 10 2 86 45 158

1993 12 4 13 58 142

1994 9 3 20 64 145

1995 10 2 29 50 152

1996 10 2 12 58 136

1997 10 2 22 50 135

1998 10 2 25 61 151

1999 10 2 2 72 140

Projections Food gap

SQ NR (w/o food aid)

2000 10 2 17 66 19 82

2005 14 2 16 79 26 87

2010 15 2 18 94 35 90

Cape Verde depends more upon

imports than domestic production

to fulfill food requirements.

Commercial import growth is projected to be slow—less than 1 percent per year—and food gaps will

grow as a result.

2000 2005 2010

0

20

40

60

80

100

120

140

1,000 tons

All food availability versus

requirement

Nutritional requirement

Statistical table 28--Chad (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 794 212 0 67 1,382

1992 836 183 51 0 1,410

1993 671 176 58 17 1,283

1994 846 186 33 15 1,397

1995 779 215 26 8 1,470

1996 786 215 13 32 1,490

1997 916 220 29 28 1,690

1998 1,236 220 32 15 1,991

1999 1,096 220 56 11 1,896

Projections Food gap

SQ NR (w/o food aid)

2000 1,216 225 40 0 0 1,986

2005 1,358 248 39 0 19 2,225

2010 1,569 273 40 0 4 2,545

Grain production grew more than 4

percent per year during the last

two decades due principally to

acreage expansion. While growth

is projected to slow to 3 percent

per year through 2010, it will be

adequate to maintain base per

capita consumption levels.

1990 92 94 96 98

0

500

1,000

1,500

2,000

0

0.2

0.4

0.6

0.8

1.0

1,000 ha Tons/ha

Grain production and yields

Yield

Area

	

 

				


✺ %

Statistical table 29--Côte d’Ivoire (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,031 1,579 574 36 3,739

1992 962 1,619 561 41 3,757

1993 1,009 1,629 600 45 3,773

1994 1,042 1,669 444 56 3,709

1995 1,092 1,689 680 30 3,997

1996 1,160 1,744 522 45 3,958

1997 1,130 1,786 738 26 4,159

1998 1,078 1,759 821 35 4,349

1999 1,140 1,752 657 3 4,228

Projections Food gap

SQ NR (w/o food aid)

2000 1,170 1,817 777 0 0 4,409

2005 1,326 1,996 822 0 0 4,843

2010 1,481 2,190 904 0 0 5,347

Production growth of more than 2

percent per year, coupled with

import growth of nearly 2 percent,

is adequate to provide enough

food to meet nutritional requirements through 2010. Consumption

in each income group is projected

to exceed the minimum nutritional

target.

1990 1995 2000 2005 2010

0

500

1,000

1,500

2,000

2,500

3,000

Sources of grain 

1,000 tons

Food aid

Commercial imports

Production

Statistical table 30--Gambia (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 108 2 80 10 284

1992 87 2 78 6 261

1993 93 2 67 11 265

1994 101 2 86 2 275

1995 101 2 118 3 327

1996 101 2 123 6 338

1997 83 2 107 5 303

1998 94 2 117 6 321

1999 94 2 90 5 300

Projections Food gap

SQ NR (w/o food aid)

2000 94 2 105 18 1 309

2005 109 2 98 55 35 315

2010 126 2 95 82 60 332

Per capita food availability is 

projected to fall 1.6 percent per

year through the next decade.

Consumption in all income groups

is projected to fall short of the 

minimum nutritional requirements

in 2010.

2000 2005 2010

0

50

100

150

200

250

Per capita food availability 

Kg
! ✺ 

				
 
	



Statistical table 31--Ghana (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,375 2,585 203 215 4,140

1992 1,198 2,469 326 75 4,203

1993 1,582 2,665 253 126 4,651

1994 1,532 2,382 403 101 4,758

1995 1,737 2,717 219 43 4,962

1996 1,673 2,960 261 63 5,075

1997 1,578 2,954 354 69 5,209

1998 1,665 3,100 448 27 5,427

1999 1,685 3,461 446 39 5,946

Projections Food gap

SQ NR (w/o food aid)

2000 1,635 3,393 438 0 0 5,736

2005 2,123 3,769 465 0 0 6,689

2010 2,460 4,179 520 0 0 7,528

While the projected production

growth rate will be less than half of

that of the historical period, it will

be sufficient to preclude food gaps

through the next decade.

Consumption in all but the lowest

income group will exceed nutritional requirements in 2010.

2000 2005 2010

0

2

4

6

8

10

Mil. tons

All food availability versus

requirement

Status quo requirement

Statistical table 32--Guinea (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 581 232 237 30 1,521

1992 505 255 285 30 1,576

1993 553 277 243 46 1,658

1994 574 284 331 29 1,731

1995 600 298 377 8 1,830

1996 610 319 283 6 1,786

1997 630 346 294 6 1,791

1998 630 372 236 26 1,777

1999 640 372 350 0 1,885

Projections Food gap

SQ NR (w/o food aid)

2000 640 371 302 0 0 1,839

2005 740 404 300 66 0 2,006

2010 832 439 309 139 0 2,190

Projected production growth of 2

percent per year will be sufficient

to supply enough food to meet

nutritional requirements through

2010. However, food supplies will

not maintain base per capita 

consumption levels.

1990 1995 2000 2005 2010

0

200

400

600

800

1,000

1,200

1,400

Sources of grain 

1,000 tons

Food aid

Commercial imports

Production

	

 

				


✺ !

Statistical table 33--Guinea-Bissau (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 172 22 42 21 303

1992 125 24 72 9 277

1993 134 24 61 9 271

1994 154 24 64 2 294

1995 152 25 60 2 291

1996 150 26 66 6 305

1997 145 26 71 3 303

1998 125 26 48 21 282

1999 145 26 99 0 335

Projections Food gap

SQ NR (w/o food aid)

2000 145 27 75 10 0 308

2005 162 28 74 24 0 329

2010 180 30 77 32 0 356

Food supplies are projected to be

adequate to meet nutritional

requirements at the aggregate

level during the next decade.

However, skewed distribution of

income will limit food access for

roughly 40 percent of the population where consumption will fall

short of nutritional requirements 

in 2010.

2000 2005 2010

0

100

200

300

400

500

1,000 tons

All food availability versus

requirement

Status quo requirement

Statistical table 34--Liberia (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 120 135 38 136 560

1992 61 141 0 149 486

1993 39 127 34 146 495

1994 30 131 0 183 478

1995 35 99 86 132 535

1996 60 116 122 88 574

1997 100 146 134 45 617

1998 125 158 123 102 726

1999 160 158 148 53 748

Projections Food gap

SQ NR (w/o food aid)

2000 160 157 140 133 41 679

2005 135 168 138 300 191 671

2010 144 180 141 437 309 706

Despite the fact that the country’s

security situation has stabilized

and the agricultural recovery has

begun, food gaps are projected to

grow. In 2010, consumption in all

income groups will fall short of

nutritional requirements.

2000 2005 2010

0

10

20

30

40

50

60

70

Percent

Food gaps as a share of total

availability

Status quo gap

Nutritional gap
! ✺ 

				
 
	



Statistical table 35--Mali (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 2,245 8 185 51 2,949

1992 1,714 6 63 35 2,276

1993 1,965 9 57 29 2,459

1994 2,234 7 23 16 2,804

1995 2,050 8 86 8 2,645

1996 2,075 9 46 29 2,623

1997 2,000 10 81 31 2,481

1998 2,275 12 94 12 2,815

1999 2,325 12 98 3 2,902

Projections Food gap

SQ NR (w/o food aid)

2000 2,325 12 95 0 0 2,856

2005 2,573 14 100 0 14 3,157

2010 2,853 15 111 81 119 3,502

Grain output grew nearly 5 percent

per year between 1980 and 1999,

supported mainly by a large jump

in area planted. Although this

growth is projected to slow during

the next decade as area expansion

slows, it will be nearly adequate to

meet nutritional requirements

through 2010.

2000 2005 2010

0

1.0

2.0

3.0

4.0

Mil. tons

All food availability versus

requirement

Nutritional requirement

Statistical table 36--Mauritania (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 96 2 275 50 673

1992 103 1 164 45 571

1993 158 1 189 63 677

1994 204 1 174 22 673

1995 210 1 174 28 723

1996 195 1 245 24 768

1997 108 1 265 27 720

1998 158 1 736 24 821

1999 193 1 249 13 372

Projections Food gap

SQ NR (w/o food aid)

2000 193 1 421 30 10 640

2005 191 2 408 185 162 580

2010 210 2 414 286 260 581

Growth in food production will fall

well short of that needed to meet

status quo or nutritional food

requirements through the next

decade. Per capita consumption is

projected to decline more than 3

percent per year through 2010.

2000 2005 2010 0

10

20

30

40

50

60

Percent

Food gaps as a share of total

availability

Status quo gap

Nutritional gap

	

 

				


✺ !

Statistical table 37--Niger (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 2,290 86 88 45 2,682

1992 2,227 92 95 28 2,623

1993 2,119 93 89 33 2,517

1994 2,190 99 67 39 2,626

1995 2,153 100 48 19 2,602

1996 2,296 100 14 46 2,825

1997 2,195 97 21 45 2,902

1998 2,940 103 34 59 3,640

1999 2,645 116 50 0 3,356

Projections Food gap

SQ NR (w/o food aid)

2000 2,845 108 36 0 0 3,425

2005 3,087 120 38 209 0 3,736

2010 3,398 133 41 451 77 4,121

Food production is projected to

grow just over 2 percent per year

through 2010. This growth would

need to accelerate by more than 1

percentage point to maintain base

per capita consumption levels.

2000 2005 2010

0

1.0

2.0

3.0

4.0

5.0

Mil. tons

All food availability versus

requirement

Status quo requirement

Statistical table 38--Nigeria (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 17,531 12,885 751 1 28,617

1992 18,248 14,717 979 0 30,889

1993 19,278 15,637 1,572 0 34,128

1994 19,897 16,348 922 0 33,884

1995 20,810 16,636 995 0 35,638

1996 18,885 17,230 1,216 0 34,428

1997 18,700 15,678 1,755 1 33,539

1998 19,390 18,482 2,937 0 37,098

1999 19,645 18,528 1,600 0 36,542

Projections Food gap

SQ NR (w/o food aid)

2000 19,345 18,386 2,139 344 0 36,394

2005 23,073 20,182 2,095 0 0 41,540

2010 25,673 22,119 2,138 0 0 45,744

Per capita consumption is projected to hold fairly steady at base

levels, and there will be no long

term food gaps. Consumption

across all income groups is 

projected to exceed nutritional

requirements in 2010.

1st 2nd 3rd 4th 5th 0

20

40

60

80

100

120

140

160

Percent

Consumption by income quintile

in 2010

Share of nutritional requirements
! ✺ 

				
 
	



Statistical table 39--Senegal (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 900 14 555 65 2,201

1992 817 20 528 71 2,198

1993 1,029 19 563 38 2,466

1994 886 31 569 18 2,288

1995 1,005 23 697 9 2,562

1996 917 16 777 6 2,557

1997 706 20 607 10 2,326

1998 686 25 859 15 2,712

1999 928 17 748 18 2,855

Projections Food gap

SQ NR (w/o food aid)

2000 898 22 762 0 0 2,801

2005 866 23 770 79 0 2,826

2010 941 23 808 265 108 3,018

Production and import growth will

be outstripped by population

growth that is projected at 2.5 percent per year through the next

decade. As a result, per capita

consumption will fall 1.5 percent

per year, and consumption in only

the top income group will exceed

minimum nutritional requirements

in 2010.

2000 2005 2010 0

50

100

150

200

250

300

Per capita food availability

Kg

Statistical table 40--Sierra Leone (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 268 50 115 66 783

1992 315 48 114 29 732

1993 321 44 116 29 773

1994 270 104 240 30 800

1995 193 95 236 48 867

1996 260 118 239 58 935

1997 275 129 261 32 831

1998 235 119 246 70 849

1999 255 93 310 20 852

Projections Food gap

SQ NR (w/o food aid)

2000 255 120 291 63 142 941

2005 262 129 312 124 212 996

2010 273 138 349 166 264 1,079

Civil disturbances continued

through the summer, adversely

affecting planting that takes place

in May and June. Distribution of

inputs and relief supplies were also

interrupted. Consumption across

all income groups is projected to

fall short of the nutritional requirement in 2010.

2000 2005 2010 0

200

400

600

800

1,000

1,200

1,400

1,000 tons

All food availability versus

requirement

Nutritional requirement

	

 

				


✺ !!

Statistical table 41--Togo (West Africa)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 427 327 89 14 806

1992 492 302 156 4 912

1993 611 351 55 11 999

1994 405 289 48 8 700

1995 450 416 69 4 933

1996 600 423 88 5 1,141

1997 705 470 104 6 1,262

1998 565 469 138 4 1,194

1999 620 469 67 4 1,219

Projections Food gap

SQ NR (w/o food aid)

2000 620 488 104 61 0 1,222

2005 801 546 100 0 0 1,454

2010 912 610 101 22 0 1,628

The nutritional food gap, on the

aggregate level, is projected to be

zero in the long term. Skewed

income distribution, however, will

preclude roughly 40 percent of the

population from consuming a nutritionally adequate diet in 2010.

1990 1995 2000 2005 2010 0

200

400

600

800

1,000

1,200

Sources of grain 

1,000 tons

Food aid

Commercial imports

Production

Statistical table 42--Afghanistan (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 2,830 86 82 56 3,625

1992 2,830 86 45 108 3,676

1993 2,930 88 144 71 3,773

1994 3,210 88 0 151 3,949

1995 3,320 90 76 124 4,313

1996 3,420 90 12 174 4,311

1997 3,510 90 158 85 4,428

1998 3,620 90 163 73 3,743

1999 3,630 90 120 117 3,863

Projections Food gap

SQ NR (w/o food aid)

2000 2,675 93 151 1,273 1,928 3,515

2005 3,889 100 147 1,331 2,166 4,772

2010 4,150 108 149 1,847 2,795 5,086

Per capita consumption in 1999

was roughly half of the mid-1980s

level. It is projected to fall more

than 1 percent per year through

2010. In even the highest income

group, consumption is projected at

only 80 percent of nutritional

requirements.

2000 2005 2010 0

10

20

30

40

50

60

70

Percent

Food gaps as a share of total

availability

Status quo gap

Nutritional gap
!" ✺ 

				
 
	



Statistical table 43--Bangladesh (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 19,301 422 162 1,469 23,636

1992 19,452 454 784 719 24,171

1993 19,264 446 332 745 23,648

1994 18,011 457 0 858 21,836

1995 18,979 467 1,849 755 25,179

1996 20,299 472 1,976 527 26,622

1997 20,365 469 1,106 531 25,815

1998 21,706 478 2,463 1,301 26,990

1999 23,480 515 1,137 895 30,044

Projections Food gap

SQ NR (w/o food aid)

2000 23,350 501 1,710 0 0 28,942

2005 24,490 540 1,972 0 0 30,682

2010 26,434 582 2,408 0 0 33,450

Production growth is projected at

only about 1.6 percent per year.

However, population growth is projected to slow from a current rate

of more than 1.7 percent to 1.5

percent by 2010. As a result, food

supplies will be sufficient to preclude food gaps throughout the

next decade.

1991 93 95 97 99 0

500

1,000

1,500

2,000

2,500

Imports in Bangladesh 

1,000 tons

Food aid

Commercial grain imports

Statistical table 44--India (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 155,744 5,248 0 277 229,112

1992 165,337 5,597 1,352 261 234,785

1993 168,530 5,239 67 336 239,764

1994 170,844 5,906 0 271 247,063

1995 174,870 5,845 0 268 249,759

1996 177,758 6,102 393 275 258,468

1997 182,842 7,493 2,075 264 263,507

1998 184,020 5,955 1,902 323 263,796

1999 189,430 7,118 1,842 246 272,394

Projections Food gap

SQ NR (w/o food aid)

2000 194,300 7,112 2,113 0 0 281,692

2005 208,776 7,788 2,402 0 0 304,313

2010 226,431 8,520 2,894 0 0 330,988

Sustained growth in grain production, relatively strong growth in

commercial import capacity, and a

slowdown in population growth will

ensure nutritionally adequate food

supplies for each income group 

in 2010.

1980 85 90 95 2000

94

96

98

100

102

104

106

108

0

0.5

1.0

1.5

2.0

2.5

Grain area and yields

Mil. ha Tons/ha

Yield

Area

	

 

				


✺ !#

Statistical table 45--Indonesia (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 36,750 5,713 2,787 59 52,685

1992 36,968 5,977 3,314 41 55,535

1993 35,715 6,218 3,084 52 54,193

1994 38,433 5,695 5,363 15 56,097

1995 39,215 5,755 8,664 12 62,596

1996 38,034 6,204 6,998 0 62,015

1997 36,818 5,496 5,294 9 56,702

1998 38,600 5,450 1,877 973 55,678

1999 38,300 5,670 5,744 487 62,713

Projections Food gap

SQ NR (w/o food aid)

2000 38,300 5,694 4,497 0 0 59,794

2005 42,589 6,068 5,171 0 0 66,323

2010 46,020 6,461 6,007 0 0 72,239

Food production growth is projected to slow relative to historical

levels. However, population growth

is projected to slow as well. Per

capita consumption will rise and

consumption in even the lowest

income group will equal 117 percent of nutritional requirements 

in 2010.

1st 2nd 3rd 4th 5th 0

25

50

75

100

125

150

Percent

Consumption by income quintile

in 2010

Share of nutritional requirements

Statistical table 46--Korea, Dem. People's Rep. (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 3,855 315 1,578 0 6,779

1992 3,723 350 1,130 0 6,114

1993 3,423 163 1,570 0 5,805

1994 3,825 232 495 75 5,463

1995 3,375 176 219 736 5,447

1996 3,175 207 470 508 5,269

1997 3,075 182 500 833 5,571

1998 3,400 128 0 1,036 5,547

1999 3,450 457 692 339 5,983

Projections Food gap

SQ NR (w/o food aid)

2000 2,900 265 401 1,155 997 4,611

2005 3,573 282 394 786 617 5,353

2010 3,762 300 405 835 658 5,610

Per capita consumption fell 25 percent during the 1990s. Production

is projected to grow at roughly the

same rate as population through

the next decade. Consumption in

only the top income group will

exceed nutritional requirements 

in 2010.

1980 85 90 95 2000

0

0.5

1.0

1.5

2.0

2.5

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Grain area and yields

Mil. ha Tons/ha

Yield

Area
!$ ✺ 

				
 
	



Statistical table 47--Nepal (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 4,437 199 8 8 4,921

1992 4,003 198 44 18 4,644

1993 4,075 199 17 44 4,747

1994 4,427 211 50 26 5,234

1995 4,585 223 16 42 5,438

1996 4,985 237 59 28 5,721

1997 5,110 251 22 33 5,847

1998 5,165 253 2 52 5,967

1999 5,308 280 59 6 6,200

Projections Food gap

SQ NR (w/o food aid)

2000 5,310 270 31 165 0 6,074

2005 5,813 291 35 328 0 6,648

2010 6,301 312 42 536 0 7,212

Production growth is projected to be

outstripped by population growth

that remains high relative to other

countries in the region—more than

2 percent per year. The diets of

roughly 40 percent of the population

will be nutritionally inadequate.

2000 2005 2010

0

100

200

300

400

500

600

Commercial imports

Status quo gaps

Grain imports and food gaps

1,000 tons

Statistical table 48--Pakistan (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 19,390 248 604 373 31,599

1992 20,458 279 1,816 236 32,246

1993 21,915 301 2,832 67 36,286

1994 20,537 331 1,829 93 36,127

1995 22,833 343 2,680 18 38,359

1996 23,013 336 1,942 48 38,868

1997 22,826 316 2,355 159 38,991

1998 25,285 425 2,232 300 41,180

1999 24,774 425 2,256 267 43,068

Projections Food gap

SQ NR (w/o food aid)

2000 27,720 402 2,442 0 0 45,030

2005 28,687 444 2,675 0 0 48,013

2010 32,208 488 3,058 0 0 53,971

Per capita consumption is projected to decline marginally as production and import growth fall just

short of the high population

growth. However, nutritional food

needs will be met across all

income groups through 2010.

1st 2nd 3rd 4th 5th 0

50

100

150

200

Percent

Consumption by income quintile

share of nutritional requirements

2010

2000

	

 

				


✺ !%

Statistical table 49--Philippines (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 10,426 924 1,652 48 17,037

1992 11,000 934 2,003 53 16,731

1993 11,480 940 2,150 52 17,856

1994 11,343 972 2,391 44 18,705

1995 11,587 978 2,819 11 18,394

1996 11,480 984 2,420 40 19,183

1997 10,016 992 3,763 9 19,626

1998 11,568 909 4,786 3 20,669

1999 12,295 909 3,387 128 20,418

Projections Food gap

SQ NR (w/o food aid)

2000 11,900 955 4,214 0 0 21,450

2005 12,182 1,003 4,560 0 0 22,271

2010 12,863 1,053 5,192 0 0 23,972

Although there are no food gaps at

the aggregate level, consumption

for roughly 20 percent of the population will fall below minimum nutritional requirements. Growth in

grain yields is projected at 1 percent per year—half that of the 

historical period. Grain area is 

projected to stagnate.

2000 2005 2010

255

260

265

270

275

280

285

Total annual food availability

Kg per capita

Statistical table 50--Sri Lanka (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,691 162 423 439 4,264

1992 1,649 140 818 249 4,417

1993 1,748 145 806 338 4,507

1994 1,905 140 596 346 4,910

1995 1,679 138 1,034 120 4,731

1996 1,502 137 1,242 57 4,744

1997 1,758 118 1,257 83 5,007

1998 1,845 107 1,106 82 5,092

1999 1,815 107 1,150 49 5,138

Projections Food gap

SQ NR (w/o food aid)

2000 1,815 111 1,222 0 0 5,194

2005 1,879 115 1,323 0 0 5,460

2010 1,927 119 1,494 0 0 5,831

Population growth is projected to

remain steady at 1 percent per

year—the lowest rate in the region.

Food supplies are projected to be

adequate throughout the next

decade. Consumption in all income

groups is projected to exceed minimum nutritional requirements.

1990 1995 2000 2005 2010 0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Sources of grain

1,000 tons

Food aid

Commercial imports

Production
" ✺ 

				
 
	



Statistical table 51--Vietnam (Asia)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 15,310 1,488 190 80 17,635

1992 15,389 1,654 156 84 17,005

1993 16,931 1,561 293 87 18,978

1994 17,390 1,400 248 64 19,217

1995 18,860 1,281 466 20 20,860

1996 19,540 1,246 388 65 19,900

1997 20,744 1,213 418 49 21,029

1998 21,720 1,120 688 50 22,003

1999 22,500 1,197 603 0 26,073

Projections Food gap

SQ NR (w/o food aid)

2000 22,200 1,211 622 33 0 23,638

2005 24,261 1,311 784 0 0 25,996

2010 26,227 1,420 1,049 0 0 28,410

Growth in grain output is expected

to slow considerably from the historical rate of more than 5 percent

per year. However, per capita consumption relative to nutritional

requirements will remain the highest in the region through 2010.

1980 83 86 89 92 95 99

0

50

100

150

200

250

300

350

Kg/ha

Fertilizer use, 1980-99

Kilogram per hectare arable land

Statistical table 52--Bolivia (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 760 309 143 238 1,732

1992 780 291 130 243 1,699

1993 1,055 318 89 205 1,808

1994 875 268 155 176 1,664

1995 825 272 247 94 1,805

1996 965 296 92 143 1,789

1997 1,090 336 71 149 1,916

1998 1,015 250 81 144 1,935

1999 950 338 249 23 2,012

Projections Food gap

SQ NR (w/o food aid)

2000 965 323 173 128 189 1,876

2005 1,395 364 181 0 0 2,479

2010 1,712 408 198 0 0 3,008

Grain production is projected to

continue and even accelerate its

fast growth of about 4 percent per

year. Yield improvements are the

driving force for fast production

increases that may succeed in

eliminating all food gaps within a

few years.

1994 96 98 2000

0

200

400

600

800

1,000

1,200

1,400

1.0

1.2

1.4

1.6

1.8

Grain production and yields

1,000 tons Tons/ha

Yield

Production

	

 

				


✺ "

Statistical table 53--Colombia (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 2,777 1,053 792 8 9,096

1992 2,804 1,037 1,592 17 9,844

1993 2,777 1,250 1,697 31 9,726

1994 2,610 1,257 2,392 15 10,423

1995 2,469 1,247 2,582 0 10,596

1996 2,129 1,296 3,267 9 11,451

1997 1,834 1,172 3,290 7 10,918

1998 2,026 1,116 3,861 11 11,861

1999 2,214 1,256 3,109 0 11,513

Projections Food gap

SQ NR (w/o food aid)

2000 2,219 1,220 3,754 0 0 12,334

2005 2,144 1,316 4,400 0 0 13,704

2010 2,241 1,416 5,389 0 0 15,956

In 1999, Colombia suffered its

worst recession in 60 years.

However, there is reason to hope

that economic growth will be positive in 2000 and continue to

improve. Commercial imports will

be the main source of grains, projected to increase 70 percent over

the next 10 years.

2000 2005 2010

0

1,000

2,000

3,000

4,000

5,000

6,000 Production

Com. imports

Grain imports and food production 

1,000 tons

Statistical table 54--Dominican Republic (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 343 76 732 14 1,688

1992 390 84 786 7 1,704

1993 350 57 972 7 1,949

1994 329 63 925 3 1,899

1995 316 85 1,018 1 1,990

1996 360 78 1,017 2 1,955

1997 301 63 1,152 5 2,137

1998 282 77 960 31 1,869

1999 307 82 1,100 0 1,977

Projections Food gap

SQ NR (w/o food aid)

2000 305 77 1,192 0 0 2,245

2005 316 85 1,460 0 0 2,765

2010 330 94 1,872 0 0 3,587

While food production is projected

to virtually stagnate over the next

10 years, commerical imports are

expected to increase more than 60

percent. Improvements in food

security thus depend on sufficient

export earnings to pay for these

grain imports.

1991 93 95 97 99

0

500

1,000

1,500

2,000

Production

Imports

Grain production and imports

1,000 tons
" ✺ 

				
 
	



Statistical table 55--Ecuador (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 956 104 416 45 2,795

1992 1,028 128 346 14 2,761

1993 1,104 113 271 12 2,582

1994 1,050 137 322 32 2,738

1995 1,009 123 377 1 2,792

1996 767 120 433 8 3,027

1997 831 164 643 20 2,682

1998 791 136 1,063 20 3,389

1999 901 196 661 70 3,012

Projections Food gap

SQ NR (w/o food aid)

2000 861 165 854 0 0 3,177

2005 959 174 977 0 0 3,555

2010 1,012 183 1,163 0 0 4,024

While 1999 was a year of economic crisis, 2000 brought several

encouraging changes: the dollar

was chosen as the country's currency, part of the large foreign debt

could be renegociated, and an

agreement with the IMF has contributed to raising confidence in the

Ecuadorean economy, which helps

to attract international investors.

1990 1995 2000 2005 2010 0

500

1,000

1,500

2,000

2,500

Sources of grain 

1,000 tons

Food aid

Commercial imports

Production

Statistical table 56--El Salvador (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 699 11 373 86 1,551

1992 953 15 147 131 1,455

1993 858 14 213 79 1,359

1994 690 32 469 7 1,533

1995 873 27 415 14 1,454

1996 841 26 398 7 1,202

1997 860 26 567 8 1,693

1998 790 20 325 49 1,284

1999 855 26 474 0 1,598

Projections Food gap

SQ NR (w/o food aid)

2000 890 25 459 0 0 1,545

2005 942 27 453 0 0 1,580

2010 1,030 30 465 24 0 1,685

Even though El Salvador does not

have a national nutritional food

gap, the share of people unable to

purchase nutritionally adequate

diets is projected to increase from

40 percent to 60 percent over the

next 10 years. The skewed income

distribution as well as insufficient

income keep the poor segments of

the population in food insecurity.

1980 83 86 89 92 95 98

0

2,000

4,000

6,000

8,000

10,000

12,000

GDP, 1995 U.S dollars

Mil. dollars

	

 

				


✺ "

Statistical table 57--Guatemala (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,355 14 176 252 2,242

1992 1,454 16 280 109 2,271

1993 1,400 17 276 151 2,230

1994 1,343 17 431 144 2,417

1995 1,423 17 460 35 2,371

1996 1,436 17 599 45 2,363

1997 1,258 17 588 18 2,289

1998 1,235 17 719 43 2,443

1999 1,285 17 853 110 2,774

Projections Food gap

SQ NR (w/o food aid)

2000 1,285 18 800 0 0 2,540

2005 1,368 21 973 0 6 2,845

2010 1,446 24 1,249 0 0 3,295

In Guatemala as in other countries

in the region, commercial imports

become increasingly important

compared with domestic food production. By 2010, imports are projected at 46 percent of grain supplies, up from 12 percent in 1990

and 36 percent in 2000.

1991 93 95 97 99

0

500

1,000

1,500

2,000

2,500

Production

Imports

Grain production and imports

1,000 tons

Statistical table 58--Haiti (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 330 225 218 55 1,380

1992 320 231 268 75 1,447

1993 340 223 217 114 1,411

1994 330 216 159 117 1,353

1995 345 219 291 126 1,591

1996 345 215 210 151 1,549

1997 405 211 203 146 1,660

1998 455 213 284 139 1,796

1999 455 217 424 101 1,940

Projections Food gap

SQ NR (w/o food aid)

2000 455 218 309 85 225 1,713

2005 474 231 297 202 353 1,749

2010 503 245 296 297 462 1,817

Presidential elections in Haiti were

held in for November 2000.

Political deadlock has made political as well as economic progress

impossible. Poverty and hunger

continue to be pervasive.

The lowest income quintile is projected to consume only 57 percent

of its nutritional requirements.

2000 2005 2010

0

100

200

300

400

500

600

Nutritional gap

Commercial imports

Grain imports and food gaps 

1,000 tons
" ✺ 

				
 
	



Statistical table 59--Honduras (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 693 7 100 160 1,087

1992 710 8 73 64 1,059

1993 690 8 67 149 1,118

1994 617 7 251 73 1,187

1995 780 7 233 43 1,230

1996 679 8 212 36 1,085

1997 705 8 398 20 1,432

1998 560 9 123 92 1,152

1999 613 9 301 88 1,368

Projections Food gap

SQ NR (w/o food aid)

2000 613 9 304 50 170 1,290

2005 723 10 366 8 144 1,509

2010 776 11 462 0 120 1,726

Hurricane Mitch hit Honduras in fall

1998, but its repercussions continue to be felt. However, as

houses and infrastructure are

being repaired, prospects for an

improved food security situation

become brighter. The nutritional

food gap is projected to halve during the next 10 years.

2000 2005 2010

0

100

200

300

400

500

600

Nutritional gap

Commercial imports

Grain imports and food gaps 

1,000 tons

Statistical table 60--Jamaica (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 3 72 131 323 756

1992 4 84 252 201 711

1993 5 92 299 157 792

1994 5 97 316 53 674

1995 5 102 379 60 719

1996 5 108 288 27 653

1997 5 90 499 13 836

1998 5 86 489 13 811

1999 5 86 530 0 835

Projections Food gap

SQ NR (w/o food aid)

2000 5 92 524 0 0 864

2005 5 100 533 0 0 884

2010 5 108 557 0 0 929

Jamaica continues to be one of the

better off countries in the region,

and hunger is not prevalent.

However, poverty is rising because

of a weak economy for the last 5

years. Recovery may not start until

2001 or later.

1990 92 94 96 98 1,550

1,600

1,650

1,700

1,750

1,800

GDP per capita 

1990 US dollars

	

 

				


✺ "!

Statistical table 61--Nicaragua (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 409 20 0 156 909

1992 427 20 74 86 943

1993 485 21 88 55 993

1994 290 21 162 34 921

1995 409 21 158 43 994

1996 557 21 197 33 1,072

1997 494 22 170 28 1,035

1998 490 21 65 158 1,034

1999 530 21 61 101 1,021

Projections Food gap

SQ NR (w/o food aid)

2000 530 22 107 24 152 991

2005 580 24 124 76 223 1,083

2010 604 26 153 148 313 1,157

Nicaragua's nutritional gap in 2010

is projected twice as big as total

commercial imports. International

investment into agriculture and

export industries is desparately

needed but will depend on whether

Nicaragua will manage to receive

relief on its $6.3 billion debt.

1991 93 95 97 99 0

50

100

150

200

250

Nicaragua's grain imports

1,000 tons

Food aid

Commercial imports

Statistical table 62--Peru (Latin America & Caribbean)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,250 577 1,227 492 4,370

1992 1,669 462 2,211 377 5,390

1993 1,972 611 1,864 410 5,185

1994 1,821 686 2,231 348 5,715

1995 1,634 850 2,459 105 6,319

1996 1,827 857 2,593 95 6,432

1997 1,953 917 2,565 61 5,973

1998 2,432 1,001 2,756 148 6,677

1999 2,510 1,121 2,849 0 7,098

Projections Food gap

SQ NR (w/o food aid)

2000 2,585 1,056 2,943 0 0 6,994

2005 2,559 1,156 3,497 0 0 7,811

2010 2,723 1,263 4,369 0 0 9,287

Peru now has the highest income

—$2,390 per capita—of all 11 LAC

countries studied here. This year the

economy recovered from the

1998/99 recession, and GDP is

expected to grow 4.5 percent. All

this bodes well for further improvements in food security. Less than 20

percent of the population will fall

short of nutritional requirements.

2000 2005 2010 0

1,000

2,000

3,000

4,000

5,000

6,000

Production

Commercial imports

Grain imports and food production 

1,000 tons
"" ✺ 

				
 
	



Statistical table 63--Armenia (New Independent States)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 292 --- --- --- ---

1992 292 62 456 117 808

1993 301 80 119 277 722

1994 213 77 53 367 870

1995 236 87 -19 267 873

1996 306 82 29 104 758

1997 290 69 79 158 849

1998 320 82 52 11 710

1999 290 82 94 12 729

Projections Food gap

SQ NR (w/o food aid)

2000 188 81 77 97 208 623

2005 384 90 77 0 0 869

2010 412 99 81 0 0 935

Armenia's grain production was 39

percent below trend in 2000. Food

gaps will be relatively severe: food

supplies will be 14 percent below

recent per capita consumption target and 25 percent below nutrition

target. Food supplies in all income

groups may fall short of nutrition

requirements in 2000.

0-20 20-40 40-60 60-80 80-100

0

50

100

150

200

250

300

350

Kg per capita

Armenia's food supplies relative

to requirements by income quintile

2000

2010

Nutritional requirement

Income quintile

Statistical table 64--Azerbaijan (New Independent States)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,324 --- --- --- ---

1992 1,266 30 585 6 1,982

1993 1,084 29 557 58 1,790

1994 1,015 29 -3 424 1,707

1995 878 30 298 167 1,642

1996 1,000 41 327 34 1,696

1997 1,130 43 662 63 2,238

1998 1,020 60 787 13 2,271

1999 1,070 65 624 31 2,191

Projections Food gap

SQ NR (w/o food aid)

2000 856 59 735 47 0 2,055

2005 1,233 65 752 0 0 2,486

2010 1,325 72 803 0 0 2,675

Azerbaijan's grain production in

2000 was 11 percent below trend,

leading to a modest food gap.

Food supplies in most income

groups are above nutritional

requirements in both the short 

and long run. Azerbaijan is poised

to gain strongly from recent oil 

and gas pipeline developments in

the region.

1990 95 2000 2005 2010

0

100

200

300

400

500

600

700

800

0

0.5

1.0

1.5

2.0

2.5

1,000 hectares Tons/ha

Azerbaijan area and yield

projections

Area (left)

Yield (right)

	

 

				


✺ "#

Statistical table 65--Georgia (New Independent States)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 565 --- --- --- ---

1992 496 41 394 194 1,370

1993 403 49 260 585 1,291

1994 470 58 165 569 1,265

1995 497 69 175 355 1,265

1996 658 70 523 97 1,422

1997 882 69 502 142 1,434

1998 588 68 412 94 1,427

1999 768 85 439 61 1,461

Projections Food gap

SQ NR (w/o food aid)

2000 330 77 496 26 104 1,069

2005 905 82 501 0 0 1,691

2010 961 87 533 0 0 1,815

Georgia's grain production in 2000

was 43 percent below trend.

However, the country's commercial

import capacity and other factors

may lead to more modest food

gaps. In the short run, many of the

lower income groups may face

inadequate food supplies, but not in

the long run.

1988 90 92 94 96 98 2000

-60

-40

-20

0

20

40

60

Percent of trend

Georgia's grain production: 

Deviation is large

Statistical table 66--Kyrgyzstan (New Independent States)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 1,369 --- --- --- ---

1992 1,510 70 332 91 1,323

1993 1,511 59 119 156 1,183

1994 993 60 140 61 1,119

1995 985 83 83 139 1,263

1996 1,415 108 78 31 1,296

1997 1,713 130 52 70 1,613

1998 1,713 139 105 1 1,575

1999 1,611 184 -5 108 1,659

Projections Food gap

SQ NR (w/o food aid)

2000 1,613 162 53 0 0 1,528

2005 1,926 184 54 0 0 1,867

2010 2,075 209 58 0 0 2,037

Kyrgyzstan's 2000 harvest was not

affected by the drought. Production

should be close to levels of recent

years, which have allowed for a

small volume of exports. Per 

capita food consumption levels

should continue to exceed 

nutrition requirements for most

income groups.

1987 89 91 93 95 97 99

0

20

40

60

80

100

120

140

Index (1990=100)

Kyrgyzstan's area and yield

trends

Area

Yield
"$ ✺ 

				
 
	



Statistical table 67--Tajikistan (New Independent States)

Grain Root Commercial Food aid Aggregate

Year production production imports receipts availability

(grain equiv.) (grains) (grains) of all food

---1,000 tons ---

1991 264 --- --- --- ---

1992 241 32 1,116 71 1,515

1993 236 28 834 82 1,570

1994 237 26 488 104 1,306

1995 226 22 191 168 1,059

1996 516 21 142 115 1,077

1997 606 25 212 141 1,288

1998 506 25 283 40 1,171

1999 506 26 244 66 1,170

Projections Food gap

SQ NR (w/o food aid)

2000 311 25 263 256 520 941

2005 659 27 261 0 243 1,315

2010 710 30 271 0 285 1,399

Tajikistan's drought greatly reduced

production in 2000. Because per

capita consumption was already

low, the shock may lead to relatively severe food gaps in percentage terms. Food supplies are projected to be inadequate for all

income groups in both the short

and long run.

% deviation from trend

Tajikistan's grain production

is down in 2000

1990 92 94 96 98 2000

-40

-30

-20

-10

0

10

20

30

40

50

60
The Food Security Assessment model used in this report

was developed at the USDA-ERS for use in projecting

food consumption and access, and food gaps (previously

called food needs) in 67 low-income countries through

2010. The reference to food includes grains, root crops,

and a category called “other,” which includes all other

commodities consumed, thus covering 100 percent of food

consumption. All of these commodities are expressed in

grain equivalent. 

Food security of a country is evaluated based on the gap

between projected domestic food consumption (produced

domestically plus imported commercially minus nonfood

use) and a consumption requirement. Although food aid is

expected to be available during the projection period, it is

not included in the projection of food consumption. It

should be noted that while projection results will provide a

baseline for the food security situation of the countries, they

depend on assumptions and specifications of the model.

Because the model is based on historical data, it implicitly

assumes that the historical trend in key variables will continue in the future. 

Food gaps are projected using two consumption criteria:

1) Status quo target, where the objective is to maintain average

per capita consumption of the recent past. The most recent 3-

year average (1997-99) is used for the per capita consumption

target to eliminate short-term fluctuations. 

2) Nutrition-based target, where the objective is to maintain

the minimum daily caloric intake standards recommended

by the UN’s Food and Agriculture Organization (FAO). The

caloric requirements (based on total share of grains, root

crops, and “other”) used in this assessment are those necessary to sustain life with minimum food-gathering activities.

They are comparable to the activity level for a refugee—

they do not allow for play, work, or any activity other than

food gathering.

The status quo measure embodies a “safety-net” criterion by

providing food consumption stability at recently achieved

levels. The nutrition-based target assists in comparisons of

relative well-being. Comparing the two consumption measures either for countries or regions provides an indicator of

the need depending on whether the objectives are to achieve

consumption stability and/or to meet a nutritional standard.

Large nutrition-based needs relative to status quo needs, for

example, mean additional food must be provided if

improved nutrition levels are the main objective. In cases

where nutrition-based requirements are below status quo

consumption needs, food availability could decline without

risking nutritional adequacy, on average. Both methods,

however, fail to address inequalities of food distribution

within a country. 

##46	

0
"*			##


)


Projection of Food Availability—The simulation framework used for projecting aggregate food availability is based

on partial equilibrium recursive models of 67 lower income

countries. The country models are synthetic, meaning that

the parameters that are used are either cross country estimates or are estimated by other studies. Each country model

includes three commodity groups; grains, root crops and

“other.” The production side of the grain and root crops is

divided into yield and area response. Crop area is a function

of 1-year lag return (real price times yield), while yield

responds to input use. Commercial imports are assumed to

be a function of domestic price, world commodity price, and

foreign exchange availability. Foreign exchange availability

is a key determinant of commercial food imports and is the

sum of the value of export earnings and net flow of credit.

Foreign exchange availability is assumed to be equal to foreign exchange use, meaning that foreign exchange reserve is

assumed constant during the projection period. Countries

are assumed to be price takers in the international market,

meaning that world prices are exogenous in the model.

However, producer prices are linked to the international

market. The projections of consumption for the “other”

commodities are simply based on a trend that follows the

projected growth in supply of the food crops (grains plus

root crops). Although this is a very simplistic approach, it

represents an improvement from the previous assessments

where the contribution to the diet of commodities such as

meat and dairy products was overlooked. The plan is to

enhance this aspect of the model in the future. 

For the commodity group grains and root crops (c), food

consumption (FC) is defined as domestic supply (DS) minus

nonfood use (NF), n is country index, and t is time index:

FCcnt = DScnt - NFcnt (1)

Nonfood use is the sum of seed use (SD), feed use (FD),

exports (EX), and other uses (OU):

NFcnt = SDcnt + FDcnt + EXcnt + OUcnt (2)

Domestic supply of a commodity group is the sum of

domestic production (PR) plus commercial imports (CI) and

changes in stocks (CSTK):

DScnt = PRcnt + CIcnt + CSTKcnt (3)


	

 

				


✺ "%

Appendix 1—Food Security Model: Definition and Methodology
Production is generally determined by the area and yield

response functions:

PRcnt =ARcnt * YLcnt (4) 

YLcnt = f ( LBcnt ,FRcnt , Kcnt ,Tcnt ) (5)

RPYcnt =YL cnt * DPcnt (6)

RNPYcnt =NYLcnt * NDPcnt (7)

ARcnt = f (ARcnt-1, RPYcnt-1, RNPYcnt-1, Zcnt ) (8)

where AR is area, YL is yield, LB is rural labor, FR is fertilizer

use, K is indicator of capital use, T is the indicator of technology change, DP is real domestic price, RPY is yield times real

price, NDP is real domestic substitute price, NYL is yield of

substitute commodity, RNPY is yield of substitute commodity

times substitute price, and Z is exogenous policies.

The commercial import demand function is defined as:

CIcnt = f (WPRct , NWPRct , FEXnt , PRcnt, Mnt ) (9)

where WPR is real world food price, NWPR is real world

substitute price, FEX is real foreign exchange availability,

and M is import restriction policies.

The real domestic price is defined as:

DPcnt = f (DPcnt-1 , DScnt , NDScnt ,GDnt , EXRnt ) (10)

where NDS is supply of substitute commodity, GD is real

income, and EXR is real exchange rate.

Projections of food consumption by income group—

Inadequate economic access is the most important cause of

chronic undernutrition among developing countries and is

related to the level of income. Estimates of food gaps at the

aggregate or national level fail to take into account the distribution of food consumption among different income

groups. Lack of consumption distribution data for the countries is the key factor preventing estimation of food consumption by income group. We attempted to fill this information gap by using an indirect method of projecting calorie

consumption by different income groups based on income

distribution data.1 It should be noted that this approach

ignores the consumption substitution of different food

groups by income class. The procedure uses the concept of

the income/consumption relationship and allocates the total

projected amount of available food among different income

groups in each country (income distributions are assumed

constant during the projection period). 

Assuming a declining consumption and income relationship

(semi log functional form):

C = a + b ln Y (11)

C = Co/P (12)

P = P1 +........+ Pi (13)

Y = Yo/P (14)

i = 1 to 5

where C and Y are known average per capita food consumption (all commodities in grain equivalent) and per capita

income (all quintiles), Co is total food consumption, P is the

total population, i is income quintile, a is the intercept, b is

the consumption income propensity, and b/C is consumption

income elasticity (point estimate elasticity is calculated for

individual countries). To estimate per capita consumption by

income group, the parameter of b was estimated based on

cross-country (67 low-income countries) data for per capita

calorie consumption and income. The parameter a is estimated for each country based on the known data for average

per capita calorie consumption and per capita income. 

#+##

Historical supply and use data for 1980-99 for most variables are from a USDA database. Data for grain production

in 2000 for most countries are based on a USDA database as

of October 2000. Food aid data are from the UN’s Food and

Agriculture Organization (FAO), and financial data are from

the International Monetary Fund and World Bank. Historical

nonfood-use data, including seed, waste, processing use, and

other use, are estimated from the FAO Food Balance series.

The base year data used for projections are the average for

1997-99, except export earnings that are 1996-98.

Endogenous variables:

Production, area, yield, commercial import, domestic producer price, and food consumption.

Exogenous variables:

Population— data are medium UN population projections as

of 1998. 

World prices—USDA/baseline projections data. 

Stocks—USDA data, assumed constant during the projection

period.

Seed use—USDA data; projections are based on area projections using constant base seed/area ratio. 

Food exports—USDA data, projections are either based 

on the population growth rate or extrapolation of historical

trends.

Inputs—fertilizer and capital projections are, in general, an

extrapolation of historical growth data from FAO.

Agricultural labor—projections are based on UN population

projections, accounting for urbanization growth.

Food aid—historical data from FAO; no food aid assumed

during the projection period.

Gross Domestic Product—World Bank data.

# ✺ 

				
 
	



1 The method is similar to that used by Shlomo Reutlinger and Marcelo

Selowsky in “Malnutrition and Poverty”, World Bank, 1978.
Merchandise and service imports and exports—World Bank

data.

Net foreign credit—is assumed constant during the projection period.

Value of exports—projections are based on World Bank

(Global Economic Prospects and the Developing Countries,

various issues), IMF (World Economic Outlook, various

issues), or an extrapolation of historical growth. 

Export deflator or terms of trade—World Bank

(Commodity Markets—Projection of Inflation Indices for

Developed Countries).

Income— projected based on World Bank report (Global

Economic Prospects and the Developing Countries, various

issues) or extrapolation of historical growth.

Income distribution—World Bank data. Income distributions

are assumed constant during the projection period.

(Shahla Shapouri)


	

 

				


✺ #
# ✺ 

				
 
	



Appendix table-2a--List of countries and their food gaps, 2000 

2000 food gaps 2000 food gaps

Status quo Nutrition Distribution Status quo Nutrition Distribution

1,000 tons 1,000 tons

Cameroon 0 0 113 Algeria 361 518 755

Centr. Afr. Rep. 23 56 118 Egypt 0 0 0

Congo, Dem. Rep. 156 2,141 2,439 Morocco 0 1,045 1,215

Burundi 28 412 462 Tunisia 0 0 0

Eritrea 89 236 252 North Africa 361 1,563 1,970

Ethiopia 793 3,479 3,764

Kenya 0 191 991 Afghanistan 1,273 1,928 2,103

Rwanda 443 436 462 Bangladesh 0 0 641

Somalia 159 939 991 India 0 0 1,557

Sudan 0 0 0 Indonesia 0 0 0

Tanzania 0 838 1,105 Korea, Dem. People's Rep. 1,155 997 1,121

Uganda 274 0 104 Nepal 165 0 68

Angola 231 440 577 Pakistan 0 0 0

Lesotho 25 34 82 Philippines 0 0 0

Madagascar 92 146 366 Sri Lanka 0 0 0

Malawi 0 0 35 Vietnam 33 0 0

Mozambique 132 558 1,034 Asia 2,627 2,925 5,489

Swaziland 10 0 18

Zambia 0 479 582 Bolivia 128 189 277

Zimbabwe 0 373 619 Colombia 0 0 84

Benin 105 0 0 Dominican Rep. 0 0 43

Burkina Faso 0 28 221 Ecuador 0 0 246

Cape Verde 66 19 21 El Salvador 0 0 45

Chad 0 0 149 Guatemala 0 0 235

Côte d’Ivoire 0 0 0 Haiti 85 225 370

Gambia 18 1 17 Honduras 50 170 261

Ghana 0 0 39 Jamaica 0 0 0

Guinea 0 0 78 Nicaragua 24 152 213

Guinea-Bissau 10 0 10 Peru 0 0 124

Liberia 171 42 108 Latin America and

Mali 0 0 93 the Caribbean 287 735 1,897

Mauritania 30 10 53

Niger 0 0 37 Armenia 97 208 30

Nigeria 344 0 5 Azerbaijan 47 0 0

Senegal 0 0 79 Georgia 26 104 0

Sierra Leone 63 142 198 Kyrgyzstan 0 0 0

Togo 61 0 69 Tajikistan 256 520 322

Sub-Saharan Africa 3,325 10,999 15,294 New Independent States 426 832 352

Total 7,026 17,054 25,004

	

 

				


✺ #

Appendix table-2b--List of countries and their food gaps, 2010

2010 food gaps 2010 food gaps

Status quo Nutrition Distribution Status quo Nutrition Distribution

1,000 tons 1,000 tons

Cameroon 237 0 253 Algeria 718 909 1,131

Centr. Afr. Rep. 98 137 192 Egypt 0 0 0

Congo, Dem. Rep. 1,551 4,218 4,578 Morocco 0 0 0

Burundi 142 629 689 Tunisia 0 0 1

Eritrea 237 424 441 North Africa 781 909 1,132

Ethiopia 0 2,525 3,020

Kenya 0 399 1,281 Afghanistan 1,847 2,795 3,048

Rwanda 595 585 616 Bangladesh 0 0 975

Somalia 548 1,640 1,700 India 0 0 0

Sudan 0 0 0 Indonesia 0 0 0

Tanzania 55 1,252 1,537 Korea, Dem. People's Rep. 835 658 861

Uganda 830 0 347 Nepal 536 0 182

Angola 785 1,065 1,201 Pakistan 0 0 0

Lesotho 87 97 138 Philippines 0 0 227

Madagascar 591 661 818 Sri Lanka 0 0 0

Malawi 14 401 461 Vietnam 0 0 0

Mozambique 0 95 844 Asia 3,218 3,454 5,294

Swaziland 45 21 45

Zambia 70 862 976 Bolivia 0 0 19

Zimbabwe 0 62 444 Colombia 0 0 0

Benin 227 0 0 Dominican Rep. 0 0 0

Burkina Faso 129 264 459 Ecuador 0 0 175

Cape Verde 94 35 37 El Salvador 24 0 118

Chad 0 4 203 Guatemala 0 0 287

Côte d’Ivoire 0 0 0 Haiti 297 462 576

Gambia 82 60 68 Honduras 0 120 263

Ghana 0 0 43 Jamaica 0 0 0

Guinea 139 0 155 Nicaragua 148 313 375

Guinea-Bissau 32 0 18 Peru 0 0 0

Liberia 446 264 313 Latin America and

Mali 81 119 250 the Caribbean 470 894 1,813

Mauritania 286 260 284

Niger 451 77 276 Armenia 0 0 30

Nigeria 0 0 0 Azerbaijan 0 0 0

Senegal 265 108 383 Georgia 0 0 0

Sierra Leone 166 264 314 Kyrgyzstan 0 0 0

Togo 22 0 70 Tajikistan 0 285 322

Sub-Saharan Africa 8,303 16,530 22,454 New Independent States 0 285 352

Total 12,709 22,072 31,045
# ✺ 

				
 
	

 Appendix 3--Country indicators 

Region Macroeconomic indicators and Grain production Root Per capita Per capita E

Population Coefficient production Projected GNP GNP GDP e

country Population growth Growth of variation growth annual growth 1998 growth growth g

2000 rate 1980-99 1980-99 1980-99 in supply 1998 1998 

1,000 ---------- Percent ---------- U.S. dollars ---------- P

North Africa: Algeria 31,471 2.3 0.1 45.9 4.4 0.8 1,550 3.6 5.1  Egypt 68,470 1.8 5.0 6.8 3.2 1.2 1,290 4.5 5.6  Morocco 28,351 1.7 1.3 46.7 4.9 1.2 1,240 5.3 6.5  Tunisia 9,586 1.3 2.6 45.7 5.0 1.5 2,060 4.1 5.0 Central Africa: Cameroon 15,085 2.7 1.9 11.0 2.1 2.0 610 3.8 5.0  Central African Rep. 3,615 1.8 1.1 14.3 0.0 1.1 300 2.6 4.7  Congo, Dem.Rep. 51,654 2.6 3.6 9.8 1.5 1.9 110 0.7 3.0 West Africa: Benin 6,097 2.7 4.8 9.1 6.3 2.1 380 1.9 4.5  Burkina Faso 11,937 2.8 5.3 13.7 -5.5 2.2 240 3.8 6.2  Cape Verde 428 2.4 9.3 56.3 1.2 0.6 1,200 2.2 5.0  Chad 7,651 2.6 4.2 18.5 1.1 2.7 230 5.5 8.1  Côte díIvoire 14,786 1.8 2.7 6.0 2.3 1.9 700 3.9 5.4  Gambia 1,305 3.0 1.5 17.2 0.0 1.1 340 2.0 4.7  Ghana 20,212 2.7 7.1 15.3 8.5 2.4 390 1.9 4.6  Guinea 7,430 1.0 3.4 5.9 3.0 1.7 530 1.5 4.5  Guinea-Bissau 1,213 2.2 4.7 18.7 3.3 1.5 160 -30.4 -28.1 - Liberia 3,154 7.6 -5.5 34.4 -0.5 0.9 -- -- --  Mali 11,234 2.5 4.7 11.9 1.9 2.1 250 1.3 3.6  Mauritania 2,670 2.7 9.2 33.8 -0.3 0.6 410 1.5 3.5  Niger 10,730 3.2 2.9 14.7 0.6 2.0 200 4.8 8.4  Nigeria 111,506 2.4 5.9 16.8 9.4 2.0 300 -1.5 1.8  Senegal 9,481 2.6 1.1 19.7 1.7 1.2 520 3.8 5.7  Sierra Leone 4,854 2.9 -2.5 9.3 5.7 1.3 140 -2.9 0.7  Togo 4,629 2.6 4.6 16.2 2.3 2.4 330 -3.5 -1.0 East Africa: Burundi 6,695 2.0 -2.7 16.3 1.5 1.8 140 2.6 4.8  Eritrea 3,850 3.5 1.0 53.9 0.5 1.0 200 -6.7 3.0 - Ethiopia 62,565 2.4 4.0 16.0 2.9 3.0 100 -4.2 -1.0  Kenya 30,080 1.8 0.4 14.6 2.9 1.4 350 0.3 1.8  Rwanda 7,733 2.9 -2.9 13.9 -2.6 1.6 230 7.1 9.5  Somalia 10,097 2.7 -3.5 37.5 2.2 1.2 -- -- --  Sudan 29,490 2.1 3.9 30.7 -3.7 2.3 290 2.7 5.0  Tanzania 33,517 6.9 2.0 12.8 0.0 1.9 220 3.8 3.5 - Uganda 21,778 3.0 2.2 9.2 1.0 2.4 310 2.8 5.6 -

See note at end of table. 

	

 

				


✺ #! Appendix 3--Country indicators--Continued 

Region Macroeconomic indicators and Grain production Root Per capita Per capita E

Population Coefficient production Projected GNP GNP GDP e

country Population growth Growth of variation growth annual growth 1998 growth growth g

2000 rate 1980-99 1980-99 1980-99 in supply 1998 1998 

1,000 ---------- Percent ---------- U.S. dollars ---------- P

Southern Africa: Angola 12,878 3.2 2.0 26.1 5.0 1.4 380 16.3 5.0 - Lesotho 2,153 2.1 0.6 29.9 9.2 1.0 570 -5.3 -3.6  Madagascar 15,942 4.4 1.3 3.5 1.7 1.6 260 1.7 3.9  Malawi 10,925 3.0 1.8 22.9 0.5 1.8 210 -1.0 3.1  Mozambique 19,680 2.2 6.8 33.8 1.9 2.0 210 9.7 12.0  Swaziland 1,008 2.9 0.7 27.4 -1.0 1.5 1,400 -1.3 2.0  Zambia 9,169 2.1 -1.2 33.0 5.7 1.9 330 -4.1 -2.0  Zimbabwe 11,669 1.2 -1.1 31.9 5.3 1.9 620 -1.4 2.5 Asia: Afghanistan 22,720 3.6 -1.5 12.6 -0.8 1.3 -- -- --  Bangladesh 129,155 1.7 2.1 4.5 0.7 1.7 350 4.2 5.1  India 1,013,662 1.6 2.7 4.2 3.1 1.7 440 4.3 6.1  Indonesia 212,107 1.4 2.0 4.0 1.2 1.7 640 -18.0 -13.2  Korea, D. People's Rep. 24,039 1.4 -2.2 -- -1.3 0.0 -- -- --  Nepal 23,930 2.3 3.1 6.6 6.9 1.6 210 0.3 2.3 - Pakistan 156,483 2.7 2.5 4.9 6.0 2.3 470 0.5 3.3  Philippines 75,967 2.0 2.0 5.9 0.6 1.4 1,050 -2.1 -0.5 - Sri Lanka 18,827 1.0 0.7 8.3 -4.9 1.1 810 3.3 4.7  Vietnam 79,832 1.4 5.2 6.3 -2.2 1.7 350 4.3 5.8 Latin America and the Caribbean: Bolivia 8,329 2.3 3.0 13.3 0.6 3.6 1,010 2.7 4.7  Colombia 42,321 1.8 -1.5 11.8 1.4 2.6 2,470 -2.4 0.6  Dominican Republic 8,495 1.6 -1.2 10.8 1.8 3.9 1,770 4.9 7.3  Ecuador 12,646 1.9 1.9 18.4 8.2 2.1 1,520 2.2 0.6  El Salvador 6,276 2.0 0.8 10.2 1.6 1.3 1,850 1.1 3.2  Guatemala 11,385 2.7 0.0 7.2 0.1 1.8 1,640 2.8 5.1  Haiti 8,222 1.7 1.9 16.5 4.0 0.7 410 1.1 3.1  Honduras 6,485 2.7 -3.6 13.0 2.7 2.7 740 1.1 3.0  Jamaica 2,583 0.9 1.5 51.1 3.2 0.8 1,740 0.1 0.1  Nicaragua 5,074 2.8 3.9 15.7 0.6 1.5 370 3.3 4.0  Peru 25,662 1.7 2.9 14.7 2.4 2.7 2,440 -3.3 0.3 New Independent States: Armenia 3,520 -0.2 1.7 17.0 2.0 1.4 460 3.1 7.2  Azerbaijan 7,734 0.5 -1.5 15.3 13.2 1.4 480 8.9 10.0  Georgia 4,968 -0.8 1.4 22.5 9.0 1.2 970 2.5 2.9  Kyrgyzstan 4,699 0.6 -0.2 17.6 17.7 1.5 380 2.8 3.6  Tajikistan 6,188 1.4 6.7 31.1 -4.4 1.1 370 13.3 8.2 

-- = data unavailable or not applicable due to inconsistent data set. Source: Population=UN World Population Prospects, 1998; Macroeconomic indicators=World Bank. 
1. Food availability and food gaps for 67 countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

2. Number of people with inadequate food and the size of food deficit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

Regional tables

3. Food availability and food gaps for North Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

North Africa: Land use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

4. Food availability and food gaps for Sub-Saharan Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

Sub-Saharan Africa: Land use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

5. Food availability and food gaps for Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

Asia: Land use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

6. Food availability and food gaps for Latin America and the Caribbean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

Latin America and the Caribbean: Land use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

7. Food availability and food gaps for New Independent States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

New Independent States: Land use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

Special articles tables

B-1. Grain market performance profile for selected countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31

B-2. Agricultural indicators for selected countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32

B-3 Social indicators for selected countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33

Country statistical tables

North Africa (4 countries)

1. Algeria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35

2. Egypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35

3. Morocco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36

4. Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36

Central Africa (3 countries)

5. Cameroon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37

6. Central African Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37

7. Congo, Democratic Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38

East Africa (9 countries)

8. Burundi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38

9. Eritrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .39

10. Ethiopia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .39

11. Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .40

12. Rwanda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .40

13. Somalia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41

14. Sudan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41

15. Tanzania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42

16. Uganda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42

Southern Africa (8 countries)

17. Angola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43

18. Lesotho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43

19. Madagascar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44

20. Malawi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44

#" ✺ 

				
 
	



List of Tables
21. Mozambique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45

22. Swaziland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45

23. Zambia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46

24. Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46

West Africa (17 countries)

25. Benin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .47

26. Burkina Faso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .47

27. Cape Verde . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .48

28. Chad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .48

29. Côte d'Ivoire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49

30. Gambia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49

31. Ghana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50

32. Guinea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50

33. Guinea-Bissau . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .51

34. Liberia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .51

35. Mali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52

36. Mauritania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52

37. Niger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53

38. Nigeria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53

39. Senegal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54

40. Sierra Leone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54

41. Togo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55

Asia (10 countries)

42. Afghanistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55

43. Bangladesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .56

44. India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .56

45. Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57

46. Korea, Dem. People’s Rep. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57

47. Nepal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .58

48. Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .58

49. Philippines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59

50. Sri Lanka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59

51. Vietnam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60

Latin America and the Caribbean (11 countries)

52. Bolivia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60

53. Colombia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61

54. Dominican Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61

55. Ecuador . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62

56. El Salvador . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62

57. Guatemala . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63

58. Haiti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63

59. Honduras . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64

60. Jamaica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64

61. Nicaragua . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65

62. Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65

New Independent States (5 countries)

63. Armenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66

64. Azerbaijan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66

65. Georgia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67


	

 

				


✺ ##
66. Kyrgyzstan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67

67. Tajikistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .68

Appendices

Appendix 1. Food Security Model: Definition and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69

Appendix table 2a. List of countries and their food gaps in, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72

Appendix table 2b. List of countries and their food gaps in, 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73

Appendix table 3. Country indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .74

1. Food gaps in all 67 countries, 2000-2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

2. While total number of hungry people is projected to decline, Sub-Saharan Africa’s share is rising sharply . . . . . . . . .7

3. Food aid: Donors and recipients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

4. Food gaps by region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

Regional figures

North Africa

North Africa's production shocks have led to differently sized food gaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

North Africa's grain output variability is relatively high . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

Sub-Saharan Africa

Nutritional food gap in Sub-Saharan Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

Nutritional gap as share of imports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

Asia

Status quo gaps in selected Asian countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

Status quo food gap in Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

Latin America and the Caribbean

Food gaps in Latin America and the Caribbean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

LAC's grain supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

New Independent States

NIS production shocks in 2000 translate into differently sized food gaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

NIS countries have increased area sown but yields declined in the 1990s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

Special articles figures

A-1. Global land quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25

A-2. Global mean precipitation 1961-96 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25

A-3. Global distribution of cropland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26

A-4. Cropland quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

#$ ✺ 

				
 
	



List of Figures