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Nafziger Economic Development (4th ed)

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Cereals

deficit/cereals

consumption

(%)

 

(24.6)

(39.0)

(16.4)

(5.9)

(22.7)

12.1

1.9

17.3

37.8

6.2

9.9

0

 

 

 

 

 

 

tonsandpercentages)

2020

 

Cerealsdeficit

(cereals

consumption

Cereals minus

consumption production)

(m.m.t) (m.m.t)

 

822 (202)

305 (119)

183 (30)

136 (8)

198 (45)

1,674 202

211 4

156 27

196 74

353 22

758 75

2,496 0

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

TABLE7-2.CerealsConsumptionandDeficits,1997and2020(millionmetric

1997

 

Cerealsdeficit

(cereals

consumption Cereals

Cereals minus deficit/cereals

consumption production) consumption

Region/country (m.m.t) (m.m.t) (%)

 

Developedcountries 725 (104) (14.3)

UnitedStates 244 (94) (38.5)

EuropeanUnion15 173 (31) (17.9)

FormerSovietUnion 131 7 5.3

Other 177 14 7.9

Developingcountries 1,118 104 9.3

LatinAmerica 138 14 10.1

Sub-SaharanAfrica 83 14 16.9

WestAsia/North 129 45 34.9

Africa SouthAsia 238 3 1.3

Southeast&EastAsia 530 28 5.3

World 1,843 0 0

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

indicatessurplus.

Rosegrant,Paisner,Meijer,andWitcover2001:184.

Note:()

Source:

236

7. Rural Poverty and Agricultural Transformation

237

in food distribution may mean that some people in LDCs will be undernourished. This could mean a shortfall in the Millennium Development Goal (Chapter 2) to reduce world hunger to 8–9 percent (using World Bank estimation methods) by 2015. Adequate nourishment is not only required under the Universal Declaration of Human Rights and a key for attaining Millennium Development Goals but a part of increasing the productivity of the workforce (Chapter 9).

Still, the projections in Table 7-2, although consistent with the bleakness of other food data, especially on Africa, should not obscure the fact that the crises in urban food supply, overall food production, and external imbalances are somewhat distinct. With rapid urbanization and changes in urban diets and the importation of much of urban food supply, we can expect LDC food imports to rise from 2005 to 2015, regardless of food output trends. African farmers are largely self-sufficient in basic calories, but may not be able to produce surplus for sale because of a lack of technology and market failure.

Export crops drive cash income and capacity to import. Consider Somalia, which had Africa’s lowest daily calorie consumption per capita, 1997–99 (FAO 2003:31). Peter Little (2003:135) indicates that “there is a clear and positive correlation between livestock exports and food imports in Somalia.” Saudi Arabia’s ban on Somalia livestock exports, 1997–99 and 2000, drastically reduced income and thus food imports and consumption (ibid., pp. 33, 135).

The fact that grain imports are 25–30 percent of grain consumed in Africa does not mean that imported cereals sustained one-quarter of the population. Rising cereal imports, helped by falling food import prices, means increased cereals consumed in urban areas (rice and wheat), and a shift in Madagascar, Southern Nigeria, Ghana, and Uganda from coarse grains (sorghum and millet), roots, and tubers (Jamal 1988:657–679; FAO 2003:107–111). In addition, LDCs’ meat consumption is expected to double from 1984–86 to 2015, whereas meat consumption and imports for sub-Saharan Africa are also expected to increase (FAO 2003:85–89).

Food Output and Demand Growth

Agriculturists, who agree on the rising global trend in foodgrain output per person from the early 1950s through the 1980s, noticed a fall in global average grain production after 1990. The debate between Worldwatch Institute’s neo-Malthusians (Brown 1994:26–27; Halweil 2003:28–29) and their critics, such as Tim Dyson (1994:397– 411), is whether this adverse trend will deepen in the 21st century, leading to massive famines. The controversy, discussed in connection with Figure 8-8, examines the sustainability of the contemporary global agricultural system, including regional trends, population growth, environmental and resource limitations, and agricultural technological gains (Crosson 1994:105–119).

Total world food production, which grew between the 1950s and the early 21st century, is expected to continue growing during subsequent decades in both LDCs and DCs. Meanwhile, food demand per capita will continue to rise, although not so rapidly as increases in GNP.

238 Part Two. Poverty Alleviation and Income Distribution

TABLE 7-3. Income Elasticities in Developing

Countries for Selected Commoditiesa

Item

Income elasticity

 

 

Rice

0.01–0.30

Wheat

0.04–0.98

Vegetables

0.10–0.92

Vegetable oils

0.50–1.81

Beverages

0.74

Cocoa

0.75

Fish

0.61–1.50

Shrimp

1.25

Pork

0.50–0.97

Beef

0.75–1.85

Eggs

0.80–1.20

Poultry

0.40–2.20

Milk

1.50–2.50

Fruit

1.22–2.50

Sugar

1.50–2.00

Manufactures

0.74–3.38

aThe percentage increase in quantity demanded as a result of a 1-percent increase in income. The estimates are based on studies of developing countries. The range of estimates reflects differences in per capita income levels among countries.

Source: World Bank 1994f:39.

The growth in food demand or

˙ ˙ ˙

(7-1)

D = P + αE

˙

where P is population growth, α the income elasticity of demand for food, (change in the quantity of food demanded per capita/quantity of food demanded per

˙

capita)/(change in per-capita income/per-capita income), and E per-capita income growth, all expressed in yearly figures. In empirical studies, estimates for α vary widely (from 4 percent to 85 percent), depending on location, type of survey, and income levels. Table 7-3 indicates the range of elasticities in LDCs for selected commodities. For the International Food Policy Research Institute economist Harold Alderman (1993:118–119), α averages 0.48 for LDC average incomes. If the annual figures are 1.3 percent for population growth, 2.08 percent for income per-capita growth, and 0.48 for α, than food demand growth is 1.3 percent + 1 percent or 2.3 percent yearly.

Fish, Meat, and Grains

Foodgrain output figures omit fish, an important source of high-quality protein throughout the world and one-fourth of the animal protein in the developing world.

7. Rural Poverty and Agricultural Transformation

239

LDCs ate a majority of the world’s catch of 97 million tons in 1999, which was a fivefold increase over 45 years and an increase of more than a third since 1990. World fish tonnage compared to 47 tons of beef, 61 tons of pork, and 39 tons of poultry. China, the world’s largest fish producer, dominated growth in the 1990s. China’s growth overshadowed developments in the rest of the world, where consumption per person fell, 1990–99. Outside China, this fall results from an overuse of a common property resource, the earth’s bodies of water (Chapter 13). Africa produced only 3 million tons in 1999 (FAO 2003:195–206; Iowa State University 1999; World Resources Institute 2000).

Factors Contributing to Low Income and Poverty in Rural Areas

Average income in rural areas is substantially less than in urban areas in LDCs. Rural inequality is greater than urban inequality in Latin America but less in the rest of the developing world (Jain 1975; World Bank 2003h:57–66). Not surprisingly in LDCs as a whole, there are higher poverty rates in rural areas than in cities. This section discusses why this is so.

LACK OF RESOURCES AND TECHNOLOGY

Agricultural income and productivity in LDCs are low because of minimal capital per worker and inadequate technology. Small farm owners receive limited credit and tenants, sharecroppers, and landless laborers receive almost none. Although large parts of Asia, especially large farmers, benefited from the inputs into high-yielding varieties (HYVs) associated with the Green Revolution (Chapter 8), this has bypassed most of African agriculture, which lacks a basic infrastructure. In most of Africa, there is little research and development to improve technology appropriate for small farmers, partly because they lack effective demand and political power.

CONCENTRATION OF CAPITAL, LAND, AND TECHNOLOGY

Agricultural technology and capital are often concentrated among large farmers, who have more access to markets and inputs, outbidding many small cultivators, who may be marginalized and sometimes compelled to work for a wage. Many of the poor are smallholder farmers, including a substantial share of women, who work long hours and are already deeply involved in agricultural production, but lack the productive resources (fertilizer, better seeds, equipment, tools, land, and skills) and new technology to escape from their poverty trap. Although still less than urban inequality in Afro-Asia, rural income inequality has increased since 1970 (Jain 1975; International Labour Office 1979; Jazairy, Alamgir, and Panuccio 1992:xix–xx, 105– 106; Worldwatch 2003:17–24).

Land holdings, frequently a colonial legacy, are severely concentrated in many LDCs (see Chapter 6). This is especially true in Latin America, where the average farm size is over 80 hectares or 200 acres (20 times larger than in Afro-Asia) (Table 7-4), and size dispersion is substantial (Gini coefficient = 0.84, if you include the holding of landless as zero) (Squire 1981:156; Repetto 1987:14). In Brazil, a small fraction of

 

 

Gini

coefficient

 

0.50

0.55

0.50

0.75

0.42

0.64

0.70

0.67

0.70

0.69

0.35

0.57

0.25

0.44

0.72

0.65

0.64

0.55

0.49

0.35

 

 

 

 

 

Fifth

quintile

 

56.2

73.3

65.9

88.4

50.5

76.1

81.9

79.2

88.6

83.6

55.2

74.1

35.0

58.0

90.1

67.5

79.0

65.2

55.5

45.3

PercentileGroupsofHouseholds

GroupsofHouseholds

Second Third Fourth

quintile quintile quintile

 

5.4 12.5 23.6

5.8 5.8 9.3

6.9 6.9 13.4

1.0 3.1 7.2

9.3 15.0 21.6

2.8 2.8 15.5

1.3 3.8 12.6

0.8 7.1 12.1

3.4 3.4 3.4

1.6 4.2 9.6

11.2 11.2 11.2

5.1 5.1 10.6

15.1 18.3 23.9

7.8 7.8 18.6

1.6 3.3 4.2

0.8 0.9 30.0

2.9 3.8 11.4

4.1 6.3 20.3

6.2 11.3 24.0

16.1 18.1 18.1

Landholdingby

 

Lowest(first) quintile(twenty

percent)

 

2.3

5.8

6.9

0.3

3.6

2.8

0.4

0.8

1.2

1.0

11.2

5.1

7.7

7.8

0.8

0.8

2.9

4.1

3.0

2.4

TABLE7-4.DistributionofAgricultural

 

 

Country Year

 

Bangladesh 1983–1984

Bolivia 1978

Botswana 1971

Brazil 1980

Cameroon 1984

Chile 1987

Colombia 1983–1984

CostaRica 1984

DominicanRepublic 1981

Ecuador 1987

Egypt,ArabRepublic 1984

ElSalvador 1985

Ethiopia 1984

Ghana 1984

Guaternala 1979

Haiti 1971

Honduras 1980–1981

India 1976–1977

Indonesia 1983

Iraq 1982

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

240

0.36

0.57

0.33

0.36

0.51

0.58

0.47

0.44

0.59

0.30

0.37

0.50

0.74

43.4

65.3

40.6

44.2

62.1

76.7

58.0

51.4

67.3

34.9

35.0

59.2

88.0

23.6

20.0

25.0

24.0

16.8

8.0

21.6

24.2

19.8

28.9

32.4

19.3

9.3

17.6

9.0

16.0

15.5

11.9

5.1

6.8

12.3

7.7

18.6

24.2

11.5

2.2

9.5

4.4

12.7

11.1

6.1

5.1

6.8

7.4

2.6

11.7

6.8

7.2

0.4

 

5.9

1.3

5.7

5.2

3.1

5.1

6.8

4.7

2.6

5.9

1.6

2.8

0.1

 

1988

1983

1980

1980–1981

1976

1970

1981–1982

1989–1990

1982

1980

1973–1974

1980

1981

.

IvoryCoast

Jordan

Korea,Republicof

Malawi

Malaysia

Mexico

Morocco

Myanmar(Burma)

Nepal

Niger

Nigeria

Pakistan

Panama

3.3 17.1 73.0 0.61

3.3

3.3

a 1984

Peru

0.48

0.58

0.59

0.41

0.58

0.52

0.59

0.08

56.7

67.4

68.4

47.2

68.4

59.1

74.5

28.0

20.4

18.3

18.6

24.2

16.2

21.3

12.0

18.0

11.6

8.7

7.2

16.3

9.4

11.4

4.5

18.0

8.1

2.8

3.9

8.3

3.0

6.1

4.5

18.0

3.2

2.8

1.9

4.0

3.0

2.1

4.5

18.0

 

1982

1979

 

 

1980

b

 

1981

1978

1980

1984

1981

Philippines

SriLanka

Syrian,Arab

Republic

Thailand

Tunisia

Turkey

Uganda

Zambia

Privateholdings.

Basedonfourregionsonly(Busoga,Kigezi,Masaka,andTeso).

a

b

Sources: Jazairy, Alamgir, and Panuccio 1992:416–417.

241

242 Part Two. Poverty Alleviation and Income Distribution

TABLE 7-5. Minifundios, Medium-sized Farms, and Latifundios in the Agrarian Structure of Selected Latin American Countries, 1966

 

 

 

 

 

 

Medium-sized and

 

 

 

 

 

 

Minifundiosa

 

family farmsb

 

Latifundiosc

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Percent of

 

 

Percent of

 

 

Percent of

 

 

Percent of

occupied

Percent of

occupied

 

Percent of

occupied

 

 

farms

land

farms

land

 

farms

land

 

 

 

 

 

 

 

Argentina

43.2

3.4

56.8

59.7

0.8

36.9

Brazil

22.5

0.5

72.8

40.0

4.7

59.5

Colombia

64.0

4.9

34.7

45.6

1.3

49.5

Chile

36.9

0.2

56.2

18.5

6.9

81.3

Ecuador

89.9

16.6

9.7

38.3

0.4

45.1

Guatemala

88.4

14.3

11.5

44.9

0.1

40.8

Peru

88.0

7.4

10.9

10.2

1.1

82.4

 

 

 

 

 

 

 

 

a

Employ less than two people.

 

 

 

 

 

 

b

Family farms employ two to four people and medium-sized farms four to twelve workers.

c

Employ more than 12 people.

 

 

 

 

 

 

Source: Furtado 1970:54–55.

landholders (16 percent) commands 87 percent of agricultural land. Land inequality is greater than data indicate because many small holders sharecrop or lease their holdings, and many rural have no land at all (Repetto 1987:13–14). Since the colonial period more than 100 years ago, most of Latin America has been characterized by latifundios, large land-grant estates owned by the few, and minifundios, small poor holdings that rarely provide adequate employment for a family (see Table 7-5). To obtain a subsistence income, holders of minifundios generally work as seasonal labor on the latifundios. And of course, these large estates, characterized by extensive cultivation, high capital intensity, and much unused land, have a higher output per agricultural worker.

In the last few decades, the many latifundios have increased their capitalization and levels of technology. Moreover, in some Latin American countries, a well-capitalized medium-scale sector has emerged. Yet, despite these changes and a smattering of land redistribution, Latin American still has a high degree of land concentration (Jazairy, Alamgir, and Panuccio 1992:109–113).

LOW EDUCATIONAL AND SKILL LEVELS

Average incomes in urban areas are higher than in rural areas, where skill levels and demands are lower. Years of schooling, a major indicator of skill and productivity (see Chapter 10), are fewer in rural than in urban areas. For example, in India the city-born child has twice the chance of receiving a primary or secondary education as the one born in a rural community and eight times the chance of receiving a university education. More and better quality schools are available to city children than to rural children. In addition, much rural schooling is irrelevant to its community’s economic needs. Some economists even question how much rural areas benefit from a child’s

7. Rural Poverty and Agricultural Transformation

243

education, as the most able and educated young people usually emigrate to the cities (Lipton 1977:259–260, 446).

RURAL–URBAN MIGRATION

Attracted by the prospect of better-paying jobs in urban areas, rural emigrants tend to have education, skill, and income that are higher than average in the rural areas. Poorer villagers are often at a disadvantage in migrating: (1) They simply cannot afford to migrate – acquiring job information, emigrating, and searching for work are expensive propositions, especially if they are financed at the high interest rates charged by the village money lender. And, of course, emigres´ must subsist as they wait for their first paychecks. (2) Their families find it more difficult to release them from work. (3) They are not so well educated as most other villagers. Many urban employers use education to screen job applicants, even for unskilled work (see Chapter 10). Even when the poorer villagers surmount these obstacles and move to the city, they frequently do not stay. Poverty forces them back to the village. The jobless, ill, pregnant, and elderly eventually return to relatives in the rural areas, eroding average incomes already reduced by the large economic burden from high rural birth rates (Lipton 1977:66, 149–149, 231–235).

POLICIES OF URBAN BIAS

The British economist Michael Lipton argues that the most significant class conflicts and income discrepancies are not between labor and capital, as Karl Marx contended, but between rural and urban classes. Despite development plans that proclaim agriculture as the highest priority sector, and political rhetoric that stresses the needs of the poor rural masses, government allocates most of its resources to cities, a policy of urban bias. Planners and politicians in LDCs are more likely to respond to the concerns of the more powerful, organized, and articulate urban dwellers. Thus, farm land is diverted from growing millet and beans for hungry villagers to produce meat and milk for urban middle and upper classes or to grow cocoa, coffee, tea, sugar, cotton, and jute for export. Scarce capital is spent on highways and steel mills instead of on water pumps, tube wells, and other equipment essential for growing food. High-cost administrative and management talent is used to design office buildings and sports stadiums rather than village wells and agricultural extension services.

Urban bias may take these forms:

1.Policies that raise industrial prices relative to the prices of farm goods. Government may set price ceilings on food and guarantee minimum prices for industrial goods. High taxes and low prices force agriculture to transfer income and capital to industry and social infrastructure. The most frequently cited model for such policies is the Soviet Union of the 1930s, which used low prices, sales taxes, and government monopsony purchases to divert the surplus from agriculture into heavy-industry output and investment growth unmatched by any Western country. But in the 1970s direct and indirect taxation of agriculture as a percentage of agricultural value added exceeded 40 percent in Ghana, with

244 Part Two. Poverty Alleviation and Income Distribution

62 percent; Coteˆ d’Ivoire, with 51 percent, Egypt, with 49 percent, Pakistan, with 48 percent; Sri Lanka, with 44 percent; and Thailand, with 43 percent (World Bank 1990:58–59; Lipton 1977).

2.Concentration of investment in industry. Although over half of the LDC population is in agriculture, only about 20 percent of investment is in agriculture.

3.Tax incentives and subsidies to pioneering firms in industry, but not in agriculture.

4.Setting below-market prices for foreign currency, which reduces domestic currency receipts from agricultural exports. This policy lowers the price of capital goods, other foreign inputs, and food imports, which benefits urban areas, especially large industrial establishments with privileged access to import licenses. In Pakistan, such a foreign exchange policy coupled with industrial price guarantees resulted in the transfer of about 70 percent of agricultural savings and over 24 percent of its gross product to the nonagricultural sector in 1964 and 1965.

5.Tariff and quota protection for industry, contributing to higher fertilizer, seed, equipment, materials, and consumer prices for farmers.

6.Spending more for education, training, housing, plumbing, nutrition, medical care, and transport in urban areas than in rural areas (see Chapter 9) (World Bank 1990:58–59; Griffin and Khan 1972). Thus, life expectancy, an indicator of the quality of the health care system, varies widely among regions. Buenos Aires had a 1985 life expectancy of 75 years; the rest of Argentina, 69; the poor rural areas, 63; and Argentina as a whole, 70. Algiers’s life expectancy is 77; the rest of Algeria, 69; the poor rural areas, 66; and Algeria generally, 69.

Maurice Schiff and Alberto Valdes from the World Bank label this bias “The Plundering of Agriculture in Developing Countries” (1998:226–233). Using a sample of countries from Asia, Africa, and Latin America, 1960–84, Schiff and Valdes find that the average effect of industrial protection and a price for foreign currency below market depresses agriculture’s domestic terms of trade (agricultural price/industrial price) 22 percent. The total effect, including the previous plus agricultural price controls, export taxes or quotas, and import subsidies or taxes, is a 30 percent reduction in agriculture’s terms of trade (ibid., pp. 227–228).

Although recent changes have diminished urban bias, DC and (world) agricultural overproduction in many commodities have reduced the benefits to the LDC rural poor. According to the World Bank (2004a:103):

In the last decade, developing countries shifted from taxing agriculture to protecting it. Import restrictions on manufactured products have declined dramatically, exchange rates have been devalued, multiple-exchange rate systems penalizing agriculture have been abandoned, and export taxes have effectively disappeared. . . . Meanwhile, reforms in most industrial countries, including many of the successful middle-income countries, have been modest. . . . The result of these policies have been overproduction and price declines in many commodities, reducing opportunities for many developing countries to expand exports and penalizing the poor.

7. Rural Poverty and Agricultural Transformation

245

SEASONAL POVERTY AND HUNGER

Ironically, moderate undernourishment is higher in rural than in urban areas, as it is more likely to result from inadequate income than food shortages. However, Food and Agriculture Organization (FAO) studies of several LDCs indicate that, because of greater access to subsistence food production, the percentage of the population suffering severe malnourishment in rural areas is lower than in urban areas (FAO 1977:29–46).

Yet there is substantial hunger in rural areas. A “hungry season” before the beginning of a new harvest is widespread in many LDCs, especially in West Africa. Poor rural households are caught in a poverty trap in which selling labor and obtaining credit at high interest rates to ensure survival through the hungry season result in less income and high interest payments in future years. The poverty trap is circular. Initially farmers sacrifice self-sufficiency to produce cash crops. Accordingly, they no longer grow early maturing crops that would fill the hunger gap between harvests. Poor farm families are also more vulnerable than previously as a result of individualized consumption replacing community or clan sharing. Furthermore, poor farm families cannot afford to purchase food just before harvests, when cash resources are lowest and prices are highest. At this juncture, many poor farmers neglect their own farms and sell their labor to richer farmers. They accept a lower income from their own farm to guarantee short-term survival. Reduced calorie and protein consumption during a period of more work leads to weight loss and greater chances of contracting diseases. The situation may become worse each year (Newman, Ouedraogo, and Norman 1979:241–63; Byerlee, Eicher, and Norman 1982).

VULNERABILITY OF THE RURAL POOR

Peasants and the rural poor, who face poor infrastructure, inequitable policies, high disease rates, inadequate support systems, and market failure, are highly vulnerable. Thus, they are “highly risk averse and reluctant to engage in the high-risk, high-return activities that could lift them out of poverty. One slip could send them deeper into poverty” (World Bank 2001i:138). In rural Ethiopia, three-fourths of the households suffered a harvest failure over a 20-year period, contributing to significant fluctuations in farm income. Farmers in south Indian villages also faced large fluctuations in income, with the coefficient of variation (deviation of a variable from its mean) ranging from 0.37 to 1.01. LDC farm families manage risk by diversifying crops, seeking nonfarm income, sharecropping, building social networks, or saving for a “rainy day” (ibid., pp. 138–141). Purchasing insurance against major output and price risks, however, is much more difficult (Stiglitz 2000:336).

Policies to Increase Rural Income and Reduce Poverty

This section focuses on increasing average rural incomes and reducing the percentage of the rural population in poverty by improving income distribution.

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