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The Lower strata and the lack of money.ppt
The Lower strata and the lack of money.ppt
SSDesai1
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Sep 14, 2024
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About This Presentation
Money is essential for everything. How can the poor people survive without it
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588.31 KB
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en
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Sep 14, 2024
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Slide Content
Slide 1
The Lower
Strata and the
Lack of Money
Slide 2
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Poverty, Malnutrition &
Income Inequality
How can we provide a good quality of life &
productive work for the 700-1000 million (10-
15%) of world’s 6.5 billion people who are
poor or living on no more than $1 a day?
Economic growth is the most important factor
contributing to poverty reduction (Fig. 6-1).
Country in which you live determines your
position in world’s economic class system.
Milanovic (2002): 88% of 1993 world
inequality from between-country inequality.
Slide 3
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 4
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Information sparsity
International Labour Organization – using data for
policy is like trying to run through the forest in the
dark without a flashlight.
Presently cross-national figures on poverty and
inequality but few by region or community within a
nation.
Identifying and reaching the poor to enable their
geographical targeting requires detailed poverty
mapping, with data on poverty assessment and “basic
needs” indicators at local levels (San Martin 2003).
Few national surveys are adequate for “guid[ing]
poverty alleviation efforts aimed at attacking poverty
at local levels” (ibid., 2003, p. 173).
Slide 5
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Fields on minimal data standards
(1) the database actual household survey or census;
(2) encompass all income, including nonwage income;
(3) include local price information, including rural-
urban cost-of-living differences;
(4) national in coverage;
(5) disaggregated at the canton, district, or county level;
(6) avoid lags between collection and publication, and
long gaps between survey rounds; and
(7) to compare across time, surveys, measures, and the
income concept and recipient unit must be constant.
Slide 6
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Also
For time-series consumption or income,
household data and poverty lines need to
be adjusted for inflation, frequently with
high inflation rates.
Should have information on non-cash
income such as food and other goods
produced at home.
Yet a few careful studies.
Slide 7
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Topics to be discussed
Multifaceted nature of poverty.
Global income inequality.
$1/day and $2/day poverty.
Global and regional poverty.
Effect of poverty on access to education and
health.
Poverty since the 19th century.
Sen’s 3 measures of poverty and deprivation.
Sen’s capabilities approach to poverty.
Slide 8
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Topics to be discussed (cont)
Lorenz curve & Gini index for income
distribution.
Poverty – World Bank, Bhalla, & Sala-i-Martin.
Kuznets’s inverted-U explanation for changes in
income distribution with growth.
Adelman and Morris’s dual-economy stage
theory of the inverted-U curve.
Differences in poverty and inequality by:
low-, middle-, and high-income countries;
DCs and LDCs;
slow- and fast-growing countries; and
gender.
Slide 9
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Topics to be discussed (cont)
Accompaniments of absolute poverty.
Subgroups hurt by poverty.
Case studies of LDC policies.
Policies to reduce poverty & improve
income distribution.
Relationship between inequality and
political instability.
Slide 10
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Poverty as multidimensional
1.Poverty consists of interlocked dimensions, yet
lack of food dominant.
2.Poverty has important psychological dimensions,
such as powerlessness, voicelessness,
dependency, shame, and humiliation.
3.Poor people lack access to basic infrastructure –
roads, transportation, & clean water.
4.Education offers escape if economic environment
favorable & quality of education is good.
5.Poor health & illness source of destitution.
6.Assets – physical, human, social, and
environmental – crucial. Has gender dimension
(Narayan et al. 2000:4-5).
Slide 11
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 12
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 13
CHAPTER 6 ©E.Wayne Nafziger Development Economics
$1/day & $2/day poverty
Absolute poverty – below income securing bare
essentials of food, clothing, & shelter.
Inter-country comparisons difficult although
assumed can compare $PPP.
World Bank - $PPP1/day & $PPP2/day in 1985,
same as $PPP532 & $PPP1064 yearly in 1998.
Page 172 indicates diet comparable to poverty
line: 2 cups of hot prepared rice, equivalent to
54% of total diet (based on typical gender & age
distribution).
Slide 14
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 15
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Table 6-1
Table 6-3 &
Figure 6-5
show poverty rates
over time and
by region.
Slide 16
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 17
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 18
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 19
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 20
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 21
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Sen’s Concepts &
Measures of Poverty
Emphasizes capabilities not attainments.
G, H & I.
H: Headcount approach (poverty %).
I: Income-gap approach – additional
income to bring poor up to poverty line.
G: Gini – distribution of income among
the poor.
Slide 22
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 23
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 24
CHAPTER 6 ©E.Wayne Nafziger Development Economics
3 measures of poverty:
World Bank, Institute of International Economics, &
Sala-i-Martin (Tables 6.1- 6.3)
Sala-i-Martin – goes beyond 20-percentile
quintiles (fifths) of World Bank data to 1-
percentile increments by interpolation &
testing.
Includes China but not Former Soviet
Union, Former Yugoslavia, & Bulgaria.
Fig. 6-3 (showing falling global income
inequality) is consistent with Firebaugh.
Slide 25
CHAPTER 6 ©E.Wayne Nafziger Development Economics
3 measures of poverty:
World Bank, Institute of International
Economics, & Sala-i-Martin (Tables 6.1- 6.3)
World Bank (Milanovic) – Sala-i-Martin uses
linear extrapolation for quintile shares.
- where if a nation has only one point, he assumes
constant income shares.
- where if a nation has no points, all individuals
have income per capita of country.
Are data for individual or household? Not certain.
No Former Soviet Union, Former Yugoslavia, &
Bulgaria; China’s data have large margin of error,
so inequality could be either falling or increasing.
Slide 26
CHAPTER 6 ©E.Wayne Nafziger Development Economics
3 measures of poverty:
World Bank, Institute of International Economics, &
Sala-i-Martin (Tables 6.1- 6.3)
Bhala (IIE) – World Bank’s consumption based on
household surveys that come up with absurd results –
average Korean richer than average Swede; Ethiopia is 3
times richer than India.
National income consumption not household survey
means should be used.
Bhalla uses national accounts/household survey
multiplier.
Agrees with Sala-i-Martin that inequality fell; possible
even if many national inequalities increase.
Argues that % increase in consumption of poor/%
increase in consumption of non-poor > 1.
Slide 27
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Bhalla’s argument:
imagine no country
Shift from world’s lower class (less than
$PPP10/day at 1993 prices) to world’s
middle class ($PPP10-$PPP40/day).
Consumption by the world’s poor, driven
largely by China & India, grew more
rapidly than consumption by the rich,
1980-2000.
Slide 28
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 29
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 30
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Early & late stages of development
– Adelman & Morris
Test Kuznets’ hypothesis on inverted-U
relationship between per capita income
(X-axis) & inequality (Gini) (Y-axis).
Assumes dual economy, with growing
modern sector share.
Slide 31
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 32
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Is there evidence for the
Kuznets’ inverted U?
Yes, for a given time period, as
Figure 6-10.
More questionable when you
examine long-term data for given
countries.
Slide 33
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Slide 34
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Females are the major victims
of poverty
Need resource allocation within households
& families (Dasgupta).
Data fail to show gender inequality, a
major source of interpersonal inequality.
Income inequality would be 30-40% higher
if inter-family gender inequality calculated
(e.g., 0.57 for South Africa X 1.35 = 0.77;
0.29 Bangladesh X 1.35=0.39).
Slide 35
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Sen on “missing women”: low
female to male ratio
West 105 to 100; sub-Saharan Africa 102;
98 North Africa; 94 China, Bangladesh, &
Middle East; 93 India (Kerala 104).
With sub-Saharan Africa as benchmark,
Sen estimates 44 million missing females
in China & 37 million in India.
Why? Family directs resources to males.
Slide 36
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Accompaniments of absolute poverty
for 400-1100 million $1/day
3/5- 4/5 spent on food.
50% undernourished.
2/10 die by 10 years.
Immunization rates low.
Lack access to safe & plentiful water
& sanitation.
Average life expectancy 45 years.
Slide 37
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Accompaniments of absolute
poverty for 400-1100 million $1/day
1/3 - 2/5 adults literate.
4/10 complete > 4 years primary
school.
In environmentally marginal &
vulnerable areas, higher rates of
unemployment, higher fertility rates.
Slide 38
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Poverty groups
4/7 in sub-Saharan Africa; 1/6 East Asia; 1/6
South Asia.
Indigenous & minority groups overrepresented.
4/5 live in rural areas; many urban slums.
Rural poor landless workers, sharecroppers,
tenants, & small landowners.
Urban poor unemployed, irregularly employed,
menial workers, some small business people.
Slide 39
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Poverty groups (cont)
Relatively few wage laborers, unemployed
compared to DCs.
Most illiterate.
Women, especially heads of households.
40% children under 10.
Elderly poorer.
Many live in remote regions, beyond gaze of
casual visitor to village – away from roads,
markets, & services.
Slide 40
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Income equality vs. growth
Controversy (pp. 210-212)
Slide 41
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Poverty, inequality, & war
Wars & massive state violence occur mostly in
low income countries, some of which are
failed states.
Economic stagnation worsens relative
deprivation.
Failed states associated with widespread rent
seeking.
Some predatory states, where elites plunder
the economy.
Slide 42
CHAPTER 6 ©E.Wayne Nafziger Development Economics
Policies to reduce
poverty & inequality
Combined discussion of policy
issues in Chapter 6, pp. 202-210
and Chapter 7, pp. 245-264 (see
Ch. 7 powerpoint).
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