economic development, poverty, and the disadvantaged - mark rosenzweig (yale)
TRANSCRIPT
Economic Development, Poverty and the Disadvantaged
Mark R. Rosenzweig
Yale University
Global Poverty and the Disadvantaged
From a Global perspective, whole populations of countries are poor.
While some people are poorer than others in low-income (poor) countries, thekey reason for global “poverty” is that overall productivity is low in somecountries.
Put another way, the value of skill in the labor market in poor countries is low.
We have estimates of the value of one unit of skill for almost all countries ofthe world
Enormous differences, such that increasing skills without increasing theproductivity of skill would have little impact on poverty.
The key development challenge is to increase productivity - the rewards tohuman skill - and thus incomes..
But within the population of poor countries, there are the disadvantaged.
0 2000 4000 6000 8000 10000 12000 14000 16000
Cambodia
India
Mongolia
Laos
Nepal
Sri Lanka
Vietnam
Philippines
Bangladesh
Indonesia
China
Pakistan
Thailand
Korea
Japan
Malaysia
Hong Kong
Singapore
Taiwan
OWW Skill Price (x10)NIS-P Skill Price
Estimated PPP $ (1995) Skill Prices for 19 Asian Countries,by NIS-P and OWW Sources
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2000
3000
4000
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7000
Nigeria India Indonesia Mexico Korea
High School GraduateCollege Graduate
Estimated (Purchasing-Power Adjusted 1996) Earnings of High School and College Graduates,Across Selected Countries Around the World (r=.07)
Evaluate specific development agendas in terms of their effects, especially onthe disadvantaged:
A. Did incomes grow?
B. Did education, health, nutritional status improve?
C. Were there substantial changes in occupations, socialarrangements?
Who are the disadvantaged?
1. Landless in rural areas: those owning no land where agriculture isthe main activity
2. Women: how did women fare relative to men?
3. Disadvantaged social groups: lower castes in India
(caste = social group; one is born into a caste, like a family)
Specific Development Agendas Assessed
1. Public and NGO Investments in Public Health
Rural Bangladesh, 1980-
2. Investment in Agricultural Technology
The “Green Revolution” in Rural India, 1970 -
3. Trade Policy Reforms
Urban India (Mumbai), 1990 -
4. Industrialization
Urban China, 1980 -
Examples selected because we have good data over at least 20-year period trackingchanges
Some Simple Analytics: Human Capital, Gender and Occupation
There are two broad categories of human capital
1. Skill 2. Brawn (strength)
From biology: Men have a comparative advantage in brawn (women have acomparative advantage in skill)
From education statistics: Schooling increases skill for men and women
From biology: Nutrition increases strength, but only for women
Economic theory: people choose occupations according to their comparativeadvantage
People with relatively more skill choose skill-intensive jobs if theycan choose
Therefore, women choose more skill-intensive jobs compared withmen, when that is possible
Schooling
A. Schooling improves ability to think, to decide, to make allocationdecisions
Old technology versus new technology
B. Schooling is more valuable in some occupations compared with others
1. Farm manager (landowner) versus wage worker (landless)
2. Clerk, service worker versus bricklayer
C. The overall returns to schooling will depend on the demand for differentjobs
Changes in the occupational mix (e.g., increase in skill-intensivejobs) will change the average return to schooling (e.g., increasethe return to schooling)
D. Changes in the return to schooling affect schooling investment
Development strategies will thus change schooling investment, returns toschooling if they:
1. Change the nutritional status of the population (Bangladesh)
2. Introduce (challenging) new technologies (India “green”revolution”)
3. Change the occupational mix in terms of skill-intensity (India,China openness policy)
Given the differences between men and women in brawn and whichoccupations people are in:
schooling investments, returns and the occupational choices of men andwomen and the landless will be affected differently by differentdevelopment strategies
Agenda 1: Health and School Investments in Bangladesh
A. Improvements in sanitation, water quality, provision of health education
Implemented/funded jointly government and NGO’s
Major reductions in morbidity (e.g. diarrheal disease)
B. Provision of schools
Assured access to school, subsidized schooling
What happened in rural areas?
1. Reductions in morbidity for men and women
2. Increases in height and BMI for men and women, brawn for menonly
3. Increases in schooling, especially for women
4. Occupational structure more different between men and women
What did not happen?
1. No increase in agricultural productivity or wages
2. No major change in the occupational structure
3. No change in calorie consumption
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0.8
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1.2
1.4
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Girl/Boy Enrollment RatioFraction Rural Population with Improved Sanitation
Agricultural Real Wage Index (1949=1)Fraction of Micro-Credit Members in Rural Adult Population
Rural Bangladesh: Ratio of Girls to Boys Enrolled in Rural Secondary Schools,Real Agricultural Wage Index, Fraction of Rural Population with Improved Sanitation,
and Fraction of Adult Women Belonging to Micro-Credit Groups, 1981-2002
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0.7
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0.9
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5 6 7 8 9 10 11 12 13 14 15 16
Boys Girls
Rural Bangladesh: School Attendance, by Age, Gender and Survey Year
2001-2
1981-2
12
13
14
15
16
17
18
19
20
5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43
BMI 2002
BMI 1981
Rural Bangladesh: BMI, by Age and Year for Males
12
13
14
15
16
17
18
19
205 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43
BMI 2002BMI 1981
Rural Bangladesh: BMI, by Age and Year for Females
140
145
150
155
160
165
170
1952
1954
1956
1958
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
Men in 1982 SurveyMen in 2000 SurveyWomen in 1982 SurveyWomen in 2000 Survey
Rural Bangladesh: Attained Height, by Sex and Year Person Reached Age 20
0
500
1000
1500
2000
2500
3000
3500
1981 2002
Women Men
Rural Bangladesh: Daily Calorie Intake Mean and Women Aged 20-49,1982 and 2002
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1
1981 2002
Women Men
Proportion of Adults Aged 25 – 40 in ‘Exceptionally Active’ or ‘Very Active’ Occupations,by Gender and Year, Rural Bangladesh Surveys
Table O
Occupational Distributions in 2004, by Gender and Rural-Urban
Occupation/ Population Rural Urban
Men
Farmer, agricultural laborer, fisherman 49.4 9.7
Unskilled laborer (rickshaw puller, brick
breaking, etc.)
12.0 14.8
Factory worker or blue-collar service 3.3 7.5
Semi-skilled laborer (carpenter, mason,
bus/taxi driver)
9.8 22.4
Professional (teacher, doctor, lawyer) 2.4 5.2
Business 16.4 31.3
Other 0.6 0.4
Not working 5.8 8.7
Women
Agricultural worker 1.2 0.4
Home-based manufacturing 3.7 3.1
Unskilled laborer (construction, brick
breaking, etc.)
2.7 2.4
Poultry raising, cattle raising, trading 7.8 3.5
Domestic labor 2.0 5.8
Semi-skilled service (tailor, etc.) 3.0 6.4
Professional (teacher, doctor, lawyer) 0.5 1.7
Business 1.7 2.3
The Indian Green Revolution (Technological Improvements + Policy)
A. Policies of Indian government:
1. Allowed importation of new, high-yielding seed varieties (wheat,rice, corn)
No initial investment in seed technology in India
2. Picked “winners”
Subsidized credit, increased fertilizer supply in regions wherenew seeds were expected to increase agricultural productivitythe most
B. Continued improvements in seed technology
C. Tubewell irrigation became cheaper
What happened in rural areas of India?
1. Sustained increase in agricultural yields and agricultural wages
a. So the landless benefitted, as well as those owning land
2. Increases in nutritional status for both boys and girls (height)
3. Rise in the returns to schooling, particularly in areas where technologywas most productive
4. Increases in schooling investment, particularly in those areas of highchange
a. Increases in schooling less for the landless: why?
Landless are wage worker who do not make allocation decisions
Schooling augments capacity for making decisions
b. Schooling of girls rose faster than that of boys, but still below boys
What did not happen in India?
1. No structural transformation of the whole economy
Urbanization did not advance rapidly, slow compared with othercountries with high growth rates
The size of the agricultural sector is still large
2. No structural transformation of agriculture
Still small-scale and not mechanized: brawn still important
Substantially less productive than agriculture in developed countries
3. No change in social arrangements in rural areas, role of women
Caste still plays a major role in lives of rural households
Principal role of caste groups: insurance, loan provision
HYV Yields (Rupees per acre) and Real Agricultural Wages, 1971-1999
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1971 1982 1999
HYV Yield/100 (1971 rupees)
Agricultural Wage (1982 rupees)
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10
15
20
25
30
35
40
45
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Real Agricultural Wages in India, 1970-2004 (Source: Bhalla and Das, 2006)
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20
40
60
80
100
120
2 3 4 5 6
1982 1999
Boys: Average Height by Age and Survey Year, Rural India Surveys
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20
40
60
80
100
120
2 3 4 5 6
1982 1999
Girls: Average Height by Age and Survey Year, Rural India Surveys
Change in HYV-Crop Productivity and School Enrollment in Sample Districts: 1971-82
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40
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90
1980
1982
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1990
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1994
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2006
Boys Girls
Middle School (Grades 6-8) Enrollment Rates in India, by Gender, 1980-2006
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5
10
15
20
25
30
35
40
45
50
China Indonesia India Nigeria
1975 2000
Change in Percent Urbanized, by Country, 1975-2000
0
50000
100000
150000
200000
250000
300000
0.01-0.20
0.21 -0.40
0.41 -1.00
1.0 -2.00
2.01 -3.00
3.01 -4.00
4.01 -6.00
6.0 1-8.00
>8.01
The Distribution of Owned Landholdings in Rural India (July 2006 – June 2007, NSS):Number of Households (x1,000) in Intervals of Hectares
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0.6
0.7
0.8
0.9
1
<1 1 2 3 4 5 6 7 8 9 10+
Tractor PlowThresher
Mechanization and Owned Landholdings (Acres) in India, 2007-2008
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
1950-59 1960-69 1970-79 1980-89 1990-99
Rates of Out-Marriage from Sub-caste, by Decade, Rural India 1950-1999
Trade Policy Change: Openness in India
Policy: Open to international trade and commerce
Reduction in trade barriers: reduction in tariffs, quotas
Mumbai prior to the reforms
1. Caste-based and gender-based occupational distribution
Lower castes in blue-collar, manual jobs: job referrals important
2. Occupational immobility across generations by caste group
3. Few women work
Only labor-force participation by upper caste women
4. Two types of schools: English medium, local-language
English-language schools dominated by upper castes
What happened in Mumbai (center of trade and commerce) after the reforms?
1. Rise in returns to speaking, understanding English, men and women
Demand increased for jobs in trade, finance, commerce
Reduction in demand for blue-collar (mill) jobs
2. Shift in enrollment from local-language to English-language schools
3. Shift more substantial for lower-caste women
4. Breakdown of caste-based occupational immobility
Role of caste in providing blue-collar job referrals less valuable
5. Substantial increase in labor-force participation for lower-castewomen
Jobs in which women have a comparative advantage increased
Percent of Men Receiving Job Referrals and Speaking English, by Occupation
Table 1
Occupational Distribution (%), by Caste and Generation: Mumbai Men
Relationship to
Student
Fathers (2002) Grandfathers (1980)
Occupation Low
Castes
Middle
Castes
High
Castes
Low
Castes
Middle
Castes
High
Castes
No work 2.63 2.69 0.94 1.13 1.15 0.72
Unskilled manual 11.1 7.84 4.41 9.00 3.63 2.10
Skilled manual 17.4 13.7 10.2 11.67 6.72 8.42
Organized blue collar 22.9 19.2 2.90 22.9 24.2 7.67
Clerical 28.1 36.6 20.8 22.2 23.8 28.4
Professional 8.30 8.79 43.5 5.56 6.18 33.7
Business 7.95 8.79 15.2 6.11 4.72 13.0
Petty trade 4.00 4.51 2.52 3.11 3.20 3.34
Farming 0.33 0.48 0.12 19.4 27.5 2.97
Number 1860 1774 793 1866 1934 839
Table 2
Occupational Distribution (%), by Caste: Mumbai Women
Occupation Low Castes Middle Castes High Castes
No work 79.7 80.5 49.1
Unskilled
manual
6.06 3.24 1.18
Skilled manual 1.81 1.60 3.17
Organized blue
collar
0.90 1.03 0.35
Clerical 6.38 7.88 23.4
Professional 3.46 4.53 20.3
Business 0.90 0.51 1.88
Petty trade 0.80 0.72 0.59
Farming 0 0 0
Number 1881 1942 851
0
0.05
0.1
0.15
0.2
0.25
1980 1985 1990 1995 2000
English Schooling
Mumbai: Returns to English and Schooling by Year, 1980-2000 - Men Aged 30-55
0
0.05
0.1
0.15
0.2
0.25
0.3
1980 1985 1990 1995 2000
English Schooling
Mumbai: Returns to English and Schooling by Year, 1980-2000 - Women Aged 30-55
0
10
20
30
40
50
60
Grandmothers Mothers Sisters 20+
Low Middle Upper
Mumbai: Labor-Force Participation Across Three Generations of Women, by Caste Group
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
1970-75 1975-79 1980-85 1985-90 1990-95 1995-2002
Rates of Out-Marriage from Sub-caste, by Quinquennia, Mumbai 1970-2002
Mumbai 2002: Percentage Inter-marrying, by School Type
0
5
10
15
20
25
30
35
Marathi Schooled English Schooled
China
Policy of industrialization via infrastructure investments, export promotion
What happened in urban areas?
1. Growth in skill-intensive occupations
2. Rise in rate of return to schooling
3. Increase in schooling investment
Faster for women than men
Schooling of women higher than that of men in recent cohorts
4. Increase in occupational division of labor between men and women
0.4
0.45
0.5
0.55
0.6
0.65
0.7
1967 1972 1977 1982 1987 1992 1997 2002
Proportion of Employment in in Non-Brawn Occupations, by Year, 1968-2002:in Five Chinese Cities (Source: 2002 Chinese Adult Nontwin Survey)
2
4
6
8
10
12
14
1965 1970 1975 1980 1985 1990 1995 2000 2005
Rural MalesRural FemalesUrban MalesUrban Females
Mean Years of Schooling by Gender and Urban-Rural and Year Attained Age 22, 1967-2005(Source: 2005 Chinese Census)
0.4
2.4
4.4
6.4
8.4
10.4
12.4
14.4
1987 1989 1991 1993 1995 1997 1999 2001
Women
Men
Estimated Rates of Return to Schooling, by Gender and Year, 1988-2001:in Six Chinese Provinces (Source: Chinese Urban Household Surveys)
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1967 1972 1977 1982 1987 1992 1997 2002
Females
Males
Proportion of Employment in non-Brawn Occupations, by Gender and Year, 1968-2002, in Five Chinese Cities (Source: 2002 Chinese Adult Nontwin Survey)
Conclusions
A. A supply-side policy of increasing human capital (health, schooling) alone:
Increases human capital, particularly schooling for women, but little else
No structural transformation of the economy: occupational mix unchanged
B. Investment in agricultural technology alone:
Increase incomes for rural households, including the landless
Increase rural schooling less for the landless
Favors men over women (still a brawn economy)
No structural transformation
C. Industrialization via trade openness
Increases incomes
Changes the occupational mix to more skill-intensive
Raises the returns to schooling
Increases schooling investment, particularly for women
Favors women in terms of earnings
Decreases social stratification and increases intergenerational mobility