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Economic Development, Poverty, and the Disadvantaged - Mark Rosenzweig (Yale)
 

Economic Development, Poverty, and the Disadvantaged - Mark Rosenzweig (Yale)

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Roundtable on Development: poverty, corruption, fragmentation and conflict ...

Roundtable on Development: poverty, corruption, fragmentation and conflict

Barcelona GSE Summer Forum
Barcelona Graduate School of Economics
June 14, 2013

http://www.barcelonagse.eu/summer-forum.html

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    Economic Development, Poverty, and the Disadvantaged - Mark Rosenzweig (Yale) Economic Development, Poverty, and the Disadvantaged - Mark Rosenzweig (Yale) Presentation Transcript

    • Economic Development, Poverty and the DisadvantagedMark R. RosenzweigYale University
    • Global Poverty and the DisadvantagedFrom 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 worldEnormous 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 16000CambodiaIndiaMongoliaLaosNepalSri LankaVietnamPhilippinesBangladeshIndonesiaChinaPakistanThailandKoreaJapanMalaysiaHong KongSingaporeTaiwanOWW Skill Price (x10)NIS-P Skill PriceEstimated PPP $ (1995) Skill Prices for 19 Asian Countries,by NIS-P and OWW Sources
    • 01000200030004000500060007000Nigeria India Indonesia Mexico KoreaHigh School GraduateCollege GraduateEstimated (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 activity2. 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 Assessed1. Public and NGO Investments in Public HealthRural Bangladesh, 1980-2. Investment in Agricultural TechnologyThe “Green Revolution” in Rural India, 1970 -3. Trade Policy ReformsUrban India (Mumbai), 1990 -4. IndustrializationUrban China, 1980 -Examples selected because we have good data over at least 20-year period trackingchanges
    • Some Simple Analytics: Human Capital, Gender and OccupationThere are two broad categories of human capital1. 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 womenFrom biology: Nutrition increases strength, but only for womenEconomic theory: people choose occupations according to their comparativeadvantagePeople with relatively more skill choose skill-intensive jobs if theycan chooseTherefore, women choose more skill-intensive jobs compared withmen, when that is possible
    • SchoolingA. Schooling improves ability to think, to decide, to make allocationdecisionsOld technology versus new technologyB. Schooling is more valuable in some occupations compared with others1. Farm manager (landowner) versus wage worker (landless)2. Clerk, service worker versus bricklayerC. The overall returns to schooling will depend on the demand for differentjobsChanges 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 investmentDevelopment 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 BangladeshA. Improvements in sanitation, water quality, provision of health educationImplemented/funded jointly government and NGO’sMajor reductions in morbidity (e.g. diarrheal disease)B. Provision of schoolsAssured access to school, subsidized schooling
    • What happened in rural areas?1. Reductions in morbidity for men and women2. Increases in height and BMI for men and women, brawn for menonly3. Increases in schooling, especially for women4. Occupational structure more different between men and womenWhat did not happen?1. No increase in agricultural productivity or wages2. No major change in the occupational structure3. No change in calorie consumption
    • 00.20.40.60.811.21.41981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002Girl/Boy Enrollment RatioFraction Rural Population with Improved SanitationAgricultural Real Wage Index (1949=1)Fraction of Micro-Credit Members in Rural Adult PopulationRural 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
    • 00.10.20.30.40.50.60.70.80.915 6 7 8 9 10 11 12 13 14 15 16Boys GirlsRural Bangladesh: School Attendance, by Age, Gender and Survey Year2001-21981-2
    • 1213141516171819205791113151719212325272931333537394143BMI 2002BMI 1981Rural Bangladesh: BMI, by Age and Year for Males
    • 121314151617181920 5791113151719212325272931333537394143BMI 2002BMI 1981Rural Bangladesh: BMI, by Age and Year for Females
    • 1401451501551601651701952195419561958196019621964196619681970197219741976197819801982198419861988199019921994199619982000Men in 1982 SurveyMen in 2000 SurveyWomen in 1982 SurveyWomen in 2000 SurveyRural Bangladesh: Attained Height, by Sex and Year Person Reached Age 20
    • 05001000150020002500300035001981 2002Women MenRural Bangladesh: Daily Calorie Intake Mean and Women Aged 20-49,1982 and 2002
    • 00.10.20.30.40.50.60.70.80.911981 2002Women MenProportion of Adults Aged 25 – 40 in ‘Exceptionally Active’ or ‘Very Active’ Occupations,by Gender and Year, Rural Bangladesh Surveys
    • Table OOccupational Distributions in 2004, by Gender and Rural-UrbanOccupation/ Population Rural UrbanMenFarmer, agricultural laborer, fisherman 49.4 9.7Unskilled laborer (rickshaw puller, brickbreaking, etc.)12.0 14.8Factory worker or blue-collar service 3.3 7.5Semi-skilled laborer (carpenter, mason,bus/taxi driver)9.8 22.4Professional (teacher, doctor, lawyer) 2.4 5.2Business 16.4 31.3Other 0.6 0.4Not working 5.8 8.7WomenAgricultural worker 1.2 0.4Home-based manufacturing 3.7 3.1Unskilled laborer (construction, brickbreaking, etc.)2.7 2.4Poultry raising, cattle raising, trading 7.8 3.5Domestic labor 2.0 5.8Semi-skilled service (tailor, etc.) 3.0 6.4Professional (teacher, doctor, lawyer) 0.5 1.7Business 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 India2. Picked “winners”Subsidized credit, increased fertilizer supply in regions wherenew seeds were expected to increase agricultural productivitythe mostB. Continued improvements in seed technologyC. Tubewell irrigation became cheaper
    • What happened in rural areas of India?1. Sustained increase in agricultural yields and agricultural wagesa. So the landless benefitted, as well as those owning land2. Increases in nutritional status for both boys and girls (height)3. Rise in the returns to schooling, particularly in areas where technologywas most productive4. Increases in schooling investment, particularly in those areas of highchangea. Increases in schooling less for the landless: why?Landless are wage worker who do not make allocation decisionsSchooling augments capacity for making decisionsb. 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 economyUrbanization did not advance rapidly, slow compared with othercountries with high growth ratesThe size of the agricultural sector is still large2. No structural transformation of agricultureStill small-scale and not mechanized: brawn still importantSubstantially less productive than agriculture in developed countries3. No change in social arrangements in rural areas, role of womenCaste still plays a major role in lives of rural householdsPrincipal role of caste groups: insurance, loan provision
    • HYV Yields (Rupees per acre) and Real Agricultural Wages, 1971-19990246810121416181971 1982 1999HYV Yield/100 (1971 rupees)Agricultural Wage (1982 rupees)
    • 51015202530354045197019721974197619781980198219841986198819901992199419961998200020022004Real Agricultural Wages in India, 1970-2004 (Source: Bhalla and Das, 2006)
    • 0204060801001202 3 4 5 61982 1999Boys: Average Height by Age and Survey Year, Rural India Surveys
    • 0204060801001202 3 4 5 61982 1999Girls: Average Height by Age and Survey Year, Rural India Surveys
    • Change in HYV-Crop Productivity and School Enrollment in Sample Districts: 1971-82
    • 010203040506070809019801982198419861988199019921994199619982000200220042006Boys GirlsMiddle School (Grades 6-8) Enrollment Rates in India, by Gender, 1980-2006
    • 05101520253035404550China Indonesia India Nigeria1975 2000Change in Percent Urbanized, by Country, 1975-2000
    • 0500001000001500002000002500003000000.01-0.200.21 -0.400.41 -1.001.0 -2.002.01 -3.003.01 -4.004.01 -6.006.0 1-8.00>8.01The Distribution of Owned Landholdings in Rural India (July 2006 – June 2007, NSS):Number of Households (x1,000) in Intervals of Hectares
    •    
    • 00.10.20.30.40.50.60.70.80.91<1 1 2 3 4 5 6 7 8 9 10+Tractor PlowThresherMechanization and Owned Landholdings (Acres) in India, 2007-2008
    • 00.020.040.060.080.10.120.141950-59 1960-69 1970-79 1980-89 1990-99Rates of Out-Marriage from Sub-caste, by Decade, Rural India 1950-1999
    • Trade Policy Change: Openness in IndiaPolicy: Open to international trade and commerceReduction in trade barriers: reduction in tariffs, quotasMumbai prior to the reforms1. Caste-based and gender-based occupational distributionLower castes in blue-collar, manual jobs: job referrals important2. Occupational immobility across generations by caste group3. Few women workOnly labor-force participation by upper caste women4. Two types of schools: English medium, local-languageEnglish-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 womenDemand increased for jobs in trade, finance, commerceReduction in demand for blue-collar (mill) jobs2. Shift in enrollment from local-language to English-language schools3. Shift more substantial for lower-caste women4. Breakdown of caste-based occupational immobilityRole of caste in providing blue-collar job referrals less valuable5. Substantial increase in labor-force participation for lower-castewomenJobs in which women have a comparative advantage increased
    • Percent of Men Receiving Job Referrals and Speaking English, by Occupation
    • Table 1Occupational Distribution (%), by Caste and Generation: Mumbai MenRelationship toStudentFathers (2002) Grandfathers (1980)Occupation LowCastesMiddleCastesHighCastesLowCastesMiddleCastesHighCastesNo work 2.63 2.69 0.94 1.13 1.15 0.72Unskilled manual 11.1 7.84 4.41 9.00 3.63 2.10Skilled manual 17.4 13.7 10.2 11.67 6.72 8.42Organized blue collar 22.9 19.2 2.90 22.9 24.2 7.67Clerical 28.1 36.6 20.8 22.2 23.8 28.4Professional 8.30 8.79 43.5 5.56 6.18 33.7Business 7.95 8.79 15.2 6.11 4.72 13.0Petty trade 4.00 4.51 2.52 3.11 3.20 3.34Farming 0.33 0.48 0.12 19.4 27.5 2.97Number 1860 1774 793 1866 1934 839
    • Table 2Occupational Distribution (%), by Caste: Mumbai WomenOccupation Low Castes Middle Castes High CastesNo work 79.7 80.5 49.1Unskilledmanual6.06 3.24 1.18Skilled manual 1.81 1.60 3.17Organized bluecollar0.90 1.03 0.35Clerical 6.38 7.88 23.4Professional 3.46 4.53 20.3Business 0.90 0.51 1.88Petty trade 0.80 0.72 0.59Farming 0 0 0Number 1881 1942 851
    • 00.050.10.150.20.251980 1985 1990 1995 2000English SchoolingMumbai: Returns to English and Schooling by Year, 1980-2000 - Men Aged 30-55
    • 00.050.10.150.20.250.31980 1985 1990 1995 2000English SchoolingMumbai: Returns to English and Schooling by Year, 1980-2000 - Women Aged 30-55
    • 0102030405060Grandmothers Mothers Sisters 20+Low Middle UpperMumbai: Labor-Force Participation Across Three Generations of Women, by Caste Group
    • 00.020.040.060.080.10.120.141970-75 1975-79 1980-85 1985-90 1990-95 1995-2002Rates of Out-Marriage from Sub-caste, by Quinquennia, Mumbai 1970-2002
    • Mumbai 2002: Percentage Inter-marrying, by School Type05101520253035Marathi Schooled English Schooled
    • ChinaPolicy of industrialization via infrastructure investments, export promotionWhat happened in urban areas?1. Growth in skill-intensive occupations2. Rise in rate of return to schooling3. Increase in schooling investmentFaster for women than menSchooling of women higher than that of men in recent cohorts4. Increase in occupational division of labor between men and women
    • 0.40.450.50.550.60.650.71967 1972 1977 1982 1987 1992 1997 2002Proportion of Employment in in Non-Brawn Occupations, by Year, 1968-2002:in Five Chinese Cities (Source: 2002 Chinese Adult Nontwin Survey)
    • 24681012141965 1970 1975 1980 1985 1990 1995 2000 2005Rural MalesRural FemalesUrban MalesUrban FemalesMean Years of Schooling by Gender and Urban-Rural and Year Attained Age 22, 1967-2005(Source: 2005 Chinese Census)
    • 0.42.44.46.48.410.412.414.41987 1989 1991 1993 1995 1997 1999 2001WomenMenEstimated Rates of Return to Schooling, by Gender and Year, 1988-2001:in Six Chinese Provinces (Source: Chinese Urban Household Surveys)
    • 0.20.30.40.50.60.70.80.911967 1972 1977 1982 1987 1992 1997 2002FemalesMalesProportion of Employment in non-Brawn Occupations, by Gender and Year, 1968-2002,in Five Chinese Cities (Source: 2002 Chinese Adult Nontwin Survey)
    • ConclusionsA. A supply-side policy of increasing human capital (health, schooling) alone:Increases human capital, particularly schooling for women, but little elseNo structural transformation of the economy: occupational mix unchangedB. Investment in agricultural technology alone:Increase incomes for rural households, including the landlessIncrease rural schooling less for the landlessFavors men over women (still a brawn economy)No structural transformation
    • C. Industrialization via trade opennessIncreases incomesChanges the occupational mix to more skill-intensiveRaises the returns to schoolingIncreases schooling investment, particularly for womenFavors women in terms of earningsDecreases social stratification and increases intergenerational mobility