Making the Poor Count Takes More than Counting the Poor: A Quick Poverty Assessment of the State of Bahia, Brazil
The state of Bahia, Brazil has made progress in reducing poverty and improving social indicators in the past decade. Despite this progress, Bahia's poverty is among the highest and its social indicators are among the lowest in Brazil. Currentl...
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| Format: | Policy Research Working Paper |
| Language: | English en_US |
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World Bank, Washington, D.C.
2013
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| Online Access: | http://documents.worldbank.org/curated/en/2004/02/3910308/making-poor-count-takes-more-counting-poor-quick-poverty-assessment-state-bahia-brazil http://hdl.handle.net/10986/14313 |
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okr-10986-14313 |
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oai_dc |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
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World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English en_US |
| topic |
ABSOLUTE TERMS ACCESS TO SERVICES AGED ALCOHOL ANALYTICAL WORK ANNUAL RATE AVAILABLE DATA AVERAGE AGE AVERAGE INCOMES BIRTH RATE CANCER CAPITA INCOMES CERVICAL CANCER CONDOMS DEBT DEMOGRAPHICS DEPENDENCY RATIO DEVELOPMENT INDICATORS ECONOMIC ACTIVITIES ECONOMIC CONDITIONS ECONOMIC GROWTH ECONOMIC POLICIES ECONOMIC SITUATION EDUCATIONAL ATTAINMENT ELDERLY PEOPLE EMPLOYMENT EXCHANGE RATE EXTREME POVERTY FAMILIES FAMILY PLANNING FOOD BASKET GINI COEFFICIENT GINI INDEX GROWTH RATE HEADCOUNT POVERTY HEALTH CARE HEALTH PROGRAMS HIGH INFLATION HOUSEHOLD ASSETS HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HUMAN CAPITAL HUMAN DEVELOPMENT ILLITERACY IMPROVED HEALTH INCOME DISTRIBUTION INCOME INEQUALITY INCOME POVERTY INCREASED ACCESS INFLATION INSTITUTIONAL CHANGE INTEREST RATES LABOR FORCE LABOR MARKET LIFE EXPECTANCY LIVING CONDITIONS MACROECONOMIC STABILITY MACROECONOMIC STABILIZATION MEDIAN INCOME MIGRATION MINIMUM WAGE MONETARY POLICIES MORTALITY MOTHERS MULTIVARIATE ANALYSIS NATIONAL AVERAGE NON-POOR HOUSEHOLDS NUTRITION OIL PER-CAPITA INCOME POLICY MAKING POLICY REFORMS POLICY RESEARCH POOR POOR HOUSEHOLDS POOR PERSON POPULATION GROWTH POVERTY ALLEVIATION POVERTY ASSESSMENT POVERTY GAP POVERTY INDICATORS POVERTY LINE POVERTY MEASURE POVERTY MEASURES POVERTY PROFILE POVERTY RATE POVERTY RATES POVERTY REDUCING POVERTY REDUCTION POVERTY REDUCTION STRATEGY PROSTATE CANCER PUBLIC POLICY PUBLIC PROGRAMS PUBLIC SERVICES PUBLIC UTILITIES QUALITY OF LIFE QUANTITATIVE ANALYSIS REDUCED POVERTY REDUCING INFLATION REDUCING POVERTY REGIONAL DISPARITIES RURAL AREAS RURAL ECONOMY SAVINGS SIGNIFICANT EFFECT SOCIAL ASSISTANCE SOCIAL EXCLUSION SOCIAL INDICATORS SOCIAL PROGRAMS SOCIAL PROTECTION SOCIAL PROTECTION PROGRAMS SOCIAL SERVICES SQUARED POVERTY GAP SUSTAINABLE POVERTY URBAN AREAS VIOLENCE VULNERABLE GROUPS WAGES WATER SUPPLY WORKERS YOUNG ADULTS POVERTY SOCIAL INDICATORS INFANT MORTALITY ADULT ILLITERACY POVERTY INDICATORS INCOME INEQUALITY |
| spellingShingle |
ABSOLUTE TERMS ACCESS TO SERVICES AGED ALCOHOL ANALYTICAL WORK ANNUAL RATE AVAILABLE DATA AVERAGE AGE AVERAGE INCOMES BIRTH RATE CANCER CAPITA INCOMES CERVICAL CANCER CONDOMS DEBT DEMOGRAPHICS DEPENDENCY RATIO DEVELOPMENT INDICATORS ECONOMIC ACTIVITIES ECONOMIC CONDITIONS ECONOMIC GROWTH ECONOMIC POLICIES ECONOMIC SITUATION EDUCATIONAL ATTAINMENT ELDERLY PEOPLE EMPLOYMENT EXCHANGE RATE EXTREME POVERTY FAMILIES FAMILY PLANNING FOOD BASKET GINI COEFFICIENT GINI INDEX GROWTH RATE HEADCOUNT POVERTY HEALTH CARE HEALTH PROGRAMS HIGH INFLATION HOUSEHOLD ASSETS HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HUMAN CAPITAL HUMAN DEVELOPMENT ILLITERACY IMPROVED HEALTH INCOME DISTRIBUTION INCOME INEQUALITY INCOME POVERTY INCREASED ACCESS INFLATION INSTITUTIONAL CHANGE INTEREST RATES LABOR FORCE LABOR MARKET LIFE EXPECTANCY LIVING CONDITIONS MACROECONOMIC STABILITY MACROECONOMIC STABILIZATION MEDIAN INCOME MIGRATION MINIMUM WAGE MONETARY POLICIES MORTALITY MOTHERS MULTIVARIATE ANALYSIS NATIONAL AVERAGE NON-POOR HOUSEHOLDS NUTRITION OIL PER-CAPITA INCOME POLICY MAKING POLICY REFORMS POLICY RESEARCH POOR POOR HOUSEHOLDS POOR PERSON POPULATION GROWTH POVERTY ALLEVIATION POVERTY ASSESSMENT POVERTY GAP POVERTY INDICATORS POVERTY LINE POVERTY MEASURE POVERTY MEASURES POVERTY PROFILE POVERTY RATE POVERTY RATES POVERTY REDUCING POVERTY REDUCTION POVERTY REDUCTION STRATEGY PROSTATE CANCER PUBLIC POLICY PUBLIC PROGRAMS PUBLIC SERVICES PUBLIC UTILITIES QUALITY OF LIFE QUANTITATIVE ANALYSIS REDUCED POVERTY REDUCING INFLATION REDUCING POVERTY REGIONAL DISPARITIES RURAL AREAS RURAL ECONOMY SAVINGS SIGNIFICANT EFFECT SOCIAL ASSISTANCE SOCIAL EXCLUSION SOCIAL INDICATORS SOCIAL PROGRAMS SOCIAL PROTECTION SOCIAL PROTECTION PROGRAMS SOCIAL SERVICES SQUARED POVERTY GAP SUSTAINABLE POVERTY URBAN AREAS VIOLENCE VULNERABLE GROUPS WAGES WATER SUPPLY WORKERS YOUNG ADULTS POVERTY SOCIAL INDICATORS INFANT MORTALITY ADULT ILLITERACY POVERTY INDICATORS INCOME INEQUALITY Verner, Dorte Making the Poor Count Takes More than Counting the Poor: A Quick Poverty Assessment of the State of Bahia, Brazil |
| geographic_facet |
Latin America & Caribbean Brazil |
| relation |
Policy Research Working Paper;No.3216 |
| description |
The state of Bahia, Brazil has made
progress in reducing poverty and improving social indicators
in the past decade. Despite this progress, Bahia's
poverty is among the highest and its social indicators are
among the lowest in Brazil. Currently, 41 percent of
Bahia's population live in households below the poverty
level, a drop of 14 percentage points since 1993. Moreover,
poverty is less deep than in 1993, but deeper than in 1981.
The fall in Bahia's social indicators, such as infant
mortality and adult illiteracy, corroborate the improvement
in measured income poverty. Part of the reason why the
poverty indicators of Bahia are worse than in other
countries with similar per-capita income is because of
income inequality. In 2000 the Gini coefficient for Bahia
was 0.61. The National Household Survey Data, PNAD, from
1981-2001 reveal that living in Bahia does not by itself
affect the probability of falling below the poverty line in
Brazil. Hence, other characteristics are more important for
poverty reduction than geographical location. The strongest
poverty correlates are education, experience, race, rural
location, gender, and labor market association. Analyses
reveal that the probability of being poor is decreasing with
increasing educational attainment. The gender of the
household head does not matter for poverty according to the
poverty profile, but when we control for education and other
individual characteristics, female-headed households have a
much larger likelihood of being poor than do male-headed
households. Household size also matters for poverty. Larger
households are more likely to experience poverty than
smaller households, and the effect is concave. Moreover,
households with members under age five appear more likely to
fall below the poverty line than families with no children
below five years old. The presence of old-aged people (above
65 years of age) in the household is an important factor
contributing to poverty reduction. |
| format |
Publications & Research :: Policy Research Working Paper |
| author |
Verner, Dorte |
| author_facet |
Verner, Dorte |
| author_sort |
Verner, Dorte |
| title |
Making the Poor Count Takes More than Counting the Poor: A Quick Poverty Assessment of the State of Bahia, Brazil |
| title_short |
Making the Poor Count Takes More than Counting the Poor: A Quick Poverty Assessment of the State of Bahia, Brazil |
| title_full |
Making the Poor Count Takes More than Counting the Poor: A Quick Poverty Assessment of the State of Bahia, Brazil |
| title_fullStr |
Making the Poor Count Takes More than Counting the Poor: A Quick Poverty Assessment of the State of Bahia, Brazil |
| title_full_unstemmed |
Making the Poor Count Takes More than Counting the Poor: A Quick Poverty Assessment of the State of Bahia, Brazil |
| title_sort |
making the poor count takes more than counting the poor: a quick poverty assessment of the state of bahia, brazil |
| publisher |
World Bank, Washington, D.C. |
| publishDate |
2013 |
| url |
http://documents.worldbank.org/curated/en/2004/02/3910308/making-poor-count-takes-more-counting-poor-quick-poverty-assessment-state-bahia-brazil http://hdl.handle.net/10986/14313 |
| _version_ |
1764430286473396224 |
| spelling |
okr-10986-143132021-04-23T14:03:20Z Making the Poor Count Takes More than Counting the Poor: A Quick Poverty Assessment of the State of Bahia, Brazil Verner, Dorte ABSOLUTE TERMS ACCESS TO SERVICES AGED ALCOHOL ANALYTICAL WORK ANNUAL RATE AVAILABLE DATA AVERAGE AGE AVERAGE INCOMES BIRTH RATE CANCER CAPITA INCOMES CERVICAL CANCER CONDOMS DEBT DEMOGRAPHICS DEPENDENCY RATIO DEVELOPMENT INDICATORS ECONOMIC ACTIVITIES ECONOMIC CONDITIONS ECONOMIC GROWTH ECONOMIC POLICIES ECONOMIC SITUATION EDUCATIONAL ATTAINMENT ELDERLY PEOPLE EMPLOYMENT EXCHANGE RATE EXTREME POVERTY FAMILIES FAMILY PLANNING FOOD BASKET GINI COEFFICIENT GINI INDEX GROWTH RATE HEADCOUNT POVERTY HEALTH CARE HEALTH PROGRAMS HIGH INFLATION HOUSEHOLD ASSETS HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HUMAN CAPITAL HUMAN DEVELOPMENT ILLITERACY IMPROVED HEALTH INCOME DISTRIBUTION INCOME INEQUALITY INCOME POVERTY INCREASED ACCESS INFLATION INSTITUTIONAL CHANGE INTEREST RATES LABOR FORCE LABOR MARKET LIFE EXPECTANCY LIVING CONDITIONS MACROECONOMIC STABILITY MACROECONOMIC STABILIZATION MEDIAN INCOME MIGRATION MINIMUM WAGE MONETARY POLICIES MORTALITY MOTHERS MULTIVARIATE ANALYSIS NATIONAL AVERAGE NON-POOR HOUSEHOLDS NUTRITION OIL PER-CAPITA INCOME POLICY MAKING POLICY REFORMS POLICY RESEARCH POOR POOR HOUSEHOLDS POOR PERSON POPULATION GROWTH POVERTY ALLEVIATION POVERTY ASSESSMENT POVERTY GAP POVERTY INDICATORS POVERTY LINE POVERTY MEASURE POVERTY MEASURES POVERTY PROFILE POVERTY RATE POVERTY RATES POVERTY REDUCING POVERTY REDUCTION POVERTY REDUCTION STRATEGY PROSTATE CANCER PUBLIC POLICY PUBLIC PROGRAMS PUBLIC SERVICES PUBLIC UTILITIES QUALITY OF LIFE QUANTITATIVE ANALYSIS REDUCED POVERTY REDUCING INFLATION REDUCING POVERTY REGIONAL DISPARITIES RURAL AREAS RURAL ECONOMY SAVINGS SIGNIFICANT EFFECT SOCIAL ASSISTANCE SOCIAL EXCLUSION SOCIAL INDICATORS SOCIAL PROGRAMS SOCIAL PROTECTION SOCIAL PROTECTION PROGRAMS SOCIAL SERVICES SQUARED POVERTY GAP SUSTAINABLE POVERTY URBAN AREAS VIOLENCE VULNERABLE GROUPS WAGES WATER SUPPLY WORKERS YOUNG ADULTS POVERTY SOCIAL INDICATORS INFANT MORTALITY ADULT ILLITERACY POVERTY INDICATORS INCOME INEQUALITY The state of Bahia, Brazil has made progress in reducing poverty and improving social indicators in the past decade. Despite this progress, Bahia's poverty is among the highest and its social indicators are among the lowest in Brazil. Currently, 41 percent of Bahia's population live in households below the poverty level, a drop of 14 percentage points since 1993. Moreover, poverty is less deep than in 1993, but deeper than in 1981. The fall in Bahia's social indicators, such as infant mortality and adult illiteracy, corroborate the improvement in measured income poverty. Part of the reason why the poverty indicators of Bahia are worse than in other countries with similar per-capita income is because of income inequality. In 2000 the Gini coefficient for Bahia was 0.61. The National Household Survey Data, PNAD, from 1981-2001 reveal that living in Bahia does not by itself affect the probability of falling below the poverty line in Brazil. Hence, other characteristics are more important for poverty reduction than geographical location. The strongest poverty correlates are education, experience, race, rural location, gender, and labor market association. Analyses reveal that the probability of being poor is decreasing with increasing educational attainment. The gender of the household head does not matter for poverty according to the poverty profile, but when we control for education and other individual characteristics, female-headed households have a much larger likelihood of being poor than do male-headed households. Household size also matters for poverty. Larger households are more likely to experience poverty than smaller households, and the effect is concave. Moreover, households with members under age five appear more likely to fall below the poverty line than families with no children below five years old. The presence of old-aged people (above 65 years of age) in the household is an important factor contributing to poverty reduction. 2013-07-01T18:26:22Z 2013-07-01T18:26:22Z 2004-02 http://documents.worldbank.org/curated/en/2004/02/3910308/making-poor-count-takes-more-counting-poor-quick-poverty-assessment-state-bahia-brazil http://hdl.handle.net/10986/14313 English en_US Policy Research Working Paper;No.3216 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo/ World Bank World Bank, Washington, D.C. Publications & Research :: Policy Research Working Paper Publications & Research Latin America & Caribbean Brazil |