The Dynamics of Poverty and its Determinants: The Case of the Northeast of Brazil and its States
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World Bank, Washington, D.C.
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In the northeast region of Brazil, the
poverty picture of the past two decades reveals large
fluctuations in the poverty level, and poverty depth.
Findings based on the Brazilian annual household survey
(Pesquisa Nacional de Amostra Domiciliar, PNAD) datasets
from 1981-99 reveal that individual characteristics such as
education, experience, and labor market association of the
household head are important correlates of poverty. Taking
these into account, data reveal that a Nordestino
(northeasterner) is 24 percentage points more likely to fall
below the indigent poverty line than other Brazilians.
Analyses also reveal large differences in poverty levels by
education, and these differences have increased over time.
The authors observe 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 the authors
control for education and other individual characteristics,
female-headed households have a much larger likelihood of
being poor than 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 children under age 5
appear more likely to fall below the poverty line, than
families with no children below age 5. The presence of
old-aged people (above 65 years) in the household is an
important factor contributing to poverty reduction.
Palabras clave
POVERTY INCIDENCE, ABSOLUTE POVERTY, CASE STUDY, POVERTY DEPTH, POVERTY LINE, HOUSEHOLD SURVEYS, EDUCATIONAL LEVEL, SKILLS, LABOR MARKET NEXUS, HOUSEHOLD STRUCTURE, FEMALE HEADED HOUSEHOLDS, EDUCATIONAL ACCREDITATION, POOR CHILDREN, OLD AGE, POVERTY REDUCTION, ABSOLUTE INEQUALITY, ABSOLUTE POVERTY, ACCESS TO SERVICES, AGRICULTURAL SECTOR, AVAILABLE DATA, AVERAGE INCOME, CHILD LABOR, CIVIL SOCIETY, CURRENCY UNIT, DATA SET, DATA SETS, DEVELOPED COUNTRIES, ECONOMIC ACTIVITY, ECONOMIC GROWTH, ECONOMIC RECESSION, EDUCATIONAL ATTAINMENT, EQUAL SOCIETIES, EXCHANGE RATE, FEMALE-HEADED HOUSEHOLDS, FOOD BASKET, FOOD EXPENDITURES, GINI COEFFICIENT, GROWTH RATE, HEADCOUNT INDEX, HEADCOUNT POVERTY, HEADCOUNT RATIO, HIGH GROWTH, HIGH INFLATION, HIGH POVERTY, HOUSEHOLD HEAD, HOUSEHOLD INCOME, HOUSEHOLD POVERTY, HOUSEHOLD SURVEY, HUMAN CAPITAL, INCOME, INCOME INEQUALITY, INCOME LEVEL, INCOME POVERTY, INCREASED INVESTMENT, INDIVIDUAL INCOME, INDUSTRIAL SECTOR, INEQUALITY, INEQUALITY MEASURES, INFLATION RATE, LABOR FORCE, LABOR FORCE PARTICIPATION, LABOR MARKETS, MACROECONOMIC INSTABILITY, MACROECONOMIC STABILITY, MACROECONOMIC STABILIZATION, MEAN INCOMES, MINIMUM WAGE, NATIONAL AVERAGE, NATIONAL LEVEL, NEGATIVE EFFECT, OLD AGE, OVERVALUED EXCHANGE, PENSION SYSTEM, PER-CAPITA INCOME, POLICY RESEARCH, POOR, POOR POPULATION, POVERTY GAP, POVERTY HEADCOUNT, POVERTY INDEX, POVERTY LINE, POVERTY MEASURES, POVERTY OUTCOMES, POVERTY PROFILE, POVERTY RATE, POVERTY REDUCTION, PRIMARY EDUCATION, PUBLIC INSTITUTIONS, PUBLIC POLICIES, PUBLIC SECTOR, PUBLIC SERVICES, REDUCING POVERTY, RURAL AREAS, RURAL HOUSEHOLDS, RURAL POVERTY, SAMPLE SIZE, SAVINGS, SECTOR EMPLOYMENT, SERVICE SECTOR, SOCIAL INDICATORS, SOCIAL SECURITY, SQUARED POVERTY GAP, STATE POLICIES, UNEMPLOYMENT, UNEQUAL DISTRIBUTION, URBAN AREA, URBAN AREAS, WAGE DIFFERENTIALS, WELFARE INDICATORS, WELFARE MEASURE