Estimating Poverty in the Absence of Consumption Data : The Case of Liberia
In much of the developing world, the demand for high frequency quality household data for poverty monitoring and program design far outstrips the capacity of the statistics bureau to provide such data. In these environments, all available data sour...
Main Authors: | , , , |
---|---|
Format: | Policy Research Working Paper |
Language: | English en_US |
Published: |
World Bank Group, Washington, DC
2014
|
Subjects: | |
Online Access: | http://documents.worldbank.org/curated/en/2014/09/20177049/estimating-poverty-absence-consumption-data-case-liberia http://hdl.handle.net/10986/20336 |
id |
okr-10986-20336 |
---|---|
recordtype |
oai_dc |
spelling |
okr-10986-203362021-04-23T14:03:55Z Estimating Poverty in the Absence of Consumption Data : The Case of Liberia Dabalen, Andrew Graham, Errol Himelein, Kristen Mungai, Rose ALLOCATION OF RESOURCES CALCULATION CELL PHONE CELL PHONES CELLPHONE CELLPHONES CHANGES IN POVERTY CHILD MORTALITY COMMUNITY HEALTH CONFLICT CONSUMPTION AGGREGATE CONSUMPTION DATA CONSUMPTION EXPENDITURE CONSUMPTION EXPENDITURES CONSUMPTION QUINTILES CORRELATES OF POVERTY COUNTERFACTUAL CROP DIVERSITY CROP PRODUCTION DEMOGRAPHIC INFORMATION DIMENSIONS OF POVERTY DISCRIMINANT ANALYSIS DROP IN POVERTY ECONOMIC GROWTH ELECTRICITY ENUMERATION ESTIMATES OF POVERTY EXTREME POVERTY FACTOR ANALYSIS FAMINE FIREWOOD FREE SOFTWARE GLOBAL PARTNERSHIP HOUSEHOLD CONSUMPTION HOUSEHOLD DEMOGRAPHICS HOUSEHOLD HEAD HOUSEHOLD HEADS HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HOUSEHOLD SURVEYS HOUSING HUMAN CAPITAL HUMAN DEVELOPMENT HUMAN DEVELOPMENT INDEX IMPUTATION IMPUTATION METHOD IMPUTATION METHODS IMPUTATION PROCESS IMPUTATIONS INEQUALITY INFORMATION SERVICES LAND OWNERSHIP LAND SIZE LANDHOLDINGS LIVING STANDARDS MATERNAL MORTALITY MEANS TESTS MISSING DATA MISSING VALUES MULTIPLE IMPUTATION MULTIPLE IMPUTATIONS NATIONAL POVERTY NATIONAL POVERTY LINE NUTRITION OPEN ACCESS PER CAPITA CONSUMPTION POOR POOR HOUSEHOLDS POVERTY ANALYSIS POVERTY ESTIMATES POVERTY LEVELS POVERTY LINES POVERTY MAPPING POVERTY MEASUREMENT POVERTY MEASURES POVERTY QUINTILES POVERTY RANKINGS POVERTY RATES POVERTY REDUCTION POVERTY STATUS PRECISION PREDICTION PREDICTIONS PRINCIPAL COMPONENTS ANALYSIS RADIO RESULT RESULTS RURAL RURAL AREAS RURAL ECONOMY RURAL INEQUALITY SAMPLE DESIGN SAMPLE SIZE SATELLITE SOCIAL PROGRAMS STANDARD ERRORS STATA STATISTICAL ANALYSIS STATISTICAL ANALYSIS SOFTWARE STATISTICAL METHODS STATISTICIANS TARGETING TARGETS TECHNICAL UNIVERSITY TELEVISION TIME PERIOD TIME SERIES USES VERIFICATION WEB WELFARE INDICATOR In much of the developing world, the demand for high frequency quality household data for poverty monitoring and program design far outstrips the capacity of the statistics bureau to provide such data. In these environments, all available data sources must be leveraged. Most surveys, however, do not collect the detailed consumption data necessary to construct aggregates and poverty lines to measure poverty directly. This paper benefits from a shared listing exercise for two large-scale national household surveys conducted in Liberia in 2007 to explore alternative methodologies to estimate poverty indirectly. The first is an asset-based model that is commonly used in Demographic and Health Surveys. The second is a survey-to-survey imputation that makes use of small area estimation techniques. In addition to a standard base model, separate models are estimated for urban and rural areas and an expanded model that includes climatic variables. Special attention is paid to the inclusion of cell phones, with implications for other assets whose cost and availability may be changing rapidly. The results demonstrate substantial limitations with asset-based indexes, but also leave questions as to the accuracy and stability of imputation models. 2014-10-02T19:55:24Z 2014-10-02T19:55:24Z 2014-09 http://documents.worldbank.org/curated/en/2014/09/20177049/estimating-poverty-absence-consumption-data-case-liberia http://hdl.handle.net/10986/20336 English en_US Policy Research Working Paper;No. 7024 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo/ World Bank Group, Washington, DC Publications & Research :: Policy Research Working Paper Publications & Research Africa Liberia |
repository_type |
Digital Repository |
institution_category |
Foreign Institution |
institution |
Digital Repositories |
building |
World Bank Open Knowledge Repository |
collection |
World Bank |
language |
English en_US |
topic |
ALLOCATION OF RESOURCES CALCULATION CELL PHONE CELL PHONES CELLPHONE CELLPHONES CHANGES IN POVERTY CHILD MORTALITY COMMUNITY HEALTH CONFLICT CONSUMPTION AGGREGATE CONSUMPTION DATA CONSUMPTION EXPENDITURE CONSUMPTION EXPENDITURES CONSUMPTION QUINTILES CORRELATES OF POVERTY COUNTERFACTUAL CROP DIVERSITY CROP PRODUCTION DEMOGRAPHIC INFORMATION DIMENSIONS OF POVERTY DISCRIMINANT ANALYSIS DROP IN POVERTY ECONOMIC GROWTH ELECTRICITY ENUMERATION ESTIMATES OF POVERTY EXTREME POVERTY FACTOR ANALYSIS FAMINE FIREWOOD FREE SOFTWARE GLOBAL PARTNERSHIP HOUSEHOLD CONSUMPTION HOUSEHOLD DEMOGRAPHICS HOUSEHOLD HEAD HOUSEHOLD HEADS HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HOUSEHOLD SURVEYS HOUSING HUMAN CAPITAL HUMAN DEVELOPMENT HUMAN DEVELOPMENT INDEX IMPUTATION IMPUTATION METHOD IMPUTATION METHODS IMPUTATION PROCESS IMPUTATIONS INEQUALITY INFORMATION SERVICES LAND OWNERSHIP LAND SIZE LANDHOLDINGS LIVING STANDARDS MATERNAL MORTALITY MEANS TESTS MISSING DATA MISSING VALUES MULTIPLE IMPUTATION MULTIPLE IMPUTATIONS NATIONAL POVERTY NATIONAL POVERTY LINE NUTRITION OPEN ACCESS PER CAPITA CONSUMPTION POOR POOR HOUSEHOLDS POVERTY ANALYSIS POVERTY ESTIMATES POVERTY LEVELS POVERTY LINES POVERTY MAPPING POVERTY MEASUREMENT POVERTY MEASURES POVERTY QUINTILES POVERTY RANKINGS POVERTY RATES POVERTY REDUCTION POVERTY STATUS PRECISION PREDICTION PREDICTIONS PRINCIPAL COMPONENTS ANALYSIS RADIO RESULT RESULTS RURAL RURAL AREAS RURAL ECONOMY RURAL INEQUALITY SAMPLE DESIGN SAMPLE SIZE SATELLITE SOCIAL PROGRAMS STANDARD ERRORS STATA STATISTICAL ANALYSIS STATISTICAL ANALYSIS SOFTWARE STATISTICAL METHODS STATISTICIANS TARGETING TARGETS TECHNICAL UNIVERSITY TELEVISION TIME PERIOD TIME SERIES USES VERIFICATION WEB WELFARE INDICATOR |
spellingShingle |
ALLOCATION OF RESOURCES CALCULATION CELL PHONE CELL PHONES CELLPHONE CELLPHONES CHANGES IN POVERTY CHILD MORTALITY COMMUNITY HEALTH CONFLICT CONSUMPTION AGGREGATE CONSUMPTION DATA CONSUMPTION EXPENDITURE CONSUMPTION EXPENDITURES CONSUMPTION QUINTILES CORRELATES OF POVERTY COUNTERFACTUAL CROP DIVERSITY CROP PRODUCTION DEMOGRAPHIC INFORMATION DIMENSIONS OF POVERTY DISCRIMINANT ANALYSIS DROP IN POVERTY ECONOMIC GROWTH ELECTRICITY ENUMERATION ESTIMATES OF POVERTY EXTREME POVERTY FACTOR ANALYSIS FAMINE FIREWOOD FREE SOFTWARE GLOBAL PARTNERSHIP HOUSEHOLD CONSUMPTION HOUSEHOLD DEMOGRAPHICS HOUSEHOLD HEAD HOUSEHOLD HEADS HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HOUSEHOLD SURVEYS HOUSING HUMAN CAPITAL HUMAN DEVELOPMENT HUMAN DEVELOPMENT INDEX IMPUTATION IMPUTATION METHOD IMPUTATION METHODS IMPUTATION PROCESS IMPUTATIONS INEQUALITY INFORMATION SERVICES LAND OWNERSHIP LAND SIZE LANDHOLDINGS LIVING STANDARDS MATERNAL MORTALITY MEANS TESTS MISSING DATA MISSING VALUES MULTIPLE IMPUTATION MULTIPLE IMPUTATIONS NATIONAL POVERTY NATIONAL POVERTY LINE NUTRITION OPEN ACCESS PER CAPITA CONSUMPTION POOR POOR HOUSEHOLDS POVERTY ANALYSIS POVERTY ESTIMATES POVERTY LEVELS POVERTY LINES POVERTY MAPPING POVERTY MEASUREMENT POVERTY MEASURES POVERTY QUINTILES POVERTY RANKINGS POVERTY RATES POVERTY REDUCTION POVERTY STATUS PRECISION PREDICTION PREDICTIONS PRINCIPAL COMPONENTS ANALYSIS RADIO RESULT RESULTS RURAL RURAL AREAS RURAL ECONOMY RURAL INEQUALITY SAMPLE DESIGN SAMPLE SIZE SATELLITE SOCIAL PROGRAMS STANDARD ERRORS STATA STATISTICAL ANALYSIS STATISTICAL ANALYSIS SOFTWARE STATISTICAL METHODS STATISTICIANS TARGETING TARGETS TECHNICAL UNIVERSITY TELEVISION TIME PERIOD TIME SERIES USES VERIFICATION WEB WELFARE INDICATOR Dabalen, Andrew Graham, Errol Himelein, Kristen Mungai, Rose Estimating Poverty in the Absence of Consumption Data : The Case of Liberia |
geographic_facet |
Africa Liberia |
relation |
Policy Research Working Paper;No. 7024 |
description |
In much of the developing world, the
demand for high frequency quality household data for poverty
monitoring and program design far outstrips the capacity of
the statistics bureau to provide such data. In these
environments, all available data sources must be leveraged.
Most surveys, however, do not collect the detailed
consumption data necessary to construct aggregates and
poverty lines to measure poverty directly. This paper
benefits from a shared listing exercise for two large-scale
national household surveys conducted in Liberia in 2007 to
explore alternative methodologies to estimate poverty
indirectly. The first is an asset-based model that is
commonly used in Demographic and Health Surveys. The second
is a survey-to-survey imputation that makes use of small
area estimation techniques. In addition to a standard base
model, separate models are estimated for urban and rural
areas and an expanded model that includes climatic
variables. Special attention is paid to the inclusion of
cell phones, with implications for other assets whose cost
and availability may be changing rapidly. The results
demonstrate substantial limitations with asset-based
indexes, but also leave questions as to the accuracy and
stability of imputation models. |
format |
Publications & Research :: Policy Research Working Paper |
author |
Dabalen, Andrew Graham, Errol Himelein, Kristen Mungai, Rose |
author_facet |
Dabalen, Andrew Graham, Errol Himelein, Kristen Mungai, Rose |
author_sort |
Dabalen, Andrew |
title |
Estimating Poverty in the Absence of Consumption Data : The Case of Liberia |
title_short |
Estimating Poverty in the Absence of Consumption Data : The Case of Liberia |
title_full |
Estimating Poverty in the Absence of Consumption Data : The Case of Liberia |
title_fullStr |
Estimating Poverty in the Absence of Consumption Data : The Case of Liberia |
title_full_unstemmed |
Estimating Poverty in the Absence of Consumption Data : The Case of Liberia |
title_sort |
estimating poverty in the absence of consumption data : the case of liberia |
publisher |
World Bank Group, Washington, DC |
publishDate |
2014 |
url |
http://documents.worldbank.org/curated/en/2014/09/20177049/estimating-poverty-absence-consumption-data-case-liberia http://hdl.handle.net/10986/20336 |
_version_ |
1764445064917942272 |