Data Gaps, Data Incomparability, and Data Imputation

This paper reviews methods that have been employed to estimate poverty in contexts where household consumption data are unavailable or missing. These contexts range from completely missing and partially missing consumption data in cross-sectional household surveys, to missing panel household data. The paper focuses on methods that aim to compare trends and dynamic patterns of poverty outcomes over time. It presents the various methods under a common framework, with pedagogical discussion on the intuition. Empirical illustrations are provided using several rounds of household survey data from Vietnam. Furthermore, the paper provides a practical guide with detailed instructions on computer programs that can be used to implement the reviewed techniques.

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Bibliographic Details
Main Authors: Carletto, Calogero, Dang, Hai-Anh, Jolliffe, Dean
Format: Working Paper biblioteca
Language:English
Published: World Bank, Washington, DC 2017-12
Subjects:POVERTY MEASUREMENT, WEALTH INDEX, SYNTHETIC PANELS, HOUSEHOLD SURVEYS, CONSUMPTION, IMPUTATION, MOBILITY, POVERTY,
Online Access:http://documents.worldbank.org/curated/en/551171513690220305/Data-gaps-data-incomparability-and-data-imputation-a-review-of-poverty-measurement-methods-for-data-scarce-environments
https://hdl.handle.net/10986/29074
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spelling dig-okr-10986290742024-06-23T08:03:41Z Data Gaps, Data Incomparability, and Data Imputation A Review of Poverty Measurement Methods for Data-Scarce Environments Carletto, Calogero Dang, Hai-Anh Jolliffe, Dean POVERTY MEASUREMENT WEALTH INDEX SYNTHETIC PANELS HOUSEHOLD SURVEYS CONSUMPTION IMPUTATION MOBILITY POVERTY This paper reviews methods that have been employed to estimate poverty in contexts where household consumption data are unavailable or missing. These contexts range from completely missing and partially missing consumption data in cross-sectional household surveys, to missing panel household data. The paper focuses on methods that aim to compare trends and dynamic patterns of poverty outcomes over time. It presents the various methods under a common framework, with pedagogical discussion on the intuition. Empirical illustrations are provided using several rounds of household survey data from Vietnam. Furthermore, the paper provides a practical guide with detailed instructions on computer programs that can be used to implement the reviewed techniques. 2017-12-21T20:28:21Z 2017-12-21T20:28:21Z 2017-12 Working Paper Document de travail Documento de trabajo http://documents.worldbank.org/curated/en/551171513690220305/Data-gaps-data-incomparability-and-data-imputation-a-review-of-poverty-measurement-methods-for-data-scarce-environments https://hdl.handle.net/10986/29074 English Policy Research Working Paper;No. 8282 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank application/pdf World Bank, Washington, DC
institution Banco Mundial
collection DSpace
country Estados Unidos
countrycode US
component Bibliográfico
access En linea
databasecode dig-okr
tag biblioteca
region America del Norte
libraryname Biblioteca del Banco Mundial
language English
topic POVERTY MEASUREMENT
WEALTH INDEX
SYNTHETIC PANELS
HOUSEHOLD SURVEYS
CONSUMPTION
IMPUTATION
MOBILITY
POVERTY
POVERTY MEASUREMENT
WEALTH INDEX
SYNTHETIC PANELS
HOUSEHOLD SURVEYS
CONSUMPTION
IMPUTATION
MOBILITY
POVERTY
spellingShingle POVERTY MEASUREMENT
WEALTH INDEX
SYNTHETIC PANELS
HOUSEHOLD SURVEYS
CONSUMPTION
IMPUTATION
MOBILITY
POVERTY
POVERTY MEASUREMENT
WEALTH INDEX
SYNTHETIC PANELS
HOUSEHOLD SURVEYS
CONSUMPTION
IMPUTATION
MOBILITY
POVERTY
Carletto, Calogero
Dang, Hai-Anh
Jolliffe, Dean
Data Gaps, Data Incomparability, and Data Imputation
description This paper reviews methods that have been employed to estimate poverty in contexts where household consumption data are unavailable or missing. These contexts range from completely missing and partially missing consumption data in cross-sectional household surveys, to missing panel household data. The paper focuses on methods that aim to compare trends and dynamic patterns of poverty outcomes over time. It presents the various methods under a common framework, with pedagogical discussion on the intuition. Empirical illustrations are provided using several rounds of household survey data from Vietnam. Furthermore, the paper provides a practical guide with detailed instructions on computer programs that can be used to implement the reviewed techniques.
format Working Paper
topic_facet POVERTY MEASUREMENT
WEALTH INDEX
SYNTHETIC PANELS
HOUSEHOLD SURVEYS
CONSUMPTION
IMPUTATION
MOBILITY
POVERTY
author Carletto, Calogero
Dang, Hai-Anh
Jolliffe, Dean
author_facet Carletto, Calogero
Dang, Hai-Anh
Jolliffe, Dean
author_sort Carletto, Calogero
title Data Gaps, Data Incomparability, and Data Imputation
title_short Data Gaps, Data Incomparability, and Data Imputation
title_full Data Gaps, Data Incomparability, and Data Imputation
title_fullStr Data Gaps, Data Incomparability, and Data Imputation
title_full_unstemmed Data Gaps, Data Incomparability, and Data Imputation
title_sort data gaps, data incomparability, and data imputation
publisher World Bank, Washington, DC
publishDate 2017-12
url http://documents.worldbank.org/curated/en/551171513690220305/Data-gaps-data-incomparability-and-data-imputation-a-review-of-poverty-measurement-methods-for-data-scarce-environments
https://hdl.handle.net/10986/29074
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AT danghaianh datagapsdataincomparabilityanddataimputation
AT jolliffedean datagapsdataincomparabilityanddataimputation
AT carlettocalogero areviewofpovertymeasurementmethodsfordatascarceenvironments
AT danghaianh areviewofpovertymeasurementmethodsfordatascarceenvironments
AT jolliffedean areviewofpovertymeasurementmethodsfordatascarceenvironments
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