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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Format: | Working Paper biblioteca |
Language: | English |
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World Bank, Washington, DC
2017-12
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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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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 |
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biblioteca |
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America del Norte |
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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 |
work_keys_str_mv |
AT carlettocalogero datagapsdataincomparabilityanddataimputation AT danghaianh datagapsdataincomparabilityanddataimputation AT jolliffedean datagapsdataincomparabilityanddataimputation AT carlettocalogero areviewofpovertymeasurementmethodsfordatascarceenvironments AT danghaianh areviewofpovertymeasurementmethodsfordatascarceenvironments AT jolliffedean areviewofpovertymeasurementmethodsfordatascarceenvironments |
_version_ |
1802820846574632960 |