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 sources must be leveraged. Most surveys, however, do not...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Washington, D.C
The World Bank
2014
|
| Links: | https://doi.org/10.1596/1813-9450-7024 |
| Zusammenfassung: | 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 |
| Umfang: | 1 Online-Ressource (27 p) |
| DOI: | 10.1596/1813-9450-7024 |
Internformat
MARC
| LEADER | 00000nam a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV048266457 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 220609s2014 xx o|||| 00||| eng d | ||
| 024 | 7 | |a 10.1596/1813-9450-7024 |2 doi | |
| 035 | |a (ZDB-1-WBA)NLM010341129 | ||
| 035 | |a (OCoLC)1334032539 | ||
| 035 | |a (DE-599)GBVNLM010341129 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-12 |a DE-521 |a DE-573 |a DE-523 |a DE-Re13 |a DE-19 |a DE-355 |a DE-703 |a DE-91 |a DE-706 |a DE-29 |a DE-M347 |a DE-473 |a DE-824 |a DE-20 |a DE-739 |a DE-1043 |a DE-863 |a DE-862 | ||
| 100 | 1 | |a Dabalen, Andrew |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Estimating Poverty in the Absence of Consumption Data |b The Case of Liberia |c Dabalen, Andrew |
| 264 | 1 | |a Washington, D.C |b The World Bank |c 2014 | |
| 300 | |a 1 Online-Ressource (27 p) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 520 | |a 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 | ||
| 700 | 1 | |a Dabalen, Andrew |4 oth | |
| 700 | 1 | |a Graham, Errol |4 oth | |
| 700 | 1 | |a Himelein, Kristen |4 oth | |
| 700 | 1 | |a Mungai, Rose |4 oth | |
| 776 | 0 | 8 | |i Dabalen, Andrew |a Estimating Poverty in the Absence of Consumption Data |
| 856 | 4 | 0 | |u https://doi.org/10.1596/1813-9450-7024 |x Verlag |z kostenfrei |3 Volltext |
| 912 | |a ZDB-1-WBA | ||
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-033646651 | |
Datensatz im Suchindex
| DE-BY-TUM_katkey | 2817677 |
|---|---|
| _version_ | 1821937176737218560 |
| any_adam_object | |
| author | Dabalen, Andrew |
| author_facet | Dabalen, Andrew |
| author_role | aut |
| author_sort | Dabalen, Andrew |
| author_variant | a d ad |
| building | Verbundindex |
| bvnumber | BV048266457 |
| collection | ZDB-1-WBA |
| ctrlnum | (ZDB-1-WBA)NLM010341129 (OCoLC)1334032539 (DE-599)GBVNLM010341129 |
| discipline | Wirtschaftswissenschaften |
| doi_str_mv | 10.1596/1813-9450-7024 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02562nam a2200361zc 4500</leader><controlfield tag="001">BV048266457</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">220609s2014 xx o|||| 00||| eng d</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1596/1813-9450-7024</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-1-WBA)NLM010341129</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1334032539</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVNLM010341129</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-12</subfield><subfield code="a">DE-521</subfield><subfield code="a">DE-573</subfield><subfield code="a">DE-523</subfield><subfield code="a">DE-Re13</subfield><subfield code="a">DE-19</subfield><subfield code="a">DE-355</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-706</subfield><subfield code="a">DE-29</subfield><subfield code="a">DE-M347</subfield><subfield code="a">DE-473</subfield><subfield code="a">DE-824</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-739</subfield><subfield code="a">DE-1043</subfield><subfield code="a">DE-863</subfield><subfield code="a">DE-862</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Dabalen, Andrew</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Estimating Poverty in the Absence of Consumption Data</subfield><subfield code="b">The Case of Liberia</subfield><subfield code="c">Dabalen, Andrew</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Washington, D.C</subfield><subfield code="b">The World Bank</subfield><subfield code="c">2014</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (27 p)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dabalen, Andrew</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Graham, Errol</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Himelein, Kristen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mungai, Rose</subfield><subfield code="4">oth</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Dabalen, Andrew</subfield><subfield code="a">Estimating Poverty in the Absence of Consumption Data</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1596/1813-9450-7024</subfield><subfield code="x">Verlag</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-1-WBA</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033646651</subfield></datafield></record></collection> |
| id | DE-604.BV048266457 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T19:40:09Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033646651 |
| oclc_num | 1334032539 |
| open_access_boolean | 1 |
| owner | DE-12 DE-521 DE-573 DE-523 DE-Re13 DE-BY-UBR DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-703 DE-91 DE-BY-TUM DE-706 DE-29 DE-M347 DE-473 DE-BY-UBG DE-824 DE-20 DE-739 DE-1043 DE-863 DE-BY-FWS DE-862 DE-BY-FWS |
| owner_facet | DE-12 DE-521 DE-573 DE-523 DE-Re13 DE-BY-UBR DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-703 DE-91 DE-BY-TUM DE-706 DE-29 DE-M347 DE-473 DE-BY-UBG DE-824 DE-20 DE-739 DE-1043 DE-863 DE-BY-FWS DE-862 DE-BY-FWS |
| physical | 1 Online-Ressource (27 p) |
| psigel | ZDB-1-WBA |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | The World Bank |
| record_format | marc |
| spellingShingle | Dabalen, Andrew Estimating Poverty in the Absence of Consumption Data The Case of Liberia |
| title | Estimating Poverty in the Absence of Consumption Data The Case of Liberia |
| title_auth | Estimating Poverty in the Absence of Consumption Data The Case of Liberia |
| title_exact_search | 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 Dabalen, Andrew |
| title_fullStr | Estimating Poverty in the Absence of Consumption Data The Case of Liberia Dabalen, Andrew |
| title_full_unstemmed | Estimating Poverty in the Absence of Consumption Data The Case of Liberia Dabalen, Andrew |
| title_short | Estimating Poverty in the Absence of Consumption Data |
| title_sort | estimating poverty in the absence of consumption data the case of liberia |
| title_sub | The Case of Liberia |
| url | https://doi.org/10.1596/1813-9450-7024 |
| work_keys_str_mv | AT dabalenandrew estimatingpovertyintheabsenceofconsumptiondatathecaseofliberia AT grahamerrol estimatingpovertyintheabsenceofconsumptiondatathecaseofliberia AT himeleinkristen estimatingpovertyintheabsenceofconsumptiondatathecaseofliberia AT mungairose estimatingpovertyintheabsenceofconsumptiondatathecaseofliberia |