Detecting anomalous data in household surveys: Evidence for Argentina
- Autores
- González, Fernando Antonio Ignacio
- Año de publicación
- 2020
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- This paper advances in the detection of anomalous data in income reports of Argentina.In particular, income declared by households surveyed in the Encuesta Permanente deHogares (EPH, Permanent Household Survey in English) -for the period 2003-2017-and in the Encuesta Anual de Hogares Urbanos (EAHU, Annual Urban HouseholdSurvey in English) -for the period 2010-2014- are analyzed.A widely known technique in forensic accounting and auditing, such as Benford´s law-also known as the first digit law- is used. If the analyzed data were generated naturally-free of manipulation- it should follow the logarithmic distribution of Benford. The Chisquare test and the absolute mean deviation (MAD) are used for verification.The results suggest that the income reported in the EPH does not follow the Benforddistribution and the degree of compliance with this law decreases significantly between2007-2015 coinciding with the intervention period of the Instituto Nacional deEstadísticas y Censos (INDEC, National Institute of Statistics and Censuses inEnglish).
Fil: González, Fernando Antonio Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina - Materia
-
INCOME
ENCUESTA PERMANENTE DE HOGARES
BENFORD´S LAW - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/147992
Ver los metadatos del registro completo
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Detecting anomalous data in household surveys: Evidence for ArgentinaGonzález, Fernando Antonio IgnacioINCOMEENCUESTA PERMANENTE DE HOGARESBENFORD´S LAWhttps://purl.org/becyt/ford/5.2https://purl.org/becyt/ford/5This paper advances in the detection of anomalous data in income reports of Argentina.In particular, income declared by households surveyed in the Encuesta Permanente deHogares (EPH, Permanent Household Survey in English) -for the period 2003-2017-and in the Encuesta Anual de Hogares Urbanos (EAHU, Annual Urban HouseholdSurvey in English) -for the period 2010-2014- are analyzed.A widely known technique in forensic accounting and auditing, such as Benford´s law-also known as the first digit law- is used. If the analyzed data were generated naturally-free of manipulation- it should follow the logarithmic distribution of Benford. The Chisquare test and the absolute mean deviation (MAD) are used for verification.The results suggest that the income reported in the EPH does not follow the Benforddistribution and the degree of compliance with this law decreases significantly between2007-2015 coinciding with the intervention period of the Instituto Nacional deEstadísticas y Censos (INDEC, National Institute of Statistics and Censuses inEnglish).Fil: González, Fernando Antonio Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaBucharest Academy of Economic Studies. Department of Statistics and Econometrics2020-01-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/147992González, Fernando Antonio Ignacio; Detecting anomalous data in household surveys: Evidence for Argentina; Bucharest Academy of Economic Studies. Department of Statistics and Econometrics; Journal of Social and Economic Statistics; 8; 2; 4-1-2020; 1-102285-388XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.2478/jses-2019-0001info:eu-repo/semantics/altIdentifier/url/https://www.sciendo.com/article/10.2478/jses-2019-0001info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:52:14Zoai:ri.conicet.gov.ar:11336/147992instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:52:14.486CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Detecting anomalous data in household surveys: Evidence for Argentina |
title |
Detecting anomalous data in household surveys: Evidence for Argentina |
spellingShingle |
Detecting anomalous data in household surveys: Evidence for Argentina González, Fernando Antonio Ignacio INCOME ENCUESTA PERMANENTE DE HOGARES BENFORD´S LAW |
title_short |
Detecting anomalous data in household surveys: Evidence for Argentina |
title_full |
Detecting anomalous data in household surveys: Evidence for Argentina |
title_fullStr |
Detecting anomalous data in household surveys: Evidence for Argentina |
title_full_unstemmed |
Detecting anomalous data in household surveys: Evidence for Argentina |
title_sort |
Detecting anomalous data in household surveys: Evidence for Argentina |
dc.creator.none.fl_str_mv |
González, Fernando Antonio Ignacio |
author |
González, Fernando Antonio Ignacio |
author_facet |
González, Fernando Antonio Ignacio |
author_role |
author |
dc.subject.none.fl_str_mv |
INCOME ENCUESTA PERMANENTE DE HOGARES BENFORD´S LAW |
topic |
INCOME ENCUESTA PERMANENTE DE HOGARES BENFORD´S LAW |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/5.2 https://purl.org/becyt/ford/5 |
dc.description.none.fl_txt_mv |
This paper advances in the detection of anomalous data in income reports of Argentina.In particular, income declared by households surveyed in the Encuesta Permanente deHogares (EPH, Permanent Household Survey in English) -for the period 2003-2017-and in the Encuesta Anual de Hogares Urbanos (EAHU, Annual Urban HouseholdSurvey in English) -for the period 2010-2014- are analyzed.A widely known technique in forensic accounting and auditing, such as Benford´s law-also known as the first digit law- is used. If the analyzed data were generated naturally-free of manipulation- it should follow the logarithmic distribution of Benford. The Chisquare test and the absolute mean deviation (MAD) are used for verification.The results suggest that the income reported in the EPH does not follow the Benforddistribution and the degree of compliance with this law decreases significantly between2007-2015 coinciding with the intervention period of the Instituto Nacional deEstadísticas y Censos (INDEC, National Institute of Statistics and Censuses inEnglish). Fil: González, Fernando Antonio Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina |
description |
This paper advances in the detection of anomalous data in income reports of Argentina.In particular, income declared by households surveyed in the Encuesta Permanente deHogares (EPH, Permanent Household Survey in English) -for the period 2003-2017-and in the Encuesta Anual de Hogares Urbanos (EAHU, Annual Urban HouseholdSurvey in English) -for the period 2010-2014- are analyzed.A widely known technique in forensic accounting and auditing, such as Benford´s law-also known as the first digit law- is used. If the analyzed data were generated naturally-free of manipulation- it should follow the logarithmic distribution of Benford. The Chisquare test and the absolute mean deviation (MAD) are used for verification.The results suggest that the income reported in the EPH does not follow the Benforddistribution and the degree of compliance with this law decreases significantly between2007-2015 coinciding with the intervention period of the Instituto Nacional deEstadísticas y Censos (INDEC, National Institute of Statistics and Censuses inEnglish). |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-04 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/147992 González, Fernando Antonio Ignacio; Detecting anomalous data in household surveys: Evidence for Argentina; Bucharest Academy of Economic Studies. Department of Statistics and Econometrics; Journal of Social and Economic Statistics; 8; 2; 4-1-2020; 1-10 2285-388X CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/147992 |
identifier_str_mv |
González, Fernando Antonio Ignacio; Detecting anomalous data in household surveys: Evidence for Argentina; Bucharest Academy of Economic Studies. Department of Statistics and Econometrics; Journal of Social and Economic Statistics; 8; 2; 4-1-2020; 1-10 2285-388X CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.2478/jses-2019-0001 info:eu-repo/semantics/altIdentifier/url/https://www.sciendo.com/article/10.2478/jses-2019-0001 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/2.5/ar/ |
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openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/2.5/ar/ |
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application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Bucharest Academy of Economic Studies. Department of Statistics and Econometrics |
publisher.none.fl_str_mv |
Bucharest Academy of Economic Studies. Department of Statistics and Econometrics |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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13.22299 |