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Detecting Anomalous Data in Household Surveys: Evidence for Argentina

Author

Listed:
  • González Fernando Antonio Ignacio

    (Instituto de Investigaciones Económicas y Sociales del Sur, UNS-CONICET.)

Abstract
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 de Hogares (EPH, Permanent Household Survey in English) -for the period 2003-2017- and in the Encuesta Anual de Hogares Urbanos (EAHU, Annual Urban Household Survey 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 Chi-square 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 Benford distribution and the degree of compliance with this law decreases significantly between 2007-2015 coinciding with the intervention period of the Instituto Nacional de Estadísticas y Censos (INDEC, National Institute of Statistics and Censuses in English).

Suggested Citation

  • González Fernando Antonio Ignacio, 2019. "Detecting Anomalous Data in Household Surveys: Evidence for Argentina," Journal of Social and Economic Statistics, Sciendo, vol. 8(2), pages 1-10, December.
    • Handle: RePEc:vrs:jsesro:v:8:y:2019:i:2:p:1-10:n:1
    DOI: 10.2478/jses-2019-0001
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    References listed on IDEAS

    as
    1. Marcelo Medeiros & Juliana Castro Galvão & Luísa Azevedo Nazareno, 2018. "Correcting the Underestimation of Top Incomes: Combining Data from Income Tax Reports and the Brazilian 2010 Census," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 233-244, January.
    2. Tariq Ahmad Mir & Marcel Ausloos & Roy Cerqueti, 2014. "Benford's law predicted digit distribution of aggregated income taxes: the surprising conformity of Italian cities and regions," Papers 1410.2890, arXiv.org.
    3. Ricardo Sartori Cella & Ercilio Zanolla, 2018. "Benford’s Law and transparency: an analysis of municipal expenditure," Brazilian Business Review, Fucape Business School, vol. 15(4), pages 331-347, July.
    4. Henselmann, Klaus & Scherr, Elisabeth & Ditter, Dominik, 2012. "Applying Benford's Law to individual financial reports: An empirical investigation on the basis of SEC XBRL filings," Working Papers in Accounting Valuation Auditing 2012-1, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Accounting and Auditing.
    5. Villas-Boas, Sofia B. & Fu, Qiuzi & Judge, George, 2017. "Benford’s law and the FSD distribution of economic behavioral micro data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 711-719.
    6. Druică, Elena & Oancea, Bogdan & Vâlsan, Călin, 2018. "Benford's law and the limits of digit analysis," International Journal of Accounting Information Systems, Elsevier, vol. 31(C), pages 75-82.
    7. George Judge & Laura Schechter, 2009. "Detecting Problems in Survey Data Using Benford’s Law," Journal of Human Resources, University of Wisconsin Press, vol. 44(1).
    8. Sofia B. Villas-Boas & Qiuzi Fu & George Judge, 2015. "Is Benford’s Law a Universal Behavioral Theory?," Econometrics, MDPI, vol. 3(4), pages 1-11, October.
    9. Finn, Arden & Ranchhod, Vimal, 2013. "Genuine Fakes: The prevalence and implications of fieldworker fraud in a large South African survey," SALDRU Working Papers 115, Southern Africa Labour and Development Research Unit, University of Cape Town.
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    More about this item

    Keywords

    Income; Household surveys; Benford’s law;
    All these keywords.

    JEL classification:

    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing
    • M48 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Government Policy and Regulation

    Statistics

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