Measuring participation in undeclared work using surveys has been criticized for under-estimating the level of engagement due to social desirability bias that leads to an under-reporting of “bad” behavior. Until now, few studies have sought to quantify the amplitude of this bias in surveys of undeclared work. The aim of this paper is to fill this gap by using the most appropriate methodologies for estimating the probability of misleading responses in such surveys. Reporting data from special Eurobarometer survey no. 498 conducted in 2019 and involving 27,565 respondents in EU-27 countries and the UK, only 3.5% openly admitted to participating in undeclared work. The results of a Probit model with correction for misclassified cases (i.e., those undertaking undeclared work but declaring that they do not) reveals that nearly a quarter (23.3%) of the respondents undertaking undeclared work refused to openly admit this during the survey, due to the social desirability bias. The estimated overall proportion of undeclared workers is 17.3%. We obtained this value by correcting for both misclassification and the additional source of negative bias due to the large imbalance in the data (i.e., observations in one class are much lower than the other). The outcome of this new advanced approach in analysing undeclared work is that survey estimates can now report its size and determinants in a more accurate manner than has been previously the case.

Measuring participation in undeclared work in Europe using survey data: A method for resolving social desirability bias / Arezzo, Maria Felice; Horodnic, Ioana A.; Williams, Colin C.; Guagnano, Giuseppina. - In: SOCIO-ECONOMIC PLANNING SCIENCES. - ISSN 0038-0121. - 91:(2023). [10.1016/j.seps.2023.101779]

Measuring participation in undeclared work in Europe using survey data: A method for resolving social desirability bias

Arezzo, Maria Felice
;
Horodnic, Ioana A.;Guagnano, Giuseppina
2023

Abstract

Measuring participation in undeclared work using surveys has been criticized for under-estimating the level of engagement due to social desirability bias that leads to an under-reporting of “bad” behavior. Until now, few studies have sought to quantify the amplitude of this bias in surveys of undeclared work. The aim of this paper is to fill this gap by using the most appropriate methodologies for estimating the probability of misleading responses in such surveys. Reporting data from special Eurobarometer survey no. 498 conducted in 2019 and involving 27,565 respondents in EU-27 countries and the UK, only 3.5% openly admitted to participating in undeclared work. The results of a Probit model with correction for misclassified cases (i.e., those undertaking undeclared work but declaring that they do not) reveals that nearly a quarter (23.3%) of the respondents undertaking undeclared work refused to openly admit this during the survey, due to the social desirability bias. The estimated overall proportion of undeclared workers is 17.3%. We obtained this value by correcting for both misclassification and the additional source of negative bias due to the large imbalance in the data (i.e., observations in one class are much lower than the other). The outcome of this new advanced approach in analysing undeclared work is that survey estimates can now report its size and determinants in a more accurate manner than has been previously the case.
2023
undeclared work; shadow economy; social desirability bias; binary choice models; misclassification
01 Pubblicazione su rivista::01a Articolo in rivista
Measuring participation in undeclared work in Europe using survey data: A method for resolving social desirability bias / Arezzo, Maria Felice; Horodnic, Ioana A.; Williams, Colin C.; Guagnano, Giuseppina. - In: SOCIO-ECONOMIC PLANNING SCIENCES. - ISSN 0038-0121. - 91:(2023). [10.1016/j.seps.2023.101779]
File allegati a questo prodotto
File Dimensione Formato  
Arezzo_Measuring-participation_2023.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.06 MB
Formato Adobe PDF
2.06 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1695719
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 0
social impact