2011
DOI: 10.1111/j.1475-5890.2011.00150.x
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The Distributional Implications of Income Under‐Reporting in Hungary*

Abstract: The paper estimates the distributional implications of income tax evasion in Hungary based on a random sample of administrative tax records of 230 thousand individuals. Gross incomes in the administrative tax records are compared with those in a nationally representative household budget survey, assuming that tax-evaders are more likely to report their true incomes in an anonymous interview. Our estimates show that the average rate of underreporting is 11%, which conceals large differences between self-employe… Show more

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Cited by 21 publications
(14 citation statements)
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“…Moreover, it partially addresses the panel dimension of the data because the same household may appear several times in the dataset. 5 Also, the quality of the earnings data is likely to be higher for wage workers than for self-employed individuals (Benedek and Lelkes 2011;Johansson 2005), although Torosyan and Filer (2014) find that in Georgia the degree of underreporting is in fact similar between these groups. 6 Skill corresponds to four occupational categories based on the ISCO-88 single-digit occupation coding: 1-3 = high-skilled white-collar (such as teachers, physicians, engineers); 4-5 = low-skilled white-collar (such as office clerks, sales, and customer service personnel); 6-7 = high-skilled blue-collar (such as machine operators and skilled agricultural workers); and 8-9 = low-skilled blue-collar (such as drivers, movers).…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, it partially addresses the panel dimension of the data because the same household may appear several times in the dataset. 5 Also, the quality of the earnings data is likely to be higher for wage workers than for self-employed individuals (Benedek and Lelkes 2011;Johansson 2005), although Torosyan and Filer (2014) find that in Georgia the degree of underreporting is in fact similar between these groups. 6 Skill corresponds to four occupational categories based on the ISCO-88 single-digit occupation coding: 1-3 = high-skilled white-collar (such as teachers, physicians, engineers); 4-5 = low-skilled white-collar (such as office clerks, sales, and customer service personnel); 6-7 = high-skilled blue-collar (such as machine operators and skilled agricultural workers); and 8-9 = low-skilled blue-collar (such as drivers, movers).…”
Section: Discussionmentioning
confidence: 99%
“…An equally important reason, however, is the finding that the labor market experience of self-employed individuals differs from the experience of hired workers and therefore merits separate attention (Garcia-Mainar and Montuenga-Gomez [2005], for evidence on Spain and Portugal). In particular, the levels of income underreporting tend to be much higher for self-employed individuals than for workers (Benedek and Orsolya 2009;Johansson 2001). In Georgia, Yemtsov (2001) finds 10 In the sample of individuals above the retirement age, 822 (8.57% of the total number of individuals at or above retirement age) report being hired workers.…”
Section: Datamentioning
confidence: 99%
“…On the one hand, focusing on wage workers highlights that the earnings determination processes of wage workers and self-employed individuals vary, with the measure of interest being the gender wage gap as opposed to the gender earnings gap (Garcia-Mainar and Montuega-Gomez 2005). In addition, the quality of pay data among self-employed workers may be lower than among wage workers, justifying restricting the sample to wage workers only (Benedek and Lelkes 2011). With that said, Torosyan and Filer (2014) find that the level of underreporting is similar between wage workers and the self-employed in Georgia.…”
mentioning
confidence: 98%