The paper estimates the extent of evasion of personal income tax (PIT) in Italy by integrating two methods that the literature has previously applied separately. The consumption-based method introduced by Pissarides and Weber (1989) is used to estimate misreporting of income in micro data collected in the household IT-SILC survey. We adopt an econometric specification close in spirit to that of Feldman and Slemrod (2007), which allows us to estimate income misreporting at different rates for different income sources. The misreporting estimates are then used in the discrepancy method to correct the incomes compared with administrative registered data. The comparison provides new estimates of evasion of personal income tax by type of income, region and income class. The estimates are used to improve microsimulation analyses of the distributional impact of tax evasion.

Income Underreporting and Tax Evasion in Italy: Estimates and Distributional Effects

Andrea Albarea;Michele Bernasconi;Anna Marenzi
;
Dino Rizzi
2020-01-01

Abstract

The paper estimates the extent of evasion of personal income tax (PIT) in Italy by integrating two methods that the literature has previously applied separately. The consumption-based method introduced by Pissarides and Weber (1989) is used to estimate misreporting of income in micro data collected in the household IT-SILC survey. We adopt an econometric specification close in spirit to that of Feldman and Slemrod (2007), which allows us to estimate income misreporting at different rates for different income sources. The misreporting estimates are then used in the discrepancy method to correct the incomes compared with administrative registered data. The comparison provides new estimates of evasion of personal income tax by type of income, region and income class. The estimates are used to improve microsimulation analyses of the distributional impact of tax evasion.
2020
66
File in questo prodotto:
File Dimensione Formato  
Revised version.pdf

non disponibili

Tipologia: Documento in Pre-print
Licenza: Accesso chiuso-personale
Dimensione 1.29 MB
Formato Adobe PDF
1.29 MB Adobe PDF   Visualizza/Apri

I documenti in ARCA 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/10278/3718477
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 10
  • ???jsp.display-item.citation.isi??? 11
social impact