Eliciting Permanent and Transitory Undeclared Work from Matched Administrative and Survey Data

Arbeitspapier

We study the undeclared work patterns of Hungarian employees in relatively stable jobs, using a panel dataset that matches individual-level self-reported Labour Force Survey data with administrative records of the Pension Directorate for 2001–2006. We estimate the determinants of undeclared work using Heckman-type random-effects panel probit models, and develop a two-regime model to separate permanent and transitory undeclared work, where the latter follows a Markov chain. We find that about 6-7 per cent of workers went permanently unreported for six consecutive years, and a further 4 per cent were transitorily unreported in any given year. The models show lower reporting rates – especially in the permanent segment – among males, high-school graduates, those in agriculture and transport, various forms of atypical employment, and small firms. Transitory non-reporting may be partly explained by administrative records missing for technical reasons. The results suggest that (i) the 'aggregate labour input method' widely used in Europe can indeed be a simple yet reliable tool to estimate the size of informal employment, although it slightly overestimates the true magnitude of black work (ii) the long-term pension consequences of undeclared work are substantial because of the high share of permanent non-reporting.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: IZA Discussion Papers ; No. 10800

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models ; Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities ; Tax Evasion and Avoidance ; Informal Labor Markets
• Subject: random-effects panel probit with endogenous selection ; matched administrative-survey data ; labour input method ; undeclared work ; Markov chain

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Elek, Peter ; Köllő, János
• Event: Veröffentlichung
• (who): Institute of Labor Economics (IZA)
• (where): Bonn
• (when): 2017

Further information

• Handle: http://hdl.handle.net/10419/170784
• Last update: 10.03.2025, 11:43 AM CET