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Polish Households' behavior in the Regular and Informal Economies

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  • François Gardes

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Christophe Starzec

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper analyzes characteristics of the informal economy in Poland in the context of transition, using a specific survey carried out in the framework of the classic Labour Force Survey, conducted by the Polish National Statistical office (GUS), in 1995. The participation probabilities of three types of informal activities (working, buying and hiring) are discussed. Their interdependencies are analyzed in the light of the hypothesis of network or neighborhood effects. The impact of a household's participation in informal markets on its regular consumption is estimated by imputing the probability of its informal activity in the consumption surveys and panels. Such participation does significantly influence more than half of household's expenditure on goods and services. Moreover, the participants of the informal economy distinguish themselves by higher individual full prices (integrating both monetary and non-monetary constraints and resources).

Suggested Citation

  • François Gardes & Christophe Starzec, 2009. "Polish Households' behavior in the Regular and Informal Economies," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00375543, HAL.
    • Handle: RePEc:hal:cesptp:halshs-00375543
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00375543
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    References listed on IDEAS

    as
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    Cited by:

    1. Dagmara Nikulin, 2016. "How To Define And Measure Informal Employment In Developed Countries? A Case Of Poland," GUT FME Working Paper Series A 35, Faculty of Management and Economics, Gdansk University of Technology.
    2. Nesma Mohamed Ali, 2017. "Towards a better integration of the informal sector: three empirical essays on the interaction between formal and informal firms in Egypt and beyond," Erudite Ph.D Dissertations, Erudite, number ph17-05 edited by Manon Domingues Dos Santos & Boris Najman.
    3. Nesma Ali & Boris Najman, 2016. "Informal Competition, Firms Productivity and Policy Reforms in Egypt," Working Papers 1025, Economic Research Forum, revised Jul 2016.
    4. Murashov, Yaroslav & Ratnikova, Tatiana, 2016. "Under-reported income of Russian households," Russian Journal of Economics, Elsevier, vol. 2(1), pages 56-85.
    5. Izabela Styczynska, 2012. "Determinants of household demand for services - Formal Versus Informal Sector," CASE Network Studies and Analyses 444, CASE-Center for Social and Economic Research.

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    More about this item

    Keywords

    Informal economy; consumer behavior; cross-section-panel estimation; L'économie informelle; comportement de consommation; estimation en coupe transversale et en panel;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • J49 - Labor and Demographic Economics - - Particular Labor Markets - - - Other
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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