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Size and determinants of shadow economies in the Baltic States


  • Tālis J. Putniņš

    () (Stockholm School of Economics in Riga)

  • Arnis Sauka

    () (Stockholm School of Economics in Riga)


This study develops and estimates an index of the size of shadow economies in Estonia, Latvia and Lithuania, and analyses the factors that influence participation in the shadow sector. The index can be used to track shadow economies through time or across sectors and therefore is a useful tool to evaluate the effectiveness of policies aimed ar reducing the size of shadow economies. Our results suggest that the shadow economy in Latvia in 2010 is considerably larger than in neighbouring Estonia and Lithuania. While the shadow economy as a percentage of GDP in Estonia contracted from 2009 to 2010, it expanded in Latvia and Lithuania. An important driver of shadow activity in the Baltic States is entrepreneurs' dissatisfaction with and distrust in the government and the tax system. We also find involvement in the shadow economy is more pervasive among younger firms and firms in the construction sector. The findings of this study have a number of policy implications: (i) the relatively large size of shadow economies in the Baltic States and their different expansion/contraction trends cause significant error in official estimates of GDP and its rates of change; (ii) tax compliance can be encouraged by addressing the high level of dissatisfaction with the tax system and with government (e.g., making tax policy more stable and increasing the transparency with which taxes are spent); and (iii) significant scope exists for all three governments to increase their tax revenues by bringing entrepreneurs 'out of the shadows'.

Suggested Citation

  • Tālis J. Putniņš & Arnis Sauka, 2011. "Size and determinants of shadow economies in the Baltic States," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 11(2), pages 5-25, December.
  • Handle: RePEc:bic:journl:v:11:y:2011:i:2:p:5-25

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    Cited by:

    1. Colin C. Williams & Ioana A. Horodnic, 2015. "Explaining and tackling the shadow economy in Estonia, Latvia and Lithuania: a tax morale approach," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 15(2), pages 81-98.
    2. Awadh Ahmed Mohammed Gamal & Jauhari B.Dahalan, 2015. "Estimating the Size of the Underground Economy in Saudi: Evidence from Gregory-Hansen Cointegration Based Currency Demand Approach," Abstract of Economic, Finance and Management Outlook, Conscientia Beam, vol. 3, pages 1-6.
    3. Majid Maddah & Bahareh Sobhani, 2014. "The Effective Factors on Informal Economy in Developing Countries (Panel Data Model)," International Journal of Regional Development, Macrothink Institute, vol. 1(1), pages 12-25, December.
    4. Jaanika Merikull & Tairi Room & Karsten Staehr, 2013. "Perceptions of unreported economic activities in Baltic Firms. Individualistic and non-individualistic motives," Bank of Estonia Working Papers wp2012-8, Bank of Estonia, revised 04 Feb 2013.
    5. Jekaterina Navicke & Romas Lazutka, 2016. "Work incentives across the income distribution and for model families in Lithuania: 2005-2013," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 16(2), pages 175-191.

    More about this item


    shadow economy; tax evasion; Estonia; Latvia; Lithuania;

    JEL classification:

    • E26 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Informal Economy; Underground Economy
    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods


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