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Drivers of the shadow economy in European Union welfare states: A panel data analysis

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  • Mara, Eugenia Ramona

Abstract

This paper carries out an extensive analysis of the drivers of the shadow economy (SE) in the welfare states of the European Union for the period 1995-2017. The empirical analysis is applied to the 28 EU11As we consider the period before the Brexit, when the United Kingdom is still EU member. member states, which are divided into the following clusters, according to their welfare model: Nordic, Liberal, Continental, Mediterranean, and Eastern models. The relationship between the SE and its determinants is analyzed based on the panel corrected standard errors (PCSEs) model in the presence of cross-section dependence and fully modified ordinary least square (FMOLS) for investigating the long-run impact. The main empirical findings derived from a causality analysis reveal the important role played by economic development and welfare in the SE’s decline in the past two decades. Increasing social protection expenditure and government efficiency are also considered as drivers of the SE’s decline and for this reason, need to be included in the European Union’s policy for combating the SE. Based on the results from this empirical study it is argued that EU countries need to implement an integrated set of rules and regulations in order to reduce the level of the SE in the long run.

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  • Mara, Eugenia Ramona, 2021. "Drivers of the shadow economy in European Union welfare states: A panel data analysis," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 309-325.
    • Handle: RePEc:eee:ecanpo:v:72:y:2021:i:c:p:309-325
    DOI: 10.1016/j.eap.2021.09.004
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    Cited by:

    1. Colin C. Williams, 2023. "A Modern Guide to the Informal Economy," Books, Edward Elgar Publishing, number 18668.
    2. Aysel Amir & Korhan Gökmenoğlu, 2023. "Analyzing the Drivers of the Shadow Economy for the Case of the CESEE Region," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 71(2), pages 155-181, February.
    3. Qin, Yong & Xu, Zeshui & Luo, Chaoguang & Skare, Marinko, 2024. "Investigating the nexus among resource curse, energy transition and sustainable development: Evidence from a global panel data," Resources Policy, Elsevier, vol. 88(C).
    4. Aziz N. Berdiev & Brandon Gomes & James W. Saunoris, 2023. "Revisiting the nexus between globalisation and the shadow economy: Untying the influences of de jure versus de facto globalisation," The World Economy, Wiley Blackwell, vol. 46(1), pages 27-54, January.
    5. Kuti Ayomide Oluwafunmisho & Aderogba Taiwo Adebusuyi & Ezenwa Ndubuisi Johnbosco & Quadri Rasheed Adegboyega, 2023. "Catalysts of Economic Welfare in Africa: A Cross-Sectional Autoregressive Distributed Lag Approach," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 11(1), pages 18-41, October.

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    More about this item

    Keywords

    Shadow economy; Informal economy; Welfare state; Social protection expenditure; Panel data;
    All these keywords.

    JEL classification:

    • E26 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Informal Economy; Underground Economy
    • O17 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements
    • D69 - Microeconomics - - Welfare Economics - - - Other
    • H53 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Welfare Programs
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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