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A general equilibrium analysis of the economic impact of the post-2006 EU regulation in the services sector

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Abstract

This study uses both econometric and modelling techniques to quantify the macroeconomic impact of regulatory reforms removing barriers in the European Single Market for services that have taken place in the European Union between 2006 and 2017. It also provides scenario analyses of the impact of a number of hypothetical additional reforms aimed at further reducing regulatory restrictions. The results of the modelling simulations indicate that the regulatory reforms implemented between 2006 and 2017 will result in discounted cumulative gains of 2.1% of GDP by the year 2027. Furthermore, ambitious additional reforms from 2017 onwards would generate an additional growth potential of 2.5% of GDP by 2027. Combining the realised and potential gains would result in a cumulative gain in GDP of 4.65% and a rise in employment of more than 300,000 full time equivalents by 2027. More conservative hypotheses on the additional reforms from 2017 onwards would lead to a GDP cumulative gain of 3.22% by 2027.

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  • Javier Barbero & Manol Bengyuzov & Martin Christensen & Andrea Conte & Simone Salotti & Aleksei Trofimov, 2022. "A general equilibrium analysis of the economic impact of the post-2006 EU regulation in the services sector," JRC Working Papers on Territorial Modelling and Analysis 2022-03, Joint Research Centre.
  • Handle: RePEc:ipt:termod:202203
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    File URL: https://publications.jrc.ec.europa.eu/repository/handle/JRC128322
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    1. Mark Thissen & Olga Ivanova & Giovanni Mandras & Trond Husby, 2019. "European NUTS 2 regions: construction of interregional trade-linked Supply and Use tables with consistent transport flows," JRC Working Papers on Territorial Modelling and Analysis 2019-01, Joint Research Centre.
    2. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    3. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    4. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
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    More about this item

    Keywords

    rhomolo; region; growth; Services regulation; general equilibrium modelling; Single Market;
    All these keywords.

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • R13 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies

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