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Do EU Funds boost productivity and employment?: Firm level analysis for Latvia

Author

Listed:
  • Konstantins Benkovskis

    (OECD)

  • Olegs Tkacevs

    (OECD)

  • Naomitsu Yashiro

    (OECD)

Abstract

This paper investigates the effects of spending the European Regional Development Fund (ERDF) on productivity, employment and other performance indicators of Latvian firms. After controlling for the fact that more productive and larger firms are more likely to benefit from ERDF resources, we find that participation in projects co-financed by the ERDF increases firms’ employment, turnover and capital stock per employee immediately, while it raises their productivity only three years after the launch of such projects. Furthermore, participants that were initially less productive, larger, less capital intensive and more financially leveraged enjoy larger productivity gains. Also, financing capital investment through the ERDF does not result in any productivity gains compared to the case when it is financed through private funding. However, it results in a larger increase in employment, which is possibly partly due to the firm’s plan to increase employment being one of important criteria for selecting the ERDF beneficiaries.

Suggested Citation

  • Konstantins Benkovskis & Olegs Tkacevs & Naomitsu Yashiro, 2018. "Do EU Funds boost productivity and employment?: Firm level analysis for Latvia," OECD Economics Department Working Papers 1525, OECD Publishing.
  • Handle: RePEc:oec:ecoaaa:1525-en
    DOI: 10.1787/98e0a368-en
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    File URL: https://doi.org/10.1787/98e0a368-en
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    References listed on IDEAS

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    1. Michael Lechner, 2002. "Program Heterogeneity And Propensity Score Matching: An Application To The Evaluation Of Active Labor Market Policies," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 205-220, May.
    2. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
    3. Andrea Pufahl & Christoph R. Weiss, 2009. "Evaluating the effects of farm programmes: results from propensity score matching," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 36(1), pages 79-101, March.
    4. John A. List & Daniel L. Millimet & Per G. Fredriksson & W. Warren McHone, 2003. "Effects of Environmental Regulations on Manufacturing Plant Births: Evidence from a Propensity Score Matching Estimator," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 944-952, November.
    5. Julia Bachtrögler & Christoph Hammer & Wolf Heinrich Reuter & Florian Schwendinger, 2017. "Spotlight on the beneficiaries of EU regional funds: A new firm-level dataset," Department of Economics Working Papers wuwp246, Vienna University of Economics and Business, Department of Economics.
    6. Loriane Py & Antoine Bozio & Delphine Irac, 2014. "Impact of research tax credit on R&D and innovation: evidence from the 2008 French reform," EcoMod2014 6873, EcoMod.
    7. Gruševaja, Marina & Pusch, Toralf, 2011. "How does Institutional Setting Affect the Impact of EU Structural Funds on Economic Cohesion? New Evidence from Central and Eastern Europe," IWH Discussion Papers 17/2011, Halle Institute for Economic Research (IWH).
    8. Michela Bia & Alessandra Mattei, 2012. "Assessing the effect of the amount of financial aids to Piedmont firms using the generalized propensity score," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(4), pages 485-516, November.
    9. Sjef Ederveen & Henri L.F. de Groot & Richard Nahuis, 2006. "Fertile Soil for Structural Funds?A Panel Data Analysis of the Conditional Effectiveness of European Cohesion Policy," Kyklos, Wiley Blackwell, vol. 59(1), pages 17-42, February.
    10. Wooldridge, Jeffrey M., 2009. "On estimating firm-level production functions using proxy variables to control for unobservables," Economics Letters, Elsevier, vol. 104(3), pages 112-114, September.
    11. Julia Bachtrögler, 2016. "On the effectiveness of EU structural funds during the Great Recession: Estimates from a heterogeneous local average treatment effects framework," Department of Economics Working Papers wuwp230, Vienna University of Economics and Business, Department of Economics.
    12. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2012. "Causal Inference without Balance Checking: Coarsened Exact Matching," Political Analysis, Cambridge University Press, vol. 20(1), pages 1-24, January.
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    Cited by:

    1. Julia Bachtrögler & Harald Oberhofer, 2018. "Euroscepticism and EU Cohesion Policy: The Impact of Micro-Level Policy Effectiveness on Voting Behavior," Department of Economics Working Papers wuwp273, Vienna University of Economics and Business, Department of Economics.

    More about this item

    Keywords

    EU funds; firm-level data; productivity; propensity score matching;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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