IDEAS home Printed from https://ideas.repec.org/p/ven/wpaper/201904.html
   My bibliography  Save this paper

European Social Fund's lifelong learning and regional development: a case study

Author

Listed:
  • Francesca Volo

    (Department of Economics, Ca' Foscari University of Venice)

  • Alessandra Drigo

    (Department of Economics, Ca' Foscari University of Venice)

  • M. Bruna Zolin

    (Department of Economics, Ca' Foscari University of Venice)

  • Domenico Sartore

    (Department of Economics, Ca' Foscari University of Venice)

Abstract

The aim of this paper is to evaluate the first impacts of the European Social Fund (hereafter ESF) lifelong learning interventions on the regional development. As is well known, lifelong learning is defined as the all purposeful learning activity, undertaken throughout life, on an ongoing basis, with the aim of improving knowledge, skills, and competence within a personal, civic, social and/or employment-related perspective (CEC, 2000). Beyond the benefits, lifelong learning represents an advantage for the regional economy that could be measured in terms of both estimation of direct impact on domestic demand and evaluation of impacts on the performance of the local economies. The combination of these two kinds of effects generates a positive impact on a wider scale: a higher and skilled workforce attracts more investment, contributing to improve the well-being of a local economy. The case study is the Veneto region. The applied methodologies used in the case study are both a survey and an econometric model. In the first case, the utilized method approaches the topic from a microeconomic perspective, while in the second case the approach is purely macroeconomic.

Suggested Citation

  • Francesca Volo & Alessandra Drigo & M. Bruna Zolin & Domenico Sartore, 2019. "European Social Fund's lifelong learning and regional development: a case study," Working Papers 2019:04, Department of Economics, University of Venice "Ca' Foscari".
  • Handle: RePEc:ven:wpaper:2019:04
    as

    Download full text from publisher

    File URL: http://www.unive.it/pag/fileadmin/user_upload/dipartimenti/economia/doc/Pubblicazioni_scientifiche/working_papers/2019/WP_DSE_volo_drigo_zolin_sartore_04_19.pdf
    File Function: First version, anno
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Daron Acemoglu & Jörn-Steffen Pischke, 1998. "Why Do Firms Train? Theory and Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(1), pages 79-119.
    2. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    3. Alan Barrett & Philip J. O'Connell, 2001. "Does Training Generally Work? The Returns to in-Company Training," ILR Review, Cornell University, ILR School, vol. 54(3), pages 647-662, April.
    4. J.J. Heckman & E.E. Leamer (ed.), 2007. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 6, number 6b.
    5. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 487-535.
    6. Ilya Korshunov & Olga Gaponova, 2017. "Lifelong Learning in the Context of Economic Development and Government Effectiveness," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 4, pages 36-59.
    7. Giorgio Brunello & Pietro Garibaldi & Etienne Wasmer, 2007. "Education and training in Europe," SciencePo Working papers Main hal-03415950, HAL.
    8. James J. Heckman & Vytlacil, Edward J., 2007. "Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 70, Elsevier.
    9. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    10. Misbah Tanveer Choudhry & Enrico Marelli & Marcello Signorelli, 2012. "Youth unemployment rate and impact of financial crises," International Journal of Manpower, Emerald Group Publishing Limited, vol. 33(1), pages 76-95, March.
    11. Imran Khan & Sabiya Mufti & Nazir Ahmed Nazir, 2015. "Transfer of Training: A Reorganized Review on Work Environment and Motivation to Transfer," International Journal of Management, Knowledge and Learning, International School for Social and Business Studies, Celje, Slovenia, vol. 4(2), pages 197-219.
    12. Verick, Sher, 2009. "Who Is Hit Hardest during a Financial Crisis? The Vulnerability of Young Men and Women to Unemployment in an Economic Downturn," IZA Discussion Papers 4359, Institute of Labor Economics (IZA).
    13. J.J. Heckman & E.E. Leamer (ed.), 2007. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 6, number 6a.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Francesca Caselli & Mr. Philippe Wingender, 2018. "Bunching at 3 Percent: The Maastricht Fiscal Criterion and Government Deficits," IMF Working Papers 2018/182, International Monetary Fund.
    2. Muller, Paul & van der Klaauw, Bas & Heyma, Arjan, 2017. "Comparing Econometric Methods to Empirically Evaluate Job-Search Assistance," IZA Discussion Papers 10531, Institute of Labor Economics (IZA).
    3. Ismaël Mourifié & Marc Henry & Romuald Méango, 2020. "Sharp Bounds and Testability of a Roy Model of STEM Major Choices," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 3220-3283.
    4. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    5. Peter Howard-Jones & Jens Hölscher & Dragana Radicic, 2017. "Firm Productivity In The Western Balkans: The Impact Of European Union Membership And Access To Finance," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 62(215), pages 7-52, October –.
    6. Cattaneo, Matias D. & Jansson, Michael & Newey, Whitney K., 2018. "Alternative Asymptotics And The Partially Linear Model With Many Regressors," Econometric Theory, Cambridge University Press, vol. 34(2), pages 277-301, April.
    7. James J. Heckman, 1991. "Randomization and Social Policy Evaluation Revisited," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc.
    8. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    9. Michel Mouchart & Renzo Orsi, 2016. "Building a Structural Model: Parameterization and Structurality," Econometrics, MDPI, vol. 4(2), pages 1-16, April.
    10. Sokbae Lee & Bernard Salanié, 2018. "Identifying Effects of Multivalued Treatments," Econometrica, Econometric Society, vol. 86(6), pages 1939-1963, November.
    11. Siddhartha Bandyopadhyay & Sanjukta Sarkar & Rudra Sensarma, 2021. "Does Access to Key Household Resources Help in Reducing Violence against Women?," Working papers 440, Indian Institute of Management Kozhikode.
    12. Andrew M. Jones, 2007. "Identification of treatment effects in Health Economics," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1127-1131.
    13. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    14. Jens Ruhose & Stephan L. Thomsen & Insa Weilage, 2018. "The Wider Benefits of Adult Learning: Work-Related Training and Social Capital," CESifo Working Paper Series 7268, CESifo.
    15. Francesco Agostinelli & Emilio Borghesan & Giuseppe Sorrenti, 2020. "Welfare, Workfare and Labor Supply: A Unified Evaluation," Working Papers 2020-083, Human Capital and Economic Opportunity Working Group.
    16. van den Berg, Gerard J. & Bonev, Petyo & Mammen, Enno, 2016. "Nonparametric Instrumental Variable Methods for Dynamic Treatment Evaluation," IZA Discussion Papers 9782, Institute of Labor Economics (IZA).
    17. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, vol. 76(1), pages 1-27, April.
    18. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "ddml: Double/debiased machine learning in Stata," Stata Journal, StataCorp LP, vol. 24(1), pages 3-45, March.
    19. Bryan S. Graham, 2019. "Network Data," Papers 1912.06346, arXiv.org.
    20. Sung Jae Jun & Sokbae Lee, 2023. "Identifying the Effect of Persuasion," Journal of Political Economy, University of Chicago Press, vol. 131(8), pages 2032-2058.

    More about this item

    Keywords

    Education; Lifelong learning; Regional economic development; regional policy; regional labour market;
    All these keywords.

    JEL classification:

    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ven:wpaper:2019:04. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Geraldine Ludbrook (email available below). General contact details of provider: https://edirc.repec.org/data/dsvenit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.