IDEAS home Printed from https://ideas.repec.org/p/col/000561/018987.html
   My bibliography  Save this paper

Possible uses of labour demand and supply information to reduce skill mismatches

Author

Listed:
  • Cardenas, J

Abstract

Unemployment and informality are widespread phenomena in the Colombian economy that affect people with different profiles. This working paper discusses how the vacancy database can be used to build a detection system of skill shortages. Also, it elaborates on, for the first time in Colombia, a set of macro indicators within the vacancy database’s labour demand and supply information for the identification of possible skill shortages. Finally, it illustrates how detailed information from vacancies (job descriptions) can be used to update occupational classifications (ISCO) and the labour force skills according to employers’ requirements. The results suggest low-skilled occupations tend to show more signs of oversupply: a considerably higher informality rate compared to other skill groups. On the other hand, the first quarter of the year for each occupation is characterised by higher unemployment rates and lower vacancy rates. The skill mismatch indicators for Colombia demonstrate that 30 occupations are currently in short supply. Therefore, the evidence suggests that formal labour market opportunities exist for people with different profiles in terms of age, education and work experience, amongst others. Based on these results, policymakers and education and training providers can promote and update policy/curriculums quickly, according to the current occupational labour demand structure and specific skills required, and the job seekers can receive relevant information regarding occupation shortages, and in this way, unemployed and informal people can make better and informed decisions about their training and job search.

Suggested Citation

  • Cardenas, J, 2020. "Possible uses of labour demand and supply information to reduce skill mismatches," Documentos de trabajo - Alianza EFI 18987, Alianza EFI.
  • Handle: RePEc:col:000561:018987
    as

    Download full text from publisher

    File URL: https://alianzaefi.com/download/possible-uses-of-labour-demand-and-supply-information-to-reduce-skill-mismatches/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Turrell, Arthur & Speigner, Bradley & Djumalieva, Jyldyz & Copple, David & Thurgood, James, 2018. "Using job vacancies to understand the effects of labour market mismatch on UK output and productivity," Bank of England working papers 737, Bank of England.
    2. Hoyt Bleakley & Jeffrey C. Fuhrer, 1997. "Shifts in the Beveridge Curve, job matching, and labor market dynamics," New England Economic Review, Federal Reserve Bank of Boston, issue Sep, pages 3-19.
    3. Shah, C & Burke, G, 2005. "Skills Shortages: Concepts, Measurement and Policy Responses," Australian Bulletin of Labour, National Institute of Labour Studies.
    4. Bosworth, Derek, 1993. "Skill Shortages in Britain," Scottish Journal of Political Economy, Scottish Economic Society, vol. 40(3), pages 241-271, August.
    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. Jan Gottschalk & Ulrich Fritsche, 2005. "The New Keynesian Model and the Long-Run Vertical Phillips Curve: Does It Hold for Germany?," Discussion Papers of DIW Berlin 521, DIW Berlin, German Institute for Economic Research.
    2. Maciej Berk{e}sewicz & Herman Cherniaiev & Robert Pater, 2021. "Estimating the number of entities with vacancies using administrative and online data," Papers 2106.03263, arXiv.org.
    3. Regis Barnichon & Andrew Figura, 2015. "Labor Market Heterogeneity and the Aggregate Matching Function," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(4), pages 222-249, October.
    4. Reinhold Kosfeld & Christian Dreger & Hans-Friedrich Eckey, 2008. "On the stability of the German Beveridge curve: a spatial econometric perspective," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(4), pages 967-986, December.
    5. Carsten Ochsen, 2009. "On the measurement of mismatch," Applied Economics Letters, Taylor & Francis Journals, vol. 16(4), pages 405-409.
    6. Mangan, John & Trendle, Bernard, 2017. "Hard-to-fill vacancies: An analysis of demand side responses in the Australian state of Queensland," Economic Analysis and Policy, Elsevier, vol. 54(C), pages 49-56.
    7. Andrés Álvarez, 2016. "La Curva de Beveridge en Colombia (1976-2014): Cambios cíclicos y estructurales," Borradores de Economia 962, Banco de la Republica de Colombia.
    8. Carlo Di Giorgio & Massimo Giannini, 2012. "A comparison of the Beveridge curve dynamics in Italy and USA," Empirical Economics, Springer, vol. 43(3), pages 945-983, December.
    9. Jane Sneddon Little & Robert K. Triest, 2002. "The impact of demographic change on U. S. labor markets," New England Economic Review, Federal Reserve Bank of Boston, issue Q 1, pages 47-68.
    10. Bradley, Jake & Ruggieri, Alessandro & Spencer, Adam Hal, 2021. "Twin Peaks: Covid-19 and the labor market," European Economic Review, Elsevier, vol. 138(C).
    11. Kyungho Song & Hyun Kim & Jisoo Cha & Taedong Lee, 2021. "Matching and Mismatching of Green Jobs: A Big Data Analysis of Job Recruiting and Searching," Sustainability, MDPI, vol. 13(7), pages 1-15, April.
    12. Giorgio Fagiolo & Giovanni Dosi & Roberto Gabriele, 2005. "Towards an evolutionary interpretation of aggregate labor market regularities," Springer Books, in: Uwe Cantner & Elias Dinopoulos & Robert F. Lanzillotti (ed.), Entrepreneurships, the New Economy and Public Policy, pages 223-252, Springer.
    13. Antoni, Manfred & Janser, Markus & Lehmer, Florian, 2015. "The hidden winners of renewable energy promotion: Insights into sector-specific wage differentials," Energy Policy, Elsevier, vol. 86(C), pages 595-613.
    14. Tony Meagher & James Giesecke, 2008. "Population Ageing and Structural Adjustment," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 11(3), pages 227-247.
    15. Sylwia Roszkowska, 2009. "Aggregate Matching Function. The Case of Poland," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(2), pages 157-177, November.
    16. Thomas Ziesemer, 2003. "Information and Communication Technology as Technical Change in Matching and Production," Journal of Economics, Springer, vol. 79(3), pages 263-287, July.
    17. Варшавская Е. Я. & Котырло Е. С., 2019. "Выпускники Инженерно-Технических И Экономических Специальностей: Между Спросом И Предложением," Вопросы образования // Educational Studies Moscow, National Research University Higher School of Economics, issue 2, pages 98-128.
    18. Shigeru Fujita & Garey Ramey, 2005. "The Dynamic Beveridge Curve," Macroeconomics 0509026, University Library of Munich, Germany.
    19. Kory Kroft & Devin G. Pope, 2014. "Does Online Search Crowd Out Traditional Search and Improve Matching Efficiency? Evidence from Craigslist," Journal of Labor Economics, University of Chicago Press, vol. 32(2), pages 259-303.
    20. Jukka Petteri Lahtonen & Sanna-Mari Hynninen, 2005. "Does population density matter in the matching process of heterogeneous job seekers and vacancies?," ERSA conference papers ersa05p438, European Regional Science Association.

    More about this item

    Keywords

    Skill; Skill mismatches; Beveridge curve; online job portals; informality; unemployment;
    All these keywords.

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

    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:col:000561:018987. 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: Alianza EFI (email available below). General contact details of provider: .

    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.