IDEAS home Printed from https://ideas.repec.org/p/bdr/borrec/1228.html
   My bibliography  Save this paper

Estimating Vacancy Stocks from Aggregated Data on Hires: A Methodology to Study Frictions in the Labor Market

Author

Listed:
  • Leonardo Fabio Morales
  • Eleonora Dávalos
  • Raquel Zapata

Abstract

We develop a methodology that recovers an estimate of the average stock of vacancies using the information on aggregated hires. We show that our prediction of the vacancy stock is unbiased, and it captures well the level and the dynamics of the United States job opening positions reported in the Job Openings and Labor Turnover Survey. We use the methodology to predict vacancies in Colombia for formal and informal salaried workers; together with unemployment, we estimate Beveridge curves and matching functions by occupations, which allows us to study the nature of the efficiency, frictions, and mismatches for different occupations. We find that the formal labor market of technicians is the most inefficient of them all; this inefficiency comes from the mismatch between the abilities of the workers and the requirement of the vacancies. Reducing friction in this occupation will require education and job-oriented training policies. In contrast, the frictions in the market for unskilled workers come from informational lacks. The reductions of friction, in this case, will come from better intermediation and active search policies. **** RESUMEN: Este trabajo desarrolla una metodología de estimación del stock vacantes a partir de información de contrataciones agregadas. Mostramos que nuestra predicción es consistente en la medida que captura el nivel y la dinámica de las vacantes recolectadas en la Encuesta de Vacantes y Rotación Laboral (JOLTS) en los Estados Unidos. Como una aplicación de la metodología, el trabajo predice las vacantes en Colombia para trabajadores asalariados formales e informales. Posteriormente se estiman curvas de Beveridge y funciones de emparejamiento por ocupaciones, lo que permite estudiar la naturaleza de la eficiencia, las fricciones y los desajustes para los sub-mercados laborales de diferentes ocupaciones. Se encuentra que el mercado laboral formal de técnicos es el más ineficiente de todos; esta ineficiencia proviene del desajuste entre las capacidades de los trabajadores y el requerimiento de las vacantes. Reducir la fricción en esta ocupación requerirá políticas de educación y formación orientadas al trabajo. En cambio, las fricciones en el mercado de trabajadores no calificados provienen de carencias de información. Las reducciones de fricciones, en este caso, vendrán de mejores políticas de intermediación y búsqueda activa.

Suggested Citation

  • Leonardo Fabio Morales & Eleonora Dávalos & Raquel Zapata, 2023. "Estimating Vacancy Stocks from Aggregated Data on Hires: A Methodology to Study Frictions in the Labor Market," Borradores de Economia 1228, Banco de la Republica de Colombia.
  • Handle: RePEc:bdr:borrec:1228
    DOI: 10.32468/be.1228
    as

    Download full text from publisher

    File URL: https://doi.org/10.32468/be.1228
    Download Restriction: no

    File URL: https://libkey.io/10.32468/be.1228?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Christopher A. Pissarides, 2000. "Equilibrium Unemployment Theory, 2nd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161877, April.
    2. Coles, Melvyn G, 1994. "Understanding the Matching Function: The Role of Newspapers and Job Agencies," CEPR Discussion Papers 939, C.E.P.R. Discussion Papers.
    3. Edward P. Lazear & James R. Spletzer, 2012. "Hiring, Churn, and the Business Cycle," American Economic Review, American Economic Association, vol. 102(3), pages 575-579, May.
    4. Luis Eduardo Arango, 2013. "Puestos de trabajo vacantes según anuncios de la prensa escrita de las siete principales ciudades de Colombia," Borradores de Economia 11097, Banco de la Republica.
    5. Michael W. L. Elsby & Ryan Michaels & David Ratner, 2015. "The Beveridge Curve: A Survey," Journal of Economic Literature, American Economic Association, vol. 53(3), pages 571-630, September.
    6. Martyn J. Andrews & Steve Bradley & Dave Stott & Richard Upward, 2013. "Estimating The Stock-Flow Matching Model Using Micro Data," Journal of the European Economic Association, European Economic Association, vol. 11(5), pages 1153-1177, October.
    7. Masaru Sasaki, 2008. "Matching Function For The Japanese Labour Market: Random Or Stock–Flow?," Bulletin of Economic Research, Wiley Blackwell, vol. 60(2), pages 209-230, April.
    8. Patricia M. Anderson & Simon M. Burgess, 2000. "Empirical Matching Functions: Estimation and Interpretation Using State-Level Data," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 93-102, February.
    9. Abraham, Katharine G, 1983. "Structural-Frictional vs. Deficient Demand Unemployment: Some New Evidence," American Economic Review, American Economic Association, vol. 73(4), pages 708-724, September.
    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. Masaru Sasaki & Miki Kohara & Tomohiro Machikita, 2013. "Measuring Search Frictions Using Japanese Microdata," The Japanese Economic Review, Japanese Economic Association, vol. 64(4), pages 431-451, December.
    2. Gottfries, Nils & Stadin, Karolina, 2016. "The Matching Process:Search Or Mismatch?," Working Paper Series 2016:14, Uppsala University, Department of Economics.
    3. Leonardo Fabio Morales & José Lobo, 2017. "Estimating Vacancies from Firms’ Hiring behavior: The Case of a Developing Economy," Borradores de Economia 1017, Banco de la Republica de Colombia.
    4. Christian Gianella, 2006. "Les trente-cinq heures : un réexamen des effets sur l'emploi," Économie et Prévision, Programme National Persée, vol. 175(4), pages 163-178.
    5. Postel-Vinay, Fabien & Jolivet, Grégory & Borowczyk-Martins, Daniel, 2011. "Accounting For Endogenous Search Behavior in Matching Function Estimation," CEPR Discussion Papers 8471, C.E.P.R. Discussion Papers.
    6. Rüdiger Wapler & Daniel Werner & Katja Wolf, 2018. "Active labour market policies in Germany: do regional labour markets benefit?," Applied Economics, Taylor & Francis Journals, vol. 50(51), pages 5561-5578, November.
    7. Ehrenfried, Felix & Holzner, Christian, 2019. "Dynamics and endogeneity of firms’ recruitment behaviour," Labour Economics, Elsevier, vol. 57(C), pages 63-84.
    8. Miyamoto, Hiroaki, 2011. "Cyclical behavior of unemployment and job vacancies in Japan," Japan and the World Economy, Elsevier, vol. 23(3), pages 214-225.
    9. repec:hal:spmain:info:hdl:2441/4l136f59vb8mcalu5p6p5li007 is not listed on IDEAS
    10. Eriksson, Stefan & Stadin, Karolina, 2015. "What are the determinants of hiring? The role of demand and supply factors," Working Paper Series 2015:14, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    11. Andreas I Mueller & Damian Osterwalder & Josef Zweimüller & Andreas Kettemann, 2024. "Vacancy Durations and Entry Wages: Evidence from Linked Vacancy–Employer–Employee Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(3), pages 1807-1841.
    12. Gomme, Paul & Lkhagvasuren, Damba, 2015. "Worker search effort as an amplification mechanism," Journal of Monetary Economics, Elsevier, vol. 75(C), pages 106-122.
    13. Hie Joo Ahn & Leland D. Crane, 2020. "Dynamic Beveridge Curve Accounting," Finance and Economics Discussion Series 2020-027, Board of Governors of the Federal Reserve System (U.S.).
    14. Jason Anastasopoulos & George J. Borjas & Gavin G. Cook & Michael Lachanski, 2018. "Job Vacancies, the Beveridge Curve, and Supply Shocks: The Frequency and Content of Help-Wanted Ads in Pre- and Post-Mariel Miami," NBER Working Papers 24580, National Bureau of Economic Research, Inc.
    15. Kano, Shigeki & Ohta, Makoto, 2005. "Estimating a matching function and regional matching efficiencies: Japanese panel data for 1973-1999," Japan and the World Economy, Elsevier, vol. 17(1), pages 25-41, January.
    16. Luis Eduardo Arango, 2013. "Puestos de trabajo vacantes según anuncios de la prensa escrita de las siete principales ciudades de Colombia," Borradores de Economia 11097, Banco de la Republica.
    17. Daniel Borowczyk-Martins & Gregory Jolivet & Fabien Postel-Vinay, 2013. "Accounting For Endogeneity in Matching Function Estimation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(3), pages 440-451, July.
    18. Sanna‐Mari Hynninen & Aki Kangasharju & Jaakko Pehkonen, 2009. "Matching Inefficiencies, Regional Disparities, and Unemployment," LABOUR, CEIS, vol. 23(3), pages 481-506, September.
    19. 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.
    20. Simon Mongey & Giovanni L. Violante, 2019. "Macro Recruiting Intensity from Micro Data," NBER Working Papers 26231, National Bureau of Economic Research, Inc.
    21. Higashi, Yudai, 2018. "Spatial spillovers in job matching: Evidence from the Japanese local labor markets," Journal of the Japanese and International Economies, Elsevier, vol. 50(C), pages 1-15.

    More about this item

    Keywords

    Vacantes; demanda laboral; fricciones; Vacancies; labor demand; labor market frictions;
    All these keywords.

    JEL classification:

    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand

    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:bdr:borrec:1228. 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: Clorith Angélica Bahos Olivera (email available below). General contact details of provider: https://edirc.repec.org/data/brcgvco.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.