IDEAS home Printed from https://ideas.repec.org/p/hhs/ifauwp/2012_017.html
   My bibliography  Save this paper

Measuring workers' health and psychosocial work-environment on firm productivity

Author

Listed:
  • Ödegaard, Fredrik

    (Ivey School of Business, Western University)

  • Roos, Pontus

    (R.R. Institute of Applied Economics)

Abstract

We discuss a model for analyzing and measuring workers' health and psychosocial work-environment on firm productivity. Productivity is measured through the Malmquist productivity index approach using Data Envelopment Analysis. A novel component of the model is that in addition to standard quantity (or tradable) vairables, we incorporate quality (or non-tradable) variables. Specifically we focus on two quality input variables: workers' health status and psychosocial work-environment. The two variables are modeled as latent or unobserved variables using Item Response Theory. Changes over time in productivity are decomposed to asses the contribution from the changes of the input quality variables. The model is illustrated using data from a worksite health promotion program conducted at three large Swedish manufacturing plants (2 paper mills, 1 steel factory) from 2000 to 2003. Over the four years we observe a general improvement in efficiency of 2-5 %, out of which half can be attributed to the improvement in the quality input variables.

Suggested Citation

  • Ödegaard, Fredrik & Roos, Pontus, 2012. "Measuring workers' health and psychosocial work-environment on firm productivity," Working Paper Series 2012:17, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    • Handle: RePEc:hhs:ifauwp:2012_017
    as

    Download full text from publisher

    File URL: http://www.ifau.se/Upload/pdf/se/2012/wp12-17-Measuring-workers-health-and-psychosocial-work-environment-on-firm-productivity.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Knut Røed & Elisabeth Fevang, 2007. "Organizational Change, Absenteeism, and Welfare Dependency," Journal of Human Resources, University of Wisconsin Press, vol. 42(1).
    2. Johnson, Matthew S., 2007. "Marginal Maximum Likelihood Estimation of Item Response Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 20(i10).
    3. Fare, Rolf & Grosskopf, Shawna & Kokkelenberg, Edward C, 1989. "Measuring Plant Capacity, Utilization and Technical Change: A Nonparametric Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 655-666, August.
    4. Subodh Kumar & R. Robert Russell, 2002. "Technological Change, Technological Catch-up, and Capital Deepening: Relative Contributions to Growth and Convergence," American Economic Review, American Economic Association, vol. 92(3), pages 527-548, June.
    5. Daniel J. Henderson & R. Robert Russell, 2005. "Human Capital And Convergence: A Production-Frontier Approach ," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(4), pages 1167-1205, November.
    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. Kerstin Enflo & Per Hjertstrand, 2009. "Relative Sources of European Regional Productivity Convergence: A Bootstrap Frontier Approach," Regional Studies, Taylor & Francis Journals, vol. 43(5), pages 643-659.
    2. Kevin S. Nell & Maria M. De Mello, 2019. "The interdependence between the saving rate and technology across regimes: evidence from South Africa," Empirical Economics, Springer, vol. 56(1), pages 269-300, January.
    3. R. Russell & William Schworm, 2009. "Axiomatic foundations of efficiency measurement on data-generated technologies," Journal of Productivity Analysis, Springer, vol. 31(2), pages 77-86, April.
    4. Camilla Mastromarco & Léopold Simar, 2021. "Latent heterogeneity to evaluate the effect of human capital on world technology frontier," Journal of Productivity Analysis, Springer, vol. 55(2), pages 71-89, April.
    5. Jens J. Krüger, 2020. "Long‐run productivity trends: A global update with a global index," Review of Development Economics, Wiley Blackwell, vol. 24(4), pages 1393-1412, November.
    6. Oleg Badunenko & Daniel Henderson & Romain Houssa, 2014. "Significant drivers of growth in Africa," Journal of Productivity Analysis, Springer, vol. 42(3), pages 339-354, December.
    7. Daniel J. Henderson & Christopher F. Parmeter & R. Robert Russell, 2008. "Modes, weighted modes, and calibrated modes: evidence of clustering using modality tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 607-638.
    8. Tero Kuusi, 2015. "The dynamics of ICT adaptation and the productivity gaps across advanced nations," Journal of Productivity Analysis, Springer, vol. 44(2), pages 175-188, October.
    9. Kerekes, Monika, 2007. "Analyzing patterns of economic growth: a production frontier approach," Discussion Papers 2007/15, Free University Berlin, School of Business & Economics.
    10. Claudia Curi & Paolo Guarda & Valentin Zelenyuk, 2011. "Changes in bank specialisation: comparing foreign subsidiaries and branches in Luxembourg," BCL working papers 67, Central Bank of Luxembourg.
    11. Laurens Cherchye & Bram De Rock & Antonio Estache & Barnabé Walheer, 2013. "Reducing Energy Use without Affecting the Economic Objectives: a Sectoral Analysis," Working Papers ECARES ECARES 2013-11, ULB -- Universite Libre de Bruxelles.
    12. Barnabé Walheer, 2016. "Multi-Sector Nonparametric Production-Frontier Analysis of the Economic Growth and the Convergence of the European Countries," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 498-524, October.
    13. Alexander Schiersch & Heike Belitz & Martin Gornig, 2012. "Is Technical Progress Sectorally Concentrated?: An Empirical Analysis for Western European Countries," Discussion Papers of DIW Berlin 1217, DIW Berlin, German Institute for Economic Research.
    14. Pieralli, Simone, 2015. "The impacts of climate change on French agricultural productivity," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205892, Agricultural and Applied Economics Association.
    15. Eiji Yamamura & Inyong Shin, 2013. "Decomposition of Ethnic Heterogeneity on Growth," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 55(1), pages 59-75, March.
    16. Po-Chi Chen & Ming-Miin Yu, 2014. "Total factor productivity growth and directions of technical change bias: evidence from 99 OECD and non-OECD countries," Annals of Operations Research, Springer, vol. 214(1), pages 143-165, March.
    17. Oleg Badunenko & Diego Romero‐Ávila, 2013. "Financial Development And The Sources Of Growth And Convergence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(2), pages 629-663, May.
    18. Li, Ke & Lin, Boqiang, 2018. "How to promote energy efficiency through technological progress in China?," Energy, Elsevier, vol. 143(C), pages 812-821.
    19. Shiu, Alice & Zelenyuk, Valentin, 2009. "Production Efficiency versus Ownership: The Case of China," MPRA Paper 23760, University Library of Munich, Germany, revised 22 Mar 2010.
    20. Isabel Narbón-Perpiñá & Maria Teresa Balaguer-Coll & Diego Prior & Emili Tortosa-Ausina, 2021. "Searching for the optimal territorial structure: the case of Spanish provincial councils," Regional Studies, Taylor & Francis Journals, vol. 55(4), pages 645-664, April.

    More about this item

    Keywords

    Productivity; Decomposition of efficiency; Human resource management; Health status; Psychosocial work-environment; Ordinal data; Latent variables;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • I10 - Health, Education, and Welfare - - Health - - - General

    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:hhs:ifauwp:2012_017. 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: Ali Ghooloo (email available below). General contact details of provider: https://edirc.repec.org/data/ifagvse.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.