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Macroeconomic labour productivity and its impact on firm's profitability

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  • K Choi

    (Texas A&M University, College Station, USA)

  • M Haque

    (Texas A&M University, College Station, USA)

  • H W Lee

    (Oregon State University, Corvallis, USA)

  • Y K Cho

    (University of Nebraska-Lincoln, Omaha, USA)

  • Y H Kwak

    (The George Washington University, Washington DC, USA)

Abstract

The construction industry is one of the largest sectors in the US economy, yet little is known about the key macroeconomic parameters that affect its industry’s structure and performance. The main objectives of this research are (1) to analyse the macroeconomic performance of construction industry as a whole and at 14 of its sub-sectors in terms of labour productivity, gross margin, and worker's wages; and (2) to develop a quantitative model that predicts a firm's profitability by analysing various levels of labour productivity. The results of a non-linear regression analysis based on the comprehensive US Economic Census data show that the construction industry’s sub-sectors with the highest productivity are the most profitable with regard to the gross margins that they are able to generate. This study and its model will help decision makers better assess macroeconomic performance and conduct trend analysis of the construction industry to serve as a basis for developing strategic roadmap for the future.

Suggested Citation

  • K Choi & M Haque & H W Lee & Y K Cho & Y H Kwak, 2013. "Macroeconomic labour productivity and its impact on firm's profitability," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(8), pages 1258-1268, August.
    • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:8:p:1258-1268
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    Cited by:

    1. Abbott, Brant & Phan, Nam Van, 2023. "Should wages be subsidized in a pandemic?," Macroeconomic Dynamics, Cambridge University Press, vol. 27(6), pages 1549-1580, September.
    2. Ioannis E. Tsolas, 2020. "Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    3. Pokhrel, Jharna & Seo, Junwon, 2021. "Statistical model for fragility estimates of offshore wind turbines subjected to aero-hydro dynamic loads," Renewable Energy, Elsevier, vol. 163(C), pages 1495-1507.

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