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Understanding the effect of cancer incidence on labour productivity in the UK: An empirical approach with a health augmented production function

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Listed:
  • Bradley Pycroft
  • Aleksandar Vasilev

Abstract

This study represents a new way of looking at health, by investigating the effect of aggregate cancer incidence rates on labour productivity, using a macroeconomic methodology. The health of the labour force is a key determinant of labour productivity, with poor health comes both physical and mental stresses that corrode the productive capacity of workers. Within this study, cancer was selected as an approximation of labour force health, given its ability to capture a range of lifestyle choices. Workers afflicted by cancer often face three choices: continue working, temporarily/permanently leave employment or retire early – all resulting in productivity loss. Moreover, the effect on productivity may not just be felt by the patient but also their family. This creates a negative externality, the result of which is additional productivity loss. The study used an autoregressive distributed lag (ARDL) model to assess the impact of cancer rates in the short-run and long-run. The results were clear, with cancer rates having a significant short-run one year lagged effect on labour productivity. With a 10% short-run lagged increase in cancer rates, leading to a loss of -$1711 in labour productivity per worker – using 2010 GDP per worker. In the long-run, the effect was positive suggesting cancer does not impact long-run economic growth. This research offers a new insight into the mechanics of health within the environment of macroeconomics. With this study potentially unlocking a new avenue of productivity policy framework, aimed at health improvement rather than more traditional approaches involving training and technological advancement.

Suggested Citation

  • Bradley Pycroft & Aleksandar Vasilev, 2022. "Understanding the effect of cancer incidence on labour productivity in the UK: An empirical approach with a health augmented production function," EERI Research Paper Series EERI RP 2022/12, Economics and Econometrics Research Institute (EERI), Brussels.
  • Handle: RePEc:eei:rpaper:eeri_rp_2022_12
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    References listed on IDEAS

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    1. Godfrey, Leslie G, 1978. "Testing against General Autoregressive and Moving Average Error Models When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1293-1301, November.
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    More about this item

    Keywords

    Labour Productivity; Health Economics; Cancer; UK Productivity; Productivity Growth;
    All these keywords.

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • I10 - Health, Education, and Welfare - - Health - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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