Evidence map›Paper›PMID 27418338›Full record

ArticleThe European journal of health economics : HEPAC : health economics in prevention and care2017

A comparison of average wages with age-specific wages for assessing indirect productivity losses: analytic simplicity versus analytic precision.

Mark P Connolly, Cole Tashjian, Nikolaos Kotsopoulos, Aomesh Bhatt, Maarten J Postma

Abstract read
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Article in The European journal of health economics : HEPAC : health economics in prevention and care, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Adjusted productivity costs of stroke by human capital and friction cost methods: a Northern Finland Birth Cohort 1966 study.The European journal of health economics : HEPAC : health economics in prevention and care · 2021
    Article
  2. Health Care and Productivity Costs of Non-Fatal Traffic Injuries: A Comparison of Road User Types.International journal of environmental research and public health · 2020
    Article
  3. Variation in the methodological approach to productivity cost valuation: the case of prostate cancer.The European journal of health economics : HEPAC : health economics in prevention and care · 2019
    Article
  4. The impact of health on wages: evidence for Europe.The European journal of health economics : HEPAC : health economics in prevention and care · 2018
    Article
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mark P ConnollyUnit of PharmacoEpidemiology and PharmacoEconomics, Department of Pharmacy, University of Groningen, Antonius Deusinglaan 1, 9713 AV, Groningen, The Netherlands. m.connolly@rug.nl.
Cole TashjianGlobal Market Access Solutions (GMAS), St-Prex, Switzerland.
Nikolaos KotsopoulosGlobal Market Access Solutions (GMAS), St-Prex, Switzerland.
Aomesh BhattJohn Radcliffe Hospital, Oxford, OX3 9DU, UK.
Maarten J PostmaUnit of PharmacoEpidemiology and PharmacoEconomics, Department of Pharmacy, University of Groningen, Antonius Deusinglaan 1, 9713 AV, Groningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesNumerous approaches are used to estimate indirect productivity losses using various wage estimates applied to poor health in working aged adults. Considering the different wage estimation approaches observed in the published literature, we sought to assess variation in productivity loss estimates when using average wages compared with age-specific wages.

methodsPublished estimates for average and age-specific wages for combined male/female wages were obtained from the UK Office of National Statistics. A polynomial interpolation was used to convert 5-year age-banded wage data into annual age-specific wages estimates. To compare indirect cost estimates, average wages and age-specific wages were used to project productivity losses at various stages of life based on the human capital approach. Discount rates of 0, 3, and 6 % were applied to projected age-specific and average wage losses.

resultsUsing average wages was found to overestimate lifetime wages in conditions afflicting those aged 1-27 and 57-67, while underestimating lifetime wages in those aged 27-57. The difference was most significant for children where average wage overestimated wages by 15 % and for 40-year-olds where it underestimated wages by 14 %.

conclusionsLarge differences in projecting productivity losses exist when using the average wage applied over a lifetime. Specifically, use of average wages overestimates productivity losses between 8 and 15 % for childhood illnesses. Furthermore, during prime working years, use of average wages will underestimate productivity losses by 14 %. We suggest that to achieve more precise estimates of productivity losses, age-specific wages should become the standard analytic approach.

Indexed as

Cost of IllnessEfficiencyAdolescentAdultAgedAge FactorsChildChild, PreschoolFemaleHumansInfantMaleMiddle AgedModels, EconomicSalaries and Fringe BenefitsUnited KingdomAge-specific wagesAverage wagesIndirect costsProductivity

Identifiers

PMID27418338
PMCPMC5486450

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.