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The role of the staff MFF in distributing NHS funding: taking account of differences in local labour market conditions

  • Robert Elliott

    (Health Economics Research Unit, University of Aberdeen, Aberdeen, UK)

  • Ada Ma

    (Health Economics Research Unit, University of Aberdeen, Aberdeen, UK)

  • Matt Sutton

    (Health Methodology Research Group, School of Community Based Medicine, University of Manchester, University Place, Manchester, UK)

  • Diane Skatun

    (Health Economics Research Unit, University of Aberdeen, Aberdeen, UK)

  • Nigel Rice

    (Centre for Health Economics, University of York, York, UK)

  • Stephen Morris

    (Department of Epidemiology and Public Health, University College London, London, UK)

  • Alex McConnachie

    (Robertson Centre for Biostatistics, University of Glasglow, Glasgow, UK)

The National Health Service (NHS) in England distributes substantial funds to health-care providers in different geographical areas to pay for the health care required by the populations they serve. The formulae that determine this distribution reflect populations' health needs and local differences in the prices of inputs. Labour is the most important input and area differences in the price of labour are measured by the Staff Market Forces Factor (MFF). This Staff MFF has been the subject of much debate. Though the Staff MFF has operated for almost 30 years this is the first academic paper to evaluate and test the theory and method that underpin the MFF. The theory underpinning the Staff MFF is the General Labour Market method. The analysis reported here reveals empirical support for this theory in the case of nursing staff employed by NHS hospitals, but fails to identify similar support for its application to medical staff. The paper demonstrates the extent of spatial variation in private sector and NHS wages, considers the choice of comparators and spatial geography, incorporates vacancy modelling and illustrates the effect of spatial smoothing. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/hec.1489
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Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 19 (2010)
Issue (Month): 5 ()
Pages: 532-548

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Handle: RePEc:wly:hlthec:v:19:y:2010:i:5:p:532-548
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749

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  1. Elliott, Robert F. & Ma, Ada H.Y. & Scott, Anthony & Bell, David & Roberts, Elizabeth, 2007. "Geographically differentiated pay in the labour market for nurses," Journal of Health Economics, Elsevier, vol. 26(1), pages 190-212, January.
  2. Peter C. Smith & Nigel Rice & Roy Carr-Hill, 2001. "Capitation funding in the public sector," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(2), pages 217-257.
  3. David Blanchflower & Alex Bryson, 2002. "Changes over time in union relative wage effects in the UK and the US revisited," NBER Working Papers 9395, National Bureau of Economic Research, Inc.
  4. Elliott, Robert F. & Sandy, Robert, 1998. "Adam Smith may have been right after all: A new approach to the analysis of compensating differentials," Economics Letters, Elsevier, vol. 59(1), pages 127-131, April.
  5. Nigel Rice & Peter Smith, 1999. "Approaches to capitation and risk adjustment in health care: an international survey," Working Papers 038cheop, Centre for Health Economics, University of York.
  6. Sandy, Robert & Elliott, Robert F, 1996. "Unions and Risk: Their Impact on the Level of Compensation for Fatal Risk," Economica, London School of Economics and Political Science, vol. 63(250), pages 291-309, May.
  7. H. Ada & Elizabeth Roberts & Robert Elliott & David Bell & Anthony Scott, 2006. "Comparing the New Earnings Survey (NES) and the Labour Force Survey (LFS): An Analysis of the differences between the data sets and their implications for the pattern of geographical pay in the UK," Regional Studies, Taylor & Francis Journals, vol. 40(6), pages 645-665.
  8. Robert Sandy & Robert F. Elliott, 2005. "Long-term Illness and Wages: The Impact of the Risk of Occupationally Related Long-term Illness on Earnings," Journal of Human Resources, University of Wisconsin Press, vol. 40(3).
  9. Kennedy, Peter, 1986. "Interpreting Dummy Variables," The Review of Economics and Statistics, MIT Press, vol. 68(1), pages 174-75, February.
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