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Economies of scale and efficiency measurement in Switzerland's Nursing homes

Author

Listed:
  • Medhi Farsi

    (Department of Management, Technology and Economics, ETH Zurich, Switzerland)

  • Massimo Filippini

    (Istituto microeconomia e economia pubblica (MecoP), Facoltà di scienze economiche, Università della Svizzera italiana, Svizzera)

  • Diego Lunati

    (Istituto microeconomia e economia pubblica (MecoP), Facoltà di scienze economiche, Università della Svizzera italiana, Svizzera)

Abstract

This paper examines the cost efficiency in the nursing home industry, an issue of concern to Swiss policy makers because of the explosive growth of national expenditure on elderly care and the aging of the population. A stochastic cost frontier model with a translog function has been applied to a balanced panel data of 1780 observations from 356 nursing homes operating over five years (1998-2002) in Switzerland. We compare the estimation results from different panel data econometric techniques focusing on the various methods of specification of unobserved heterogeneity across firms. In particular, the potential effects of such unobserved factors on the estimation results and their interpretation have been discussed. The paper eventually addresses three empirical issues: (1) the measurement of economies of scale in the nursing home sector, (2) the assessment of the economic performance of the firms by estimating their cost efficiency scores, and (3) the role of unobserved heterogeneity in the estimation process. The findings suggest that the economies of scale are an important potential source of cost reduction in a majority of Swiss nursing homes. Taking the size as given the efficiency performance of most individual units is practically very close to the estimated best practice. Nevertheless, the efficiency estimates suggest that some of the nursing homes can significantly reduce their costs by improving their operations.

Suggested Citation

  • Medhi Farsi & Massimo Filippini & Diego Lunati, 2008. "Economies of scale and efficiency measurement in Switzerland's Nursing homes," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 0801, USI Università della Svizzera italiana.
    • Handle: RePEc:lug:wpaper:0801
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Di Giorgio, L. & Filippini, M. & Masiero, G., 2015. "Structural and managerial cost differences in nonprofit nursing homes," Economic Modelling, Elsevier, vol. 51(C), pages 289-298.
    2. L. Di Giorgio & M. Filippini & G. Masiero, 2016. "Is higher nursing home quality more costly?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 1011-1026, November.
    3. Alice Tran & Kim-Huong Nguyen & Len Gray & Tracy Comans, 2019. "A Systematic Literature Review of Efficiency Measurement in Nursing Homes," IJERPH, MDPI, vol. 16(12), pages 1-18, June.
    4. Iparraguirre, José Luis & Ma, Ruosi, 2015. "Efficiency in the provision of social care for older people. A three-stage Data Envelopment Analysis using self-reported quality of life," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 33-46.
    5. INUI Tomohiko & KAWASAKI Kazuyasu & ITO Yukiko & MIYAGAWA Tsutomu & MANO Toshiki, 2019. "Management Practices and Labor Productivity in Intensive Care Homes for the Elderly (Japanese)," Discussion Papers (Japanese) 19049, Research Institute of Economy, Trade and Industry (RIETI).
    6. Laura Di Giorgio & Massimo Filippini & Giuliano Masiero, 2012. "The impact of the institutional form on the cost efficiency of nursing homes," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 1203, USI Università della Svizzera italiana.
    7. Shiovan Ni Luasa & Declan Dineen & Marta Zieba, 2018. "Technical and scale efficiency in public and private Irish nursing homes – a bootstrap DEA approach," Health Care Management Science, Springer, vol. 21(3), pages 326-347, September.

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    More about this item

    Keywords

    COST EFFICIENCY; ECONOMIES OF SCALE; NURSING HOMES; STOCHASTIC FRONTIER; PANEL DATA;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • H70 - Public Economics - - State and Local Government; Intergovernmental Relations - - - General
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • L30 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - General

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