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Cost efficiency and scale economies in general dental practices in the US: a non-parametric and parametric analysis of Colorado data

Author

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  • L Chen

    (School of Business Jianghan University, Wuhan, China)

  • S C Ray

    (University of Connecticut, Storrs, CT, USA)

Abstract

This paper uses both the non-parametric method of data envelopment analysis (DEA) and the econometric method of stochastic frontier analysis (SFA) to study the production technology and cost efficiency of the US dental care industry using practice level data. The American Dental Association 2006 survey data for a number of general dental practices in the state of Colorado in the US are used for the empirical analysis. The findings suggest that the cost efficiency score is between 0.79 and 0.87, on average, and the cost inefficiency is mostly due to allocative rather than technical inefficiency. The optimal output level for a dental practice to fully exploit the economies of scale is estimated to be at $1.68 million. Average cost at this level of output is 50.6 cents for each dollar of gross billing generated. The DEA and SFA approaches provide generally consistent results.

Suggested Citation

  • L Chen & S C Ray, 2013. "Cost efficiency and scale economies in general dental practices in the US: a non-parametric and parametric analysis of Colorado data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(5), pages 762-774, May.
    • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:5:p:762-774
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    Cited by:

    1. Subhash C. Ray & John Walden & Lei Chen, 2018. "Economic Measures of Capacity Utilization: A Nonparametric Cost Function Analysis," Working papers 2018-02, University of Connecticut, Department of Economics.
    2. Tsionas, Mike G., 2017. "Microfoundations for stochastic frontiers," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1165-1170.
    3. Ray, Subhash C. & Walden, John & Chen, Lei, 2021. "Economic measures of capacity utilization: A nonparametric short-run cost function analysis," European Journal of Operational Research, Elsevier, vol. 293(1), pages 375-387.

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