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Data envelopment analysis with heterogeneous data: an application

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  • J K Sengupta

    (University of California)

Abstract

The effects of data heterogeneity on the efficiency estimate by data envelopment analysis are evaluated here in terms of empirical applications in the computer industry. Scale or size variations of firms and heteroscedasticity are the two forms of heterogeneity considered here. Our empirical results show that the adverse effects of data heterogeneity can be considerably reduced by the methods suggested here.

Suggested Citation

  • J K Sengupta, 2005. "Data envelopment analysis with heterogeneous data: an application," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 676-686, June.
    • Handle: RePEc:pal:jorsoc:v:56:y:2005:i:6:d:10.1057_palgrave.jors.2601861
    DOI: 10.1057/palgrave.jors.2601861
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    References listed on IDEAS

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    1. Bojani, Antonio N. & Caudill, Steven B. & Ford, Jon M., 1998. "Small-sample properties of ML, COLS, and DEA estimators of frontier models in the presence of heteroscedasticity," European Journal of Operational Research, Elsevier, vol. 108(1), pages 140-148, July.
    2. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    3. Sengupta, Jati K., 1990. "Transformations in stochastic DEA models," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 109-123.
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    Cited by:

    1. Pérez-López, Gemma & Prior, Diego & Zafra-Gómez, José L., 2018. "Temporal scale efficiency in DEA panel data estimations. An application to the solid waste disposal service in Spain," Omega, Elsevier, vol. 76(C), pages 18-27.
    2. Ramakrushna Panigrahi, 2021. "Evaluating Level Efficiency Versus Growth Efficiency in the Indian Automobile Industry in a Non-parametric DEA Approach," Global Business Review, International Management Institute, vol. 22(4), pages 963-976, August.
    3. Avkiran, Necmi K. & Rowlands, Terry, 2008. "How to better identify the true managerial performance: State of the art using DEA," Omega, Elsevier, vol. 36(2), pages 317-324, April.
    4. Sahoo, Biresh K & Khoveyni, Mohammad & Eslami, Robabeh & Chaudhury, Pradipta, 2016. "Returns to scale and most productive scale size in DEA with negative data," European Journal of Operational Research, Elsevier, vol. 255(2), pages 545-558.
    5. Ramakrushna Panigrahi, 2021. "Returns to Growth in Indian Automobile Industry: A Non-Parametric Data Envelopment Analysis (DEA) Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 747-765, December.
    6. Sahoo, Biresh K. & Tone, Kaoru, 2013. "Non-parametric measurement of economies of scale and scope in non-competitive environment with price uncertainty," Omega, Elsevier, vol. 41(1), pages 97-111.

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