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Factor-Analysis-Based Directional Distance Function: The case of New Zealand hospitals

Author

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  • Nan Jiang

    (School of Economics, Auckland University of Technology)

  • Zhongqi Deng

    (School of Economics, Sichuan University, China)

  • Ruizhi Pang

    (College of Economics and Social Development, Nankai University, China)

Abstract

This paper develops a new factor-analysis-based (FAB) approach for choosing the optimal direction in a directional distance function (DDF) analysis. It has the combined merits of factor analysis and slacks-based measure (SBM) and incorporates the relative ease with which various input-output could be adjusted. This development relieves the dependency of price information that is normally unavailable in the provision of public goods. This new FAB-DDF model has been applied on a dataset containing all public hospitals in New Zealand (NZ) observed during 2011-2017. The empirical results indicate that the average reduction across different labor is in the range of 3-10 percent, and the corresponding figure for capital input is 25.7 percent. The case-adjusted inpatient-discharge and price-adjusted outpatient-visit are used as measures of desirable output, the average efficiencies are 92.7 percent and 99 percent respectively. Hospital readmission within 28 days of discharge is used as a measure for undesirable output, and the average efficiency score is 90 percent. These evidence support the suspicion that perverse incentives might exist under the National Health Targets abolished in 2018, which was a set of six indicators used in the last decade to evaluate the performance of local District Health Boards.

Suggested Citation

  • Nan Jiang & Zhongqi Deng & Ruizhi Pang, 2019. "Factor-Analysis-Based Directional Distance Function: The case of New Zealand hospitals," Working Papers 2019-01, Auckland University of Technology, Department of Economics.
    • Handle: RePEc:aut:wpaper:201901
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    1. Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2011. "Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 1-38.
    2. McFadden, Daniel, 1978. "Cost, Revenue, and Profit Functions," Histoy of Economic Thought Chapters, in: Fuss, Melvyn & McFadden, Daniel (ed.),Production Economics: A Dual Approach to Theory and Applications, volume 1, chapter 1, McMaster University Archive for the History of Economic Thought.
    3. Chambers, Robert & Färe, Rolf & Grosskopf, Shawna & Vardanyan, Michael, 2013. "Generalized quadratic revenue functions," Journal of Econometrics, Elsevier, vol. 173(1), pages 11-21.
    4. Atkinson, Scott E. & Tsionas, Mike G., 2016. "Directional distance functions: Optimal endogenous directions," Journal of Econometrics, Elsevier, vol. 190(2), pages 301-314.
    5. Aletras, Vassilios & Kontodimopoulos, Nick & Zagouldoudis, Athanasios & Niakas, Dimitris, 2007. "The short-term effect on technical and scale efficiency of establishing regional health systems and general management in Greek NHS hospitals," Health Policy, Elsevier, vol. 83(2-3), pages 236-245, October.
    6. Chang, Hsihui & Cheng, Mei-Ai & Das, Somnath, 2004. "Hospital ownership and operating efficiency: Evidence from Taiwan," European Journal of Operational Research, Elsevier, vol. 159(2), pages 513-527, December.
    7. R. Färe & S. Grosskopf & G. Whittaker, 2013. "Directional output distance functions: endogenous directions based on exogenous normalization constraints," Journal of Productivity Analysis, Springer, vol. 40(3), pages 267-269, December.
    8. Pang, Rui-Zhi & Deng, Zhong-Qi & Hu, Jin-li, 2015. "Clean energy use and total-factor efficiencies: An international comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1158-1171.
    9. Annika Herr, 2008. "Cost and technical efficiency of German hospitals: does ownership matter?," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1057-1071, September.
    10. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    11. Ancarani, A. & Di Mauro, C. & Giammanco, M.D., 2009. "The impact of managerial and organizational aspects on hospital wards' efficiency: Evidence from a case study," European Journal of Operational Research, Elsevier, vol. 194(1), pages 280-293, April.
    12. David Parkin & Bruce Hollingsworth, 1997. "Measuring production efficiency of acute hospitals in Scotland, 1991-94: validity issues in data envelopment analysis," Applied Economics, Taylor & Francis Journals, vol. 29(11), pages 1425-1433.
    13. Luenberger, David G., 1992. "Benefit functions and duality," Journal of Mathematical Economics, Elsevier, vol. 21(5), pages 461-481.
    14. Kumar, Surender, 2006. "Environmentally sensitive productivity growth: A global analysis using Malmquist-Luenberger index," Ecological Economics, Elsevier, vol. 56(2), pages 280-293, February.
    15. Rolf Färe & Shawna Grosskopf & Carl A. Pasurka & William L. Weber, 2012. "Substitutability among undesirable outputs," Applied Economics, Taylor & Francis Journals, vol. 44(1), pages 39-47, January.
    16. Jens J. Krüger, 2017. "Revisiting the world technology frontier: a directional distance function approach," Journal of Economic Growth, Springer, vol. 22(1), pages 67-95, March.
    17. Oxholm, Anne Sophie & Kristensen, Søren Rud & Sutton, Matt, 2018. "Uncertainty about the effort–performance relationship in threshold-based payment schemes," Journal of Health Economics, Elsevier, vol. 62(C), pages 69-83.
    18. Fuss, Melvyn & McFadden, Daniel (ed.), 1978. "Production Economics: A Dual Approach to Theory and Applications," Elsevier Monographs, Elsevier, edition 1, number 9780444850133.
    19. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    20. Badau, Flavius & Färe, Rolf & Gopinath, Munisamy, 2016. "Global resilience to climate change: Examining global economic and environmental performance resulting from a global carbon dioxide market," Resource and Energy Economics, Elsevier, vol. 45(C), pages 46-64.
    21. Fuss, Melvyn & McFadden, Daniel, 1978. "Production Economics: A Dual Approach to Theory and Applications (I): The Theory of Production," History of Economic Thought Books, McMaster University Archive for the History of Economic Thought, volume 1, number fuss1978.
    22. Gale Boyd & George Tolley & Joseph Pang, 2002. "Plant Level Productivity, Efficiency, and Environmental Performance of the Container Glass Industry," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(1), pages 29-43, September.
    23. Feng, Guohua & Serletis, Apostolos, 2014. "Undesirable outputs and a primal Divisia productivity index based on the directional output distance function," Journal of Econometrics, Elsevier, vol. 183(1), pages 135-146.
    24. Fuss, Melvyn & McFadden, Daniel, 1978. "Production Economics: A Dual Approach to Theory and Applications (II): Applications of the Theory of Production," History of Economic Thought Books, McMaster University Archive for the History of Economic Thought, volume 2, number fuss1978a.
    25. Fare, Rolf & Grosskopf, Shawna & Weber, William L., 2006. "Shadow prices and pollution costs in U.S. agriculture," Ecological Economics, Elsevier, vol. 56(1), pages 89-103, January.
    26. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    27. Jose Zofio & Jesus Pastor & Juan Aparicio, 2013. "The directional profit efficiency measure: on why profit inefficiency is either technical or allocative," Journal of Productivity Analysis, Springer, vol. 40(3), pages 257-266, December.
    28. Eggleston, Karen, 2005. "Multitasking and mixed systems for provider payment," Journal of Health Economics, Elsevier, vol. 24(1), pages 211-223, January.
    29. Mark Agee & Scott Atkinson & Thomas Crocker, 2012. "Child maturation, time-invariant, and time-varying inputs: their interaction in the production of child human capital," Journal of Productivity Analysis, Springer, vol. 38(1), pages 29-44, August.
    30. Lee, Chia-Yen, 2014. "Meta-data envelopment analysis: Finding a direction towards marginal profit maximization," European Journal of Operational Research, Elsevier, vol. 237(1), pages 207-216.
    31. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    32. Schmitt, Matt, 2017. "Do hospital mergers reduce costs?," Journal of Health Economics, Elsevier, vol. 52(C), pages 74-94.
    33. Annika Herr & Hendrik Schmitz & Boris Augurzky, 2011. "Profit efficiency and ownership of German hospitals," Health Economics, John Wiley & Sons, Ltd., vol. 20(6), pages 660-674, June.
    34. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    35. H. Shelton Brown, 2003. "Managed care and technical efficiency," Health Economics, John Wiley & Sons, Ltd., vol. 12(2), pages 149-158, February.
    36. Friesner, Daniel & Mittelhammer, Ron & Rosenman, Robert, 2013. "Inferring the incidence of industry inefficiency from DEA estimates," European Journal of Operational Research, Elsevier, vol. 224(2), pages 414-424.
    37. Rolf Färe & Shawna Grosskopf, 2000. "Theory and Application of Directional Distance Functions," Journal of Productivity Analysis, Springer, vol. 13(2), pages 93-103, March.
    38. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    39. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    40. Luenberger, David G., 1995. "Externalities and benefits," Journal of Mathematical Economics, Elsevier, vol. 24(2), pages 159-177.
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    2. Gao, Qiuming & Wang, Derek, 2021. "Hospital efficiency and equity in health care delivery: A study based in China," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    3. Zhongqi Deng & Yu Zhang & Ao Yu, 2020. "The New Economy in China: An Intercity Comparison," SAGE Open, , vol. 10(4), pages 21582440209, December.
    4. Vardanyan, Michael & Valdmanis, Vivian G. & Leleu, Hervé & Ferrier, Gary D., 2022. "Estimating technology characteristics of the U.S. hospital industry using directional distance functions with optimal directions," Omega, Elsevier, vol. 113(C).
    5. Zhichao Wang & Valentin Zelenyuk, 2021. "Performance Analysis of Hospitals in Australia and its Peers: A Systematic Review," CEPA Working Papers Series WP012021, School of Economics, University of Queensland, Australia.
    6. Deng, Zhongqi & Song, Shunfeng & Jiang, Nan & Pang, Ruizhi, 2023. "Sustainable development in China? A nonparametric decomposition of economic growth," China Economic Review, Elsevier, vol. 81(C).
    7. Tavana, Madjid & Izadikhah, Mohammad & Toloo, Mehdi & Roostaee, Razieh, 2021. "A new non-radial directional distance model for data envelopment analysis problems with negative and flexible measures," Omega, Elsevier, vol. 102(C).
    8. Zhongqi Deng & Qianyu Zhao & Helen X. H. Bao, 2020. "The Impact of Urbanization on Farmland Productivity: Implications for China’s Requisition–Compensation Balance of Farmland Policy," Land, MDPI, vol. 9(9), pages 1-24, September.

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    More about this item

    Keywords

    factor-analysis-based measure; directional distance function; NZ hospital efficiency; hospital readmission;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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