Measuring efficiency in health care: Analytic techniques and health policy

Measuring Efficiency in Health Care: Analytic Techniques and Health Policy

Volumn , Issue , 2006, Pages 1-243

  Jacobs, Rowena ^a   Smith, Peter C ^a   Street, Andrew ^a  

^a UNIVERSITY OF YORK   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84926079120     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1017/CBO9780511617492     Document Type: Book

References (188)

1. Aigner, D., Lovell, C. A. K. and Schmidt, P. 1977. ‘Formulation and estimation of stochastic frontier production function models’. Journal of Econometrics 6: 21-37.
2. Ali, A. I. and Seiford, L. M. 1993. ‘The mathematical programming approach to efficiency analysis’, in H. O Fried, C. A. K. Lovell and S. S. Schmidt (eds.), The Measurement of Productive Efficiency. Oxford: Oxford University Press, pp. 120-59.
3. Allen, R., Athanassopoulos, A., Dyson, R. G. and Thanassoulis, E. 1997. ‘Weight restrictions and value judgements in data envelopment analysis: evolution, development and future directions’. Annals of Operations Research 73: 13-34.
4. Anand, S., Ammar, W., Evans, T., Hasegawa, T., Kissimova-Skarbek, K., Langer, A., Lucas, A. O., Makubalo, L., Marandi, A., Meyer, G., Podger, A., Smith, P. C. and Wibulpolprasert, S. 2002. Report of the Scientific Peer Review Group on Health Systems Performance Assessment. Geneva: World Health Organization.
5. Atkinson, T. 2005. Atkinson Review: Final Report. Measurement of Government Output and Productivity for the National Accounts. Basingstoke: Palgrave Macmillan. Audit Commission and Department of Health 1999. NHS Trust Profiles Handbook-1997/98. London: Audit Commission.
6. Baltagi, B. H. 2005. Econometric Analysis of PanelData, 3rd edn.Chichester: Wiley.
7. Banker, R. D. and Morey, R. C. 1986. ‘Efficiency analysis for exogenously fixed inputs and outputs’. Operations Research 34: 513-21.
8. Banker, R. D., Charnes, A. and Cooper, W. W. 1984. ‘Some models for estimating technical and scale inefficiencies in data envelopment analysis’. Management Science 30: 1078-92.
9. Banker, R. D., Conrad, R. F. and Strauss, R. P. 1986. ‘A comparative application of data envelopment analysis and translog methods: an illustrative study of hospital production’.Management Science 32: 30-44.
10. Banker, R. D., Gadh, V. M. and Gorr, W. L. 1993. ‘A Monte Carlo comparison of two production frontier estimation methods: corrected ordinary least squares and data envelopment analysis’. European Journal of Operational Research 67: 332-43.
11. Banker, R. D., Charnes, A., Cooper, W., Swarts, J. and Thomas, D. 1989. ‘An introduction to data envelopment analysis with some models and their uses’. Research in Governmental and Non-Profit Accounting 5: 125-63.
12. Barth, W. and Staat, M. 2005. ‘Environmental variables and relative efficiency of bank branches: A DEA-bootstrap approach’. International Journal of Business Performance Management 7: 228-40.
13. Bates, J. M., Baines, D. and Whynes, D. K. 1996. ‘Measuring the efficiency of prescribing by general practitioners’. Journal of the Operational Research Society 47: 1443-51.
14. Bates, J. M., Baines, D. and Whynes, D. K. 1998. ‘Assessing efficiency in general practice: an application of data envelopment analysis’. Health Services Management Research 11: 103-8.
15. Battese, G. E. and Coelli, T. 1988. ‘Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data’. Journal of Econometrics 38: 387-99.
16. Battese, G. E. and Coelli, T. 1992. ‘Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India’. Journal of Productivity Analysis 3: 153-69.
17. Bauer, P. W., Berger, A. N., Ferrier, G. D. and Humphrey, D. B. 1998. ‘Consistency conditions for regulatory analysis of financial institutions: a comparison of frontier efficiency methods’. Journal of Economics and Business 50: 85-114.
18. Benton, P. L., Anthony, P., Evans, H., Light, S. M., Mountney, L. M. and Sanderson, H. F. 1998. ‘The development of Healthcare Resource Groups version 3’. Journal of Public Health Medicine 20: 351-8.
19. Bessent, A., Bessent, W., Elam, J. and Clark, T. 1988. ‘Efficiency frontier determination by constrained facet analysis’. Operations Research 36: 785-96.
20. Bhattacharya, A., Lovell, C. A. K. and Sahay, P. 1997. ‘The impact of liberalization on the productive efficiency of Indian commercial banks’. European Journal of Operational Research 98: 332-47.
21. Blank, J. L. T. and Valdmanis, V. 2005. ‘A modified three-stage data envelopment analysis: The Netherlands’. European Journal of Health Economics 6: 65-71.
22. Bond, S. 2002. ‘Dynamic panel data models: a guide to micro data methods and practice’. Portuguese Economic Journal 1: 141-62.
23. Bowlin, W. F., Charnes, A., Cooper, W. and Sherman, H. D. 1985. ‘Data envelopment analysis and regression approaches to efficiency estimation and evaluation’. Annals of Operations Research 2: 113-38.
24. Breyer, F. 1987. ‘The specification of a hospital cost function’. Journal of Health Economics 6: 147-57.
25. Burgess, D. F. 1975. ‘Duality theory and pitfalls in the specification of technologies’. Journal of Econometrics 3: 105-21.
26. Burgess, J. F. and Wilson, P. W. 1995. ‘Decomposing hospital productivity changes, 1985-1988: a nonparametric Malmquist approach’. Journal of Productivity Analysis 6: 343-63.
27. Casu, B., Girardone, C. and Molyneux, P. 2004. ‘Productivity change in European banking: a comparison of parametric and non-parametric approaches’. Journal of Banking and Finance 28: 2521-40.
28. Caves, D. W., Christensen, L. R. and Diewert, W. E. 1982. ‘The economic theory of index numbers and the measurement of input, output and productivity’. Econometrica 50: 1393-414.
29. Charnes, A., Cooper, W. W. and Rhodes, E. 1978. ‘Measuring the efficiency of decision making units’. European Journal of Operational Research 2: 429-44.
30. Charnes, A., Cooper, W. W. and Rhodes, E. 1981. ‘Evaluating program and managerial efficiency: an application of Data Envelopment Analysis to program follow through’. Management Science 27: 668-97.
31. Charnes, A., Cooper, W. W., Lewin, A. Y. and Seiford, L. M. (eds.) 1994. Data Envelopment Analysis: Theory, Methodology, and Application. Boston: Kluwer Academic Publishers.
32. Charnes, A., Cooper, W. W., Wei, Q. L. and Huang, Z. 1989. ‘Cone ratio data envelopment analysis and multi-objective programming’. International Journal of Systems Science 20: 1099-118.
33. Chilingerian, J. A. 1994. ‘Exploring why some physicians’ hospital practices are more efficient: taking DEA inside the hospital’, in Charnes, A., Cooper, W. W., Lewin, A. Y. and Seiford, L. M. (eds.), Data Envelopment Analysis: Theory, Methodology and Application. Boston: Kluwer Academic Publishers, pp. 167-94.
34. Christensen, L. R. and Greene, W. H. 1976. ‘Economies of scale in US electric power generation’. Journal of Political Economy 84: 655-76.
35. Christensen, L. R., Jorgenson, D. W. and Lau, L. J. 1973. ‘Transcendental logarithmic production functions’. Review of Economics and Statistics 55: 28-45.
36. Coase, R. H. 1937. ‘The nature of the firm’. Economica 4: 386-405.
37. Coelli, T. 1996a. ‘A guide to FRONTIER version 4.1: a computer program for stochastic frontier production and cost function estimation’. Working Paper 96/07, Centre for Efficiency and Productivity Analysis, University of New England, Armidale, NSW.
38. Coelli, T. 1996b. ‘A guide to DEAP version 2.1: a data envelopment analysis (computer) program’. Working Paper 96/08, Centre for Efficiency and Productivity Analysis, University of New England, Armidale, NSW.
39. Coelli, T. 1998. ‘A multi-stage methodology for the solution of orientated DEA models’. Operations Research Letters 23: 143-49.
40. Coelli, T. and Perelman, S. 1996. ‘Efficiency measurement, multiple-output technologies and distance functions: with application to European railways’. Discussion Paper 96/05, CREPP, University of Liege.
41. Coelli, T. and Perelman, S. 2000. ‘Technical efficiency of European railways: a distance function approach’. Applied Economics 32: 1967-76.
42. Coelli, T., Rao, D. and Battese, G. 1998. An Introduction to Efficiency and Productivity Analysis. Boston: Kluwer Academic Publishers.
43. Cook, R. D. and Weisberg, S. 1982. Residuals and Influence in Regression. London: Chapman and Hall.
44. Cooper, W. W., Seiford, L. M. and Tone, K. 2000. Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-solver Software. Boston: Kluwer Academic Publishers.
45. Cornwell, C., Schmidt, P. and Sickles, R. C. 1990. ‘Production frontiers with cross-sectional and time-series variation in efficiency levels’. Journal of Econometrics 46: 185-200.
46. Coulter, A., and Magee, H. 2003. The European Patient of the Future. Maidenhead, Berkshire: Open University Press.
47. Davidson, R. and MacKinnon, J. G. 1985. ‘Testing linear and loglinear regressions against Box-Cox alternatives’. Canadian Journal of Economics 18: 499-517.
48. Dismuke, C. and Sena, V. 1999. ‘Has DRG payment influenced the technical efficiency and productivity of diagnostic technologies in Portuguese public hospitals?’ Health Care Management Science 2: 107-16.
49. Doyle, J. and Green, R. 1994. ‘Efficiency and cross-efficiency in DEA: derivations, meanings and uses’. Journal of the Operational Research Society 45: 567-78.
50. EuroQol Group 1990. ‘EuroQol-a new facility for the measurement of health-related quality of life’. Health Policy 16: 199-208.
51. Everitt, B., Landau, S. and Leese, M. 2001. Cluster Analysis. London: Arnold.
52. Färe, R. and Grosskopf, S. 1996. Intertemporal Production Frontiers: With Dynamic DEA. Boston: Kluwer Academic Publishers.
53. Färe, R., Grosskopf, S., Lindgren, B. and Poullier, J. P. 1997. ‘Productivity growth in health care delivery’. Medical Care 35: 354-66.
54. Färe, R., Grosskopf, S., Lindgren, B. and Roos, P. 1992. ‘Productivity changes in Swedish pharmacies 1980-1989: a non-parametricMalmquist approach’. Journal of Productivity Analysis 3: 85-101.
55. Färe, R., Grosskopf, S., Norris, M. and Zhang, Z. 1994. ‘Productivity growth, technical progress and efficiency changes in industrialised countries’. American Economic Review 84: 66-83.
56. Farley, D. E. 1989. ‘Measuring case mix specialization and the concentration of diagnoses in hospitals using information theory’. Journal of Health Economics 8: 185-207.
57. Farley, D. E. and Hogan, C. 1990. ‘Case-mix specialization in the market for hospital services’. Health Services Research 25: 757-83.
58. Farrell, M. J. 1957. ‘The measurement of productive efficiency’. Journal of the Royal Statistical Society, Series A, 120: 253-90.
59. Farsi, M., Filippini, M. and Kuenzle, M. 2003. ‘Unobserved heterogeneity in stochastic frontier models: a comparative analysis’. Working Paper 03-11, Department of Economics, University of Lugano.
60. Feldstein, M. S. 1967. Economic Analysis for Health Service Efficiency: Econometric Studies of the British National Health Service. Amsterdam: North-Holland.
61. Fernández, C., Koop, G. and Steel, M. 2000. ‘A Bayesian analysis of multiple-output production frontiers’. Journal of Econometrics 98: 47-79.
62. Ferrier, G. D. and Lovell, C. A. K. 1990. ‘Measuring cost efficiency in banking: econometric and linear programming evidence’. Journal of Econometrics 46: 229-45.
63. Ferrier, G. D. and Valdmanis, V. 1996. ‘Rural hospital performance and its correlates’. Journal of Productivity Analysis 7: 63-80.
64. Fisher, I. 1922. The Making of Index Numbers. Boston: Houghton Mifflin.
65. Folland, S. T. and Hofler, R. A. 2001. ‘How reliable are hospital efficiency estimates? Exploiting the dual to homothetic production’. Health Economics 10: 683-98.
66. Fried, H. O., Lovell, C. A. K. and Schmidt, S. S. (eds.) 1993. The Measurement of Productive Efficiency. Oxford: Oxford University Press.
67. Fried, H. O., Lovell, C. A. K. and vanden Eeckaut, P. 1993. ‘Evaluating the performance of U.S. credit unions’. Journal of Banking and Finance 17: 251-65.
68. Fried, H. O., Schmidt, S. S. and Yaisawarng, S. 1999. ‘Incorporating the operating environment into a nonparametric measure of technical efficiency’. Journal of Productivity Analysis 12: 249-67.
69. Fried, H. O., Lovell, C. A. K., Schmidt, S. S. and Yaisawarng, S. 2002. ‘Accounting for environmental effects and statistical noise in data envelopment analysis’. Journal of Productivity Analysis 17: 157-74.
70. Gerdtham, U. G., Rehnberg, C. and Tambour, M. 1999. ‘The impact of internal markets on health care efficiency: evidence from health care reforms in Sweden’. Applied Economics 31: 935-45.
71. Gilthorpe, M. S. and Cunningham, S. J. 2000. ‘The application of multilevel, multivariate modelling to orthodontic research data’. Community Dental Health 17: 236-42.
72. Giuffrida, A. 1999. ‘Productivity and efficiency changes in primary care: a Malmquist index approach’.Health CareManagement Science 2: 11-26.
73. Giuffrida, A. and Gravelle, H. 2001. ‘Measuring performance in primary care: econometric analysis and DEA’. Applied Economics 33: 163-75.
74. Giuffrida, A., Gravelle, H. and Sutton, M. 2000. ‘Efficiency and administrative costs in primary care’. Journal of Health Economics 19: 983-1006.
75. Goldstein, H. and Spiegelhalter, D. J. 1996. ‘League tables and their limitations: statistical issues in comparisons of institutional performance’. Journal of the Royal Statistical Society, series A, 159: 385-443.
76. González, E. and Gascón, F. 2004. ‘Sources of productivity growth in the Spanish pharmaceutical industry 1994-2000’. Research Policy 33: 735-45.
77. Greene, W. H. 1990. ‘A gamma-distributed stochastic frontier model’. Journal of Econometrics 46: 141-63.
78. Greene, W. H. 1993. ‘The econometric approach to efficiency analysis’, in Fried, H. O., Lovell, C. A. K. and Schmidt, S. S. (eds.), The Measurement of Productive Efficiency. Oxford: Oxford University Press, pp. 68-119.
79. Greene, W. H. 1995. Limdep Version 7.0 User’s Manual. Castle Hill, NSW: Econometric Software, Inc.
80. Greene, W. H. 2000. Econometric Analysis. Upper Saddle River, N. J.: Prentice-Hall.
81. Greene, W. H. 2002. Limdep Version 8.0 Econometric Modelling Guide. Plainview, N.Y.: Econometric Software, Inc.
82. Greene, W. H. 2004. ‘Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization’s panel data on national health care systems’. Health Economics 13: 959-80.
83. Greene, W. H. 2005. ‘Reconsidering heterogeneity in panel data estimators of the stochastic frontier model’. Journal of Econometrics 126: 269-303.
84. Grifell-Tatjé, E. and Lovell, C. A. K. 1995. ‘A note on the Malmquist productivity index’. Economics Letters 47: 169-75.
85. Grosskopf, S. and Valdmanis, V. 1987. ‘Measuring hospital performance: a non-parametric approach’. Journal of Health Economics 6: 89-107.
86. Hadley, J. and Zuckerman, S. 1994. ‘The role of efficiency measurement in hospital rate setting’. Journal of Health Economics 13: 335-40.
87. Harris, J. E. 1977. ‘The internal organisation of hospitals: some economic implications’. Bell Journal of Economics 8: 467-82.
88. Hauck, K. and Street, A. 2005. ‘Performance assessment in the context of multiple objectives: a multivariate multilevel approach’, Centre for Health Economics, University of York, Mimeo.
89. Hauck, K., Rice, N. and Smith, P. 2003. ‘The influence of health care organisations on indicators of health system performance’. Journal of Health Services Research and Policy 8: 68-74.
90. Hausman, J. 1978. ‘Specification tests in econometrics’. Econometrica 46: 1251-71.
91. Hill, P. W. and Goldstein, H. 1998. ‘Multilevel modelling of educational data with cross classification and missing identification for units’. Journal of Educational and Behavioural Statistics 23: 117-28.
92. Hirschberg, J. G. and Lloyd, P. J. 2000. ‘An application of post-DEA bootstrap regression analysis to the spillover of the technology of foreign-invested enterprises in China’. Paper 732, Department of Economics, University of Melbourne.
93. Hollingsworth, B. 2003. ‘Non-parametric and parametric applications measuring efficiency in health care’. Health Care Management Science 6: 203-18.
94. Hollingsworth, B. and Parkin, D. 2001. ‘The efficiency of the delivery of neonatal care in the UK’. Journal of Public Health Medicine 23: 47-50.
95. Hollingsworth, B. and Smith, P. C. 2003. ‘The use of ratios in data envelopment analysis’. Applied Economics Letters 10: 733-5.
96. Horrace, W. C. and Schmidt, P. 1996. ‘Confidence statements for efficiency estimates from stochastic frontier models’. Journal of Productivity Analysis 7: 257-82.
97. Hough, J. R. 1985. ‘A note on economies of scale in schools’. Applied Economics 17: 143-4.
98. Iezzoni, L. I. 2003. Risk Adjustment for Measuring Healthcare Outcomes, 3rd edn. Baltimore: Health Administration Press.
99. Intriligator, M. D. 1978. Econometric Models, Techniques and Applications. Englewood Cliffs, N. J.: Prentice-Hall.
100. Jensen, U. 2000. ‘Is it efficient to analyse efficiency rankings?’ Empirical Economics 25: 189-208.
101. Jondrow, J., Lovell, C. A. K., Materov, I. S. and Schmidt, P. 1982. ‘On the estimation of technical inefficiency in the stochastic frontier production function model.’ Journal of Econometrics 19: 233-8.
102. Koopmans, T. C. 1951. ‘An analysis of production as an efficient combination of activities’, in Koopmans, T. C. (ed.), Activity Analysis of Production and Allocation. Monograph No. 13, New York:Wiley.
103. Kooreman, P. 1994. ‘Nursing home care in The Netherlands: a nonparametric efficiency analysis’. Journal of Health Economics 13: 301-16.
104. Kuh, E. and Meyer, J. R. 1955. ‘Correlation and regression estimates when the data are ratios’. Econometrica 23: 400-16.
105. Kumbhakar, S. C. 1990. ‘Production frontiers, panel data, and time-varying technical efficiency’. Journal of Econometrics 46: 201-11.
106. Kumbhakar, S. C. and Lovell, C. A. K. 2000. Stochastic Frontier Analysis. Cambridge: Cambridge University Press.
107. Laspeyres, E. 1871. ‘Die Berechnug einer mittlerenWaaren-preissteigerung’. Jahrbücherfür Nationalökonomie und Statistik 16: 296-314.
108. Lee, Y. H. and Schmidt, P. 1993. ‘A production function model with flexible temporal variation in technical efficiency’, in Fried, H. O., Lovell, C. A. K. and Schmidt, S. S. (eds.), The Measurement of Productive Efficiency. New York: Oxford University Press, pp. 237-55.
109. Lewis, H. F. and Sexton, T. R. 2004. ‘Data envelopment analysis with reverse inputs and outputs’. Journal of Productivity Analysis 21: 113-32.
110. Linna, M. 1998. ‘Measuring hospital cost efficiency with panel data models’. Health Economics 7: 415-27.
111. Linna, M. and Häkkinen, U. 1998. ‘Determinants of cost efficiency of Finnish hospitals: a comparison of DEA and SFA’. Systems Analysis Laboratory Research Report A78, Helsinki University of Technology.
112. Löthgren, M. 1998. ‘How to bootstrap DEA estimators: a Monte Carlo comparison’. Working Paper Series in Economics and Finance 223, Stockholm School of Economics. 2000. ‘Specification and estimation of stochastic multiple-output production and technical inefficiency’. Applied Economics 32: 1533-40.
113. Lovell, C. A. K. 2000. ‘Measuring efficiency in the public sector’, in Blank, J. L. T. (ed.), Public Provision and Performance: Contributions from Efficiency and Productivity Measurement. The Hague: North-Holland.
114. Lozano-Vivas, A., Pastor, J. T. and Pastor, J. M. 2002. ‘An efficiency comparison of European banking systems operating under different environmental conditions’. Journal of Productivity Analysis 18: 59-77.
115. Maddala, G. S. 1988. Introduction to Econometrics. London: Collier Macmillan.
116. Malmquist, S. 1953. ‘Index numbers and indifference surfaces’. Trabajos de Estatistica 4: 209-42.
117. Maniadakis, N. and Thanassoulis, E. 2000. ‘Assessing productivity changes in UK hospitals reflecting technology and input prices’. Applied Economics 32: 1575-89.
118. Maniadakis, N., Hollingsworth, B. and Thanassoulis, E. 1999. ‘The impact of the internal market on hospital efficiency, productivity and service quality’. Health Care Management Science 2: 75-85.
119. Martin, S. and Smith, P. C. 2003. ‘Using panel methods to model waiting times for NHS surgery’. Journal of the Royal Statistical Society, Series A, 166: 369-87.
120. Maniadakis, N., Hollingsworth, B. and Thanassoulis, E. 2005. ‘Multiple public service performance indicators: towards an integrated statistical approach’. Journal of Public Administration, Research and Theory 15: 599-613.
121. McKinnish, T. G. 2000. ‘Model sensitivity in panel data analysis: some caveats about the interpretation of fixed effects and differences estimators’. Unpublished manuscript, Department of Economics, University of Colorado, Boulder. Available at http://spot.colorado.edu/~mckinnis/fe053100.pdf (accessed February 2006).
122. Mooney, C. Z. and Duval, R. D. 1993. Bootstrapping: A Nonparametric Approach to Statistical Inference. London: Sage Publications.
123. Newhouse, J. P. 1994. ‘Frontier analysis: how useful a tool for health economics?’ Journal of Health Economics 13: 317-22.
124. Nishimizu, M. and Page, J. M. 1982. ‘Total factor productivity growth, technical progress and technical efficiency change: dimensions of productivity change in Yugoslavia, 1965-78’. Economic Journal 92: 920-36.
125. Nunamaker, T. R. 1985. ‘Using data envelopment analysis to measure the efficiency of non-profit organizations: a critical evaluation’. Management and Decision Economics 6: 50-8.
126. Office of Water Services 1999. Future Water and Sewerage Charges 2000-05: Draft Determination. London: OFWAT.
127. Ozcan, Y. A. and Cotter, J. J. 1994. ‘An assessment of efficiency of area agencies on aging in Virginia through data envelopment analysis’. The Gerontologist 34: 363-70.
128. Paasche, H. 1874. ‘Ueber die Presentwicklung der letzen Jahre nach den Hamburger Börsennotirungen’. Jahrbücher für Nationalökonomie und Statistik 23: 168-78.
129. Parkin, D. and Hollingsworth, B. 1997. ‘Measuring production efficiency of acute hospitals in Scotland, 1991-94: validity issues in data envelopment analysis’. Applied Economics 29: 1425-33.
130. Paul, C. J. M., Johnston, W. E. and Frengley, G. A. G. 2000. ‘Efficiency in New Zealand sheep and beef farming: the impacts of regulatory reform’. Review of Economics and Statistics 82: 325-37.
131. Pedraja-Chaparro, F, Salinas-Jiménez, J. and Smith, P. C. 1997. ‘On the role of weight restrictions in data envelopment analysis’. Journal of Productivity Analysis 8: 215-30.
132. Pedraja-Chaparro, F, Salinas-Jiménez, J. and Smith, P. C. 1999. ‘On the quality of the data envelopment analysis model’. Journal of the Operational Research Society 50: 636-44.
133. Pindyck, R. S. and Rubinfeld, D. L. 1991. Econometric Models and Economic Forecasts. New York: McGraw-Hill.
134. Pitt, M. M. and Lee, L. F. 1981. ‘The measurement and sources of technical efficiency in the Indonesian weaving industry’. Journal of Development Economics 9: 43-64.
135. Polachek, S. and Yoon, B. 1996. ‘Panel estimates of a two-tiered earnings frontier’. Journal of Applied Econometrics 11: 169-78.
136. Puig-Junoy, J 1998a. ‘Measuring health production performance in the OECD’. Applied Economics Letters 5: 255-9.
137. Puig-Junoy, J 1998b. ‘Technical efficiency in the clinical management of critically ill patients’. Health Economics 7: 263-77.
138. Resti, A. 1997. ‘Evaluating the cost-efficiency of the Italian banking system: what can be learned from the joint application of parametric and non-parametric techniques’. Journal of Banking and Finance 21: 221-50.
139. Rice, N. and Jones, A. 1997. ‘Multilevel models and health economics’. Health Economics 6: 561-75.
140. Roll, Y., Cook, W. and Golany, B. 1991. ‘Controlling factor weights in data envelopment analysis’. IEEE Transactions 23: 2-9.
141. Rosko, M. D. 2001. ‘Cost efficiency of US hospitals: a stochastic frontier approach’. Health Economics 10: 539-51.
142. Ryan, M., Scott, D. A., Reeves, C., Bate, A., van Teijlingen, E., Russell, E. M., Napper, M. and Robb, C. M. 2001. ‘Eliciting public preferences for healthcare: a systematic review of techniques’. Health Technology Assessment 5(5): 1-4.
143. Salinas-Jiménez, J., Pedraja-Chaparro, F. and Smith, P. C. 2003. ‘Evaluating the introduction of a quasi-market in community care: assessment of a Malmquist index approach’. Socio-Economic Planning Sciences 37: 1-13.
144. Scheel, H. 2001. ‘Undesirable outputs in efficiency valuations’. European Journal of Operational Research 132: 400-10.
145. Schleifer, A. 1985. ‘A theory of yardstick competition’. Rand Journal of Economics 16: 319-27.
146. Schmidt, P. 1985. ‘Frontier production functions’. Econometric Reviews 4: 289-328.
147. Schmidt, P. and Lin, T. 1984. ‘Simple tests of alternative specifications in stochastic frontier models’. Journal of Econometrics 24: 349-61.
148. Schmidt, P. and Lovell, C. A. K. 1980. ‘Estimating stochastic production and cost frontiers when technical and allocative inefficiency are correlated’. Journal of Econometrics 13: 83-100.
149. Schmidt, P. and Sickles, R. C. 1984. ‘Production frontiers and panel data’. Journal of Business and Economic Studies 2: 299-326.
150. Shephard, R. W. 1970. Theory of Cost and Production Functions. Princeton: Princeton University Press.
151. Simar, L. and Wilson, P. W. 2004. ‘Estimation and inference in two-stage, semi-parametric models of production processes’. Discussion Paper. 0307, Institut de Statistique, Université Catholique de Louvain.
152. Skinner, J. 1994. ‘What do stochastic frontier cost functions tell us about inefficiency?’ Journal of Health Economics 13: 323-8.
153. Smith, P. C. 1997. ‘Model misspecification in data envelopment analysis’. Annals of Operations Research 73: 233-52.
154. Smith, P. C. 2002. Measuring Up: Improving Health System Performance in OECD Countries. Paris: OECD.
155. Smith, P. C. 2003. ‘Formula funding of public services: an economic analysis’. Oxford Review of Economic Policy 19: 301-22.
156. Smith, P. C. and Street, A. 2005. ‘Measuring the efficiency of public services: the limits of analysis’. Journal of the Royal Statistical Society, Series A, 168: 401-17.
157. Smith, P. C., Rice, N. and Carr-Hill, R. 2001. ‘Capitation funding in the public sector’. Journal of the Royal Statistical Society, Series A, 164: 217-41.
158. Smith, V. K. 1981. ‘Elasticities of substitution for a regulated cost function’. Economic Letters 7: 215-19.
159. Söderlund, N. and van der Merwe, R. 1999. ‘ Hospital benchmarking analysis and the derivation of cost indices’. Discussion Paper 178, Centre for Health Economics, University of York.
160. Söderlund, N., Milne, R., Gray, A. and Raftery, J. 1995. ‘Differences in hospital case mix, and the relationship between case mix and hospital costs’. Journal of Public Health and Medicine 17: 25-32.
161. Sommersguter-Reichmann, M 2000. ‘The impact of the Austrian hospital financing reform on hospital productivity: empirical evidence on efficiency and technology changes using a non-parametric inputbased Malmquist approach’. Health Care Management Science 3: 309-21.
162. Stevenson, R. F. 1980. ‘Likelihood functions for generalized stochastic frontier estimation’. Journal of Econometrics 13: 57-66.
163. Stone, M. 2002. ‘How not to measure the efficiency of public services (and how one might)’. Journal of the Royal Statistical Society, Series A, 165: 405-34.
164. Street, A. 2003. ‘How much confidence should we place in efficiency estimates?’ Health Economics 12: 895-907.
165. Street, A. and Dawson, D. 2002. ‘Costing hospital activity: the experience with healthcare resource groups in England’. European Journal of Health Economics 3: 3-9.
166. Tambour, M. 1997. ‘The impact of health care policy initiatives on productivity’. Health Economics 6: 57-70.
167. Thanassoulis, E. 1993. ‘A comparison of regression analysis and data envelopment analysis as alternative methods for performance assessments’. Journal of the Operational Research Society 44: 1129-44.
168. Thanassoulis, E. 2001. Introduction to the Theory and Application of Data Envelopment Analysis: A Foundation Text with Integrated Software. Dordrecht: Kluwer Academic Publishers.
169. Thompson, R. G., Langemeier, L. N., Lee, C. T. and Thrall, R. M. 1990. ‘The role of multiplier bounds in efficiency analysis with application to Kansas farming’. Journal of Econometrics 46: 93-108.
170. Timmer, C. P. 1971. ‘Using a probabilistic frontier production function to measure technical efficiency’. Journal of Political Economy 79: 776-94.
171. Tofallis, C. 2001. ‘Combining two approaches to efficiency assessment’. Journal of the Operational Research Society 52: 1225-31.
172. Torgerson, A. M., Forsund, F. R. and Kittelesen, S. A. C. 1996. ‘Slackadjusted efficiency measures and ranking of efficient units’. Journal of Productivity Analysis 7: 379-98.
173. Törnqvist, L. 1936. ‘The Bank of Finland’s consumption price index’. Bank of Finland Monthly Bulletin 10: 1-8.
174. Üstün, T. B., Chatterji, S., Mechbal, A., Murray, C. J. L. and WHS Collaborating Groups. 2003. ‘TheWorld Health Surveys’, in Murray, C. J. L. and Evans, D. B. (eds.), Health Systems Performance Assessment: Debates, Methods and Empiricism. Geneva:World Health Organization.
175. Varian, H. R. 1978. Microeconomic Analysis. New York: W. W. Norton.
176. Vitaliano, D. F. 1987. ‘On the estimation of hospital cost functions’. Journal of Health Economics 6: 305-18.
177. Wagstaff, A. 1989. ‘Estimating efficiency in the hospital sector: a comparison of three statistical cost frontier models’. Applied Economics 21: 659-72.
178. Ware, J. E. and Sherbourne, C. D. 1992. ‘The MOS 36-item Short Form Health Status Survey (SF-36)’. Medical Care 30: 473-83.
179. White, H. A. 1980. ‘A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity’. Econometrica 84: 817-30.
180. Williams, A. 2001. ‘Science or marketing at WHO? A commentary on “World Health 2000”’. Health Economics 10: 93-100.
181. Williamson, O. E. 1973. ‘Markets and hierarchies: some elementary considerations’. American Economic Association 63: 316-34.
182. Wong, Y. H. B. and Beasley, J. E. 1990. ‘Restricting weight flexibility in data envelopment analysis’. Journal of the Operational Research Society 41: 829-35.
183. World Health Organization 2000. World Health Report 2000. Geneva: WHO.
184. World Health Organization 2001. Report of the Scientific Peer Review Group on Health Systems Performance Assessment. Geneva: WHO.
185. Yang, M., Goldstein, H., Browne, W. and Woodhouse, G. 2002. ‘Multivariate multilevel analyses of examination results’. Journal of the Royal Statistical Society, Series A, 165: 137-46.
186. Zellner, A. 1962. ‘An efficient method of estimating seemingly unrelated regressions and tests of aggregation bias’. Journal of the American Statistical Association 57: 500-79.
187. Zhao, Y., Guthridge, S., Magnus, A. and Vos, T. 2004. ‘The burden of disease and injury in Aboriginal and non-Aboriginal populations in the Northern Territory’. Medical Journal of Australia 180: 498-502.
188. Zuckerman, S., Hadley, J. and Lezzoni, L. I. 1994. ‘Measuring hospital efficiency with frontier cost functions’. Journal of Health Economics 13: 255-80.