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Non-Parametric Analysis of Efficiency: An Application to the Pharmaceutical Industry

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  • Ricardo F. Díaz

    (Department of Economic Analysis, Facultad CC Económicas y Empresariales, UNED, Senda del Rey 11, 28040 Madrid, Spain)

  • Blanca Sanchez-Robles

    (Department of Economic Analysis, Facultad CC Económicas y Empresariales, UNED, Senda del Rey 11, 28040 Madrid, Spain)

Abstract

Increases in the cost of research, specialization and reductions in public expenditure in health are changing the economic environment for the pharmaceutical industry. Gains in productivity and efficiency are increasingly important in order for firms to succeed in this environment. We analyze empirically the performance of efficiency in the pharmaceutical industry over the period 2010–2018. We work with microdata from a large sample of European firms of different characteristics regarding size, main activity, country of origin and other idiosyncratic features. We compute efficiency scores for the firms in the sample on a yearly basis by means of non-parametric data envelopment analysis (DEA) techniques. Basic results show a moderate average level of efficiency for the firms which encompass the sample. Efficiency is higher for companies which engage in manufacturing and distribution than for firms focusing on research and development (R&D) activities. Large firms display higher levels of efficiency than medium-size and small firms. Our estimates point to a decreasing pattern of average efficiency over the years 2010–2018. Furthermore, we explore the potential correlation of efficiency with particular aspects of the firms’ performance. Profit margins and financial solvency are positively correlated with efficiency, whereas employee costs display a negative correlation. Institutional aspects of the countries of origin also influence efficiency levels.

Suggested Citation

  • Ricardo F. Díaz & Blanca Sanchez-Robles, 2020. "Non-Parametric Analysis of Efficiency: An Application to the Pharmaceutical Industry," Mathematics, MDPI, vol. 8(9), pages 1-27, September.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:9:p:1522-:d:409804
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    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. James H. Stock & Mark W. Watson, 2008. "Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression," Econometrica, Econometric Society, vol. 76(1), pages 155-174, January.
    3. Khezrimotlagh, Dariush & Zhu, Joe & Cook, Wade D. & Toloo, Mehdi, 2019. "Data envelopment analysis and big data," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1047-1054.
    4. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "DEA radial measurement for environmental assessment: A comparative study between Japanese chemical and pharmaceutical firms," Applied Energy, Elsevier, vol. 115(C), pages 502-513.
    5. Massimo Filippini & Lester C. Hunt, 2013. "'Underlying Energy Efficiency' in the US," CER-ETH Economics working paper series 13/181, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    6. Casper, Steven & Matraves, Catherine, 2003. "Institutional frameworks and innovation in the German and UK pharmaceutical industry," Research Policy, Elsevier, vol. 32(10), pages 1865-1879, December.
    7. Ching-Fu Chen & Kwok Tong Soo, 2010. "Some university students are more equal than others: Efficiency evidence from England," Economics Bulletin, AccessEcon, vol. 30(4), pages 2697-2708.
    8. Danzon, Patricia M. & Nicholson, Sean & Pereira, Nuno Sousa, 2005. "Productivity in pharmaceutical-biotechnology R&D: the role of experience and alliances," Journal of Health Economics, Elsevier, vol. 24(2), pages 317-339, March.
    9. Emrouznejad, Ali & Yang, Guo-liang, 2018. "A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 4-8.
    10. Hashimoto, Akihiro & Haneda, Shoko, 2008. "Measuring the change in R&D efficiency of the Japanese pharmaceutical industry," Research Policy, Elsevier, vol. 37(10), pages 1829-1836, December.
    11. Kuosmanen, Timo & Saastamoinen, Antti & Sipiläinen, Timo, 2013. "What is the best practice for benchmark regulation of electricity distribution? Comparison of DEA, SFA and StoNED methods," Energy Policy, Elsevier, vol. 61(C), pages 740-750.
    12. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    13. Marchetti, Dalmo & Wanke, Peter F., 2019. "Efficiency in rail transport: Evaluation of the main drivers through meta-analysis with resampling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 83-100.
    14. Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2016. "International Data on Measuring Management Practices," American Economic Review, American Economic Association, vol. 106(5), pages 152-156, May.
    15. William Greene, 2004. "The behaviour of the maximum likelihood estimator of limited dependent variable models in the presence of fixed effects," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 98-119, June.
    16. 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.
    17. Fall, François & Akim, Al-mouksit & Wassongma, Harouna, 2018. "DEA and SFA research on the efficiency of microfinance institutions: A meta-analysis," World Development, Elsevier, vol. 107(C), pages 176-188.
    18. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    19. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    20. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    21. Cherchye, Laurens & Rock, Bram De & Walheer, Barnabé, 2015. "Multi-output efficiency with good and bad outputs," European Journal of Operational Research, Elsevier, vol. 240(3), pages 872-881.
    22. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    23. Sebastián Lozano & Ester Gutiérrez, 2014. "A slacks-based network DEA efficiency analysis of European airlines," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(7), pages 623-637, October.
    24. Rebecca Henderson & Iain Cockburn, 1993. "Scale, Scope and Spillovers: The Determinants of Research Productivity in the Pharmaceutical Industry," NBER Working Papers 4466, National Bureau of Economic Research, Inc.
    25. Bengoa, Marta & Sanchez-Robles, Blanca, 2005. "Policy shocks as a source of endogenous growth," Journal of Policy Modeling, Elsevier, vol. 27(2), pages 249-261, March.
    26. 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.
    27. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2015. "A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand," Energy Economics, Elsevier, vol. 49(C), pages 599-609.
    28. Rajiv D. Banker & Ram Natarajan, 2008. "Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis," Operations Research, INFORMS, vol. 56(1), pages 48-58, February.
    29. Roland Bénabou & Jean Tirole, 2016. "Mindful Economics: The Production, Consumption, and Value of Beliefs," Journal of Economic Perspectives, American Economic Association, vol. 30(3), pages 141-164, Summer.
    30. McDonald, John, 2009. "Using least squares and tobit in second stage DEA efficiency analyses," European Journal of Operational Research, Elsevier, vol. 197(2), pages 792-798, September.
    31. Henderson, Rebecca. & Cockburn, Iain., 1993. "Scale, scope and spillovers : the determinants of research productivity in ethical drug discovery," Working papers 3629-93., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    32. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    33. Taewoo You & Xiaoying Chen & Mark Holder, 2010. "Efficiency and its determinants in pharmaceutical industries: ownership, R&D and scale economy," Applied Economics, Taylor & Francis Journals, vol. 42(17), pages 2217-2241.
    34. Hoff, Ayoe, 2007. "Second stage DEA: Comparison of approaches for modelling the DEA score," European Journal of Operational Research, Elsevier, vol. 181(1), pages 425-435, August.
    35. Mainak Mazumdar & Meenakshi Rajeev, 2009. "Output and Input Efficiency of Manufacturing Firms in India: A Case of the Indian Pharmaceutical Sector," Working Papers 219, Institute for Social and Economic Change, Bangalore.
    36. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    37. Cockburn, Iain M. & Henderson, Rebecca M., 2001. "Scale and scope in drug development: unpacking the advantages of size in pharmaceutical research," Journal of Health Economics, Elsevier, vol. 20(6), pages 1033-1057, November.
    38. Odeck, James & Bråthen, Svein, 2012. "A meta-analysis of DEA and SFA studies of the technical efficiency of seaports: A comparison of fixed and random-effects regression models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1574-1585.
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