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KMID : 1170320200260020025
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Korean Journal of Health Economics and Policy
2020 Volume.26 No. 2 p.25 ~ p.57
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A Cross-National Comparative Study on the Innovation Efficiency of the Biopharmaceutical Industry
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Park Ha-Young
Cha Min-Kyeong
Lee Hye-Rin
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Abstract
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Both emerging and advanced economies have been eager to develop the biopharmaceutical industry as their future economic growth engines. The objective of this study is to draw policy implications for countries who are aspired to develop the biopharmaceutical industry through analyses and comparison of national innovation efficiencies in the new drug development. We collected biopharmaceutical research and development (R&D) input (expenditures and number of researchers) and output (publication, patent, clinical trials, and new drugs) data between 2001 and 2018 for 20 OECD countries, and analyzed them using the two-stage network data envelopment analysis (DEA) with the meta-frontier framework. The major findings of this study were i) traditional industry leaders achieved high levels of innovation performance, although there were distinct groups of countries regarding their innovation efficiency characteristics, ii) the innovation gap cited by previous studies seemed to be caused by the decrease in development efficiency rather than research efficiency, and the prevalence of the problem was not universal, and iii) extremely low development efficiency was hindering the Korean biopharmaceutical industry from harvesting the final innovation outcome, despite its steady improvement in research and development efficiencies during the study period. Building the development capability through open innovation and manpower acquisition seemed to be the most eminent policy priority at this stage for Korea to succeed in its efforts to become one of leading nations in this industry. This study contributed in providing policy makers with insights in formulating the biopharmaceutical industry policy despite several limitations due to data and methods.
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KEYWORD
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Biopharmaceutical industry, R&D efficiency, innovation productivity, two-stage network DEA(Data Envelopment Analysis), meta-frontier analysis
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