Evaluation of productivity in Iranian pharmaceutical companies: A DEA-based Malmquist approach and panel data analysis
Mehdi Varmaghani1, Amir Hashemi Meshkini1, Farshad Farzadfar2, Mehdi Yousefi3, Saeed Yaghoubifard4, Vida Varahrami5, Ehsan Rezaei Darzi2, Majid Anabi4, Abbas Kebriaeezadeh4, Hedieh-Sadat Zekri6
1 Department of Pharmacoeconomics and Pharmaceutical Administration; Non communicable Disease Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
2 Non-communicable Disease Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
3 Department of Health and Management, Mashhad University of Medical Sciences, Mashhad, Iran
4 Department of Pharmacoeconomics and Pharmaceutical Administration, Tehran University of Medical Sciences, Tehran, Iran
5 Department of Economics, Shahid Beheshti University, Tehran, Iran
6 Faculty of Economics, Allameh-Tabatabaiee University of Human Sciences, Tehran, Iran
Department of Pharmacoeconomics and Pharmaceutical Administration, Tehran University of Medical Sciences, Tehran
Source of Support: None, Conflict of Interest: None
Objective: In this study, we aimed to assess comparative productivity of 21 pharmaceutical companies in Iran during 2000-2013.
Methods: To evaluate the productivity trend of pharmaceutical companies in Iran, we used data envelopment analysis-based Malmquist index. "Total assets" and "capital stock" as inputs and "net sales" and "net profit" as outputs extracted from Tehran stock exchange, were selected to be included in the analysis. This method provides the possibility for analyzing the performance of each company in term of productivity changes over time. We also used an estimation generalized least square panel data model to identify the factors that might affect productivity of pharmaceutical companies in Iran using EViews 7 and Deep 2.1 software.
Findings: The mean total productivity during all years of the study was 0.9829, which indicates the improvement in their overall productivity. The results, over the 13-year period, indicated that the range of productivity changes in pharmaceutical companies, that were included in this study, was between 0.884 and 1.098. Panel data model indicated that age of company could positively (t = 4.765978, P < 0.001) and being located in cities other than Tehran (the capital) could negatively (t = −5.369549, P < 0.001) affect the productivity of pharmaceutical companies. The analysis showed the new policy (brand-generic scheme) and also the type of ownership did not have a significant effect on the productivity of pharmaceutical companies.
Conclusion: In this study, pharmaceutical productivity trends were fluctuated that could be due to the sub-optimal attention of policy makers and managers of pharmaceutical companies toward long-term strategic planning, focusing on productivity improvement.