Saving plays an important role in economics. Private Pension System (PPS) helps individuals make savings and contribute to the nation’s economy. Therefore, it is important to know the performance of Private Pension Companies (PPCs) that manage the pension funds. Data Envelopment Analysis (DEA) is one of the useful nonparametric techniques to measure the relative efficiency of Decisions Making Units (DMUs) for a specific time or process. In this study, relative efficiency scores of PPCs are investigated for a time interval with Dynamic DEA and compared with the traditional DEA. Inputs of the model are considered as the number of workers, total assets; and the outputs of the model are the number of contracts, total contribution and the market share of each PPC. Also, to ensure the dynamic procedure, Shareholders’ Equity is used as a quasi-fixed input data to link consecutive periods in the time interval. Our results demonstrate that the efficiency score can be improved by considering the effects of the inter-relations of the consecutive periods. The implications arising from the results of the study are important for the companies’ policies.

中文翻译：

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使用动态数据包络分析的私人养老金公司的效率

储蓄在经济学中起着重要作用。私人养老金系统（PPS）可帮助个人储蓄并为国家经济做出贡献。因此，了解管理养老金的私人养老金公司（PPC）的绩效非常重要。数据包络分析（DEA）是一种有用的非参数技术，用于测量特定时间或过程中决策部门（DMU）的相对效率。在这项研究中，使用动态DEA研究了一段时间内PPC的相对效率得分，并将其与传统DEA进行了比较。该模型的输入被认为是工人人数，总资产；模型的输出是每个PPC的合同数量，总贡献和市场份额。另外，为了确保动态程序，股东权益用作准固定输入数据，以链接时间间隔中的连续期间。我们的结果表明，通过考虑连续期之间相互关系的影响可以提高效率得分。研究结果产生的含义对于公司的政策很重要。