产品专利法的出台是否影响了印度制药行业的生产力?

IF 0.8 Q4 DEVELOPMENT STUDIES
Varun Mahajan
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引用次数: 6

摘要

本文的目的是使用非参数数据包络分析实证研究产品专利制度对印度制药公司所有权、研发、规模和产品等不同类别生产率的影响。,本研究应用Ray和Desli的Malmquist生产率指数及其分解来衡量2000-2001年至2014-2015年间141家印度制药公司的全要素生产率(TFP)变化、纯技术效率变化、规模效率变化和可变规模回报率(VRS)技术假设下的技术变化。,研究发现,产品专利制度对生产率的影响微乎其微。技术变革对生产力的增长起到了积极作用,而技术效率的变革则体现了明智地利用资源来提高绩效。研究结果表明,与非研发型企业相比,研发密集型企业在TFP中表现出更好的稳定性。然而,格兰杰因果关系在研发和生产力之间没有发现任何关系。生产力更直接地受到固定资产投资的影响,而不是研发投资的影响。研发主要关注品牌/普通通用产品市场的增值。在所有权方面,发现外国私营公司在TFP方面取得了进展,而其他公司则出现了边际倒退,这可能归因于外国公司除了拥有专有技术外,还拥有卓越的营销和管理技能。与专利前制度相比,新制度中的小型和大型公司都表现出了正增长。这些小公司之所以能够与大公司竞争,是因为它们通过提高获得更好外国技术的机会,提高了技术基础。所有企业的全要素生产率增长都可以归因于技术的进步和高资本产出率方面的创新。此外,本文试图通过面板随机效应回归来确定生产率的决定因素,发现出口强度、年龄和新专利制度与生产率存在负相关和显著关系,而研发、所有权、规模和资本进口等其他变量则不显著。最后,敏感性分析结果证实了所选变量的有效性。,研究结果表明,印度制药公司需要通过提高管理效率和规模效率来大幅提高TFP。印度制药业(IPI)需要提高整个网络的生产力,并通过卓越运营和数字化举措推动整个支出基础的卓越成本举措。本文的结果可用于制定未来增长和提高IPI生产力的政策。,本文旨在对现有文献做出几点新的贡献。大多数研究论文只分析了整个行业的TFP,需要详细的企业分析来捕捉单位层面的真实影响。这项研究分析了所有权、研发、规模和产品以及生产力决定因素等不同类别的影响。这项研究使用了更宽的时间段和更大的面板数据来预测更好的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Is productivity of Indian pharmaceutical industry affected with the introduction of product patent act?
The purpose of this paper is to empirically study the impact of product patent regime on the productivity of different categories such as ownership, R&D, size and product-wise of Indian pharmaceutical firms using non-parametric data envelopment analysis.,The present study has applied Ray and Desli’s Malmquist productivity index and its decomposition to measure total factor productivity (TFP) change, pure technical efficiency change, scale efficiency change and technical change under variable returns to scale (VRS) technology assumption for 141 Indian pharmaceutical firms during 2000-2001 to 2014-2015.,The study found the negligible impact of product patent regime on productivity. The technological change has played a positive role in the growth of productivity, whereas technical efficiency change depicts the judicious utilization of resources for improving performance. From the results, it is found that R&D intensive firms depict better stability in the TFP than the non-R&D firms. However, Granger causality between R&D and productivity found no relationship. Productivity is more directly affected by investment in fixed assets rather than in R&D, which focusses on incremental value additions in a largely branded/plain generic product market. In case of ownership, private foreign firms found to have registered progress in TFP while others have recorded marginal regress, which probably could be attributed to the superior marketing and management skills of the foreign firms, besides possessing proprietary technology. Both small and large firms have shown positive growth in the new regime as compared to the pre-patent regime. These small firms are able to compete with large firms because of their up-gradation of the technological base by improving access to better foreign technology. TFP growth for all the firms can be attributed to improvement in technology, and innovation in terms of high capital-output ratio. Further, the paper tried to identify the determinants of productivity from panel random effect regression, and it is found that export intensity, age and the new patent regime have negative and significant relationship with productivity, whereas other variables such as R&D, ownership, size and capital imports are insignificant. In the end, the results of sensitivity analysis have confirmed the validity of the selected variables.,The results suggest that Indian pharmaceutical firms need substantive improvement in TFP by improving managerial and scale efficiency. Indian pharmaceutical industry (IPI) needs to improve productivity across the network and drive cost excellence initiatives across the spend base through operational excellence and digital initiatives. The results of this paper can be applied in framing policies for future growth and improvement in the productivity of IPI.,The paper aims to make several new contributions to the existing literature. Most of the research papers only analysed TFP of the industry as a whole and detailed firm-wise analysis is needed to capture the true impact at a unit level. This study has analysed the impact of different categories such as ownership, R&D, size and product-wise, and determinants of productivity. The study has used a broader time period and larger panel data to predict the better picture.
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CiteScore
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