Suppr超能文献

衡量大型制药公司的效率:行业分析。

Measuring the efficiency of large pharmaceutical companies: an industry analysis.

作者信息

Gascón Fernando, Lozano Jesús, Ponte Borja, de la Fuente David

机构信息

Faculty of Economics and Business, Department of Business Administration, University of Oviedo, Campus del Cristo s/n, 33006, Oviedo, Spain.

Polytechnic School of Engineering, Department of Business Administration, University of Oviedo, Campus de Viesques s/n, 33204, Gijón, Spain.

出版信息

Eur J Health Econ. 2017 Jun;18(5):587-608. doi: 10.1007/s10198-016-0812-3. Epub 2016 Jun 25.

Abstract

This paper evaluates the relative efficiency of a sample of 37 large pharmaceutical laboratories in the period 2008-2013 using a data envelopment analysis (DEA) approach. We describe in detail the procedure followed to select and construct relevant inputs and outputs that characterize the production and innovation activity of these pharmaceutical firms. Models are estimated with financial information from Datastream, including R&D investment, and the number of new drugs authorized by the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) considering the time effect. The relative performances of these firms-taking into consideration the strategic importance of R&D-suggest that the pharmaceutical industry is a highly competitive sector given that there are many laboratories at the efficient frontier and many inefficient laboratories close to this border. Additionally, we use data from S&P Capital IQ to analyze 2071 financial transactions announced by our sample of laboratories as an alternative way to gain access to new drugs, and we link these transactions with R&D investment and DEA efficiency. We find that efficient laboratories make on average more financial transactions, and the relative size of each transaction is larger. However, pharmaceutical companies that simultaneously are more efficient and invest more internally in R&D announce smaller transactions relative to total assets.

摘要

本文运用数据包络分析(DEA)方法,评估了2008年至2013年期间37家大型制药实验室样本的相对效率。我们详细描述了为选择和构建相关投入与产出所遵循的程序,这些投入与产出表征了这些制药公司的生产和创新活动。利用来自数据流(Datastream)的财务信息,包括研发投资,以及考虑到时间效应的欧洲药品管理局(EMA)和美国食品药品监督管理局(FDA)批准的新药数量,对模型进行了估计。考虑到研发的战略重要性,这些公司的相对表现表明,制药行业是一个竞争激烈的行业,因为在有效前沿有许多实验室,且有许多低效实验室接近这一边界。此外,我们使用标准普尔资本智商(S&P Capital IQ)的数据,分析了我们样本中的实验室宣布的2071笔金融交易,作为获取新药的另一种方式,并将这些交易与研发投资和DEA效率联系起来。我们发现,高效实验室平均进行更多的金融交易,且每笔交易的相对规模更大。然而,同时效率更高且在内部研发投入更多的制药公司,相对于总资产而言,宣布的交易规模更小。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验