Measuring the efficiency of large pharmaceutical companies: an industry analysis

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.

Keywords: Business performance; DEA; Market for technology; New chemical entities; Non-parametric efficiency; Pharmaceutical laboratories; R&D.

MeSH terms

  • Biomedical Research / statistics & numerical data
  • Drug Approval / statistics & numerical data
  • Drug Industry / economics
  • Drug Industry / organization & administration*
  • Efficiency, Organizational / statistics & numerical data*
  • Europe
  • Humans
  • Models, Economic
  • United States