Iain M. Cockburn

Scale, Scope, and Spillovers: The Determinants of Research Productivity in Drug Discovery

We examine the relationship between firm size and research productivity in the pharmaceutical industry. Using detailed internal firm data, we find that larger research efforts are more productive, not only because they enjoy economies of scale, but also because they realize economies of scope by sustaining diverse portfolios of research projects that capture internal and external knowledge spillovers. In pharmaceuticals, economies of scope in research are important in shaping the boundaries of the firm, and it may be worth tolerating the static efficiency loss attributable to the market power of large firms in exchange for their superior innovative performance.

The Economics of Reproducibility in Preclinical Research

Low reproducibility rates within life science research undermine cumulative knowledge production and contribute to both delays and costs of therapeutic drug development. An analysis of past studies indicates that the cumulative (total) prevalence of irreproducible preclinical research exceeds 50%, resulting in approximately US

Characteristics of Demand for Pharmaceutical Products: An Examination of Four Cephalosporins

28,000,000,000 (US

Information Technology and Intangible Output: The Impact of IT Investment on Innovation Productivity

28B)/year spent on preclinical research that is not reproducible—in the United States alone. We outline a framework for solutions and a plan for long-term improvements in reproducibility rates that will help to accelerate the discovery of life-saving therapies and cures.

Mixed Poisson regression models with covariate dependent rates.

We model demand for four cephalosporins and compute own- and cross-price elasticities between branded and generic versions of the four drugs. We model demand as a multistage budgeting problem, and we argue that such a model is appropriate to the multistage nature of the purchase of pharmaceutical products, in particular the prescribing and dispensing stages. We find quite high elasticities between generic substitutes and also significant elasticities between some therapeutic substitutes.

New Pills for Poor People? Empirical Evidence after GATT

Prior research concerning IT business value has established a link between firm-level IT investment and tangible returns such as output productivity. Research also suggests that IT is vital to intermediate processes such as those that produce intangible output. Among these, the use of IT in innovation and knowledge creation processes is perhaps the most critical to a firms long-term success. However, little is known about the relationship between IT, knowledge creation, and innovation output. In this study, we contribute to the literature by comprehensively examining the contribution of IT to innovation production across multiple contexts using a quality-based measure of innovation output. Analyzing annual information from 1987 to 1997 for a panel of large U.S. manufacturing firms, we find that a 10% increase in IT input is associated with a 1.7% increase in innovation output for a given level of innovation-related spending. This relationship between IT, research and development (R&D), and innovation production is robust across multiple econometric methodologies and is found to be particularly strong in the mid to late 1990s, a period of rapid technological innovation. Our results also demonstrate the importance of IT in creating value at an intermediate stage of production, in this case, through improved innovation productivity. However, R&D and its related intangible factors (skill, knowledge, etc.) appear to play a more crucial role in the creation of breakthrough innovations.

Analysis of Patent Data—A Mixed-Poisson-Regression-Model Approach

This paper studies a class of Poisson mixture models that includes covariates in rates. This model contains Poisson regression and independent Poisson mixtures as special cases. Estimation methods based on the EM and quasi-Newton algorithms, properties of these estimates, a model selection procedure, residual analysis, and goodness-of-fit test are discussed. A Monte Carlo study investigates implementation and model choice issues. This methodology is used to analyze seizure frequency and Ames salmonella assay data.

Publicly Funded Science and the Productivity of the Pharmaceutical Industry

Abstract The protection of pharmaceutical innovations is being dramatically extended as much of the developing world introduces patent protection for new drug products. This change in intellectual property rights may lead to more research on drugs to address developing country needs. We use new survey data from India, the results of interviews, and measures of research and development (R&D) constructed from a variety of statistical sources to determine trends in the allocation of research to products specific to developing country markets. There is some, although limited, evidence of an increase in the mid- to late 1980s which appears to have leveled off in the 1990s.The picture presented provides a “baseline” against which future patterns in research activity can be compared.

Pharmaceutical Innovations and Market Dynamics: Tracking Effects on Price Indexes for Antidepressant Drugs

Count-data models are used to analyze the relationship between patents and research and development spending at the firm level, accounting for overdispersion using a finite mixed Poisson regression model with covariates in both Poisson rates and mixing probabilities. Maximum likelihood estimation using the EM and quasi-Newton algorithms is discussed. Monte Carlo studies suggest that (a) penalized likelihood criteria are a reliable basis for model selection and can be used to determine whether continuous or finite support for the mixing distribution is more appropriate and (b) when the mixing distribution is incorrectly specified, parameter estimates remain unbiased but have inflated variances.

DO FIRMS CHANGE CAPABILITIES BY HIRING NEW PEOPLE? A STUDY OF THE ADOPTION OF SCIENCE-BASED DRUG DISCOVERY

U.S. taxpayers funded