A common problem with micro-level analysis is that capital stock data is missing. Typically, a feasible measure of capital is calculated by accumulating investment flows from an initial value of the capital stock. As the time dimension of most disaggregated data is rather short, the choice of this initial value can have significant effects on the resulting capital estimates. Most empirical studies impute the initial value using a single arbitrary proxy. In this paper, we propose a panel data framework that assigns weighting coefficients to multiple proxy variables. We conduct a series of Monte Carlo experiments to test the performance of the proposed method and apply the method to a U.S. manufacturing dataset. The results suggest that our method improves the approximation of the capital stock and thus in turn reduces the bias in the production function estimation.

A common problem in the empirical production analysis at the firm-level is that the initial values of capital are often missing in the data. Most empirical studies impute initial capital according to some ad hoc criteria based on a single arbitrary proxy. This paper evaluates the bias of production function estimations that is introduced when these traditional initial value approximations are used. We propose a generalized framework to deal with the missing initial capital problem by using multiple proxies where the choice of proxies is data-driven. We conduct a series of Monte Carlo experiments where the proposed method is tested against traditional approaches and apply the method to the firm-level data.

A problem in the empirical production analysis at the firm-level is that the values of capital are missing in the data. Most empirical studies impute initial capital according to some ad hoc criteria and then estimate the parameters of production function based on these imputed values. This paper proposes a generalized method to deal with the missing initial capital problem.

In this paper we focus on proximity as one of the main determinants of international collaboration in pharmaceutical research. We use various count data specifications of the gravity model to estimate the intensity of collaboration between pairs of countries as explained by the geographical, cognitive, institutional, social, and cultural dimensions of proximity. Our results suggest that geographical distance has a significant negative relation to the collaboration intensity between countries. The amount of previous collaborations, as a proxy for social proximity, is positively related to the number of cross-country collaborations. We do not find robust significant associations between cognitive proximity or institutional proximity with the intensity of international research collaboration. Our findings for cultural proximity do not allow of unambiguous conclusions concerning their influence on the collaboration intensity between countries.

This paper aims to investigate the effect of knowledge characteristics on the total factor productivity of firms developing drugs in the pharmaceutical industry. We decompose knowledge into knowledge associated with the technological firm portfolio and knowledge related to R&D projects, which represent drug development at the clinical testing stage. The latter is attributed to the knowledge of relevant markets where the drugs will be sold. The results show that the effect of technological coherence vs. market coherence and of accumulated knowledge on the productivity of firms differs. Productivity increases with the number of patents and decreases with the patent diversity and project portfolio coherence. When considering only the project knowledge, the diversity of the project portfolio positively affects productivity.

This paper investigates the determinants of success in the development of new drugs. In specific, it explores the factors of success in drug development programs at different stages of innovation process. We use economies of scale, scope, R&D competition and technological spillovers as explanatory variables and test whether the effect of these variables on the success of a project differs in relation to the discovery and development stages of innovation, respectively. Our main finding is that spillovers, including spillovers from collaboration, are important in explaining the success of projects during the discovery stage of innovation, while in the later development stage, the effects of competition outweigh any benefits from spillovers.

This paper empirically investigates the determinants of R&D diversification strategies in the drug industry. It enriches the existing literature by proposing to look at diversification factors, which reflect market and technological proximity of an R&D project towards other projects within a firm’s portfolio as well as R&D competition factors. Additionally, the characteristics of R&D in the market where a new potential product is developed affect future product choice. The analysis is performed for products-in-development data, merged with firms’ patents, which allows us to separate project proximity in market niches from technological proximity. The results of empirical estimation support an idea that R&D diversification is governed by the economies of scope as well as the escape competition motive. Moreover, it is found that competition rather than spillovers in the niche where an R&D project is developed defines firms’ decisions to diversify.

This paper deals with the topic of related R&D and innovation strategies of large firms. We ask what determines the diversity of a firm's product portfolio. More specifically, we try to explain large firms' expansion into new product markets driven by the characteristics of their technological knowledge. Empirically, we study firms in the pharmaceutical and biotech industries, using relevant data on product development and technological knowledge. We find a positive relationship between the diversity of a firm's future product portfolio and the diversity of its stock of technological knowledge. This relationship becomes weaker when the breadth of technological knowledge increases.