Search

This paper contributes to the literature on the impact of Big Science Centres on technological innovation. We exploit a unique dataset with information on CERN's procurement orders to study the collaborative innovation process between CERN and its industrial partners. After a qualitative discussion of case studies, survival and count data models are estimated; the impact of CERN procurement on suppliers' innovation is captured by the number of patent applications. The fact that firms in our sample received their first order over a long time span (1995-2008) delivers a natural partition of industrial partners into "suppliers" and "not yet suppliers". This allows estimating the impact of CERN on the hazard to file a patent for the first time and on the number of patent applications, as well as the time needed for these effects to show up. We find that a "CERN effect" does exist: being an industrial partner of CERN is associated with an increase in the hazard to file a patent for the first time and in the number of patent applications. These effects require a significant "gestation lag" in the range of five to eight years, pointing to a relatively slow process of absorption of new ideas.

Proxies for regulatory reforms based on categorical variables are increasingly used in empirical evaluation models. We surveyed 63 studies that rely on such indices to analyze the effects of entry liberalization, privatization, unbundling, and independent regulation of the electricity, natural gas, and telecommunications sectors. We highlight methodological issues related to the use of these proxies. Next, taking stock of the literature, we provide practical advice for the design of the empirical strategy and discuss the selection of control and instrumental variables to attenuate endogeneity problems undermining identification of the effects of regulatory reforms.

Preliminary evidence on the long--run trajectory of the accelerator industry suggests that it may be close to the maturity phase of its cycle. If this is the case, how can we measure the benefits of an uncertain breakthrough in acceleration technology? Who are the main stakeholders interested by such a breakthrough? We identify these subjects and sketch some avenues for answering these questions. We thus present a model for the social Cost-Benefit Analysis (CBA) of research infrastructures and illustrate the results of its implementation for assessing the benefits of accelerators in basic science and hadrontherapy. Lastly, we move from the social CBA of single research infrastructures to modeling a major change in the accelerator technology and hence in the industry. A research agenda on the potential impacts of a technological breakthrough is presented.

More than 36,000 students and post-docs will be involved in experiments at the Large Hadron Collider (LHC) until 2025. Do they expect that their learning experience will have an impact on their professional future? By drawing from earlier salary expectations literature, this paper proposes a framework aiming at explaining the professional expectations of early career researchers (ECR) at the LHC. Results from different ordered logistic models suggest that experiential learning at LHC positively correlates with both current and former students' salary expectations. At least two not mutually exclusive explanations underlie such a relationship. First, the training at LHC gives early career researchers valuable expertise, which in turn affects salary expectations; secondly, respondents recognise that the LHC research experience per se may act as a signal in the labour market. Respondents put a price tag on their experience at LHC, a "salary premium" ranging from 5% to 12% in terms of future salaries compared with what they would have expected without such experience., Comment: 27 pages

This paper presents the results and the lessons learned on how to apply ex-ante CBQ for major RDI infrastructures by a team of economists and scientists at the University of Milan and CSIL during a three-year research project supported by a EIBURS grant of the European Investment Bank Institute. Albeit the comprehensive conceptual framework presented in the paper builds on principles firmly rooted in CBA tradition, their application to the RDI sector is still in its infancy. So far, the model has been applied on two cases in physics involving particle accelerators (the Large Hadron Collider, LHC, at CERN and the National Centre for Oncological Treatment, CNAO, in Italy)., Comment: 86 pages

An increasing number of countries and institutions are investing in large-scale research infrastructures (RIs) and in basic research. Scientific discoveries, which are expected thanks to RIs, may have a non-use value, in analogy with environmental and cultural public goods. This paper provides, for the first time, an empirical estimation of the willingness to pay (WTP) for discoveries in basic research by the general public. We focus on the Large Hadron Collider (LHC), the largest particle accelerator worldwide, where in 2012 the Higgs boson was discovered. Nobody knows the practical value of such discovery, beyond knowledge per se. The findings of our study are based on a dichotomous choice contingent valuation (CV) survey carried out in line with the NOAA guidelines. The survey involved 1,022 undergraduate students enrolled in more than 30 different degrees (including the humanities) at five universities located in four countries (Italy, France, Spain, UK). We ask two main research questions: Which are the determinants of the WTP for the LHC discoveries? What is the average contribution that the respondents would be willing to pay? Our results confirm that income, interest and attitudes towards basic research are positively associated with the WTP, while other potential explanatory variables play a limited role. The estimated mean of WTP for basic research in particle physics is EUR 7.7 per person una-tantum. Although this is a small amount compared to other CV studies for environmental and cultural goods, it points to positive social attitudes for basic science as a public good., Comment: 28 pages, 9 tables, 2 figures

In this paper we develop a cost-benefit analysis of a major research infrastructure, the Large Hadron Collider (LHC), the highest-energy accelerator in the world, currently operating at CERN. We show that the evaluation of benefits can be made quantitative by estimating their welfare effects on different types of agents. Four classes of direct benefits are identified, according to the main social groups involved: (a) scientists; (b) students and young researchers; (c) firms in the procurement chain and other organizations; (d) the general public, including onsite and website visitors and other media users. These benefits are respectively related to the knowledge output of scientists; human capital formation; technological spillovers; and direct cultural effects for the general public. Welfare effects for taxpayers can also be estimated by the contingent valuation of the willingness to pay for a pure public good for which there is no specific direct use (i.e., as non-use value). Using a Monte Carlo approach, we estimate the conditional probability distribution of costs and benefits for the LHC from 1993 until its planned decommissioning in 2025, assuming a range of values for some critical stochastic variables. We conservatively estimate that there is around a 90\% probability that benefits exceed costs, with an expected net present value of about 2.9 billion euro, not considering the unpredictable applications of scientific discovery., Comment: 28 pages, 7 figures; extended version of arXiv:1507.05638; to be submitted to the journal "Technological Forecasting and Social Change"

Social cost-benefit analysis (CBA) of projects has been successfully applied in different fields such as transport, energy, health, education, and environment, including climate change. It is often argued that it is impossible to extend the CBA approach to the evaluation of the social impact of research infrastructures, because the final benefit to society of scientific discovery is generally unpredictable. Here, we propose a quantitative approach to this problem, we use it to design an empirically testable CBA model, and we apply it to the the Large Hadron Collider (LHC), the highest-energy accelerator in the world, currently operating at CERN. We show that the evaluation of benefits can be made quantitative by determining their value to users (scientists, early-stage researchers, firms, visitors) and non-users (the general public). Four classes of contributions to users are identified: knowledge output, human capital development, technological spillovers, and cultural effects. Benefits for non-users can be estimated, in analogy to public goods with no practical use (such as environment preservation), using willingness to pay. We determine the probability distribution of cost and benefits for the LHC since 1993 until planned decommissioning in 2025, and we find there is a 92% probability that benefits exceed its costs, with an expected net present value of about 3 billion euro, not including the unpredictable economic value of discovery of any new physics. We argue that the evaluation approach proposed here can be replicated for any large-scale research infrastructure, thus helping the decision-making on competing projects, with a socio-economic appraisal complementary to other evaluation criteria., Comment: 17 pages, 7 figures