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• This paper discusses and addresses the main challenges of evaluating the socio-economic impact of high-tech public infrastructures using Earth observations (EO). • The EO infrastructure employs an array of cutting-edge technologies that ultimately contribute to understanding, analysing and managing different natural and societal aspects of Earth with a tremendous socio-economic impact on current and future generations. However, this impact is challenging to understand and quantify. • This paper reviews the current fragmented literature on the socio-economic impact of high-tech infrastructure and builds on a new stream of studies on the cost–benefit analysis of large-scale research science-based infrastructures and on investing in the space economy. • This new evaluation framework estimates EO infrastructures' benefits from the perspective of different types of social agents, directly or indirectly involved, along the value chain. • The framework can be adapted to estimate the socio-economic returns of other high-tech infrastructure investments. This paper addresses the main challenges of evaluating the socio-economic impact of high-tech infrastructures, using Earth observation (EO) as an example. EO is a critical domain of the space economy, providing valuable insights into planet Earth's natural and societal aspects. As national agencies invest in high-tech infrastructures like EO, there is a growing need for evaluate their socio-economic returns (not to be confused with their financial returns). However, there is no clear consensus on how to assess such social impact. Building on a new field of studies of social cost–benefit analysis of research infrastructures and the socio-economic impact of investment in the space economy, we propose a new evaluation framework that considers the various stakeholders along the EO value chain. This approach can be adapted to evaluate the socio-economic returns of other high-tech public infrastructures, such as telescopes, particle accelerators, genomic platforms, synchrotron light sources, supercomputers and cloud infrastructures. [ABSTRACT FROM AUTHOR]

After a brief analysis of the causes underlying the failure of both governments and the pharma industry in terms of preparedness for the COVID‐19 pandemic, and after a discussion of further risks of health emergencies in the coming decades, this paper proposes a new public policy approach. The proposal aims at a major European initiative for the provision of research and development (R&D) in the biomedical field, based on public health priorities. A plan is discussed for an international, interconnected, transparent, science‐informed and publicly funded research infrastructure for pharmaceutical and biomedical research combined with a public enterprise: Biomed Europa. The proposed platform aims to identify research priorities in the public health sector, focusing its efforts on the development of preventive and therapeutic strategies against those diseases that will pose the greatest threats to human and social welfare over future decades. Biomed Europa could be managed as both an international research infrastructure, along the model of CERN, or the EMBL (European Molecular Biology Laboratory, Heidelberg) and as a knowledge‐intensive public enterprise with an industrial policy mission, such as the ESA (European Space Agency). [ABSTRACT FROM AUTHOR]

This paper explores some of the methodological issues involved in a cost–benefit analysis framework for large scale capital-intensive research infrastructures. We propose a conceptual model based on the estimation of quantities and shadow prices of cost aggregates, and of six main categories of economic benefits: technological spillovers, human capital formation, knowledge outputs, cultural effects, services to third parties including consumers, and a public good, the pure value of discovery. We justify the reasons why these benefits of research infrastructures should be often expected to be the core ones in ex-ante project evaluation. Other benefits may be considered as well, but often by qualitative methods only. Empirical approaches are suggested for further applied research. [ABSTRACT FROM AUTHOR]

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; and (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. [ABSTRACT FROM AUTHOR]

This paper draws from a recent ex-post evaluation carried out for the European Commission aimed at assessing the long term effects produced by a sample of ten major infrastructures in the Transport and Environment sectors and interpreting the key determinants of the observed performance. It discusses some methodological and institutional implications related to the use of cost-benefit analysis with an ex-post perspective. [ABSTRACT FROM AUTHOR]

This paper examines the return to infrastructure in the European Union regions in a spatial framework. It innovates on the earlier literature on infrastructure and growth by a combination of regional focus, disaggregation of infrastructure types and consideration of spatial dependence. Different types of infrastructure capital are considered as determinants of economic performance at the Nomenclature des Unités Territoriales Statistiques level. To account for growth spillovers among regions, a spatial Durbin model is estimated. The results confirm the important role of infrastructure and identify the highest rates of return as associated with telecommunication, quality and accessibility of transportation networks, with a positive impact of roads and railways. [ABSTRACT FROM PUBLISHER]

We consider results of cost-benefit analysis (CBA) in a large sample of ISPA ( Structural Instrument for Pre-Accession countries) projects co-financed by the European Union to support investment in transport and environment. The research focus is on the empirical analysis of the variability of financial and economic rates of return and how to integrate this information in the EU co-financing mechanism. We investigate to what extent the variability of expected returns and of EU co-financing rates is due to structural project characteristics (sectors, countries) or to other unexplained factors, including errors in the appraisal. We find that while the absolute level of grants is related to sectors, the EU co-financing rate depends on countries. There is no justification in economic analysis of such a country bias, because the variability of economic rate of returns is unrelated either to sector or country factors. These findings points to the need of a more consistent approach to evaluation and EU co-financing of infrastructure supported by the EU funds. We suggest possible improvements, based on the idea to offer an incentive to projects with high-expected economic␣rates of return relative to a benchmark and showing ex-post the realism of the initial analysis. [ABSTRACT FROM AUTHOR]