Navigability of temporal networks in hyperbolic space

Information routing is one of the main tasks in many complex networks with a communication function. Maps produced by embedding the networks in hyperbolic space can assist this task enabling the implementation of efficient navigation strategies. However, only static maps have been considered so far, while navigation in more realistic situations, where the network structure may vary in time, remain largely unexplored. Here, we analyze the navigability of real networks by using greedy routing in hyperbolic space, where the nodes are subject to a stochastic activation-inactivation dynamics. We find that such dynamics enhances navigability with respect to the static case. Interestingly, there exists an optimal intermediate activation value, which ensures the best trade-off between the increase in the number of successful paths and a limited growth of their length. Contrary to expectations, the enhanced navigability is robust even when the most connected nodes inactivate with very high probability. Finally, our results indicate that some real networks are ultranavigable and remain highly navigable even if the network structure is extremely unsteady. These findings have important implications for the design and evaluation of efficient routing protocols that account for the temporal nature of real complex networks.Comment: 10 pages, 4 figures. Includes Supplemental Informatio

Which projects are selected for an innovation subsidy? The Portuguese case

Several empirical studies have analyzed which firm characteristics influence government evaluators in the decision to select specific firms to participate in Research and Develop- ment and Innovation subsidy programs. However, few authors have provided a precise analysis about the selection process of applications submitted for public support. The aim of the present article is to assess differences in investment project characteristics (expected impact) between firms with approved and non-approved applications and to understand which kinds of projects are selected for a subsidy. The analysis is focused on the case study of applications submitted to the Portuguese Innovation Incentive System (SI Innovation) between 2007 and 2013. The impact variables under study are those used in the selection procedure to grant the firm a subsidy, namely the expected impact on exports, value creation, productivity, patent application and qualified employment. Using a counterfactual analysis and Propensity Score Matching estimators, the results show that firms with approved applications are those that expect to invest more and forecast a higher increase in exports and productivity as the result of the investment project. However, these firms in comparison with the control group (those with non-approved applications) have investment projects with a lower contribution to growth and lower economic efficiency (return on investment in terms of productivity). The conclusions of this study could be useful for policy-makers since it provides evidence about firms’ strategic choice concerning investment projects submitted for an Innovation subsidy.info:eu-repo/semantics/publishedVersio

Geometric randomization of real networks with prescribed degree sequence

We introduce a model for the randomization of complex networks with geometric structure. The geometric randomization (GR) model assumes a homogeneous distribution of the nodes in a hidden similarity space and uses rewirings of the links to find configurations that maximize a connection probability akin to that of the popularity-similarity geometric network models. The rewiring preserves exactly the original degree sequence, thus preventing fluctuations in the degree cutoff. The GR model is manifestly simple as it relies upon a single free parameter controlling the clustering of the rewired network, and it does not require the explicit estimation of hidden degree variables. We demonstrate the applicability of GR by implementing it as a null model for the analysis of community structure. As a result, we find that geometric and topological communities detected in real networks are consistent, while topological communities are also detected in randomized counterparts as an effect of structural constraints.Peer ReviewedPostprint (published version

The interconnected wealth of nations: Shock propagation on global trade-investment multiplex networks

The increasing integration of world economies, which organize in complex multilayer networks of interactions, is one of the critical factors for the global propagation of economic crises. We adopt the network science approach to quantify shock propagation on the global trade-investment multiplex network. To this aim, we propose a model that couples a spreading dynamics, describing how economic distress propagates between connected countries, with an internal contagion mechanism, describing the spreading of such economic distress within a given country. At the local level, we find that the interplay between trade and financial interactions influences the vulnerabilities of countries to shocks. At the large scale, we find a simple linear relation between the relative magnitude of a shock in a country and its global impact on the whole economic system, albeit the strength of internal contagion is country-dependent and the inter-country propagation dynamics is non-linear. Interestingly, this systemic impact can be associated to intra-layer and inter-layer scale factors that we name network multipliers, that are independent of the magnitude of the initial shock. Our model sets-up a quantitative framework to stress-test the robustness of individual countries and of the world economy.Peer ReviewedPostprint (published version

The interconnected wealth of nations: Shock propagation on global trade-investment multiplex networks

The increasing integration of world economies, which organize in complex multilayer networks of interactions, is one of the critical factors for the global propagation of economic crises. We adopt the network science approach to quantify shock propagation on the global trade-investment multiplex network. To this aim, we propose a model that couples a Susceptible-Infected-Recovered epidemic spreading dynamics, describing how economic distress propagates between connected countries, with an internal contagion mechanism, describing the spreading of such economic distress within a given country. At the local level, we find that the interplay between trade and financial interactions influences the vulnerabilities of countries to shocks. At the large scale, we find a simple linear relation between the relative magnitude of a shock in a country and its global impact on the whole economic system, albeit the strength of internal contagion is country-dependent and the intercountry propagation dynamics is non-linear. Interestingly, this systemic impact can be predicted on the basis of intra-layer and inter-layer scale factors that we name network multipliers, that are independent of the magnitude of the initial shock. Our model sets-up a quantitative framework to stress-test the robustness of individual countries and of the world economy to propagating crashes

“Who Gets Public Support to Innovation? Evidence from the Portuguese Alentejo Region”

The aim of the study is to assess which factors influence the policymaking decisions to financially support an innovative investment project. Based on the case study of the Portuguese Innovation Incentive System in the Alentejo region, we estimated an econometric model based on firms’ and application’ characteristics, controlling for macroeconomic environment. The results indicate that the selection process is more focused on the expected project impact than on firms’ past performance. Furthermore, we found that government preference for promoting employment and exportation are shown to be higher than the impact on firm productivity

The Selection Process of Applications to the Portuguese Innovation Incentive System: Who Gets Financial Support?

Public policies to support entrepreneurship and innovation play a vital role when firms have difficulties in accessing external finance. However, some authors have found evidence of long-term inefficiency in subsidized firms (Bernini and Pelligrini, 2011; Cerqua and Pelligrini, 2014) and ineffectiveness of public funds (Jorge and Suárez, 2011). The aim of the paper is to assess the effectiveness in the selection process of applications to public financial support for stimulating innovation. Using a binary choice model, we investigate which factors influence the probability of obtaining public support for an innovative investment. The explanatory variables are connected to firm profile, the characteristics of the project and the macroeconomic environment. The analysis is based on the case study of the Portuguese Innovation.Incentive System (PIIS) and on the applications managed by the Alentejo Regional Operational Program in the period 2007 – 2013. The results show that the selection process is more focused on the expected impact of the project than on the firm’s past performance. Factors that influence the credit risk and the decision to grant a bank loan do not seem to influence the government evaluator regarding the funding of some projects. Past activities in R&D do not significantly affect the probability of having an application approved under the PIIS, whereas an increase in the number of patents and the number of skilled jobs are both relevant factors. Nevertheless, some evidence of firms’ short-term inefficiency was found, in that receiving public financial support is linked to a smaller increase in productivity compared to non-approved firm applications. At the macroeconomic level, periods with a higher cost of capital in financial markets are linked to a greater probability of getting an application for public support approved, which could be associated with the effectiveness of public support in correcting market failings

Competition effect on innovation and productivity - The Portuguese case

The aim of the present paper is to assess the effect of competition on innovation (patent applications) and on productivity (Total Factor Productivity and Labour Productivity), using data from 654 Portuguese firms, according to 208 NACE 4-digits sectors, and over the period 2007 to 2015. For this purpose, two different methodological approaches were used, a Poisson regression model for the patent function and a log-log fixed effect model for the productivity function. The results reveal that, on average, competition has a negative, U-shaped form effect on innovation in the short term, and a positive effect in the medium-long term. Nevertheless, the model focusing only on manufacturing sectors shows some differences from the model considering all economic activities, namely a linear positive effect of competition on innovation. Concerning the effect of competition on productivity, a positive effect on Total Factor Productivity emerged from the analysis, while for labour productivity a negative one prevails

“Productivity and Employment in Firm’s Acess to Public Funding to Support Innovation”

Innovation is at the heart of the Europe 2020 Strategy, in order to promote higher levels of employment and productivity. Special attention is given to increasing the effectiveness of innovation policy instruments, mainly as some authors found evidence that productivity could be negatively affected by subsidies. The aim of the study is to assess how the expected impact on firm productivity and employment is taken into account, when firms apply for public funding for innovation. The analysis is based on the case study of the Portuguese Innovation Incentive System in the Alentejo region. In order to understand which factors influence the public decision to financially support private investment, we estimated a logit model based on firms’ and applications’ characteristics, controlling for the macroeconomic environment. The results indicate that government preferences for promoting exports, exploiting firms R&D results and stimulating the level of qualified employment are shown to be more relevant than the impact on firm productivity. Furthermore, the cost to the government of new jobs created, measured at least by exemption of interest and financial charges on the loan, is almost twice as much for non-SMEs as for SMEs

The interconnected wealth of nations: Shock propagation on global trade-investment multiplex networks

The increasing integration of world economies, which organize in complex multilayer networks of interactions, is one of the critical factors for the global propagation of economic crises. We adopt the network science approach to quantify shock propagation on the global trade-investment multiplex network. To this aim, we propose a model that couples a spreading dynamics, describing how economic distress propagates between connected countries, with an internal contagion mechanism, describing the spreading of such economic distress within a given country. At the local level, we find that the interplay between trade and financial interactions influences the vulnerabilities of countries to shocks. At the large scale, we find a simple linear relation between the relative magnitude of a shock in a country and its global impact on the whole economic system, albeit the strength of internal contagion is country-dependent and the inter-country propagation dynamics is non-linear. Interestingly, this systemic impact can be associated to intra-layer and inter-layer scale factors that we name network multipliers, that are independent of the magnitude of the initial shock. Our model sets-up a quantitative framework to stress-test the robustness of individual countries and of the world economy