Reputation is an important social construct in science, which enables informed quality assessments of both publications and careers of scientists in the absence of complete systemic information. However, the relation between reputation and career growth of an individual remains poorly understood, despite recent proliferation of quantitative research evaluation methods. Here, we develop an original framework for measuring how a publication's citation rate Δc depends on the reputation of its central author i, in addition to its net citation count c. To estimate the strength of the reputation effect, we perform a longitudinal analysis on the careers of 450 highly cited scientists, using the total citations C i of each scientist as his/her reputation measure. We find a citation crossover c × , which distinguishes the strength of the reputation effect. For publications with c < c × , the author's reputation is found to dominate the annual citation rate. Hence, a new publication may gain a significant early advantage corresponding to roughly a 66% increase in the citation rate for each tenfold increase in C i . However, the reputation effect becomes negligible for highly cited publications meaning that, for c ≥ c × , the citation rate measures scientific impact more transparently. In addition, we have developed a stochastic reputation model, which is found to reproduce numerous statistical observations for real careers, thus providing insight into the microscopic mechanisms underlying cumulative advantage in science.computational sociology | science of science | networks of networks | Matthew effect | sociophysics C itation counts are widely used to judge the impact of both scientists and their publications (1-4). Although it is recognized that many factors outside the pure merit of the research or the authors influence such counts, little effort has been devoted to identifying and quantifying the role of the author-specific factors. Recent investigations have begun to study the impact the individual scientists have through collaboration and reputation spillovers (5, 6), two integrative features of scientific careers that contribute to cumulative advantage (7-9). However, the majority of citation models avoid author-specific effects, mainly due to the difficulty in acquiring comprehensive disambiguated career data (10-13). As the measures are becoming increasingly common in evaluation scenarios throughout science, it is crucial to better understand what the citation measures actually represent in the context of scientists' careers. Moreover, how does reputation affect a scientist's access to key resources, the incentives to publish quality over quantity, and other key decisions along the career path (14-18)? In addition, what role does reputation play in the mentor-matching process within academic institutions, in the effectiveness of single/double blinding in peer review, and in the reward system of science (14,15,19)?It is against this background that we have developed a quantitative framework with the goal of isola...

This paper analyzes the performance of global value chains during the trade collapse.To do so, it exploits a unique transaction-level dataset on French …rms containing information on cross-border monthly transactions matched with data on worldwide intra-…rm linkages as de…ned by property rights (multinational business groups, hierarchies of …rms).This newly assembled dataset allows us to distinguish …rm-level transactions among two alternative organizational modes of global value chains: internalization of activities (intragroup trade/trade among related parties) or establishment of supply contracts (arm's length trade/trade among unrelated parties). After an overall assessment of the role of global value chains during the trade collapse, we document that intra-group trade in intermediates was characterized by a faster drop followed by a faster recovery than arm's length trade. Ampli…ed ‡uctuations in terms of trade elasticities by value chains have been referred to as the "bullwhip e¤ect" and have been attributed to the adjustment of inventories within supply chains. In this paper we …rst con…rm the existence of such an e¤ect due to trade in intermediates, and we underline the role that di¤erent organizational modes can play in driving this adjustment.JEL codes: F23, F15, L22.Keywords: trade collapse, multinational …rms, global value chains, hierarchies of …rms , vertical integration. Non-technical summaryThe "Great Trade Collapse" has been one of the most striking features of the recent global financial crisis, with the ongoing recovery still driving a wedge between output and trade. The drop in trade flows has been very fast, particularly severe and synchronized across all countries, as several empirical studies already suggest. Such features make the current trade drop quite unique among the many episodes of trade decline typically associated to economic crises, and a number of transmission mechanisms have been proposed which could account for these peculiarities. Among those mechanisms, a particular role has been attributed to the emergence over the last decade of global supply chains, and to the different compositional effects of the demand shock entailed by vertical linkages on trade and GDP.In this paper we exploit transaction-level French trade data matched with ownership data for the period 2007-2009 to find evidence of a role for global value chains in explaining the magnitude of the trade collapse. Consistent with other results, we find that trade in intermediates has been the main driver of the trade collapse. However we also find that different organizational modes of the supply chain entailed different dynamic responses: related-party trade in intermediates exhibits a faster drop followed by a faster rebound with respect to arm's length trade in intermediates. In other words, trade originated within multinational groups seems to have reacted faster to the negative demand shock but has also recovered faster in the following months than arm's length trade. Among the alternative channels of t...

Complex economic systems can often be described by a network, with nodes representing economic entities and edges their interdependencies, while network centrality is often a good indicator of importance. Recent publications have implemented a nonlinear iterative Fitness-Complexity (FC) algorithm to measure centrality in a bipartite trade network, which aims to represent the ‘Fitness’ of national economies as well as the ‘Complexity’ of the products being traded. In this paper, we discuss this methodological approach and conclude that further work is needed to identify stable and reliable measures of fitness and complexity. We provide theoretical and numerical evidence for the intrinsic instability in the nonlinear definition of the FC algorithm. We perform an in-depth evaluation of the algorithm’s rankings in two real world networks at the country level: the global trade network, and the patent network in different technological domains. In both networks, we find evidence of the instabilities predicted theoretically, and show that ‘complex’ products or patents tend often to be those that countries rarely produce, rather than those that are intrinsically more difficult to produce.

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In this paper we study the organization of Global Value Chains on a sample of about 4,000 manufacturing parent companies operating more than 90,000 affiliates on a global scale, which chose to integrate at least once in the period [2004][2005][2006][2007][2008][2009][2010][2011][2012]. Assuming a technological sequence of production stages, a recent property rights framework (Antràs and Chor, 2013;Alfaro et al., 2015) predicts that a choice of vertical integration is crucially based on both the position of a supplier along the chain and on the relative size of demand elasticities faced by the final producer and the supplier. We positively test whether, if final demand is sufficiently elastic (inelastic), producers of final goods integrate production stages that are more proximate to (far from) the consumers. However, this is not valid for cases of midstream parents, i.e. for producers of intermediate inputs that can integrate either backward or forward along the chain. We document that midstream are at least as common as are downstream parent companies but that existing theory neglects them. In these cases, we find that demand elasticities do not play a significant role in integration choices. Interestingly, both midstream and downstream parents tend to integrate affiliates that are more proximate in segments of a supply chain. Our findings point to a role for technological determinants that may be as important as are contracting frictions in organizing Global Value Chains.

This paper analyzes the performance of global value chains during the trade collapse.To do so, it exploits a unique transaction-level dataset on French …rms containing information on cross-border monthly transactions matched with data on worldwide intra-…rm linkages as de…ned by property rights (multinational business groups, hierarchies of …rms).This newly assembled dataset allows us to distinguish …rm-level transactions among two alternative organizational modes of global value chains: internalization of activities (intragroup trade/trade among related parties) or establishment of supply contracts (arm's length trade/trade among unrelated parties). After an overall assessment of the role of global value chains during the trade collapse, we document that intra-group trade in intermediates was characterized by a faster drop followed by a faster recovery than arm's length trade. Ampli…ed ‡uctuations in terms of trade elasticities by value chains have been referred to as the "bullwhip e¤ect" and have been attributed to the adjustment of inventories within supply chains. In this paper we …rst con…rm the existence of such an e¤ect due to trade in intermediates, and we underline the role that di¤erent organizational modes can play in driving this adjustment.JEL codes: F23, F15, L22.Keywords: trade collapse, multinational …rms, global value chains, hierarchies of …rms , vertical integration. Non-technical summaryThe "Great Trade Collapse" has been one of the most striking features of the recent global financial crisis, with the ongoing recovery still driving a wedge between output and trade. The drop in trade flows has been very fast, particularly severe and synchronized across all countries, as several empirical studies already suggest. Such features make the current trade drop quite unique among the many episodes of trade decline typically associated to economic crises, and a number of transmission mechanisms have been proposed which could account for these peculiarities. Among those mechanisms, a particular role has been attributed to the emergence over the last decade of global supply chains, and to the different compositional effects of the demand shock entailed by vertical linkages on trade and GDP.In this paper we exploit transaction-level French trade data matched with ownership data for the period 2007-2009 to find evidence of a role for global value chains in explaining the magnitude of the trade collapse. Consistent with other results, we find that trade in intermediates has been the main driver of the trade collapse. However we also find that different organizational modes of the supply chain entailed different dynamic responses: related-party trade in intermediates exhibits a faster drop followed by a faster rebound with respect to arm's length trade in intermediates. In other words, trade originated within multinational groups seems to have reacted faster to the negative demand shock but has also recovered faster in the following months than arm's length trade. Among the alternative channels of t...

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