Coscia, M., 2018.
Popularity Spikes Hurt Future Chances For Viral Propagation of Protomemes.
Communications of the ACM , 61 (1) , pp. 70-77.
Publisher's VersionAbstractA meme is a concept introduced by Dawkins
12 as an equivalent in cultural studies of a gene in biology. A meme is a cultural unit, perhaps a joke, musical tune, or behavior, that can replicate in people's minds, spreading from person to person. During the replication process, memes can mutate and compete with each other for attention, because people's consciousness has finite capacity. Meme viral spreading causes behavioral change, for the better, as when, say, the "ALS Bucket Challenge" meme caused a cascade of humanitarian donations,
a and for the worse, as when researchers proved obesity
7 and smoking
8 are socially transmittable diseases. A better theory of meme spreading could help prevent an outbreak of bad behaviors and favor positive ones.
Coscia, M., 2018.
Using arborescences to estimate hierarchicalness in directed complex networks.
PLoS ONE , 13 (1).
Publisher's VersionAbstractComplex networks are a useful tool for the understanding of complex systems. One of the emerging properties of such systems is their tendency to form hierarchies: networks can be organized in levels, with nodes in each level exerting control on the ones beneath them. In this paper, we focus on the problem of estimating how hierarchical a directed network is. We propose a structural argument: a network has a strong top-down organization if we need to delete only few edges to reduce it to a perfect hierarchy—an arborescence. In an arborescence, all edges point away from the root and there are no horizontal connections, both characteristics we desire in our idealization of what a perfect hierarchy requires. We test our arborescence score in synthetic and real-world directed networks against the current state of the art in hierarchy detection: agony, flow hierarchy and global reaching centrality. These tests highlight that our arborescence score is intuitive and we can visualize it; it is able to better distinguish between networks with and without a hierarchical structure; it agrees the most with the literature about the hierarchy of well-studied complex systems; and it is not just a score, but it provides an overall scheme of the underlying hierarchy of any directed complex network.
Barone, M. & Coscia, M., 2018.
Birds of a feather scam together: Trustworthiness homophily in a business network.
Social Networks , 54 (July 2018) , pp. 228-237.
Publisher's VersionAbstractEstimating the trustworthiness of a set of actors when all the available information is provided by the actors themselves is a hard problem. When two actors have conflicting reports about each other, how do we establish which of the two (if any) deserves our trust? In this paper, we model this scenario as a network problem: actors are nodes in a network and their reports about each other are the edges of the network. To estimate their trustworthiness levels, we develop an iterative framework which looks at all the reports about each connected actor pair to define its trustworthiness balance. We apply this framework to a customer/supplier business network. We show that our trustworthiness score is a significant predictor of the likelihood a business will pay a fine if audited. We show that the market network is characterized by homophily: businesses tend to connect to partners with similar trustworthiness degrees. This suggests that the topology of the network influences the behavior of the actors composing it, indicating that market regulatory efforts should take into account network theory to prevent further degeneration and failures.
Neffke, F., Otto, A. & Hidalgo, C., 2018.
The Mobility of Displaced Workers: How the Local Industry Mix Affects Job Search.
Journal of Urban Economics , 108 (November 2018) , pp. 124-140.
Publisher's VersionAbstractAre there Marshallian externalities in job search? We study how workers who lose their jobs in establishment closures in Germany cope with their loss of employment. About a fifth of these displaced workers do not return to social-security covered employment within the next three years. Among those who do get re-employed, about two-thirds leave their old industry and one-third move out of their region. However, which of these two types of mobility responses workers will choose depends on the local industry mix in ways that are suggestive of Marshallian benefits to job search. In particular, large concentrations of one’s old industry makes it easier to find new jobs: in regions where the pre-displacement industry is large, displaced workers suffer relatively small earnings losses and find new work faster. In contrast, large local industries skill-related to the pre-displacement industry increase earnings losses but also protect against long-term unemployment. Analyzed through the lens of a job-search model, the exact spatial and industrial job-switching patterns reveal that workers take these Marshallian externalities into account when deciding how to allocate search efforts among industries.
Hausmann, R. & Neffke, F., 2018.
The workforce of pioneer plants: The role of worker mobility in the diffusion of industries.
Research Policy.
Publisher's VersionAbstractDoes technology require labour mobility to diffuse? To explore this, we use German social-security data and ask how plants that pioneer an industry in a location – and for which the local labour market offers no experienced workers – assemble their workforces. These pioneers use different recruiting strategies than plants elsewhere: they hire more workers from outside their industry and from outside their region, especially when workers come from closely related industries or are highly skilled. The importance of access to experienced workers is highlighted in the diffusion of industries from western Germany to the post-reunification economy of eastern German. While manufacturing employment declined in most advanced economies, eastern German regions managed to reindustrialise. The pioneers involved in this process relied heavily on expertise from western Germany: while establishing new manufacturing industries in the East, they sourced half of their experienced workers from the West.
Kosack, S., et al., 2018.
Functional structures of US state governments.
Proceedings of the National Academy of Sciences of the United States of America.
Publisher's VersionAbstractGovernments in modern societies undertake an array of complex functions that shape politics and economics, individual and group behavior, and the natural, social, and built environment. How are governments structured to execute these diverse responsibilities? How do those structures vary, and what explains the differences? To examine these longstanding questions, we develop a technique for mapping Internet “footprint” of government with network science methods. We use this approach to describe and analyze the diversity in functional scale and structure among the 50 US state governments reflected in the webpages and links they have created online: 32.5 million webpages and 110 million hyperlinks among 47,631 agencies. We first verify that this extensive online footprint systematically reflects known characteristics: 50 hierarchically organized networks of state agencies that scale with population and are specialized around easily identifiable functions in accordance with legal mandates. We also find that the footprint reflects extensive diversity among these state functional hierarchies. We hypothesize that this variation should reflect, among other factors, state income, economic structure, ideology, and location. We find that government structures are most strongly associated with state economic structures, with location and income playing more limited roles. Voters’ recent ideological preferences about the proper roles and extent of government are not significantly associated with the scale and structure of their state governments as reflected online. We conclude that the online footprint of governments offers a broad and comprehensive window on how they are structured that can help deepen understanding of those structures.
Visualizations and datasets available on project website >>
government-structure-paper.pdf Thorbecke, W., 2018.
The Exposure of U.S. Manufacturing Industries to Exchange Rates.
International Review of Economics and Finance.
Publisher's VersionAbstractSafe asset demand and currency manipulation increase the dollar and the U.S. current account deficit. Deficits in manufacturing trade cause dislocation and generate protectionism. Dynamic OLS results indicate that U.S. export elasticities exceed unity for automobiles, toys, wood, aluminum, iron, steel, and other goods. Elasticities for U.S. imports from China are close to one or higher for footwear, radios, sports equipment, lamps, and watches and exceed 0.5 for iron, steel, aluminum, miscellaneous manufacturing, and metal tools. Elasticities for U.S. imports from other countries are large for electrothermal appliances, radios, furniture, lamps, miscellaneous manufacturing, aluminum, automobiles, plastics, and other categories. Stock returns on many of these sectors also fall when the dollar appreciates. Several manufacturing industries are thus exposed to a strong dollar. Policymakers could weaken the dollar and deflect protectionist pressure by promoting the euro, the yen, and the renminbi as alternative reserve currencies.
exchange_rates_iref_thorbecke.pdf Bahar, D. & Santos, M., 2018.
One more resource curse: Dutch disease and export concentration.
Journal of Development Economics , 132 (May 2018) , pp. 102-114.
Publisher's VersionAbstractEconomists have long discussed the negative effect of Dutch disease episodes on the non-resource tradable sector as a whole, but little has been said on its impact on the composition of the non-resource export sector. This paper fills this gap by exploring to what extent concentration of a country's non-resource export basket is determined by their exports of natural resources. We present a theoretical framework that shows how upward pressure in wages caused by a resource windfall results in higher export concentration. We then document two robust empirical findings consistent with the theory. First, using data on discovery of oil and gas fields and of commodity prices as sources of exogenous variation, we find that countries with larger shares of natural resources in exports have more concentrated non-resource export baskets. Second, we find capital-intensive exports tend to dominate the export basket of countries prone to Dutch disease episodes.
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Czaika, M. & Orazbayev, S., 2018.
The globalisation of scientific mobility, 1970–2014.
Applied Geography , 96 (July).
AbstractThis article provides an empirical assessment of global scientific mobility over the past four decades, based on bibliometric data. We find (i) an increasing diversity of origin and destination countries integrated in global scientific mobility, with (ii) the centre of gravity of scientific knowledge production and migration destinations moving continuously eastwards by about 1300 km per decade, (iii) an increase in average migration distances of scientists reflecting integration of global peripheries into the global science system, (iv) significantly lower mobility frictions for internationally mobile scientists compared to non-scientist migrants, (v) with visa restrictions establishing a statistically significant barrier affecting international mobility of scientists hampering the global diffusion of scientific knowledge.
Manchin, M. & Orazbayev, S., 2018.
Social networks and the intention to migrate.
World Development , 109 (September ) , pp. 360–374.
Publisher's VersionAbstractUsing a large individual-level survey spanning several years and more than 150 countries, we examine the importance of social networks in influencing individuals’ intention to migrate internationally and locally. We distinguish close social networks (composed of friends and family) abroad and at the current location, and broad social networks (composed of same-country residents with intention to migrate, either internationally or locally). We find that social networks abroad are the most important driving forces of international migration intentions, with close and broad networks jointly explaining about 37% of variation in the probability intentions. Social networks are found to be more important factors driving migration intentions than work-related aspects or wealth (wealth accounts for less than 3% of the variation). In addition, we find that having stronger close social networks at home has the opposite effect by reducing the likelihood of migration intentions, both internationally and locally.
