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Journal Articles

Coscia, M., et al., 2020. The Node Vector Distance Problem in Complex Networks. ACM Computing Surveys , 53 (6). Publisher's VersionAbstract

We describe a problem in complex networks we call the Node Vector Distance (NVD) problem, and we survey algorithms currently able to address it. Complex networks are a useful tool to map a non-trivial set of relationships among connected entities, or nodes. An agent—e.g., a disease—can occupy multiple nodes at the same time and can spread through the edges. The node vector distance problem is to estimate the distance traveled by the agent between two moments in time. This is closely related to the Optimal Transportation Problem (OTP), which has received attention in fields such as computer vision. OTP solutions can be used to solve the node vector distance problem, but they are not the only valid approaches. Here, we examine four classes of solutions, showing their differences and similarities both on synthetic networks and real world network data. The NVD problem has a much wider applicability than computer vision, being related to problems in economics, epidemiology, viral marketing, and sociology, to cite a few. We show how solutions to the NVD problem have a wide range of applications, and we provide a roadmap to general and computationally tractable solutions. We have implemented all methods presented in this article in a publicly available open source library, which can be used for result replication.

Zhao, D., Chen, Y. & Shen, J.H., 2020. Mortgage Payments and Household Consumption in Urban China. Economic Modelling , 93 , pp. 100-111. Publisher's VersionAbstract

By exploiting variation both in mortgage payoffs and mortgage interest rate resets, we find that a decline in mortgage payments induces a significant increase in nondurable goods spending, even when households have substantial amounts of liquidity. Following mortgage payoff, households increase consumption expenditures by 61% of the original payment. In comparison, households increase consumption by only 36% in response to a transitory payment adjustment induced by interest rate changes. Households with a higher payment-to-income ratio have a significantly lower marginal propensity to consume (MPC). These results have practical implications for policy markers seeking to design consumption boosting policies and are important for understanding how changes in monetary policy may affect consumer spending patterns.

Knowledge Diffusion in the Network of International Business Travel
Coscia, M., Neffke, F. & Hausmann, R., 2020. Knowledge Diffusion in the Network of International Business Travel. Nature Human Behaviour , 4 (10). Publisher's VersionAbstract

We use aggregated and anonymized information based on international expenditures through corporate payment cards to map the network of global business travel. We combine this network with information on the industrial composition and export baskets of national economies. The business travel network helps to predict which economic activities will grow in a country, which new activities will develop and which old activities will be abandoned. In statistical terms, business travel has the most substantial impact among a range of bilateral relationships between countries, such as trade, foreign direct investments and migration. Moreover, our analysis suggests that this impact is causal: business travel from countries specializing in a specific industry causes growth in that economic activity in the destination country. Our interpretation of this is that business travel helps to diffuse knowledge, and we use our estimates to assess which countries contribute or benefit the most from the diffusion of knowledge through global business travel.

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Hausmann, R., Ganguli, I. & Viarengo, M., 2014. Marriage, Education, and Assortative Mating in Latin America. Applied Economic Letters , 21 (12) , pp. 806-811. Publisher's VersionAbstract
In this article, we establish facts related to marriage and education in Latin American countries. Using census data from IPUMS International, we show how marriage and assortative mating patterns have changed from 1980 to 2000 and how the patterns in Latin America compare to the United States. We find that in Latin American countries, highly educated individuals are less likely to be married than the less educated, and the pattern is stronger for women. We also show that while it has been increasing over time, there is less positive assortative mating in Latin America than in the United States.
Hausmann, R., Ganguli, I. & Viarengo, M., 2014. Closing the gender gap in education: What is the state of gaps in labour force participation for women, wives and mothers?. International Labor Review , 153 (2) , pp. 173-207. Publisher's VersionAbstract

The educational gender gap has closed or reversed in many countries. But what of gendered labour market inequalities? Using micro‐level census data for some 40 countries, the authors examine the labour force participation gap between men and women, the “marriage gap” between married and single women's participation, and the “motherhood gap” between mothers' and non‐mothers' participation. They find significant heterogeneity among countries in terms of the size of these gaps, the speed at which they are changing, and the relationships between them and the educational gap. But counterfactual regression analysis shows that the labour force participation gap remains largely unexplained by the other gaps.

Fernandez-Arias, E., Hausmann, R. & Panizza, U., 2020. Smart Development Banks. Journal of Industry, Competition and Trade , 19 (69). Publisher's VersionAbstract
The conventional paradigm about development banks is that these institutions exist to target well-identified market failures. However, market failures are not directly observable and can only be ascertained with a suitable learning process. Hence, the question is how do the policymakers know what activities should be promoted; how do they learn about the obstacles to the creation of new activities? Rather than assuming that the government has arrived at the right list of market failures and uses development banks to close some well-identified market gaps, we suggest that development banks can be in charge of identifying these market failures through their loan-screening and lending activities to guide their operations and provide critical inputs for the design of productive development policies. In fact, they can also identify government failures that stand in the way of development and call for needed public inputs. This intelligence role of development banks is similar to the role that modern theories of financial intermediation assign to banks as institutions with a comparative advantage in producing and processing information. However, while private banks focus on information on private returns, development banks would potentially produce and organize information about social returns.
Machine-learned patterns suggest that diversification drives economic development
Gomez, A., et al., 2020. Machine-learned patterns suggest that diversification drives economic development. Journal of the Royal Society Interface , 17 (162). Publisher's VersionAbstract
We combine a sequence of machine-learning techniques, together called Principal Smooth-Dynamics Analysis (PriSDA), to identify patterns in the dynamics of complex systems. Here, we deploy this method on the task of automating the development of new theory of economic growth. Traditionally, economic growth is modelled with a few aggregate quantities derived from simplified theoretical models. PriSDA, by contrast, identifies important quantities. Applied to 55 years of data on countries’ exports, PriSDA finds that what most distinguishes countries’ export baskets is their diversity, with extra weight assigned to more sophisticated products. The weights are consistent with previous measures of product complexity. The second dimension of variation is proficiency in machinery relative to agriculture. PriSDA then infers the dynamics of these two quantities and of per capita income. The inferred model predicts that diversification drives growth in income, that diversified middle-income countries will grow the fastest, and that countries will converge onto intermediate levels of income and specialization. PriSDA is generalizable and may illuminate dynamics of elusive quantities such as diversity and complexity in other natural and social systems.
The Value of Complementary Coworkers
Neffke, F., 2019. The Value of Complementary Coworkers. Science Advances , 5 (12). Publisher's VersionAbstract

As individuals specialize in specific knowledge areas, a society’s know-how becomes distributed across different workers. To use this distributed know-how, workers must be coordinated into teams that, collectively, can cover a wide range of expertise. This paper studies the interdependencies among co-workers that result from this process in a population-wide dataset covering educational specializations of millions of workers and their co-workers in Sweden over a 10-year period. The analysis shows that the value of what a person knows depends on whom that person works with. Whereas having co-workers with qualifications similar to one’s own is costly, having co-workers with complementary qualifications is beneficial. This co-worker complementarity increases over a worker’s career and offers a unifying framework to explain seemingly disparate observations, answering questions such as “Why do returns to education differ so widely?” “Why do workers earn higher wages in large establishments?” “Why are wages so high in large cities?”

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Nedelkoska, L. & Neffke, F., 2019. Skill Mismatch and Skill Transferability: Review of Concepts and Measurements. Papers in Evolutionary Economic Geography , 19 (21). Publisher's VersionAbstract
The notion of skills plays an increasingly important role in a variety of research fields. Since the foundational work on human capital theory, economists have approached skills through the lens of education, training and work experience, whereas early work in evolutionary economics and management stressed the analogy between skills of individuals and the organizational routines of firms. We survey how the concept of skills has evolved into notions such as skills mismatch, skill transferability and skill distance or skill relatedness in labor economics, management, and evolutionary approaches to economics and economic geography. We find that these disciplines converged in embracing increasingly sophisticated approaches to measuring skills. Economists have expanded their approach from quantifying skills in terms of years of education to measuring them more directly, using skill tests, self-reported skills and job tasks, or skills and job tasks reported by occupational experts. Others have turned to administrative and other large-scale data sets to infer skill similarities and complementarities from the careers of sometimes millions of workers. Finally, a growing literature on team human capital and skill complementarities has started thinking of skills as features of collectives, instead of only of individuals. At the same time, scholars in corporate strategy have studied the micro-determinants of team formation. Combined, the developments in both strands of research may pave the way to an understanding of how individual-level skills connect to firm-level routines.
Schetter, U., Gersbach, H. & Schneider, M.T., 2019. Taxation, Innovation, and Entrepreneurship. The Economic Journal , 129 (620) , pp. 1731-1781. Publisher's VersionAbstract
We explore optimal and politically feasible growth policies consisting of basic research investments and taxation. We show that the impact of basic research on the general economy rationalises a taxation pecking order with high labour taxes and low profit taxes. This scheme induces a significant proportion of agents to become entrepreneurs, thereby rationalising substantial investments in basic research fostering their innovation prospects. These entrepreneurial economies, however, may make a majority of workers worse off, giving rise to a conflict between efficiency and equality. We discuss ways of mitigating this conflict, and thus strengthening political support for growth policies.
Popularity Spikes Hurt Future Chances For Viral Propagation of Protomemes
Coscia, M., 2018. Popularity Spikes Hurt Future Chances For Viral Propagation of Protomemes. Communications of the ACM , 61 (1) , pp. 70-77. Publisher's VersionAbstract
A meme is a concept introduced by Dawkins12 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 obesity7 and smoking8 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 VersionAbstract
Complex 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.
Birds of a feather scam together: Trustworthiness homophily in a business 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 VersionAbstract
Estimating 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.
Coscia, M. & Neffke, F., 2017. Network Backboning with Noisy Data. 2017 IEEE 33rd International Conference on Data Engineering (ICDE) , (May) , pp. 425-436. Publisher's VersionAbstract
Networks are powerful instruments to study complex phenomena, but they become hard to analyze in data that contain noise. Network backbones provide a tool to extract the latent structure from noisy networks by pruning non-salient edges. We describe a new approach to extract such backbones. We assume that edge weights are drawn from a binomial distribution, and estimate the error-variance in edge weights using a Bayesian framework. Our approach uses a more realistic null model for the edge weight creation process than prior work. In particular, it simultaneously considers the propensity of nodes to send and receive connections, whereas previous approaches only considered nodes as emitters of edges. We test our model with real world networks of different types (flows, stocks, cooccurrences, directed, undirected) and show that our Noise-Corrected approach returns backbones that outperform other approaches on a number of criteria. Our approach is scalable, able to deal with networks with millions of edges.
The Mobility of Displaced Workers: How the Local Industry Mix Affects Job Search
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 VersionAbstract
Are 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.

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