Contributions in Merlin

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Do credit ratings help enforce market discipline on banks? Analyzing a uniquely comprehensive dataset consisting of 1,081 rating change announcements for 154 international financial institutions between January 2004 and December 2015, we find that rating downgrades for internal reasons, such as adverse changes in the operating performance or capital structure of banks, are associated with a significant CDS spread widening. However, this widening only occurs for banks that are not perceived as to be Too-Big-to-Fail (TBTF). Our findings question the reliability of credit ratings as a tool to discipline TBTF banks and suggest that regulatory monitoring should remain the main mechanism for disciplining these banks.

In emerging markets and Southern Europe, large capital inflows have led to a decrease in the allocative efficiency of capital. Do capital inflows also affect the allocation of workers and skills? To address this question, we exploit exogenous variations in Portuguese banks' ability to channel capital inflows over the 2002-2007 period. Using comprehensive bank-firm-employee data, we show that not only leverage, but also employment and skill-intensity increase in firms exposed to bank-channeled capital inflows.

Sketch-based query formulation is very common in image and video retrieval as these techniques often complement textual retrieval methods that are based on either manual or machine generated annotations. In this paper, we present a retrieval approach that allows to query visual media collections by sketching concept maps, thereby merging sketch-based retrieval with the search for semantic labels. Users can draw a spatial distribution of different concept labels, such as "sky", "sea" or "person" and then use these sketches to find images or video scenes that exhibit a similar distribution of these concepts. Hence, this approach does not only take the semantic concepts themselves into account, but also their semantic relations as well as their spatial context. The efficient vector representation enables efficient retrieval even in large multimedia collections. We have integrated the semantic sketch query mode into our retrieval engine vitrivr and demonstrated its effectiveness.

Since the launch of the iTunes Music Store in the US in 2003 and in much of Europe in the following years, music trade has shifted rapidly from physical to digital products, raising the availability of products in different countries. Despite substantial growth in availability, choice sets have not converged across countries; and observers point to copyright-related transaction costs as an obstacle to greater availability. Policy makers are now contemplating various copyright reforms that could reduce these trade costs. The possibility of these changes raises the question of how much benefit they would create for consumers and producers around the world. We address these questions with a structural model of supply and demand for music in 17 countries, which we employ to counterfactually simulate the effect of a European digital single market on the welfare of consumers and producers. We also simulate autarky and worldwide frictionless trade - in which all products are available in all countries - allowing us to quantify both the conventional gains from status quo trade as well as the maximum possible gains available to free trade. Existing and additional trade have different patterns of benefit to consumers and producers. Status quo trade benefits consumers everywhere, but European consumers have benefited more than North Americans. Existing trade has had large benefits to American producers but on balance small benefits to European producers. Additional trade would continue the pattern of consumers' benefits with larger gains to European consumers but would reverse the pattern for producers. Greater availability of digital music resulting from easing of copyright restrictions would raise per capita gains to producers in Europe more than in North America. A Europeandigital single market for music would bring total benefits of €19 million to European consumers and €10 million to European producers. Finally, we find that a European digital single market would bring most of the benefits of worldwide frictionless trade to both consumers and producers alike.

Did weather shocks increase interpersonal conflict in early modern Europe? I address this question by exploiting year-to-year seasonal variations in temperature and detailed crime data I assembled from Savoyard criminal procedures over the period 1749--89. I find that temperature shocks had a positive and significant effect on the level of property crimes, but no significant effect on violent crimes. I further document how seasonal migration may help to increase the coping capacity of local communities in which they were widely used. Migrant labourers brought remittances to supplement communities' resources and also temporarily relieve their communities of the burden of feeding them. I show that temperature shocks were strongly associated with increase in the property crimes rate, but the effect is much lower in provinces with high levels of seasonal migration. I provide historical evidence to show that the inflow of remittances may drive this relationship.

Identifying and explaining the structure of complex networks at different scales has become an important problem across disciplines. At the mesoscale, modular architecture has attracted most of the attention. At the macroscale, other arrangements --e.g. nestedness or core-periphery-- have been studied in parallel, but to a much lesser extent. However, empirical evidence increasingly suggests that characterizing a network with a unique pattern typology may be too simplistic, since a system can integrate properties from distinct organizations at different scales. Here, we explore the relationship between some of those organizational patterns: two at the mesoscale (modularity and in-block nestedness); and one at the macroscale (nestedness). We analytically show that nestedness can be used to provide approximate bounds for modularity, with exact results in an idealized scenario. Specifically, we show that nestedness and modularity are antagonistic. Furthermore, we evince that in-block nestedness provides a parsimonious transition between nested and modular networks, taking properties of both. Far from a mere theoretical exercise, understanding the boundaries that discriminate each architecture is fundamental, to the extent modularity and nestedness are known to place heavy constraints on the stability of several dynamical processes, specially in ecology.

This paper argues that an integrated financial sector mitigates negative effects of population aging. We show that U.S. counties with an aging population see an increase in local deposits, reflecting higher saving rates of seniors. Banks use these deposits to increase credit supply. Using detailed data on mortgage lending, we find that banks channel deposits from aging counties towards counties with a younger population. We find no evidence that banks engage in risky lending: they lend less to counties with a high share of sub-prime borrowers or low incomes, and do not lend disproportionately to low-income borrowers. The increase in credit supply has real effects. Counties with a higher market share of aging-exposed banks see an increase in house prices and building permits, as well as in firm formation. Results are robust to controlling for bank and county characteristics through granular fixed effects and instrumenting local aging with casualties during World War II.

This study investigates the role of environmental management control systems as mechanisms to translate environmental strategy into environmental managerial performance. While prior research focuses primarily on environmental performance at the organizational level, this study specifically addresses individual managerial performance with regard to environmental outcomes. In addition, we investigate how the level of integration between regular and environmental management control systems influences the relation between environmental strategy and environmental managerial performance as well as the mediating role of environmental management control systems. Based on survey data from 218 firms and structural equation modeling, the results show that environmental management control systems mediate the relationship between environmental strategy and environmental managerial performance. Moreover, the level of integration significantly impacts the relationship between environmental management control systems and environmental managerial performance. Therefore, environmental management control systems are important mechanisms to translate environmental strategy into managerial performance, and a high level of integration can reinforce this role.

Graph or network representations are an important foundation for data mining and machine learning tasks in relational data. Many tools of network analysis, like centrality measures, information ranking, or cluster detection rest on the assumption that links capture direct influence, and that paths represent possible indirect influence. This assumption is invalidated in time-stamped network data capturing, e.g., dynamic social networks, biological sequences or financial transactions. In such data, for two time-stamped links (A,B) and (B,C) the chronological ordering and timing determines whether a causal path from node A via B to C exists. A number of works has shown that for that reason network analysis cannot be directly applied to time-stamped network data. Existing methods to address this issue require statistics on causal paths, which is computationally challenging for big data sets. Addressing this problem, we develop an efficient algorithm to count causal paths in time-stamped network data. Applying it to empirical data, we show that our method is more efficient than a baseline method implemented in an OpenSource data analytics package. Our method works efficiently for different values of the maximum time difference between consecutive links of a causal path and supports streaming scenarios. With it, we are closing a gap that hinders an efficient analysis of big time series data on complex networks.