Sustainability of CAPS Social Network: a Network Analysis Approach using Agent-Based Simulation

This paper focuses on analyzing the structure of several egocentric networks of collective awareness platforms for sustainable innovation (CAPS). It answers the question whether the network structure is determinative for the sustainability of the created awareness. Based on a thorough literature review a model is developed explaining and operationalizing the concept of sustainability of a social network in terms of importance, effectiveness and robustness. By developing an agent-based model, the expected outcomes after the dissolution of the CAPS are predicted and compared with the results of a network with the same participants but with different ties. Twitter data from different CAPS is collected and used to feed the simulation. The results show that the structure of the network is of key importance for its sustainability. With this knowledge and the ability to simulate the results after network changes have taken place, CAPS can assess the sustainability of their legacy and actively steer towards a longer lasting potential for social innovation. The retrieved knowledge urges organizations like the European Commission to adopt a more blended approach focusing not only on solving societal issues but on building a community to sustain the initiated development

Markets and innovativeness: Does structure influence innovation performance?

This empirical analysis of a microeconomic dataset for the year 1992 and 833 Dutch industrial firms finds that innovativeness (i.e. the share of ?radically or completely new products? in turnover) is related to the length of the product life cycle, R&D intensity and technological opportunities at firm level. The Schumpeterian notion that entree barriers, market power and market concentration are important for innovativeness is contested by our findings as firm size, the concentration ratio, persistence of profit parameters, and entry and exit rates turn out to be insignificant. On average, knowledge protection by patenting reduces the firms? innovation performance whereas market-induced knowledge protection created by first mover advantages increases innovativeness at the firm level. Our investigation supports the notion of modern innovation theory that co-operation between suppliers, main producers and users improves firms? innovation performance

Using “responsive regulation” to reduce tax base erosion

How can governments get individuals and firms to pay taxes, especially given increasing tax base erosion via tax evasion, tax avoidance, and money laundering? In this paper we discuss the many different perspectives to explain why people pay – and do not pay – their taxes, especially perspectives based on “responsive regulation,” and we use then these perspectives to suggest policies that governments may use to improve tax collections. We first describe an approach that is based on a single individual pursuing a single motivation by choosing a single method (tax evasion) and operating in a single country. This perspective has generated important insights, but it nonetheless has significant limitations. As a result, we then argue that this perspective must be expanded to include additional actors in the field, all pursuing additional motivations. We also expand our discussion to include additional methods of tax base erosion like tax avoidance and money laundering, as well as additional countries. We argue that explaining behavior and then devising appropriate policies requires incorporating all of these additional considerations. We also discuss the likely impact of technological innovations both on the ability of governments to collect taxes and on the ability of private agents to reduce their taxes. An important contribution of our paper is that we simulate the effects of all of these expansions to the basic model using a novel agent‐based model that is fully grounded in theory and calibrated for 33 European economics. We use this model to simulate the impacts over time of various reforms, especially reforms that implement international information‐sharing programs, by comparing tax base erosion in the absence of these reforms to erosion in their presence. Our simulation results demonstrate the importance of using a fully specified theoretical model that goes well beyond the standard economics of crime approach when considering the effects of government policy innovations. We conclude with recommendations that can in principle reduce tax base erosion via evasion, avoidance, and money laundering in the current multi‐dimensional environment as derived from the responsive regulation framework. However, these recommendations require a firm commitment from governments to their tax administrations, and these recommendations also cannot be introduced unilaterally by a single country but require international cooperation, especially via information sharing across borders

Bilateral responsive regulation and international tax competition: An agent‐based simulation

Country‐by‐Country Reporting and Automatic Exchange of Information have recently been implemented in European Union (EU) countries. These international tax reforms increase tax compliance in the short term. In the long run, however, taxpayers will continue looking abroad to avoid taxation and, countries, looking for additional revenues, will provide opportunities. As a result, tax competition intensifies and the initial increase in compliance could reverse. To avoid international tax reforms being counteracted by tax competition, this paper suggests bilateral responsive regulation to maximize compliance. This implies that countries would use different tax policy instruments toward other countries, including tax and secrecy havens. Our agent‐based simulation finds that a differentiated policy response could increase tax compliance by 6.54 percent, which translates into an annual increase of €105 billion in EU tax revenues on income, profits, and capital gains. Corporate income tax revenues in France, Spain, and the UK alone would already account for €35 billion

The effect of anti-money laundering policies: an empirical network analysis

Aim: There is a growing literature analyzing money laundering and the policies to fight it, but the overall effectiveness of anti-money laundering policies is still unclear. This paper investigates whether anti-money laundering policies affect the behavior of money launderers and their networks. Method: With an algorithm to match clusters over time, we build a unique dataset of multi-mode, undirected, binary, dynamic networks of natural and legal persons. The data includes ownership and employment relations and associated financial ties and is enriched with criminal records and police-related activities. The networks of money launderers, other criminals, and non-criminal individuals are analyzed and compared with temporal social network analysis techniques and panel data regressions on centrality measures, transitivity and assortativity indicators, and levels of constraint. Findings: We find that after the announcement of the fourth EU anti-money laundering directive in 2015, money laundering networks show a significant increase in the use of foreigners and corporate structures. At the individual level, money launderers become more dominant in criminal clusters (increased closeness centrality). This paper shows that (the announcement of) anti-money laundering policies can affect criminal networks and how such effects can be tested

Tax Dynamics and Money Laundering: Simulating Policy Reforms in a Complex System

International mobility of natural and legal persons and the application of new technologies, create more opportunities to avoid and evade taxes. To retain tax revenues, governments must provide an internationally attractive tax environment, making them compete with other governments. To counter this dynamic, new EU regulation is implemented, i.e. country-by-country reporting and the automatic exchange of information. This dissertation tests the effect of this legislation on tax evasion and avoidance, through an agent-based simulation model that incorporates the individual choices of natural and legal persons. The model estimates the European corporate tax losses in 2019 to be € 104.9 billion, which will increase to an annual loss of € 135.8 billion in 2029 under the current policy regime. Fully implementing CbCR and AEoI decreases the expected tax gap of 2029 by 16.4% to € 113.5 billion. As for the effectiveness of both policies, AEoI is demonstrated to be effective against tax evasion but not against tax avoidance, making the total tax losses € 134.0 billion (a merely 1.3% decline). The expected small effect of CbCR becomes much larger in the long run, it results in € 121.2 billion tax losses which represents a decline of 10.8%. The effectiveness of CbCR is explained by its positive effect on the tax morale of individuals. Given that compliance choices are affected by international differences between legal and tax systems and by information that agents receive from other agents that surround them, compliance must be governed responsively. The model shows that short-term effects of the aforementioned regulations increase the overall compliance level, but also indicates that long-term effects could counteract the intended goals. This dissertation provides a framework that improves tax compliance without fueling tax competition in the long term. The agent-based simulation shows that without responsive regulation, tax competition intensifies and the initial increase in compliance could reverse. A differentiated policy response could increase tax compliance by 6.54%, which translates into an annual increase of € 105 billion in EU tax revenues on income, profits, and capital gains. Attractive tax legislation frequently offers higher levels of financial secrecy, which obscure corporate ownership and the origin of revenues. Besides evading and avoiding taxes, such legislation also provides opportunities for criminal organizations to launder their criminal proceeds. Anti-money laundering regulation aims to mitigate the associated risks of financial secrecy and influence how criminal networks operate. Therefore, this dissertation evaluates the effect of anti-money laundering regulation on the network structures of criminal organizations. It is expected that the AML legislation makes money laundering more difficult and forces money launderers to both specialize and compete with others, which the analysis confirms due to significant changes in the structure of money laundering networks. An adverse effect of AML legislation is that it affects non-criminal organizations too. The importance of high quality corporate registers and transparently sharing this information internationally is an important basis for detecting and prosecuting money laundering

Tax Dynamics and Money Laundering: Simulating Policy Reforms in a Complex System

International mobility of natural and legal persons and the application of new technologies, create more opportunities to avoid and evade taxes. To retain tax revenues, governments must provide an internationally attractive tax environment, making them compete with other governments. To counter this dynamic, new EU regulation is implemented, i.e. country-by-country reporting and the automatic exchange of information. This dissertation tests the effect of this legislation on tax evasion and avoidance, through an agent-based simulation model that incorporates the individual choices of natural and legal persons. The model estimates the European corporate tax losses in 2019 to be € 104.9 billion, which will increase to an annual loss of € 135.8 billion in 2029 under the current policy regime. Fully implementing CbCR and AEoI decreases the expected tax gap of 2029 by 16.4% to € 113.5 billion. As for the effectiveness of both policies, AEoI is demonstrated to be effective against tax evasion but not against tax avoidance, making the total tax losses € 134.0 billion (a merely 1.3% decline). The expected small effect of CbCR becomes much larger in the long run, it results in € 121.2 billion tax losses which represents a decline of 10.8%. The effectiveness of CbCR is explained by its positive effect on the tax morale of individuals. Given that compliance choices are affected by international differences between legal and tax systems and by information that agents receive from other agents that surround them, compliance must be governed responsively. The model shows that short-term effects of the aforementioned regulations increase the overall compliance level, but also indicates that long-term effects could counteract the intended goals. This dissertation provides a framework that improves tax compliance without fueling tax competition in the long term. The agent-based simulation shows that without responsive regulation, tax competition intensifies and the initial increase in compliance could reverse. A differentiated policy response could increase tax compliance by 6.54%, which translates into an annual increase of € 105 billion in EU tax revenues on income, profits, and capital gains. Attractive tax legislation frequently offers higher levels of financial secrecy, which obscure corporate ownership and the origin of revenues. Besides evading and avoiding taxes, such legislation also provides opportunities for criminal organizations to launder their criminal proceeds. Anti-money laundering regulation aims to mitigate the associated risks of financial secrecy and influence how criminal networks operate. Therefore, this dissertation evaluates the effect of anti-money laundering regulation on the network structures of criminal organizations. It is expected that the AML legislation makes money laundering more difficult and forces money launderers to both specialize and compete with others, which the analysis confirms due to significant changes in the structure of money laundering networks. An adverse effect of AML legislation is that it affects non-criminal organizations too. The importance of high quality corporate registers and transparently sharing this information internationally is an important basis for detecting and prosecuting money laundering