- Peter Gerbrands (1978) was born in Gouda, The Netherlands. He developed an international career in the information te... morePeter Gerbrands (1978) was born in Gouda, The Netherlands. He developed an international career in the information technology sector while completing his Bachelor in Business, IT and Management at Amsterdam University of Applied Science in 2014. He pursued his studies at the University of Amsterdam and graduated as a Master of Science in Information Studies in 2016. In October 2016 he became a Ph.D. candidate at Utrecht University School of Economics, where he completed this dissertation in 2021. The Ph.D. position was made available through the COFFERS project, funded by the European Commission's Horizon 2020 Research and Innovation Programme under grant agreement no. 727145. During this time, he served as an external researcher at `infobox Crimineel en Onverklaarbaar Vermoven' in Utrecht, The Netherlands, between 2017 and 2020. In April 2018 he was a research fellow at the Center for the Study of Democracy in Sofia, Bulgaria. His main research interests are: agent-based simulation, social network analysis, complex systems, big data analysis, and statistical learning. He applies his skills primarily for policy analysis, especially related to tax compliance and tax morale. In October 2020, he was recruited for a postdoc position at Utrecht University School of Economics where he will setup a data infrastructure with information on Dutch companies within the FIRMBACKBONE project.edit
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... more
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 lau...
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The purpose of this model is to estimate the amount of tax avoidance and tax evasion, influenced by the spillover effect that a foreign tax system has on the domestic tax compliance. By providing a stylized, representative bilateral... more
The purpose of this model is to estimate the amount of tax avoidance and tax evasion, influenced by the spillover effect that a foreign tax system has on the domestic tax compliance. By providing a stylized, representative bilateral environment that influences the individual tax compliance decision process of agents, the model provides, in contrast to reality, a fully transparent environment in which both evasion and avoidance can be directly measured.
International tax policy reforms such as Country-by-Country Reporting and Automatic Exchange of Information aim to increase tax compliance and revenues. Using a tax ecosystems perspective, this chapterapplies an agent-based simulation to... more
International tax policy reforms such as Country-by-Country Reporting and Automatic Exchange of Information aim to increase tax compliance and revenues. Using a tax ecosystems perspective, this chapterapplies an agent-based simulation to assess the effects of these reforms. We demonstrate for EU Member States and selected European countries that reforms can be counteracted by tax competition and tax spillover effects which reduce their effectiveness. The model estimates European corporate tax revenue losses from tax avoidance and evasion of €104.9 billion in 2019. Without further reforms they would increase to €135.8 billion in 2029. A complete implementation of both Country-by-Country Reporting and Automatic Exchange of Information would help to decrease the total CIT gap by 16.4 per cent to €113.5 billion in the year 2029 The model explains why the seemingly small effect of CbCR is not so small and why the effect of AEoI may not be as promising as it seems.
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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... more
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 sug- gest policies that governments may use to improve tax collections. We first describe an approach that is based on a single indi- vidual 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 addi- tional 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 simu- late 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. How- ever, these recommendations require a firm commitment from governments to their tax administrations, and these recom- mendations also cannot be introduced unilaterally by a single country but require international cooperation, especially via information sharing across borders.
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Research Interests:
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... more
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.
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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... more
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 sug- gest policies that governments may use to improve tax collections. We first describe an approach that is based on a single indi- vidual 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 addi- tional 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 simu- late 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. How- ever, these recommendations require a firm commitment from governments to their tax administrations, and these recom- mendations also cannot be introduced unilaterally by a single country but require international cooperation, especially via information sharing across borders.