Agent-based modeling has been largely overlooked in international legal research, even though it could be used to gain insights into the highly complex processes of state behavior relevant to international law that can only be insufficiently addressed with other methods. On the basis of a concrete application - state compliance with European Court of Human Rights judgments - we show the applicability of agent-based modeling to international legal research. We discuss its implications for two levels of analysis: (1) understanding the drivers of state behavior, which contributes to the international law research with unitary state actors at its center, and (2) within state dynamics and their influence during the compliance process, which breaks the black box of the state. Agent-based models addressing the questions that arise on these levels can take a variety of shapes. We provide one line of thought on the set-up of an agent-based model for each of the two levels of analysis and discuss expected difficulties. Finally, we provide an outlook on how these aspects might come together in exploring how compliance rates can be bettered.
Recent years have seen important developments in methodological approaches in international and European legal scholarship. From quantitative to qualitative social sciences approaches, historical and anthropological perspectives, new methodologies have brought new insights into how international law and its actors operate. What remains unclear, however, is to what extent the existing methodologies can explain highly complex processes of state behavior relevant to international law. Such behavior evolves through time and depends on the action and cooperation of heterogeneous actors acting at different levels – from state representatives, government officials, NGOs and state organs, international institutions, etc. In this paper, we propose that agent-based modeling, which has been largely overlooked as a method for legal research, is suited to gather further insights into these processes and lead us to new discoveries.
We show the applicability of agent-based modeling using concrete problems in international legal research: the study of state compliance with European Court of Human Rights (ECtHR) judgments. Empirical research shows that despite the fact that judgments of the ECtHR are binding for all current 46 Council of Europe member states, more than half of its decisions remain unenforced. We show how ABM can contribute to a better understanding of state behavior and within state dynamics during the compliance process.
The European Court of Human Rights (ECtHR) is the chief institution of the Council of Europe for upholding the European Convention on Human Rights (ECHR). Since its inception in 1959, the Court has been facing an increasing case load with more than 40,000 new applications each year. The Court’s main task is to determine whether a violation of a Convention right has occurred in any of the 46 Council of Europe member states, which have recognized the jurisdiction of the court. Although the Convention makes the judgments of the Court directly binding on the states, in practice more than half of all cases rendered by the court remain unenforced.
Decision making by the ECtHR and the subsequent implementation of judgments are highly
complex processes, which include a wide range of actors. The most central – aside from Court and
applicant (plaintiff) – is the Committee of Ministers (CM), which consists of representatives of all
member states and is the institution which ultimately decides whether a country has complied with a
judgment. Further complicating the process is the fact that when the Court rules a violation of the
Convention has occurred, it only determines damages to be paid to the plaintiff, but remains silent
regarding non-monetary remedies that the country has to undertake to rectify the situation which led to
the human rights abuse in the first place (for a discussion of monetary damages within the ECHR
system, see [
For the Human Rights Nudge Project, a multitude of key data on states’ compliance with ECtHR judgments has been collected. Among that data are the type of violations raised in each case – e.g., the article of the European Convention on Human Rights that the state has (allegedly) breached; whether a judgment was complied with; the duration it took for a state to comply with the judgment; the damages awarded by the Court; the remedies chosen by the state to address the judgment. This data has been collected for the years 1980-2020. In addition, for a selected number of case studies, a thorough analysis of the actors and the networks that comprise the state’s compliance apparatus was conducted. In the following, we will detail the insights gathered from this data, the questions that they leave unanswered, and how agent-based modeling might contribute to answering them.2
When pulling together all instances of (non-)compliance between 1980 and 2020, in Figure 1, we see that the average compliance rate, i.e., the compliance rate averaged over all member states and plotted by year, shows a wave like development of compliance.
Notably, we see that these waves not only occur at times when many new states enter the European Convention of Human Rights (ECHR), i.e., they do not seem to solely be driven by new members to the ECHR. Zooming in, as Figure 2 does, it is evident that existing member states also contribute to the wave structure of compliance rates. The former might have a simple explanation: when a country joins the Convention and accepts the Court’s jurisdiction, its internal practices may not (yet) be consistent with the Convention. Even if it is willing to address human rights abuses, the new state may not be able to increase its capacity to do so immediately, which impedes the implementation of subsequent ECtHR judgments. However, given that also established members contribute to the wave structure of compliance rates, this warrants a closer look. 2 See www.humanrightsnudge.com for more information. This data provides the basis for all following figures and graphs. For inquiries into data access, please contact veronika.fikfak@jur.ku.dk.
Figure 2 shows the compliance rates of (at the time) all member states of the European Convention on Human Rights in the years 2000, 2010, and 2020. Most of the new member states, which joined the Convention after 2000, have a very low compliance rate upon entering. Almost all of them steadily increase their compliance rates up until 2020. This is not the case for established member states, who in many cases exhibit decreased compliance before an overall increase in compliance towards the end of the observed period.
Empirical research has proven very useful for revealing different compliance patterns. The question that it mostly leaves open is what drives these compliance patterns. Some answers to this question can be given by case studies and through interviews with experts and practitioners. That, however, does not account for the scaling up of the compliance mechanisms and the interactions of decisions. ABM is especially useful here, as it can facilitate a more holistic view of the system, which connects individual behavioral theories and motivations with the overall outcome of many compliance processes running in parallel. We are currently investigating different behavioral assumptions for states within the ECtHR system to see how those affect compliance dynamics as states learn from each other and adapt strategies to deal with ECtHR judgments.
To do so, we plan to model states, cases, and the CM as agents. Each case signifies a certain
violation of the law; if it is litigated, the court decides on its merits and sets the level of damages. The
state, against whom the case is directed, decides to pay damages (or not) and assesses whether
nonmonetary remedies (like adoption of legislation) are appropriate to prevent future violations. The CM,
which consists of representatives from all 46 member states, decides whether remedies are suitable and
have been implemented sufficiently. Dependent variables are the selected set of remedies and whether
the case has been closed (compliance) or not (non-compliance). Independent variables are the
behavioral mechanisms which we aim to vary: (1) states adopt remedies randomly, (2) states imitate
successful compliance processes of other states, with the potential reference group being neighbors or
trade connections, etc., (3) in line with international relations theory on norm diffusion and norm
entrepreneurship, states set expectations for their own compliance and that of others and police other
states’ behavior if necessary (for the latter, see for example [
Taking state compliance with international court rulings, rather than state compliance with
international law as the object of research, allows for concrete occasions and a timeline with discreet
steps for state actors to make decisions, as well as providing a binary outcome variable, so that the
application of the method seems well suited. Nevertheless, there are many limitations to be considered:
chief among them is the fact that choosing behavioral theories and their concrete implementation in the
model is notoriously difficult (see [
Secondly, with this modelling agenda, we stay firmly within the research that assumes unitary state actors, which naturally misses a lot of nuances in how states react and how state behavior is internally conditioned. However, this is in line with much of current international law research on state compliance (not only with ECtHR judgements), so that we can contribute new insights at that level of abstraction. In the following, we take two aspects of internal state dynamics that are relevant to compliance and show how ABM might contribute insights there.
Conventional legal research methods provide insights into specific states’ compliance apparatuses –
and raise arguments that compliance depends on state capacity, rule of law index, state’s GDP [
Besides the governmental structure which reacts to ECtHR judgments, non-governmental
organizations and actors are a central force in states’ compliance with ECtHR judgments.
Nongovernmental organizations (NGOs) intervene in state compliance procedures via official channels and
unofficial channels. The former are determined by Rule 9 of the Rules of the Committee of Ministers
for the supervision of the execution of judgments and of the terms of friendly settlements. The latter may
include media campaigns and the like, i.e., interventions which are not governed by legal provisions
within the ECHR. Empirical investigations show the effect of NGO Rule 9 interventions on the decision
making of the CM and the Execution Department, the body supporting the CM, respectively [
We are currently investigating the dynamics of NGO intervention in compliance procedures [
A number of problems arise from this set-up, chiefly perhaps the definition of what constitutes a
successful intervention – it is difficult to assess the contribution that an NGO has made to the
compliance process, and correspondingly difficult to translate it into traceable model outcomes.
Secondly, the translation of qualitative research (interviews, text analysis) and legal norms into
mechanisms within the model presents a challenge, which is well-documented and has been tackled for
other fields of application [
We use the case of states’ compliance with ECtHR judgments and the empirical work on the subject as an example to show how agent-based modeling could be a beneficial addition to the international legal scholarship toolbox. Not only can it help us understand observable (non-) compliance patterns better, it can also provide insights into the state apparatus that lead to such patterns and the role that non-state actors have in the compliance process.
Eventually, understanding states’ behavior, and how it depends on their relative location, past
behavior and internal compliance apparatus should help us in determining potential remedies for poor
compliance performances within the European Human Rights regime. Studies have suggested different
approaches to such remedies – from sanctioning states to the use of rewards (for a comprehensive
discussion of "carrots and sticks" in international relations, see [
Drawing on the literature on agent-based modeling for policy making and its pitfalls (see for
example, [23]), in the future, interventions for increasing state compliance could be designed and tested.
Those studies which we sketched above would give us an understanding of the relevant factors within
compliance dynamics, which could then be varied systematically on order to understand the
comparative effects of different interventions on compliance rates while keeping all else constant.
Understanding the interdependencies of state behavior might also enable us to make more detailed
recommendations about norm nudges and allow us to use sociological studies on normative change and
norm entrepreneurs (see [
The work on this article was funded by the European Research Council (»ERC Human Rights Nudge« 803981). Additionally, KL is undertaking her PhD research, which this project is a part of, at the Humboldt Chair for Law and Economics, Legal Theory, Public International Law and European Law at the Institute of Law and Economics, University of Hamburg.
We thank the organizers and participants of the AMPM Workshop at the JURIX 2021 Conference, as well as three anonymous reviewers, for helpful comments and suggestions.
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