We propose two novel methods to “bring Agent Based Models (ABMs) to the data”. First, we describe a Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time series using data obtained from the simulation of an ABM. We apply our methodological contributions to a specific medium-scale macro ABM.
2020 / Ruse, M.G., A. Samson and S. Ditlevsen
Inference for biomedical data by using diffusion models with covariates and mixed effects
Journal of the Royal Statistical Society, Series C: Applied Statistics, Vol. 69, Issue 1, 167-193
Neurobiological data such as electroencephalography measurements pose a statistical challenge due to low spatial resolution and poor signal‐to‐noise ratio, as well as large variability from subject to subject. We propose a new modelling framework for this type of data based on stochastic processes. Stochastic differential equations with mixed effects are a popular framework for modelling biomedical data, e.g. in pharmacological studies. Whereas the inherent stochasticity of diffusion models accounts for prevalent model uncertainty or misspecification, random‐effects model intersubject variability. The two‐layer stochasticity, however, renders parameter inference challenging. Estimates are based on the discretized continuous time likelihood and we investigate finite sample and discretization bias. In applications, the comparison of, for example, treatment effects is often of interest. We discuss hypothesis testing and evaluate by simulations. Finally, we apply the framework to a statistical investigation of electroencephalography recordings from epileptic patients. We close the paper by examining asymptotics (the number of subjects going to ∞) of maximum likelihood estimators in multi‐dimensional, non‐linear and non‐homogeneous stochastic differential equations with random effects and included covariates.
2020 / Foramitti J., Savin I. and J. van den Bergh
Emission tax vs. permit trading under bounded rationality and dynamic markets
A price on emissions can be achieved through an emission tax or permit trading. The advantages and drawbacks of either instrument are debated. We present an agent-based model to compare their performance under bounded rationality and dynamic markets. It describes firms that face uncertainty about future demand and prices; use heuristic rules to decide production levels, trading prices, and technology adoption; and are heterogeneous in terms of production factors, abatement costs, and trading behavior. Using multiple evaluation criteria and a wide range of parameter values, we find that the main difference between the two policies lies in the fact that permit prices fall after successful abatement. This can lead to higher production levels under permit trading, but can also drive emission-efficient firms out of the market. Scarcity rents under permit trading can further create higher profit rates for firms, the extent of which is shown to depend on the mechanisms for market-clearing and initial allocation.
2020 / Heide-Jørgensen, M.P., S. Blackwell, T. Williams, M.H.S. Sinding, M. Skovrind, O.M. Tervo, E. Garde, R. Hansen, N.H. Nielsen, M.C. Ngo and S. Ditlevsen
Some like it cold: Temperature dependent habitat selection by narwhals
The narwhal (Monodon monoceros) is a high‐Arctic species inhabiting areas that are experiencing increases in sea temperatures, which together with reduction in sea ice are expected to modify the niches of several Arctic marine apex predators. The Scoresby Sound fjord complex in East Greenland is the summer residence for an isolated population of narwhals. The movements of 12 whales instrumented with Fastloc‐GPS transmitters were studied during summer in Scoresby Sound and at their offshore winter ground in 2017–2019. An additional four narwhals provided detailed hydrographic profiles on both summer and winter grounds. Data on diving of the whales were obtained from 20 satellite‐linked time‐depth recorders and 16 Acousonde™ recorders that also provided information on the temperature and depth of buzzes. In summer, the foraging whales targeted depths between 300 and 850 m where the preferred areas visited by the whales had temperatures ranging between 0.6 and 1.5°C (mean = 1.1°C, SD = 0.22). The highest probability of buzzing activity during summer was at a temperature of 0.7°C and at depths > 300 m. The whales targeted similar depths at their offshore winter ground where the temperature was slightly higher (range: 0.7–1.7°C, mean = 1.3°C, SD = 0.29). Both the probability of buzzing events and the spatial distribution of the whales in both seasons demonstrated a preferential selection of cold water. This was particularly pronounced in winter where cold coastal water was selected and warm Atlantic water farther offshore was avoided. It is unknown if the small temperature niche of whales while feeding is because prey is concentrated at these temperature gradients and is easier to capture at low temperatures, or because there are limitations in the thermoregulation of the whales. In any case, the small niche requirements together with their strong site fidelity emphasize the sensitivity of narwhals to changes in the thermal characteristics of their habitats.
2020 / Van Den Brink, R., D. Dimitrov and A. Rusinowska
Winning coalitions in plurality voting democracies
We study the issue of assigning weights to players that identify winning coalitions in plurality voting democracies. For this, we consider plurality games which are simple games in partition function form such that in every partition there is at least one winning coalition. Such a game is said to be precisely supportive if it is possible to assign weights to players in such a way that a coalition being winning in a partition implies that the combined weight of its members is maximal over all coalitions in the partition. A plurality game is decisive if in every partition there is exactly one winning coalition. We show that decisive plurality games with at most four players, majority games with an arbitrary number of players, and almost symmetric decisive plurality games with an arbitrary number of players are precisely supportive. Complete characterizations of a partition's winning coalitions are provided as well.
2020 / Drews, S., F. Exadaktylos and J. van den Bergh
Assessing synergy of incentives and nudges in the energy policy mix
Should policy-makers combine price incentives with behavioural nudges to encourage sustainable energy behaviour? Available evidence from various behavioural sciences is scarce and inconclusive about synergy of the two instruments. This is partly due to methodological limitations. We offer a framework to overcome such limitations in future research and to guide policy-making. It includes four cases: no synergy, positive synergy, weak negative synergy, and strong negative synergy or backfire. The adoption of a policy mix is recommended in the first two cases, and may be pursued in the third case. To clarify the underlying mechanisms of the synergy, a distinction is made between crowding (in/out) of intrinsic motivations by incentives and crowding (in/out) of extrinsic motivations by nudges. This distinction turns out to be especially relevant in the case of weakly negative synergy, as here behavioural and temporal spillover effects require consideration from the policy-maker as well. We end with broader reflections regarding other policy criteria for the design of an adequate energy policy mix.
2020 / Grabisch, M. and F. Li
Anti-conformism in the threshold model of collective behavior
Dynamic Games and Applications, Vol. 10(2), 444-477
We provide a detailed study of the threshold model, where both conformist and anti-conformist agents coexist. Our study bears essentially on the convergence of the opinion dynamics in the society of agents, i.e., finding absorbing classes, cycles, etc. Also, we are interested in the existence of cascade effects, as this may constitute an undesirable phenomenon in collective behavior. We divide our study into two parts. In the first one, we basically study the threshold model supposing a fixed complete network, where every one is connected to every one, like in the seminal work of Granovetter. We study the case of a uniform distribution of the threshold, of a Gaussian distribution, and finally give a result for arbitrary distributions, supposing there is one type of anti-conformist. In a second part, we suppose that the neighborhood of an agent is random, drawn at each time step from a distribution. We distinguish the case where the degree (number of links) of an agent is fixed, and where there is an arbitrary degree distribution. We show the existence of cascades and that for most societies, the opinion converges to a chaotic situation.
2020 / Rengs, B., M. Scholz-Wäckerle and J. van den Bergh
Evolutionary macroeconomic assessment of employment and innovation impacts of climate policy packages
Journal of Economic Behavior and Organization, 169, 332-368
Climate policy has been mainly studied with economic models that assume representative, rational agents. Such policy aims, though, at changing carbon-intensive consumption and production patterns driven by bounded rationality and other-regarding preferences, such as status and imitation. To examine climate policy under such alternative behavioral assumptions, we develop a model tool by adapting an existing general-purpose macroeconomic multi-agent model. The resulting tool allows testing various climate policies in terms of combined climate and economic performance. The model is particularly suitable to address the distributional impacts of climate policies, not only because populations of many agents are included, but also as these are composed of different classes of households. The approach accounts for two types of innovations, which improve either the carbon or labor intensity of production. We simulate policy scenarios with distinct combinations of carbon taxation, a reduction of labor taxes, subsidies for green innovation, a price subsidy to consumers for less carbon-intensive products, and green government procurement. The results show pronounced differences with those obtained by rational-agent model studies. It turns out that a supply-oriented subsidy for green innovation, funded by the revenues of a carbon tax, results in a significant reduction of carbon emissions without causing negative effects on employment. On the contrary, demand-oriented subsidies for adopting greener technologies, funded in the same manner, result in either none or considerably less reduction of carbon emissions and may even lead to higher unemployment. Our study also contributes insight on a potential double dividend of shifting taxes from labor to carbon.
2020 / Van den Brink, R. and A. Rusinowska
The degree ratio ranking method for directed graphs
European Journal of Operational Research, Vol. 288(2), 563-575
One of the most famous ranking methods for digraphs is the ranking by Copeland score. The Copeland score of a node in a digraph is the difference between its outdegree (i.e. its number of outgoing arcs) and its indegree (i.e. its number of ingoing arcs). In the ranking by Copeland score, a node is ranked higher, the higher is its Copeland score. In this paper, we deal with an alternative method to rank nodes according to their out- and indegree, namely ranking the nodes according to their degree ratio, i.e. the outdegree divided by the indegree. To avoid dividing by zero, we add 1 to both the out- as well as indegree of every node. We provide an axiomatization of the ranking by degree ratio using a clone property, which says that the entrance of a clone or a copy (i.e. a node that is in some sense similar to the original node) does not change the ranking among the original nodes. We also provide a new axiomatization of the ranking by Copeland score using the same axioms except that this method satisfies a different clone property. Finally, we modify the ranking by degree ratio by taking only the out- and indegree, but by definition assume nodes with indegree zero to be ranked higher than nodes with positive indegree. We provide an axiomatization of this ranking method using yet another clone property and a maximal property. In this way, we can compare the three ranking methods by their clone property.
2019 / Altaghlibi, M. and F. Wagener
Unconditional aid and green growth
Journal of Economic Dynamics and Control, Vol. 105, 158-181
Environmentally motivated aid can help developing countries to achieve economic growth while mitigating the impact on emission levels. We argue that the usual practice of giving aid conditionally is not effective, and we therefore study aid that is given unconditionally. Our framework is a differential open-loop Stackelberg game between a fully developed leader country and a developing follower country. The leader chooses the amount of mitigation aid given to the follower, which the follower either consumes or invests in either costly non-polluting capital or cheap high-emission capital. We show that giving aid conditionally is only rarely effective and, if so, is based on a forced intertemporal savings effect. In all other cases it is ineffective at best and counterproductive at worst. Moreover, we find that the leader gives unconditional mitigation aid only when sufficiently rich or when caring sufficiently about environmental quality. If unconditional aid is given in steady state, it decreases the steady state level of high-emission capital and capital investments in the recipient country as well as the global pollution stock, but it has no effect on the levels of non-polluting capital and non-polluting investments. Transitional aid accelerates the economic growth of the follower. Moreover, we find that the increase in growth takes place in the non-polluting sector.
This website uses various cookies for optimal functionality.
In order to be able to take full advantage of the offer, you must first agree to its use.
You can choose which type of cookies you want to allow.