Based be designed in Vensim. Inputs of this

Based onthe literature review one could notice that there is not a research thatexplores the policy space of the EU under the possible scenarios of Brexit.

Thus, this leads us to formulate the following research question based on theproblem statement:”What financial policies could the EU adoptduring and after the Brexit to protect the Union’s economy?” 3.2Sub-questionsTostructure the answer to this research question, sub-questions have to bedevised. Our objective is to identify the most suitable financial policies forthe EU in order to protect its economy. To reach the answer to this questionthe following 6 sub-questions have to be answered first:•    What are the implications of Brexit to theEU and the EU under the 3 given scenarios?•    What are the possible financial policies ofthe EU and the UK to deal with the implication of the imminent Brexit?•    What are the implications of each policyimplemented by one actor to the other one?•    What can external instruments affect thepremises of the Brexit and how?•    How are the implications of Brexit and theUnion’s real economy correlate?•    How do the possible financial policies ofthe EU and the UK affect their real economy?    4.Research ApproachThecombination of the above-mentioned questions is going to help our research toanswer the principal question. In order toanswer the first 4 questions, a multi-actor analysis is going to take place.

This way we will be able to map objectives, means and criteria that our mainagents (the EU and the UK) have. Dependent on the literature and to alreadyexisting research, an actor analysis, a means-end diagram and an objectivestree are going to be developed for each actor of the system. This work willhelp us develop a multi-actor system’s diagram, where also external actors’actions are going to affect the criteria and the actors of our system.To answerthe fifth question an SD (system dynamics) model is going to be designed inVensim. Inputs of this model would be published data and information (marketstatus, trading indices, GDPs etc.

). This model will provide us with insightregarding the impact of the financial sector and real economy by utilizingalready existing research such as agent correlations (Samitas, Polyzos, & Siriopoulos, 2017), short-term correlations(Baker, Carreras, Kirby, Meaning, & Pigott, 2016) and long-termcorrelations (Ebell, Hurst, & Warren, 2016) to describe the relations between the financial sector and the realeconomy and also set up the premises to explore the impact of possible policies.The lastsub-question refers to the impact of the possible policies to the real economy.This last part will combine all the findings from previous steps of theproject. The means from the multi-actor analysis will act as the financialpolicies, the objectives as Key Performance Indicators (KPIs) for our systemand the model as the basis of research for an exploratory modelling project.

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Byutilizing EMA Workbench, which is a Python library designed by researchers inTU Delft for exploratory modelling, deep uncertainty is going to be introducedin our research and by using the above-mentioned KPIs as optimizers we willattempt to attain an answer to the principal question posed in this researchproject.