Commit c8984687 authored by Philipp Cimiano's avatar Philipp Cimiano

minor change in abstract

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\section*{Abstract}
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We describe the result of a collaboration with the Economic Theory and Computational Economics (ETACE) group at Bielefeld University. The ETACE group applies agent modeling approaches to study dynamic equilibrium models resulting from the interaction of heterogeneous rational agents. This allows insights into the application of different industrial policy measures in different regions, the existence of varying spatial frictions on goods and labour markets, the spatial dynamics of industrial activity, technical change and growth, the micro- and macro-prudential regulations and their effects on micro-fragility and macro-financial stability, as well as financialisation of the real sector and the need for productive credit for economic development. In this paper, we describe the implementation of the FLAViz library that realizes a data analytic processing pipeline supporting the computational analysis and visualization of simulation data generated in the FLAME environment. This library is a key step towards ensuring computational reproducibility of the analyses of the available simulation data.
We describe the result of a collaboration between the Economic Theory and Computational Economics (ETACE) group at Bielefeld University and the Conquaire project. The Economic Theory and Computational Economics (ETACE) group, with a project led by Prof. van der Hoog, applies agent-based modeling approaches to study dynamic equilibrium models resulting from the interaction of heterogeneous rational agents. This allows insights into the application of different industrial policy measures in different regions, the existence of varying spatial frictions on goods and labour markets, the spatial dynamics of industrial activity, technical change and growth, the micro- and macro-prudential regulations and their effects on micro-fragility and macro-financial stability, as well as financialisation of the real sector and the need for productive credit for economic development. In this paper, we describe the implementation of the FLAViz library that realizes a data analytic processing pipeline supporting the computational analysis and visualization of simulation data generated in the FLAME environment. This library is a key step towards ensuring computational reproducibility of the analyses of the available simulation data.
\subsection*{Keywords} \label{keywords}
Computational Economics, Python, Pandas, simulation data, High-Performance Computing.
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