Eurace@Unibi Model v1.0 User Manual

Dawid H, Gemkow S, Harting P, van der Hoog S, Neugart M. Eurace@Unibi Model v1.0 User Manual. Bielefeld: Universität Bielefeld; 2011

Eurace@Unibi Model v1.0 User Manual

Dawid H, Gemkow S, Harting P, van der Hoog S, Neugart M. Eurace@Unibi Model v1.0 User Manual. Bielefeld: Universität Bielefeld; 2011

Agent-Based Macroeconomic Modeling and Policy Analysis: The Eurace@Unibi Model

Dawid H, Gemkow S, Harting P, van der Hoog S, Neugart M. Agent-Based Macroeconomic Modeling and Policy Analysis: The Eurace@Unibi Model. In: Chen S-H, Kaboudan M, Du Y-R, eds. The Oxford Handbook of Computational Economics and Finance. New York: Oxford University Press; 2018: 490-519.Agent-based simulation models are a relatively new addition to the tool-box of macroeconomists. The aim of this chapter is to review work that has been carried out in recent years. Particularly, we present the Eurace@Unibi model and set it into perspective with other agent-based macroeconomic models. Besides presenting a sketch of the Eurace@Unibi model, we show how agent-based models can be used to identify economic mechanisms, and how we have applied them for spatial policy analysis. Our assessment is that agent-based modelers have passed the stage of a proof-of-concept. It has been shown that new kinds of insights can be obtained using such an approach complementing established modeling approaches. We conclude by pointing towards potentially fruitful areas of agent-based macroeconomic research

On the Effects of Skill Upgrading in the Presence of Spatial Labor Market Frictions: An Agent-Based Analysis of Spatial Policy Design

We report results of economic policy experiments carried out in the framework of the EURACE agent-based macroeconomic model featuring a distinct geographical dimension and heterogeneous workers with respect to skill types. Using a calibrated model able to replicate a range of stylized facts of goods and labor markets, it is examined in how far effects differ if policy measures aiming at an improvement of general skills are uniformly spread over all regions in the economy or focused in one particular region. We find that it depends on the level of spatial frictions on the labor market how the spatial distribution of policy measures affects the effects of the policy. Furthermore, we show that a reduction in spatial frictions does not necessarily improve the growth of output and household income

Eurace@Unibi Model v1.0 Source Code

Gemkow S, Harting P, van der Hoog S. Eurace@Unibi Model v1.0 Source Code. Bielefeld University; 2014.Eurace@Unibi Model v1.0.1 Source Code is compatible with xparser-0.17.1 (GSL-2.4)

The Eurace@Unibi Model: An Agent-Based Macroeconomic Model for Economic Policy Analysis

Dawid H, Gemkow S, Harting P, van der Hoog S, Neugart M. The Eurace@Unibi Model: An Agent-Based Macroeconomic Model for Economic Policy Analysis. Working Papers in Economics and Management. Vol 05-2012. Bielefeld: Bielefeld University, Department of Business Administration and Economics; 2012.This document provides a description of the modeling assumptions and economic features of the Eurace@Unibi model. Furthermore, the document shows typical patterns of the output generated by this model and compares it to empirically observable stylized facts. The Eurace@Unibi model provides a representation of a closed macroeconomic model with spatial structure. The main objective is to provide a micro-founded macroeconomic model that can be used as a unified framework for policy analysis in different economic policy areas and for the examination of generic macroeconomic research questions. In spite of this general agenda the model has been constructed with certain specific research questions in mind and therefore certain parts of the model, e.g. the mechanisms driving technological change, have been worked out in more detail than others. The purpose of this document is to give an overview over the model itself and its features rather than discussing how insights into particular economic issues can be obtained using the Eurace@Unibi model. The model has been designed as a framework for economic analysis in various domains of economics. A number of economic issues have been examined using (prior versions of) the model (see Dawid et al. (2008), Dawid et al. (2009), Dawid et al. (2011a), Dawid and Harting (2011), van der Hoog and Deissenberg (2011), Cincotti et al. (2010)) and recent extensions of the model have substantially extended its applicability in various economic policy domains, however results of such policy analyses will be reported elsewhere. Whereas the overall modeling approach, the different modeling choices and the economic rationale behind these choices is discussed in some detail in this document, no detailed description of the implementation is given. Such a detailed documentation is provided in the accompanying document Dawid et al. (2011b)

Agent-Based Macroeconomic Modeling and Policy Analysis: The Eurace@Unibi Model

Dawid H, Gemkow S, Harting P, van der Hoog S, Neugart M. Agent-Based Macroeconomic Modeling and Policy Analysis: The Eurace@Unibi Model. Working Papers in Economics and Management. Vol 01-2014. Bielefeld: Bielefeld University, Department of Business Administration and Economics; 2014.Agent-based simulation models are a relatively new addition to the tool-box of macroe- conomists. In this chapter we introduce the Eurace@Unibi model and the research that has been done within this framework. We show how an agent-based model can be used to identify economic mechanisms and how it can be applied to spatial policy analysis. Our assessment is that agent-based models in economics have passed the proof-of-concept phase and it is now time to move beyond that stage. It has been shown that new kinds of insights can be obtained that complement established modeling approaches. We conclude by pointing towards some potentially fruitful areas of agent-based macroeconomic research

Skills, Innovation, and Growth: An Agent-Based Policy Analysis

We develop an agent-based macroeconomic model featuring a distinct geographical dimension and heterogeneous workers with respect to skill types. The model, which will become part of a larger simulation platform for European policymaking (EURACE), allows us to conduct exante evaluations of a wide range of public policy measures and their interaction. In particular, we study the growth and labor market effects of various policy types that promote workers’ general skill levels. Using a calibrated model it is examined in how far effects differ if spending is uniformly spread over all regions in the economy or focused in one particular region. We find that the geographic distribution of policy measures significantly affects the effects of the policy even if total spending is kept constant. Focussing training efforts in one region is the worst policy outcome while spreading funds equally across regions generates a larger output in the long-run but not in the short-run

Agent-Based Macroeconomic Modeling and Policy Analysis: The Eurace@Unibi Model

Dawid H, Gemkow S, Harting P, van der Hoog S, Neugart M. Agent-Based Macroeconomic Modeling and Policy Analysis: The Eurace@Unibi Model. Working Papers in Economics and Management. Vol 01-2014. Bielefeld: Bielefeld University, Department of Business Administration and Economics; 2014.Agent-based simulation models are a relatively new addition to the tool-box of macroe- conomists. In this chapter we introduce the Eurace@Unibi model and the research that has been done within this framework. We show how an agent-based model can be used to identify economic mechanisms and how it can be applied to spatial policy analysis. Our assessment is that agent-based models in economics have passed the proof-of-concept phase and it is now time to move beyond that stage. It has been shown that new kinds of insights can be obtained that complement established modeling approaches. We conclude by pointing towards some potentially fruitful areas of agent-based macroeconomic research

Large-Scale Modeling of Economic Systems

Following the events of the credit crunch and the onset of a global recession, alternative ways of modeling modern economies and mechanisms for carrying out policy analysis are now an urgent priority. Traditional mathematical economics is widely viewed to have been compromised through gross simplifications with many assumptions that are now seen to be unjustified. New ways of looking at economics that are more grounded in reality are required, and agent-based computational economics is now receiving a lot of attention. Although the ideas are not new, the previous attempts to use this approach have been largely limited by the inability to model realistically large systems with millions of complex agents. Without this capability, the usefulness of the approach is limited. The EU-STREP project EURACE brought together a consortium of leading economists, experts in parallel supercomputing, and the designers of the FLAME framework to build the largest and most complete model of the European Union economy ever built