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. 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

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

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)

Referral hiring, endogenous social networks, and inequality: an agent-based analysis

Referral hiring, Endogenous social networks, Inequality, Agent-based model, Labor market transitions,

How do social networks contribute to wage inequality? Insights from an agent-based analysis

Dawid H, Gemkow S. How do social networks contribute to wage inequality? Insights from an agent-based analysis. Industrial and Corporate Change. 2014;23(5):1171-1200.Based on a closed agent-based macroeconomic simulation model (Eurace@Unibi) this paper analyzes whether the density of social networks influences via referrals the residual wage inequality in different skill groups. It is shown that an increase in network density leads to a polarization of firms and a concentration of workers with high specific skills at firms with high productivities (and wages) thereby enlarging within group wage inequality, but not between group wage inequality