Simon Gemkow

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

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).

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

Summary 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.

Labor market integration policies and the convergence of regions: the role of skills and technology diffusion

We study the role of different labor market integration policies on economic performance and convergence of two distinct regions in an agent-based model. Production is characterized by a complementarity between the quality of the capital stock and the specific skills of workers using the capital stock. Hence, productivity changes in a region are influenced both by the investment of local firms in high quality capital goods and by the evolution of the specific skill distribution of workers employed in the region. We show that various labor market integration policies yield, via differing regional worker flows, to distinct regional distributions of specific skills. Through this mechanism, relative regional prices are affected, determining the shares that the regions can capture from overall consumption good demand. There occurs a trade-off between aggregate output and convergence of regions with closed labor markets resulting in relatively high convergence but low output, and more integrated labor markets yielding higher output but lower convergence. Furthermore, results differ substantially in several respects as distinct labor market opening policies are applied.

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

The importance of referral hiring, which is workers finding employment via social contacts, is nowadays an empirically well documented fact. It also has been shown that social networks for finding jobs can create stratification. These analyses are, by and large, based on exogenous network structures. We go beyond the existing work by building an agent-based model of the labor market in which the social network of potential referees is endogenous. Workers invest some of their endowments into building up and fostering their social networks as an insurance device against future job losses. We look into the manner in which social networks and inequality respond to increased uncertainty in the labor market. We find that larger variability in firms’ labor demand reduces workers’ efforts put into social networks, leading to lower inequality.