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Growth, unemployment and heterogeneity

  • Piero Ferri
  • Annalisa Cristini
  • Anna Maria VariatoEmail author
Regular Article
  • 4 Downloads

Abstract

The paper analyzes unemployment in a medium-run growth model, where aggregate demand and supply interact, using a top-down approach. The aim of the essay is the study of a nonlinear system where both aggregate demand and supply are endogenous and generate bounded unemployment, followed by a methodological effort direct to identify possible lines of convergence with the agent based models (ABM) approach. This is a by-product of the presence of heterogeneity in the model. Heterogeneity acts through two different channels and operates among class of agents: it comes into the aggregate consumption function where households are assumed employed or unemployed; it changes the learning process of pessimists and optimists. The analysis is carried on through simulations. The resulting system is fairly stable to changes in main structural parameters. On one hand, autonomous demand drives the dynamics of the system, while heterogeneity in the consumption function, due to the presence of unemployment, strengthens the links with supply aspects. On the other hand, both the rate of growth of labor productivity and labor supply are endogenous. Two major results are obtained. First, unemployment allows the so called Harrodian reconciliation between aggregate demand and supply. Second, unemployment remains bounded meaning that the interaction between aggregate demand and supply thwarts instability. These results are in keeping with those obtained by means of a bottom-up approach, typical of ABM. Possible explanations and implications of this convergence are put forward and open the venue to further deepening of complementarities among the two modeling strategies.

Keywords

Bounded unemployment Medium-run growth Endogenous supply Heterogeneity Instability Learning Top-down and bottom-up methodologies 

JEL Classification

E32 E12 J2 

Notes

Acknowledgements

We wish to thank two anonymous referees for stimulating suggestions and S. Fazzari (Washington University) for inspiring insights. We also thank the participants to the session of the WEHIA conference at the Catholic University of Milan. Financial support from the University of Bergamo is gratefully acknowledged.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Emeritus Professor, Department of Management Economics and Quantitative MethodsUniversity of BergamoBergamoItaly
  2. 2.Department of Management Economics and Quantitative MethodsUniversity of BergamoBergamoItaly

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