Arbeitspapier

The North-South divide: Sources of divergence, policies for convergence

Building upon the labour-augmented K+S modelling framework (Dosi et al., 2010, 2017, 2020), we address the analysis of the North-South divide by means of an agent-based model (ABM) endogenously reproducing divergence between two artificial macro-regions characterized by identical initial conditions in terms of productive and innovation structures, but different labour market organizations. Given the ex-ante initial conditions, we identify the role played by different functioning of the labour markets on the possible divergence across the two regions. We do find that divergences in labour market reverberate into asymmetric productive performance due to negative reinforcing feedback loop dynamics. We then confront alternative policy schemes by showing that investment policies directed at increasing machine renewal and higher substitutionary investment are the most effective in fostering the convergence process.

Sprache
Englisch

Erschienen in
Series: LEM Working Paper Series ; No. 2022/16

Klassifikation
Wirtschaft
Computational Techniques; Simulation Modeling
Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
Thema
Agent-Based Models
Technology Gap
Labour Market

Ereignis
Geistige Schöpfung
(wer)
Fanti, Lucrezia
Pereira, Marcelo C.
Virgillito, Maria Enrica
Ereignis
Veröffentlichung
(wer)
Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM)
(wo)
Pisa
(wann)
2022

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Fanti, Lucrezia
  • Pereira, Marcelo C.
  • Virgillito, Maria Enrica
  • Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM)

Entstanden

  • 2022

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