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Technological unemployment and income inequality: a stock-flow consistent agent-based approach

Author

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  • Laura Carvalho

  • Corrado Di Guilmi

Abstract

The paper presents a stock-flow consistent agent-based model with effective demand, endogenous credit creation, and labor-saving technological progress. The aim is to study the joint dynamics of both personal and functional distribution of income as a result of technological unemployment, together with the effect on household debt. Numerical simulations show the potentially destabilizing effect of technological unemployment and reveal that an increase in the profit share of income amplifies the negative effect of income inequality on business cycle and growth. The sensitivity analysis provides indications on the effectiveness of possible mixes of fiscal and redistributive policies, but also demonstrates that the effectiveness of policy measures is strongly dependent on behavioral and institutional factors.

Suggested Citation

  • Laura Carvalho & Corrado Di Guilmi, 2019. "Technological unemployment and income inequality: a stock-flow consistent agent-based approach," Working Papers, Department of Economics 2019_04, University of São Paulo (FEA-USP).
    • Handle: RePEc:spa:wpaper:2019wpecon04
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    Cited by:

    1. Patrick Mellacher, 2021. "Growth, Inequality and Declining Business Dynamism in a Unified Schumpeter Mark I + II Model," Papers 2111.09407, arXiv.org, revised Nov 2023.
    2. Yuri Lima & Carlos Eduardo Barbosa & Herbert Salazar dos Santos & Jano Moreira de Souza, 2021. "Understanding Technological Unemployment: A Review of Causes, Consequences, and Solutions," Societies, MDPI, vol. 11(2), pages 1-17, May.
    3. Schütz, Bernhard & Reiter, Oliver & Landesmann, Michael & Jovanović, Branimir, 2025. "Structural change, income distribution and unemployment related to Covid-19: An agent-based model," Structural Change and Economic Dynamics, Elsevier, vol. 74(C), pages 61-84.
    4. Gregor Semieniuk & Emanuele Campiglio & Jean‐Francois Mercure & Ulrich Volz & Neil R. Edwards, 2021. "Low‐carbon transition risks for finance," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 12(1), January.
    5. Schiozer, Nikolas & Lima, Gilberto Tadeu & Alexandre, Michel, 2026. "Heterogeneity in pricing behavior in hybrid DSGE-ABM macrodynamics," Economic Modelling, Elsevier, vol. 155(C).
    6. Lilian N. Rolim & Carolina Troncoso Baltar & Gilberto Tadeu Lima, 2023. "Income distribution, productivity growth, and workers’ bargaining power in an agent-based macroeconomic model," Journal of Evolutionary Economics, Springer, vol. 33(2), pages 473-516, April.
    7. Canh Phuc Nguyen & Binh Quang Nguyen & Duyen Thuy Le Tran, 2023. "Economic complexity and income inequality: New evidence of a nonlinear effect," Social Science Quarterly, Southwestern Social Science Association, vol. 104(4), pages 829-868, July.
    8. Guilmi, Corrado Di & Fujiwara, Yoshi, 2022. "Dual labor market, financial fragility, and deflation in an agent-based model of the Japanese macroeconomy," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 346-371.
    9. Rolim, Lilian & Carvalho, Laura & Lang, Dany, 2024. "Monetary policy rules and the inequality-augmented Phillips curve," Economic Modelling, Elsevier, vol. 139(C).

    More about this item

    Keywords

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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E25 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Aggregate Factor Income Distribution

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