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What output-capital ratio to adopt for macroeconomic calibrations?

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  • Reiner Franke

Abstract

Regarding the output-capital ratio in heterodox macroeconomic simulation studies, a surprisingly wide range of numerical values can be found. The paper discusses quarterly US data that are publicly available where, in order to capture depreciation, the construction of the capital stock by the perpetual inventory method relies on detailed estimates of its lifetime. Subsequently the paper builds up a capital stock series by alternatively having recourse to the statistics about capital consumption and furthermore determining an initial level by an assumption about the long-term growth of capital. This procedure leads to somewhat different results. In addition, the rates of depreciation and profit are studied that are implied by the two approaches. The paper closes with two numerical proposals for the steady state values of these variables and the output-capital ratio that could be readily employed for macrodynamic modelling, and that are quite different from many of the aforementioned examples.

Suggested Citation

  • Reiner Franke, 2017. "What output-capital ratio to adopt for macroeconomic calibrations?," International Review of Applied Economics, Taylor & Francis Journals, vol. 31(2), pages 208-224, March.
    • Handle: RePEc:taf:irapec:v:31:y:2017:i:2:p:208-224
    DOI: 10.1080/02692171.2016.1240153
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    References listed on IDEAS

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    Cited by:

    1. Graham White, 2023. "Autonomous demand, expectations and calibration: simulating demand led growth," Working Papers 2023-08, University of Sydney, School of Economics.
    2. Ítalo Pedrosa & Dany Lang, 2018. "Heterogeneity, distribution and financial fragility of non-financial firms: an agent-based stock-flow consistent (AB-SFC) model," Working Papers hal-01937186, HAL.
    3. Sanchez-Carrera Edgar J. & Travaglini Giuseppe & Ille Sebastian, 2021. "Macrodynamic Modeling of Innovation Equilibria and Traps," The B.E. Journal of Macroeconomics, De Gruyter, vol. 21(2), pages 659-694, June.
    4. Maria Nikolaidi, 2017. "Three decades of modelling Minsky: what we have learned and the way forward," European Journal of Economics and Economic Policies: Intervention, Edward Elgar Publishing, vol. 14(2), pages 222-237, September.
    5. Reiner Franke, 2022. "A methodological problem in a supermultiplier model with too much acceleration," Metroeconomica, Wiley Blackwell, vol. 73(1), pages 93-108, February.
    6. Franke, Reiner, 2022. "An empirical test of a fundamental Harrod-Kaldor business cycle model," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 1-14.
    7. Federico Bassi, 2020. "Chronic Excess Capacity and Unemployment Hysteresis in EU Countries. A Structural Approach," DISCE - Working Papers del Dipartimento di Economia e Finanza def091, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    8. Franke, Reiner, 2018. "Reviving Kalecki’s business cycle model in a growth context," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 157-171.
    9. Ítalo Pedrosa & Dany Lang, 2021. "To what extent does aggregate leverage determine financial fragility? New insights from an agent-based stock-flow consistent model," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1221-1275, September.

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