Autonomous demand, expectations and calibration: simulating demand led growth

Graham White

No 2023-08, Working Papers from University of Sydney, School of Economics

Abstract: The paper sets out a multi-commodity model of demand-led growth which can serve as a basis for simulation. Following Franke (2017), attention is initially on the calibration of key parameters, in particular, sectoral capital to output ratios consistent with reported estimates of the aggregate output to capital ratio. The key complexity arises from the influence of relative prices on the measured aggregate ratio and the lower limits on sectoral capital-output ratios consistent with that measure on the one hand combined with upper limits required for stability. The paper proceeds with a set of sectoral ratios as small as possible but consistent with measurement of the aggregate output-capital ratio. The model is then used to simulate responses to an autonomous demand shock in two different settings; where autonomous demand before and after the shock grows at a constant rate; and where its rate of growth is subject to random fluctuations and the shock is to its mean rate of growth. The simulation results in turn allow for a discussion of two key issues in the modelling of demand-led growth: the significance of autonomous demand including in the formation of expectations; and, the long-run convergence of utilization towards a normal rate.

Keywords: Demand-led growth; calibration; utilization (search for similar items in EconPapers)
Date: 2023-10
New Economics Papers: this item is included in nep-pke
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Citations: View citations in EconPapers (1)

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