The degree of utilisation and the slow adjustment of capacity to demand: reflections on the US Economy from the perspective of the Sraffian Supermultiplier
Guilherme Haluska, Ricardo Summa, Franklin Serrano
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引用次数: 3
Abstract
The purpose of this paper is to show that the Sraffian Supermultiplier demand-led growth model with an exogenous normal degree of capacity utilisation can be used to analyse the long-lasting reduction in the average actual degree of capacity utilisation in the US economy since the early 2000s. We follow the concept of normal degree of utilisation proposed by Ciccone and we use a simple version of the Supermultiplier model in which the adjustment of capacity to demand is slow. We show this in two steps. First, we examined the data for the industrial sector for the US economy and found no relevant change in the average-to-peak indicators, which could indicate a general reduction in the normal degree of capacity utilisation. Second, we made two simulations based on our simple Sraffian Supermultiplier model to demonstrate that (i) the process of convergence of actual utilisation to its given normal degree is slow and the model is compatible with long and lasting deviations between actual and normal utilisation after large shocks, and (ii) that successive decreases in output growth rates in the US economy since the begin of the 2000s, combined with a flexible accelerator mechanism, could explain the decrease in average utilisation.
期刊介绍:
The Cambridge Journal of Economics, founded in 1977 in the traditions of Marx, Keynes, Kalecki, Joan Robinson and Kaldor, provides a forum for theoretical, applied, policy and methodological research into social and economic issues. Its focus includes: •the organisation of social production and the distribution of its product •the causes and consequences of gender, ethnic, class and national inequities •inflation and unemployment •the changing forms and boundaries of markets and planning •uneven development and world market instability •globalisation and international integration.