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‘Kaldor Facts’ and the decline of Wage Share: An agent based-stock flow consistent model of induced technical change along Classical and Keynesian lines

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This paper introduces the classical idea about the so-called directed and induced technical change (ITC) within a Keynesian demand-side and evolutionary endogenous growth model in order to analyse the interplay… Click to show full abstract

This paper introduces the classical idea about the so-called directed and induced technical change (ITC) within a Keynesian demand-side and evolutionary endogenous growth model in order to analyse the interplay between technical change, long-run economic growth and functional income distribution. The ITC process is analysed within an Agent-Based Stock-Flow Consistent (AB-SFC) model, wherein credit-constrained heterogeneous firms choose both the intensity and the direction of innovation towards a labour- or capital-saving choice of technique. In the long-run, the model reproduces the so-called ‘Kaldor stylised facts’ (i.e. a purely labour-saving technical change process), however during the transitional phase the model shows a labour-saving/capital-using innovation pattern, as the aggregate output-capital ratio decreases until it stabilises in the long-run, and the labour share persistently decline as observed during the last decades in many advanced (and developing) economies. Within the present model, we can ascribe these results mainly to the effect exerted by the interplay between directed and biased technical change, the process of wage formation and the dynamics of aggregate demand. In order to stress the effective role of the innovation bias on the model dynamics, the baseline scenario has been compared with a ‘counterfactual’ scenario wherein ‘neutral’ technical progress is at work. The main findings are also confirmed by computing a sensitivity investigation on the key parameters shaping innovation and wage formation process.

Keywords: model; technical change; induced technical; wage; agent based

Journal Title: Journal of Evolutionary Economics
Year Published: 2020

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