Labor Share and Growth in the Long Run

Abstract

This paper establishes some stylized facts of the long-run relationship between growth and labor shares using historical data for the USA (1898–2010), the United Kingdom (1856–2010), and France (1896–2010). Performing individual country time–frequency analysis, we demonstrate the existence of long-term cycles in labor share of 30–50 years explaining a major part of the variance in the data. Further, the impact of labor share on growth changes sign with the frequency considered from negative at high frequencies to positive at low frequencies. Finally, the positive coefficient associated with the labor share at low frequencies increases over time.

On multi-sector and multi-technique models, production functions and Goodwin cycles: a reply to Libman

“…Charpe et al (2019) find that the wage share leads growth positively at very low frequencies, which is inconsistent with the Goodwin pattern.…”

“…The period of the Goodwin pattern is also imprecise, although there seems to be a broad consensus that it is a high-frequency phenomenon which is characteristic of (relatively) short cycles in the economy but not evident in the longer term (Flaschel and Groh, 1995;Harvie, 2000;Zipperer and Skott, 2011;Blecker, 2016;Barrales and von Arnim, 2017;Charpe et al, 2019;Araujo et al, 2019). 13 In reality, then, the Goodwin pattern itself does not strictly conform to the behaviour of either a closed orbit or a limit cycle.…”

Endogenous Education and Long-Run Factor Shares

“…The main text focuses soley on educational attainment. But in the appendix we show that we can achieve similar results in a model of occupational choice 8. We assume that families maximize dynastic utility, including the discounted well-being of unborn generations.…”

“…7 Our economy is populated by a unit mass of identical family dynasties. 8 The representative dynasty comprises a continuum of individuals of mass N t at time t. Each living individual generates a new member of her dynasty with a constant, instantaneous probability dt in a period of length dt and faces a constant instantaneous risk of demise dt in that same period, with > 0; 0. With these constant hazard rates of birth and death, the size of a dynasty at time t is given by N t = e ( )(t t 0 ) N t 0 .…”

Back to the past: the historical roots of labor-saving automation

“…In simple terms, with the Fourier transform, the time information carried by the signal is lost. Moreover, the Fourier transform is known to be unsuitable for analyzing non-stationary time series presenting irregular behaviors (Gallegati 2019;Charpe et al 2019).…”