The U.S. Labor Income Share and Automation Shocks

Charalampidis, Nikolaos

doi:10.1111/ecin.12829

Cited by 16 publications

(9 citation statements)

References 119 publications

(250 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among the ICT studies, four of them rely on regression analyses (Autor et al, 1998;Breemersch et al, 2019;Fonseca et al, 2018;O'Mahony et al, 2021), one study conducted a simulation exercise (Charalampidis, 2020) and another one relies on descriptive statistics (Borland and Coelli, 2017). Charalampidis (2020) studied automation technology shocks (while not providing much detail about the measurement of these shocks) and analyzed their interaction with aggregate fluctuations of the labor share. While this study found that technology shocks explain a large share of the fluctuations, it remains inconclusive with regards to the longer term impact of these shocks.…”

Section: Studies With Ambiguous Findings and Indirect Evidencementioning

confidence: 99%

Technology and jobs: A systematic literature review

Hötte¹,

Somers²,

Theodorakopoulos³

2022

Preprint

View full text Add to dashboard Cite

Does technological change destroy or create jobs? New technologies may replace human workers, but can simultaneously create jobs if workers are needed to use these technologies or if new economic activities emerge. Furthermore, technology-driven productivity growth may increase disposable income, stimulating a demand-induced expansion of employment. To synthesize the existing knowledge on this question, we systematically review the empirical literature on the past four decades of technological change and its impact on employment, distinguishing between five broad technology categories (ICT, Robots, Innovation, TFP-style, Other). Overall, we find across studies that the labor-displacing effect of technology appears to be more than offset by compensating mechanisms that create or reinstate labor. This holds for most types of technology, suggesting that previous anxieties over widespread technology-driven unemployment lack an empirical base, at least so far. Nevertheless, low-skill, production, and manufacturing workers have been adversely affected by technological change, and effective up-and reskilling strategies should remain at the forefront of policy making along with targeted social support systems.

show abstract

Section: Studies With Ambiguous Findings and Indirect Evidencementioning

confidence: 99%

Technology and jobs: A systematic literature review

Hötte¹,

Somers²,

Theodorakopoulos³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The utility function does also assume concavity with respect to t, which represents the idea that households tend to smooth consumption patterns over the life cycle, preferring a stable consumption over time rather than one with strong fluctuations (see, e.g., Romer, 1990: S88;Aghion & Howitt, 1992: 327;Barro and Sala-y-Martin, 2004: 87). 5 Empirical evidence on the relationship between technological change and the labor income share is presented among others by Briguglio and Vella (2014), Charalampidis (2020) and Kim and Kim (2020). Zuleta and Young (2013) and Mendieta-Muñoz et al (2021) show that the decline of labor share of income is however driven by innovations within manufacturing industries, and not in the service sectors.…”

Section: E N D N O T E Smentioning

confidence: 99%

“…55Empirical evidence on the relationship between technological change and the labor income share is presented among others by Briguglio and Vella (2014), Charalampidis (2020) and Kim and Kim (2020). Zuleta and Young (2013) and Mendieta‐Muñoz et al.…”

mentioning

confidence: 99%

Innovation and social welfare: A new research agenda

Castellacci

2022

Journal of Economic Surveys

View full text Add to dashboard Cite

Innovation research is motivated by the understanding that innovation contributes to address societal challenges and foster welfare. Extant research in this field has however adopted a rather narrow definition of social welfare, which focuses on economic performance and material wellbeing, and that mostly disregards distributional impacts of innovation. This paper outlines a new research agenda that will investigate the impacts of innovation on individuals' well-being and aggregate social welfare. The new research program has two major pillars. First, it adopts a broader notion of agents' well-being that comprises also non-economic factors and capabilities alongside income and material wealth. Second, it argues that welfare analyses of innovation must explicitly take into account equity and social justice in addition to efficiency and economic performance. This new research agenda opens up several novel questions for future innovation research and policy-making, pointing to the existence of trade-offs and dilemmas between efficiency and equity, and between short-and long-run impacts of innovation on social welfare.

show abstract

“…In this section, we use the model to investigate the effects of the new automatic technology on the functional distribution of income. A large and increasing body of the literature has focused on the implications of automation for labor compensation and inequality, suggesting also that automation is one of the factors originating the decline in labor share over the last decades (Graetz and Michaels, 2018;Charalampidis, 2020). Indeed, the searching for an explanation on this issue remains one of the fundamental macroeconomic topics nowadays.…”

Section: Automatic Capital and The Functional Distribution Of Incomementioning

confidence: 99%

Automation, automatic capital returns, and the functional income distribution

Casas

Torres

2021

Economics of Innovation and New Technology

View full text Add to dashboard Cite

This paper studies the economic implications of automation. We consider that automation is affected by disruptive technologies which entail a structural change consisting in the introduction of a new physical capital input (a combination of artificial intelligence and autonomous robots), additional to "traditional" capital assets and labor. This new "automatic" physical capital is assumed to carry out production activities without the need to be combined with labor. We propose a simple production function and show that the consequences of automation depend on the combination of the automatic capital adoption rate and the elasticity of substitution between traditional and automatic technology. We find out that, if the adoption rate is below a threshold that matches the marginal productivity of automatic capital, little effects are derived from automation, independently of the elasticity of substitution of the new capital to the traditional capital and labor. However, if the automatic capital adoption rate is above the threshold level and the elasticity of substitution is higher enough, the automation process can lead to a robocalypse scenario with a total shift of both traditional capital and labor. We estimate, through the benchmark calibration of the model, that the adoption rate threshold for automatic capital is about 22.5%.

show abstract

The U.S. Labor Income Share and Automation Shocks

Cited by 16 publications

References 119 publications

Technology and jobs: A systematic literature review

Technology and jobs: A systematic literature review

Innovation and social welfare: A new research agenda

Automation, automatic capital returns, and the functional income distribution

Contact Info

Product

Resources

About