On the welfare implications of automation

Eden, Maya; Gaggl, Paul

doi:10.1016/j.red.2017.12.003

Cited by 95 publications

(77 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The slope of the fitted line in these figures can be viewed as a rough estimate for σ, indicating that the elasticity of substitution may lie somewhere between 1.5 and 3. Eden and Gaggl (2018), using a somewhat different nesting than that employed here, conclude that the elasticity of substitution between labor and information-andcommunication-technology (ICT) capital has increased rapidly since the late 90s, rising from 2.5 to 3.3. Calibrating their U.S. data to a production function similar to that employed here, Berg et al (2018) find an elasticity between ICT capital and unskilled labor of 2.1.…”

Section: Calibration Of the Initial Steady Statesmentioning

confidence: 82%

“…11 Empirical evidence that speaks directly to the sort of macro model we employ here is scarce but suggestive. Eden and Gaggl (2018) distinguish between traditional capital and the subset that embodies information and communication technology (ICT). Calibrating to data for 1950-2013 for the United States, they conclude that ICT capital is more highly substitutable with labor than traditional capital, with some evidence that it has been increasingly so over time.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Will the AI Revolution Cause a Great Divergence?

Alonso¹,

Berg²,

Kothari³

et al. 2020

IMF Working Papers

View full text Add to dashboard Cite

This paper considers the implications for developing countries of a new wave of technological change that substitutes pervasively for labor. It makes simple and plausible assumptions: the AI revolution can be modeled as an increase in productivity of a distinct type of capital that substitutes closely with labor; and the only fundamental difference between the advanced and developing country is the level of TFP. This set-up is minimalist, but the resulting conclusions are powerful: improvements in the productivity of “robots” drive divergence, as advanced countries differentially benefit from their initially higher robot intensity, driven by their endogenously higher wages and stock of complementary traditional capital. In addition, capital—if internationally mobile—is pulled “uphill”, resulting in a transitional GDP decline in the developing country. In an extended model where robots substitute only for unskilled labor, the terms of trade, and hence GDP, may decline permanently for the country relatively well-endowed in unskilled labor.

show abstract

Section: Calibration Of the Initial Steady Statesmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Will the AI Revolution Cause a Great Divergence?

Alonso¹,

Berg²,

Kothari³

et al. 2020

IMF Working Papers

View full text Add to dashboard Cite

show abstract

“…The third is on the drivers of the labor share. This literature has focused on the roles of technological progress in equipment goods and implied substitution of capital for routine labor tasks (Karabarbounis and Neiman, ; Alvarez‐Cuadrado, Long and Poschke ; Eden and Gaggl ; Acemoglu and Restrepo ; Dao et al. ), rising concentration and pricing power across markets (Autor et al.…”

mentioning

confidence: 99%

The Aggregate and Distributional Effects of Financial Globalization: Evidence from Macro and Sectoral Data

Furceri¹,

Loungani²,

Ostry³

2019

J of Money Credit Banking

View full text Add to dashboard Cite

We take a fresh look at the aggregate and distributional effects of policies to liberalize international capital flows—financial globalization. Both country‐ and industry‐level results suggest that such policies have led on average to limited output gains while contributing to significant increases in inequality. The country‐level results are based on 228 capital account liberalization episodes spanning 149 advanced and developing economies from 1970 to the present. Difference‐in‐difference estimation using industry‐level data for 23 advanced economies suggests that liberalization episodes reduce the share of labor income, particularly for industries with higher external financial dependence, higher natural propensity to use layoffs to adjust to idiosyncratic shocks, and higher elasticity of substitution between capital and labor.

show abstract

“…The OECD estimates that 80% of the fall in labour's share across OECD economies is due to the growth of information and computing technologies (OECD ). The World Bank estimates it at about 50% (with various policy and institutional factors contributing as well) (Eden and Gaggl , as well as Karabarbounis and Neiman ).…”

Section: Other Contributing Factors To Income Inequality Changementioning

confidence: 99%

“…(, , , ), Chetverikov et al. (), Cortes (), Eden and Gaggl (), Goos et al. (), Green and Sand (), Keller and Utar () and Warman and Worswick ().…”

unclassified

Changing income inequality: A distributional paradigm for Canada

Beach

2016

Canadian J of Economics

View full text Add to dashboard Cite

This paper examines the major changes in income inequality in Canada since the 1970s and collects them as a distributional paradigm for Canada. It focuses on labour market changes in terms of shares of workers and earnings shares for lower earners, middle‐class workers and higher earners in a flexible general framework. Polarization of full‐time workers, loss of middle‐class earnings share and increase in a higher earnings gap are highlighted. Changing returns to human capital, role of demographics and cohort effects and declining labour share are examined. The paper also reviews evidence of changing economic mobility and estimating the role of inequality of opportunity.

show abstract

On the welfare implications of automation

Cited by 95 publications

References 44 publications

Will the AI Revolution Cause a Great Divergence?

Will the AI Revolution Cause a Great Divergence?

The Aggregate and Distributional Effects of Financial Globalization: Evidence from Macro and Sectoral Data

Changing income inequality: A distributional paradigm for Canada

Contact Info

Product

Resources

About