Adapt or Withdraw? Evidence on Technological Changes and Early Retirement Using Matched Worker-Firm Data

Hægeland, Torbjørn; Rønningen, Dag; Salvanes, Kjell G.

doi:10.2139/ssrn.1548449

Cited by 10 publications

(8 citation statements)

References 23 publications

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“…In contrast, Friedberg (2003) finds partial evidence of skill obsolescence in the USA, with technological change in a worker's environment having a negative impact on computer use, but only for workers close to retirement. Similar results are obtained by Haegeland et al (2007) for Norway. Similar results are found for the Netherlands by de Koning and Gelderblom (2006).…”

Section: Introductionsupporting

confidence: 88%

“…However, unexpected variations in the rate of technological change induce workers to retire earlier. Similar results are obtained by Haegeland et al (2007) for Norway. A last strand of papers has taken a different view and investigated the impact of the introduction of ICT and innovative work practices on firms' labour demand for older workers (Aubert et al 2006;Beckmann 2007;Ronningen 2007).…”

Section: Introductionsupporting

confidence: 88%

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Age‐biased Technical and Organizational Change, Training and Employment Prospects of Older Workers

2014

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We analyse the role of training in mitigating the negative impact of technical and organizational changes on the employment prospects of older workers. Using a panel of French firms in the late 1990s, we first estimate wage bill share equations for different age groups. As a second step, we estimate the impact of ICT, innovative work practices and training on employment flows by age group in the next period. Training appears to have a positive impact on the employability of older workers, but it offers limited prospects to dampen the age bias associated with new technologies and innovative work practices

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Section: Introductionsupporting

confidence: 88%

Section: Introductionsupporting

confidence: 88%

Age‐biased Technical and Organizational Change, Training and Employment Prospects of Older Workers

2014

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“…Such a view is in line with the human capital theory, which emphasizes cost-benefit considerations in decisions to invest in human capital (Becker, 1964;Mincer, 1974) 7 . As the result of skill erosion and shorter working life horizons, older workers may respond to radical technological change by retiring early instead of investing in new skills (Ahituv and Zeira, 2011;Haegeland et al, 2007). For instance, Bartel and Sicherman (1993) found that the skill obsolescence of older workers lowers their productivity, which leads to early retirement.…”

Section: Technology-induced Early Retirement and Its Interaction With Institutionsmentioning

confidence: 99%

“…For instance, Bartel and Sicherman (1993) found that the skill obsolescence of older workers lowers their productivity, which leads to early retirement. Using rich employee-employer data for Norway, Haegeland et al (2007) reported that a firm's investment in new equipment and the introduction of new process technology increases the likelihood of early retirement by its employees. Other studies also found that the wage bill share of older workers is negatively correlated with the adoption of new technologies like ICT (Beckmann, 2007;Behaghel et al, 2014, Peng et al, 2017.…”

Section: Technology-induced Early Retirement and Its Interaction With Institutionsmentioning

confidence: 99%

“…Indeed, their incentives to acquire new skills that would allow them to switch to tasks that are less likely to be automated are weak near retirement: because of their shorter remaining working lives, they (and their employers) would only obtain a low return on investments in new skills. They may thus choose to retire early when facing rapid technological change (Ahitiv and Zeira, 2011;Haegeland et al, 2007). Second, several OECD countries have in place various institutions that create strong incentives for early retirement.…”

Section: Introductionmentioning

confidence: 99%

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Technology, Labour Market Institutions and Early Retirement: Evidence from Finland

et al. 2020

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There are two major barriers to increasing employment of older workers. First, older workers engaged in codifiable, routine tasks are particularly prone to the risk of being displaced by computers and robots. Second, several countries have in place various labour market institutions that encourage early retirement, such as exceptional entitlements or looser criteria for unemployment and disability benefits applied to older individuals. We present evidence that these two factors reinforce each other to push older workers out of employment. We find that older workers who are more exposed to digital technologies are more likely to leave employment, and that this effect is significantly magnified when they are eligible to an extension of unemployment benefits until the earliest age for drawing old age pension. Furthermore, our findings imply that a policy reform that tightens the eligibility for the benefit extension would increase mostly the employment of older workers that are more exposed to digital technologies.

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Twisting the demand curve: Digitalization and the older workforce

Barth

Davis

Freeman

et al. 2023

Journal of Econometrics

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This paper uses U.S. Census Bureau panel data that link firm software investment to worker earnings. We regress the log of earnings of workers by age group on the software investment by their employing firm. To unpack the potential causal factors for differential software effects by age group we extend the AKM framework by including job-spell fixed effects that allow for a correlation between the worker-firm match and age and by including time-varying firm effects that allow for a correlation between wage-enhancing productivity shocks and software investments. Within job-spell, software capital raises earnings at a rate that declines post age 50 to about zero after age 65. By contrast, the effects of non-IT equipment investment on earnings increase for workers post age 50. The difference between the software and non-IT equipment effects suggests that our results are attributable to the technology rather than to age-related bargaining power. Our data further show that software capital increases the earnings of high-wage workers relative to low-wage workers and the earnings in high-wage firms relative to low-wage firms, and may thus widen earnings inequality within and across firms.

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Adapt or Withdraw? Evidence on Technological Changes and Early Retirement Using Matched Worker-Firm Data

Cited by 10 publications

References 23 publications

Age‐biased Technical and Organizational Change, Training and Employment Prospects of Older Workers

Age‐biased Technical and Organizational Change, Training and Employment Prospects of Older Workers

Technology, Labour Market Institutions and Early Retirement: Evidence from Finland

Twisting the demand curve: Digitalization and the older workforce

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