Automating Labor: Evidence From Firm-Level Patent Data

Dechezleprêtre, Antoine; Hémous, David; Olsen, Morten; Zanella, Carlo

doi:10.2139/ssrn.3508783

Cited by 27 publications

(26 citation statements)

References 38 publications

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“…With an average annual inflow rate of about 22.8 ethnic Germans per 1,000 manual and unskilled workers during the binding allocation period, the total reduction of automation patents of about 1.1 patents is economically meaningful. While these estimates are not directly comparable to other studies, we confirm Dechezleprêtre et al (2019) and San (2019) in concluding that automation innovation is quite responsive to changes in labor supply.…”

Section: Resultscontrasting

confidence: 82%

“…While the recent literature has successfully applied keyword search in patent texts (see e.g., Dechezleprêtre et al, 2019;Webb, 2019), the choice of relevant keywords can be disputed. Therefore, we examine the sensitivity of our findings to using three alternative keyword based measures of automation innovation (Table B-8).…”

Section: Alternative Measures Of Automation Innovationmentioning

confidence: 99%

“…In contrast, Doran and Yoon (2019) study the effect of US mass immigration in the early 20th century and find a positive relationship between low-skilled worker inflows and the overall rate of innovation. Using cross-country variation on wages and firmlevel data on distinct patenting activities, the results from Dechezleprêtre et al (2019) suggest that an increase in low-skilled wages increases automation innovation. Our paper also relates to the literature on the role of factor endowments for technology adoption (e.g., Zeira, 1998).…”

Section: Introductionmentioning

confidence: 99%

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Labor Supply and Automation Innovation

2020

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While economic theory suggests substitutability between labor and capital, little evidence exists regarding the causal effect of labor supply on inventing labor-saving technologies. We analyze the impact of exogenous changes in regional labor supply on automation innovation by exploiting an immigrant placement policy in Germany during the 1990s and 2000s. Difference-indifferences estimates indicate that one additional worker per 1,000 manual and unskilled workers reduces automation innovation by 0.05 patents. The effect is most pronounced two years after immigration and confined to industries containing many low-skilled workers. Labor market tightness and external demand are plausible mechanisms for the labor-innovation nexus.

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Section: Resultscontrasting

confidence: 82%

Section: Alternative Measures Of Automation Innovationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Labor Supply and Automation Innovation

2020

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“…We are currently working to this. Another avenue of research is to investigate how labor market characteristics can affect the nature of innovation, for example, whether the innovation is aimed at automation or the creation of new product lines.The former idea is explored in current work by the present authors, and the latter is explored in recent work by Dechezleprêtre et al (2019).…”

Section: * * *mentioning

confidence: 95%

Artificial Intelligence, Growth and Employment: The Role of Policy

Aghion¹,

Antonin²,

Bunel³

2019

Ecostat

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Alongside this, quality standards have improved. Originally, publication was only subject to internal approval from above. Today, the manuscripts submitted are systematically assessed by anonymous reviewers as part of a standard peer review system. And the journal, like any academic journal, now has a formal governance structure with a Scientific Committee since 2003 and an Editorial Advisory Board since 2014.As a natural corollary of these changes, the papers published in the journal do not necessarily reflect the views of Insee. Indeed, the readers are systematically reminded that "the views and opinions expressed by the authors are their own and do not necessarily reflect those of the institutions to which they belong or of Insee itself." This precaution is not always sufficient, and when there is a debate over a paper, it is often presented as "an Insee study". From my point of view as a publishing director, I find the confusion regrettable, although it does not, and indeed should not, cause us to avoid a subject or reject a paper on the grounds that it might generate controversy. In practice, informing debates cannot always be done by staying out of the debate.The editors have always been, and remain, committed to facilitating access to articles, in particular with the use of "boxes". While these were initially intended to accommodate the most technical developments so that they do not interfere with the ease of reading, they now contribute to a rigorous presentation of the sources used and their possible treatment. I am aware that this is not standard practice in academic journals, but I will nonetheless continue to defend the original model -an extremely useful model in my view -of a journal that sets high standards while at the same time striving to remain accessible to readers who may not necessarily be experts in the topics discussed.In very recent years, the journal has continued to evolve with the aim of achieving greater international openness. This is precisely why Économie et Statistique has become "Economie et Statistique/Economics and Statistics", published simultaneously in French and English, and both available on the Insee website. However, the journal has remained faithful to the same key principles, including openness to different topics and disciplines and a dual commitment to official statistics and research, which give it a distinctive place both at Insee and within the field of French journals.While I very much hope that this anniversary will be followed by many more, I would also like to thank the editors-in-chief we have had since 1969, the academics who have agreed to sit on the Scientific Committee over the past fifteen years, and all the reviewers working anonymously behind the scenes.

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“…15 These simple comparative statics still hold when both automation and capital accumulation are endogenous. For instance, Acemoglu et al (2015), Acemoglu and Restrepo (2017), Hémous and Olsen (2018) and Dechezleprêtre et al (2019) show how to make κj a choice variable. Bonfiglioli et al (2019) endogenize both κj and Kj, and derive conditions under which employment is a hump-shaped function of automation.…”

Section: A Simple Model Of Workers Machines and Tasksmentioning

confidence: 99%

Who is afraid of machines?

2019

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SUMMARY We study how various types of machines, namely, information and communication technologies, software and especially industrial robots, affect the demand for workers of different education, age and gender. We do so by exploiting differences in the composition of workers across countries, industries and time. Our data set comprises 10 high-income countries and 30 industries, which span roughly their entire economies, with annual observations over the period 1982–2005. The results suggest that software and robots reduced the demand for low- and medium-skill workers, the young and women – especially in manufacturing industries; but raised the demand for high-skill workers, older workers and men – especially in service industries. These findings are consistent with the hypothesis that automation technologies, contrary to other types of capital, replace humans performing routine tasks. We also find evidence for some types of workers, especially women, having shifted away from such tasks.

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Automating Labor: Evidence From Firm-Level Patent Data

Cited by 27 publications

References 38 publications

Labor Supply and Automation Innovation

Labor Supply and Automation Innovation

Artificial Intelligence, Growth and Employment: The Role of Policy

Who is afraid of machines?

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