Speakers: David Autor is Ford Professor in the MIT Department of Economics, Distinguished Fellow of the Luohan Academy, co-director of the NBER Labor Studies Program, and co-leader of both the MIT Work of the Future Task Force and the JPAL Work of the Future experimental initiative. His scholarship explores the labor-market impacts of technological change and globalization on job polarization, skill demands, earnings levels and inequality, and electoral outcomes.
Paper: https://academic.oup.com/qje/article/139/3/1399/7630187
Recap:
On 13th July 2021, Professor David Autor joined us in a Luohan Academy Webinar to discuss the origins and content of new work based on a novel nearly century-long inventory of new job titles linked to United States Census microdata from 1940 to 2018. The work of Professor Autor and his co-authors is aimed to understand the relationship between technological advance and employment --- the replacement of existing work or the creation of new work.
People are increasingly curious whether automation is eroding human comparative advantage. Based on previous findings regarding task change within occupations (Atack, Margo, and Rhode, 2019; Atalay et al., 2020; Deming and Noray, 2020), the study by Professor Autor contributes in three aspects: first, he consistently measures the task content of new work from 1940 to 2018 in the US; second, he explores technological and economic origins of new work; third, he analyzes the impact of technological advance on employment and wages.
Professor Autor reveals that about 63.5% of employment in 2018 does not exist in 1940. Where does the new employment come from and what is it made up of? He hypothesizes that three forces contribute to the new employment: augmentation - technologies complement the outputs of occupations, automation - technologies substitute the inputs of occupations, and demand shifts create incentives for task creation and task automation. Professor Autor tests his hypothesis both theoretically and empirically.
Professor Autor draws intuitions from a theoretical model with a skilled-intensive sector and an unskilled-intensive one, in which automation substitutes for labor inputs, new task creation responds elastically to demand, and augmentation and automation occur in the same occupations with opposing demand impacts, which respectively correspond to his three testable hypotheses.
He measures new work over eight decades from the US Census Alphabetical Index of Occupations and Industries 1930-2018. He creates augmentation and automation measures by linking the US utility patents database with the US Census Alphabetical Index of Occupations and Industries and Dictionary of Occupational Titles, respectively.
His findings are threefold. First, he finds that new work does emerge in augmentation-exposed occupations, while automation does not predict new work emergence. Second, he reveals that labor demand shifts affect new task creation. There has been less new title creation in occupations exposed to import competition from China, implying occupations shrink when exposed to negative demand shocks. There have been more new title creations in occupations exposed to positive shifts because of demographic-induced changes in industry demands. Third, he shows that employment and composition-adjusted wages increase with augmentation measure and decrease with automation measure.
To conclude, Professor Autor essentially contributes to our understanding of the nature of work: (1) new work is quantitatively important, (2) locus and skill content of new work have shifted dramatically over eight decades, matching overall change in skill demands concentrated in blue-collar and office work in post-War decades and in technical and professional and low-paid services after the 1980s, (3) occupational augmentation consistently predicts the emergence of new titles and growth of new work 1940-2018 but automation exposure does not, and demand shifts predict where new titles emerge, and (4) task displacement and new task creation occur simultaneously with opposing consequences on employment and wage growth.
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