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ABSTRACT
Worker persistence—the ability to focus on a task for long periods of time—is often highlighted as essential to success. However, computers are extraordinarily persistent, particularly for routine, repetitive work. This potentially reduces the value of human persistence in occupations that are computerized. Using a well-defined measure of worker persistence across a nationally-representative 16-year sample of 4,239 individuals, we investigate the extent to which occupations value worker persistence in the presence of computers. We find that the labor market does indeed value persistence. Nonetheless, we find that in routine jobs, the wage premium of human persistence diminishes with the degree of workplace computerization. Yet, this substitution does not occur in non-routine jobs. These findings deepen our understanding of the effect of workplace computerization on the future of work and workers, and they also warrant imlications on government job training programs, organizational talent management, as well as the redesign of the K-12 curriculum.
Disclosure Statement
No potential conflict of interest was reported by the author(s).
Notes
1. For example, it has been recently shown that worker social skill is productivity-enhancing and has an increasing wage premium [Citation19,Citation50].
2. See e.g. [Citation1, Citation5–7, Citation12, Citation13, Citation18, Citation28, Citation32, Citation33, Citation38, Citation44].
3. The data and approach used to define and measure occupational routineness and computerization will be discussed in detail in the data section.
4. Please refer to the official site for detailed information on what NLSY97 covers: https://www.nlsinfo.org/content/cohorts/nlsy97/topical-guide
5. Specifically, for Persistence, we first standardize each of its constituent items. After that, we take the simple average of the 4 standardized constituent items, and then we standardize the average. We conduct both rounds of standardization across individuals who have non-missing values of these items in the 2013 cross section. The same procedure also applies to Diligence.
6. [Citation3] provide an overview of studies on personality evolution over the life cycle.
7. The crosswalk between 2002 Census classification and 2000 SOC classification is obtained by the National Crosswalk Service Center (NCSC), www.xwalkcenter.org.
8. OES is a United States Bureau of Labor Statistics program that produces semiannual employment and wage estimates of the economy. We mainly use OES 2004 as the employment weights to best reflect employment compositional changes in early 2000s, because 2000-2003 OES covers fewer occupations than post-2003 years. Results remained robust when we used later years, e.g., 2008, as employment weights.
9. Education is in terms of the highest degree obtained in a given year.
10. Strictly speaking, the wage effect of persistence should also depend on individual cognitive ability as the interaction between grit and cognition is included in the specification. Here, we ignore that interaction effect for illustration purpose and concentrate on the persistence-computer substitution. Therefore, the effect here can be viewed as that of a representative worker with a standardized cognitive ability of 0.
11. Not reported in the table, but many demographic variables (e.g., sex, age, etc.) also tend to significantly predict occupational computer use.
12. Routine does not necessarily imply lower wage. In fact, routine occupations are mostly in the middle of the wage spectrum and include many white-collar jobs. In contrast, manual labor is often non-routine.
13. Detailed regression outputs are not reported due to space limitation but can be shared upon request.
14. Another possible explanation for the larger wage premium of persistence in later years is that entry-level jobs may be less persistence-dependent than later jobs. That is, labter jobs may have higher rewards for persistence than entry-level jobs, due to more independent decision making, higher value-added, etc.
Additional information
Notes on contributors
Erik Brynjolfsson
Erik Brynjolfsson ([email protected]) is Jerry Yang and Akiko Yamazaki Professor and Senior Fellow at the Stanford Institute for Human-Centered AI (HAI), director of the Stanford Digital Economy Lab (DEL), and research associate at National Bureau of Economic Research (NBER). He is also Professor by Courtesy at the Stanford Graduate School of Business and Stanford Department of Economics, and the Ralph Landau Senior Fellow at the Stanford Institute for Economic Policy Research (SIEPR). He received his Ph.D. in Managerial Economics from MIT Sloan School of Management. Dr. Brynjolfsson’s research examines the effects of information technologies on business strategy, productivity and performance, digital commerce, and intangible assets. He has published in leading academic journals, such as Quaterly Journal of Economics, American Economic Review, and Management Science.
Meng Liu
Meng Liu ([email protected]; corresponding author) is an assistant professor of marketing at Olin Business School of Washington University in St. Louis. She is a research fellow at MIT Initiative on the Digital Economy (IDE) and Stanford Digital Economy Lab (DEL). She earned her Ph.D. in Economics from Clemson University. Dr. Liu’s research is empirically oriented and encompasses topics in market designs, digital platforms, and economics of digitization and algorithms. She has published papers in Management Science, Scientific Reports, Information Economics and Policy, and an article in The Washington Post.
George Westerman
George Westerman ([email protected]) is a Principal Research Scientist at MIT Sloan School of Management and a Principal Research Scientist at J-WEL Workforce Learning. He is co-chair of the MIT Sloan CIO Leadership Awards and a member of the Digital Strategy Roundtable for the US Library of Congress. He earned his Ph.D. from Harvard Business School. Dr. Westerman’s research and teaching focus on digital technology leadership and innovation. He has published several award-winning books, including Leading Digital: Turning Technology into Business Transformation. He has contributed to such venues as Sloan Management Review, Harvard Business Reviewer, The Wall Street Journal, and Forbes.