We present evidence suggesting that the so-called “fourth industrial revolution”, characterized by machine learning, big data, mobile robotics and cloud computing, may be skill-biased not only with respect to skills acquired through education, as available theoretical models and empirical evidence abundantly suggest, but also with respect to facets of noncognitive skills. Measuring the future direction of technological change by estimated probabilities of occupations to be automatized during the next about two decades, and noncognitive skills by the Big Five personality traits from several German worker surveys, we find that jobs that currently require more openness to experience or more emotional stability will be less susceptible to automatization in the future. We also find some evi- dence suggesting that jobs that require more extraversion or less agreeableness may also be less susceptible to automatization. These correlations are significant even though we control extensively for formal education and work experience, the traditional measures of human capital.
As a by-product of our empirical analysis, we find interesting differences between the German worker surveys that report Big Five personality traits. Compared to the responses in the Socioeconomic Panel (SOEP) and the National Educational Panel Study (NEPS), those in the Linked Personnel Panel (LPP), an annual employer-employee survey, are skewed notably towards Big Five scores employers would prefer. And the Panel Study on Labor Markets and Social Security (PASS) may, due to its focus on problem groups in the labor market, be of limited use for general-purpose analyses of labor markets.
Our results corroborate earlier findings suggesting that formal education is a rather imperfect proxy of human capital. Personality is an important factor of success in school, and thereby affects success in subsequent work life indirectly. Over and above this indirect effect, it is also an important independent factor of success in work life, however. It affects not only wages and occupational choices directly, as James Heckman and his coauthors have shown. It also affects workers’ resilience to future technological changes directly, as we suggest in the present study.
Accounting for this role of personality may well sharpen the hypotheses to be drawn from theoretical models of skill-based technological change such as the Ricardian model in Acemoglu and Autor (2011). To account for personality, these models may put more empha- sis on labor supply. Workers are actually endowed with multifaceted skills, and tasks require a variety of different skills as productive inputs. The task of teaching, for example, requires a university degree and additionally a good deal of communication skills and a patient, outgoing and caring personality. The task of doing research also requires a university degree but a rather different personality. It requires more curiosity, determination and self-discipline while deficits in communication skills will not hurt too much. Heterogeneous skill endowments give rise to a richer variety of comparative advantages for performing tasks than edu- cation alone does. In addition to this, they open up a richer set of options in response to exog- enous technology shocks. Workers may take other jobs that involve different tasks but similar skill compositions. Or they may readjust the skills set they supply to the labor market by focusing on skills they are endowed with but have not needed in earlier jobs.
Accounting for this role of personality may also enhance the explanatory power of empirical studies founded in models of skill-based technological change. Much is left to be done by psychologists and economists to disentangling the relevant skills behind composite skill cate- gories like the Big Five or the so-called “social” skills (Weinberger 2014, Deming 2015), “people” skills (Borghans et al. 2014) or “21st-century” skills (Pellegrino and Hilton 2012). More reliable measurement of these skills is an extremely important and difficult related issue, of course.
Chosen excerpts by Job Market Monitor. Read the whole story at DIW Berlin: Worker Personality: Another Skill Bias beyond Education in the Digital Age
Discussion
Trackbacks/Pingbacks
Pingback: The Impact of Automation on Inequality – Increasing it says St. Louis Fed’s study | Job Market Monitor - November 27, 2018
Pingback: The Future of Work – Five policies to help the middle class from displacement | Job Market Monitor - December 15, 2018
Pingback: Future of Work – Fostering the benefits of new technologies requires good measures of their impact | Job Market Monitor - January 23, 2019
Pingback: The Future of Work in US – Five policy strategies for adjusting to automation | Job Market Monitor - March 4, 2019
Pingback: The Future of Work – Artificial Intelligence (AI) impacts on learning, teaching, and education | Job Market Monitor - April 1, 2019
Pingback: The Future of Work and Skills Acquisition – A shift in mindset is needed | Job Market Monitor - August 21, 2019
Pingback: The Geography of the Future of Work in US – A mosaic of local economies on diverging trajectories | Job Market Monitor - August 31, 2019