Job tasks and the comparative structure of income and employment: Routine task intensity and offshorability for the LIS*

Abstract

Comparative sociologists have long considered occupations to be a key source of inequality. However, data constraints make comparative research on two of the more important contemporary drivers of occupational stratification-globalization and technological change-relatively scarce. This article introduces a new dataset on occupational 'routine task intensity' (RTI) and 'offshorability' (OFFS) for use with the Luxembourg Income Study (LIS). To produce these data, we recoded 23 country-specific occupational schemes (74 LIS countryyears) to the two-digit ISCO-88 scheme. When combined with the handful of LIS countries already reporting their occupations in ISCO-88, we produce individual level RTI and OFFS scores for 38 LIS countries and 160 LIS country-years. To assess the validity of these recodes, we compare average labor-income ratios predicted by recoded ISCO-88 occupational categories to those predicted by reported ISCO-88 occupational categories within countries that transitioned from country-specific to ISCO-88 codes over time. To assess the utility of these RTI and OFFS scores and advance the literature on income polarization, we analyze their association with work hours and labor incomes in the global North and South. Both covariates correlate with work hours in ways that are consistent with previous research and additional theoretical considerations. Moreover, we show that both RTI and OFFS contribute to income polarization directly in the North, but not in the South. This article generates a public good data infrastructure that will be of use to a wide variety of social scientists, and brings new evidence to bear on the question of income polarization in rich democracies.

Automation, Occupational Earnings Trends, and the Moderating Role of Organized Labor

“…RTI represents the routine task intensity of the occupation, scaled from zero (least routine) to 1 (most routine). The variable included in the interaction term (see 2 ) represents a linear time trend, following similar specifications from and Goos, Manning and Salomons (2014) and Mahutga, Curran and Roberts (2018). Thus, if 2 is positive and statistically significant, this would imply that the earnings returns to higher RTI are increasing over time, independent of composition effects, such as a rise in educational attainment.…”

Does Automation in Rich Countries Hurt Developing Ones?: Evidence from the U.S. and Mexico

“…We use data from EUKLEMS on adoption of Information Technology (IT) and Communication Technology (CT) by sector and time for the US to estimate a measure of exposure of Mexican LLMs to such technologies in the US, for a robustness test. We use data on the degree of offshorability and routine task intensity of Mexican occupations from Mahutga et al (2018). We use data the susceptibility of automation of occupations from Artuc et al (2018).…”

The interplay of female empowerment and subjective beliefs about women in 51 countries

“…SUR models are composed of a pair of equations in a reciprocal system (i.e. efficiency) where the residuals are correlated across the two equations to account for potential endogeneity (Alexander, 2012; Mahutga et al, 2018). In the first equation, we regress GEM, measured in the year after the reported survey year, on the country-level prevalence of inegalitarian gender beliefs among both men and women in the reported survey year and the prevalence of these beliefs in the previous survey year.…”