Routine biased technological change and wage inequality: do workers' perceptions matter? - Silvia Vannutelli; Sergio Scicchitano; Marco Biagetti (Global Labor Organization (GLO), 2021)
The Routine-Biased Technological Change (RBTC) has been called as a relatively novel technology-based explanation of social changes like job and wage polarization. In this paper we investigate the wage inequality between routine and non-routine workers along the wage distribution in Italy. Thanks to unique survey data, we can estimate the wage differential using both actual and perceived level of routine intensity of jobs to classify workers. We adopt semi-parametric decomposition techniques to quantify the importance of characteristics of workers in explaining the gaps. We also employ non-parametric techniques to account for self-selection bias. We find evidence of a significant U-shaped pattern of the wage gap, according to both definitions, with non-routine workers earning always significantly more than routine workers. Results show that workers' characteristics fully explain the gap in the case of perceived routine, while they account for no more than 50% of the gap across the distribution in the case of actual routine. Thus, results highlight the importance of taking into account workers' perceptions when analyzing determinants of wage inequality. Overall, we confirm that, after leading to job polarization, RBTC induced a similar polarizing effects on wages in Italy.
Keywords: J31; J82; C14; 330; Blinder/Oaxaca; Counterfactual distribution; Italy; Non-parametric methodology; Quantile regression; Routine; Semi-parametric methodology; Wage inequality