Two sides, but not of the same coin: digitalization, productivity and unemployment

This paper aims to examine how input from the digital restructuring of the workplace and productivity affects the risk of job loss and unemployment.

Relying on the concepts of technological unemployment and the productivity paradox as well as the theory of skills-biased technological change, the analysis incorporated micro-level individual determinants of job loss, macro-level economic determinants of input and the contribution from traditional (machinery and equipment) vs innovative (ICT) factors of production. The model has been also controlled for “traditional” indicators of “outsiderness” in the labour market. The Quality of Work Life Survey, which is a broad-based national interview survey produced by Statistics Finland, for 2018, the latest year available (N = 4,110) has been used in the analysis. Binomial logistic regression has been applied in order to estimate the effects of individual- and macro-level factors on the risk of job loss.

The results support arguments for the divergence between effects from labour- vs total-factor productivity on the risks of job loss, as well as the divergence between effects for temporary (layoff) vs permanent job loss (dismissal or unemployment). While the contribution from “traditional” factors of production to labour productivity potentially decreases the risk of permanent job loss, input from “innovative” factors of production on total-factor productivity potentially causes adverse effects (e.g. growing risks of permanent job loss).

The paper contributes to the theoretical discussion about technological unemployment and productivity by means of including two different concepts into a single econometric model, thus enabling examination of the research problem in an innovative way.