Purpose

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

Design/methodology/approach

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.

Findings

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).

Originality/value

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.

中文翻译：

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两个方面，但不是一回事：数字化、生产力和失业率

目的

本文旨在研究工作场所和生产力的数字化重组如何影响失业和失业的风险。

设计/方法/途径

依靠技术失业和生产率悖论的概念以及技能偏向技术变革理论，该分析结合了微观层面的个人失业决定因素、宏观层面的经济投入决定因素以及传统（机械和设备）与创新（ICT）生产要素。该模型还针对劳动力市场中“局外人”的“传统”指标进行了控制。工作生活质量调查是芬兰统计局开展的一项基础广泛的全国访谈调查，分析中使用了 2018 年最新的可用年份（N  = 4,110）。已应用二项式逻辑回归来估计个人和宏观层面因素对失业风险的影响。

发现

结果支持关于劳动力生产率与全要素生产率对失业风险的影响之间存在差异的论点，以及临时（裁员）与永久性失业（解雇或失业）影响之间的差异。虽然“传统”生产要素对劳动生产率的贡献可能会降低永久性失业的风险，但“创新”生产要素对全要素生产率的投入可能会产生不利影响（例如永久性失业风险增加）。

原创性/价值

本文通过将两个不同的概念纳入一个计量经济学模型，从而以一种创新的方式对研究问题进行检验，从而促进了关于技术性失业和生产率的理论讨论。