Non-Standard Employment and Risk: How Can We Capture Job Precarity Using Survey Data?

In the mid-1980s, Ulrich Beck noted that employment relations in contemporary societies are becoming fraught with risk and uncertainty, as traditional, full-time jobs which used to last a lifetime are being replaced by fragmented careers consisting of repeated spells of short-term jobs with multiple employers. This change is well-illustrated by the rise in non-standard employment (fixed-term contracts, temporary agency work, etc.), which are commonly associated with less economic security. Currently, a much-debated issue concerns the social and political significance of the emergence of the so-called precariat, a social class consisting of people for whom uncertainty and unpredictability of life circumstances and employment relations make it impossible to plan for the future, forcing them to live on a day-to-day basis (Standing, 2011). However, it remains unclear how the precariat may be defined and operationalized. Treating formal contractual status as a basis for identifying precarious employment is likely to be misleading, as research has shown non-standard employment to be heterogeneous with respect to working conditions and chances for achieving stabilization. Although survey research has found a correlation between fixed-term employment and perceived job insecurity, this relationship is far from universal. On the other hand, perceptions of security may also be misleading as indicators of precarity, as they are compounded by psychological coping mechanisms and perceptions of reference group status. This analysis attempts to disentangle the complex relationships between non-standard employment and perceived insecurity, in order to provide grounds for a more adequate conceptualization and measurement of job precarity. Specifically, I assess the extent to which the relationship between worker contractual status and perceived job insecurity are conditional on various job and respondent characteristics, such as occupation, age, family situation, and others. The analysis is based on multi-level regression models including interaction effects, using data from the 2010 European Working Conditions Survey.