Sinead: You Might Be in Precarious Work and Not Even Know It

Are you in precarious work? Perhaps, like many people we have come across during our recent research, you don’t really know.

Last spring, we launched our first report on precarious work in Ireland and the impact that living with this uncertainty has on precarious workers’ lives. It was based on data from the Central Statistics Office, and interviews with 15 policy experts and 40 precarious workers.

We’ve followed that up with some focus groups and interviews with policy experts – the results of which we’ll publish soon in a follow-up policy report.

During the research, it became apparent that many participants and those in groups we reached out to were unaware that they were contractually precarious.

The reasons for this varied. Some had no contracts. Others didn’t understand what precarious work is. Others equated a temporary one-year contract with a permanent position.

The last of these can be explained by differing experiences of precariousness. A temporary contract might be considered more secure compared to other precarious work, such as zero-hour contracts. Many said their employment was permanent, though later they revealed that they were on temporary contracts.

Much of this confusion stems from the fact that there is no agreed official definition of what constitutes precarious employment. Many definitions are thrown around.

However, the main features have been identified as work that involves contractual uncertainty – in other words, workers don’t know their hours and aren’t permanent – low income, and limited social benefits and statutory elements.

Non-standard forms of employment – including temporary contracts, fixed-term contracts, part-time work and self-employment – are often equated with precarious work. Although non-standard employment carries a higher risk of precariousness, it is not the only form of precarious work.

All employment relationships are at some risk of precariousness, as noted by Andrea Broughton and other researchers at the Institute for Employment Studies in a 2016 study for the European Parliament.

But we have a limited grasp of this in Ireland. There are numerous shortcomings in the data available. Bottom line? We just don’t know the true scale of this type of work here.

Many commentators tend to look only at figures for non-standard employment as a measurement of precarious work. But as we’ve seen, while non-standard employment does carry the highest risk of precariousness, precarious work covers more than these.

Precarious work is complex. We need complex data to understand just how much of it is around.

The lack of a definition means, too, that people are oblivious that they are performing precarious work. This can influence the results of surveys and data sets.

The Quarterly National Household Survey (QNHS) asked about a respondent’s understanding of their employment status, rather than their actual contractual status. This has been replaced recently by the Labour Force Survey (LFS).

Those two surveys ask questions in different ways, which has thrown up different figures, as Ciarán Nugent, a research assistant at the Nevin Economic Research Institute (NERI), has pointed out.

The 2015 LFS estimate puts temporary employment at 15.6 percent for those under 30. To add to the confusion, a recent survey by RedC of a representative sample of more than 400 people aged between 18 and 30 years old conducted in February 2017 found that 38 percent of this age group were on temporary contracts.

Data sets will have discrepancies, but usually of a couple of percentage points. They shouldn’t differ by as much as 20 percent.

This all comes back to the way the questions is asked. The QNHS/LFS depended on a person’s own interpretation of their contract.

The RedC poll was more specific: “Which of the following best describes the nature of your current employment?” it asked.

It offered four options: on a permanent contract; self-employed; on a temporary contract (of limited duration and may not be renewed); don’t know.

We need accurate statistics to underpin and inform policy. Without them, we can’t understand what is going on and we can’t convince policymakers that something is needed to address it.