Income and poverty dynamics: measuring instability, volatility and persistence
Background
Over the past 25 years, substantive and methodological research at ISER, as well as advances in survey design, have made major contributions to the study of how best to measure household living standards, of why the distribution of income in the UK is changing and how this compares to other European countries, and of income and poverty dynamics. Such work continues, forming an important part of the new research programme for the ESRC-funded Research Centre on Micro-Social Change. Here we highlight two contributions: on how to measure persistent poverty when there is attrition or missing data, and on cross-country comparisons of labour market volatility.
Measuring persistent poverty with incomplete data
Poverty has more adverse effects when experienced for a long period, rather than as a transient phase. For this reason, policy makers in developed and developing countries try to monitor levels of persistent poverty, with the EU adopting a measure of persistent poverty as part of its programme of monitoring progress on social inclusion, and the 2010 Child Poverty Act (theoretically) committing UK governments to track the fraction of children in persistently poor households.
Typically, poverty persistence is measured with data from household panels in which a large group of randomly-selected households are interviewed repeatedly to assess whether they fall below a poverty line in each year. The simplest estimate of poverty persistence is then the proportion of sampled households found to be in poverty for more than a certain number of years during some period of time. But missing data can make it very hard to measure persistent poverty reliably: if we are unable to observe a household in every year, it is not possible to say whether it has been in persistent poverty.
The usual way to deal with missing data is to use only the subset of households observed in every period and then to correct any non-representativeness by giving greater weight to those types of household that appear to be under-represented in the reduced sample. In this research, we will investigate an alternative approach that constructs a lower and upper bound for the true level of persistent poverty by considering the possible outcomes that the missing poverty observations could have taken. Typically, these bounds are very wide, and this directly demonstrates that missing data introduces a very large element of uncertainty into the estimation of persistent poverty measures. The research will go on to investigate how these bounds can be narrowed by imposing some (hopefully) mild assumptions. The research will initially apply these methods to a panel survey carried out by the Peruvian National Institute of Statistics.
Instability and volatility in earnings
Although much is known about the rise in earnings inequality over the last two to three decades in many OECD countries, including the US and the UK, we know much less about trends in the level of instability in individuals’ earnings and how these trends differ across countries. Best-selling books, like Jacob Hacker’s “The Great Risk Shift”, have emphasised the connection between greater volatility and greater income risk in the US. This research provides new evidence on instability in earnings and employment for British men and women, and undertakes some transatlantic comparisons.
Earnings instability is measured using indices of ‘volatility’, which are defined in the following way: for each working-age individual, we calculate how much earnings change between one year and the next. How much instability (or volatility) there is in aggregate is summarised by the variance of these short-term earnings changes.
In addition to providing new evidence for Britain to complement the growing literature about volatility in the USA, this project has two further features. The first is that we provide evidence about volatility for women as well as men (virtually all US earnings volatility studies are about men). Second, we use measures of volatility that allow us to distinguish between labour market volatility and earnings volatility. Earnings volatility refers to volatility among individuals who have a job in two consecutive years. This is restrictive because it ignores individuals moving into or out employment or those who do not have job in either year, yet employment transitions are another source of volatility. Labour market volatility is the volatility that exists when one takes account of the earnings changes (appropriately defined) for all individuals, i.e. looking not only at those with positive earnings but also those with zero earnings.
