Description
Commenced in 2001, the Household, Income and Labour Dynamics in Australia (HILDA) Survey is a nationally representative longitudinal study of Australian households. The study is funded by the Australian Government Department of Social Services (DSS) and is managed by the Melbourne Institute at the University of Melbourne. Roy Morgan Research has conducted the fieldwork since Wave 9 (2009), prior to which The Nielsen Company was the fieldwork provider.
The HILDA Survey seeks to provide longitudinal data on the lives of Australian residents. It annually collects information on a wide range of aspects of life in Australia, including household and family relationships, child care, employment, education, income, expenditure, health and wellbeing, attitudes and values on a variety of subjects, and various life events and experiences. Information is also collected at less frequent intervals on various topics, including household wealth, fertility related behaviour and plans, relationships with non-resident family members and non-resident partners, health care utilisation, eating habits, cognitive functioning and retirement.
The important distinguishing feature of the HILDA Survey is that the same households and individuals are interviewed every year, allowing us to see how their lives are changing over time. By design, the study can be infinitely lived, following not only the initial sample members for the remainder of their lives, but also their children and all subsequent descendants. Household longitudinal data, known as panel data, provide a much more complete picture than crosssectional data because they document the life-course each person takes. Panel data tell us about dynamics—family, health, income and labour dynamics— rather than statics. They tell us about persistence and recurrence, for example, of poverty, unemployment or welfare reliance. Perhaps most importantly, panel data can tell us about the antecedents and consequences of life outcomes, such as poverty, unemployment, marital breakdown and poor health, because we can see the paths that individuals’ lives took to those outcomes and the paths they take subsequently. Indeed, one of the valuable attributes of the HILDA panel is the wealth of information on a variety of life domains that it brings together in one dataset. This allows us to understand the many linkages between these life domains; to give but one example, we can examine how the risk of poor economic outcomes depends on an individual’s health.
Panel data are also important because they allow causal inferences in many cases that are more credible than what other types of data permit. In particular, statistical methods known as ‘fixedeffects’ regression models can be employed to examine the effects of various factors on life outcomes such as earnings, unemployment, income and life satisfaction. These models can control for the effects of stable characteristics of individuals that are typically not observed, such as innate ability and motivation, that confound estimates of causal effects in cross-sectional settings.
-reprinted from Melbourne Institute, Applied Economic and Social Research