Benefit dependency: The pros and cons of using “caseload” data for national and international comparisons

Abstract

Policy‐makers in advanced welfare states have increasingly expressed concerns over large numbers of working‐age people claiming social security support. Accordingly, policies aimed at reducing the level of “benefit dependency” have gained prominence. However, such policies rest on shaky empirical evidence. Systematic collections of national “caseload” data are rare, social security programmes overlap and administrative categories vary over time. The internationally inconsistent treatment of national transfer programmes provides a further challenge for cross‐national comparisons. This article first identifies and discusses several of these problems, and ways in which they may be addressed. It then employs administrative claimant data from six European countries as a way of illustrating trends over time and across countries. The underlying aim is to explore the scientific potential of benefit recipient numbers as an indicator for welfare state change over time and across countries.

Towards a new consolidated framework for analysing benefit coverage

“…However, the European Commission and the OECD tend to focus their analyses of benefit coverage on actual recipients. Potentially, this takes us closer to the realities experienced by vulnerable groups in society (De Deken and Clasen, 2013;Finn and Goodship, 2014;Otto, 2018a;Van Oorschot, 2013).…”

Welfare reform by stealth? Cash benefit recipiency data and its additional value to the understanding of welfare state change in Europe

“…For example, this approach ignores shifts in the content or institutional structural of welfare states, such as the development of programmes addressing new social risks (Bonoli, 2005; Gingrich and Ansell, 2015; Morel et al, 2011). Other authors suggest (also) using different types of data than ‘rights’ or ‘costs’, namely benefit receipt information (De Deken and Clasen, 2013; Van Oorschot, 2013), since the ‘paper reality’ of social rights and the ‘financial cost reality’ of social expenditure only reveal particular aspects of public welfare provision. The following paragraph elaborates on the proposal of this alternative, additional indicator: benefit recipiency data.…”

“…However, to date, it has received surprisingly little attention in comparative welfare state research. This type of data has only recently been brought into the dependent variable discussion, with studies that elaborate on the indicator from a conceptual and methodological point of view and that provide new insights into how welfare states compare cross-sectionally and longitudinally with regard to particular welfare benefits (Arents et al, 2002; De Deken and Clasen, 2011, 2013; Immervoll et al, 2004, 2015; Van Oorschot, 2013).…”

Comparative Social Policy Analysis and Active Labour Market Policy: Putting Quality before Quantity

“…Even without this, however, there is arguably much that could be done to enhance the quality of cross-national ALMP comparisons through more systematic and comprehensive exploitation of data that is already publicly available. For example, alongside expenditure data the OECD and Eurostat have long published information about numbers of ALMP programme participants, and these could be used in conjunction with expenditure data to develop betterif still imperfect -proxies for ALMP 'policy logics', which can be argued to turn not only on how much money is spent on a measure but also on how many people benefit from it (see also De Deken and Clasen, 2013). Moreover, as Oldervoll (2014) has pointed out, comparative analysts could make better use of the more disaggregated ALMP data published annually by Eurostat (e.g.…”

“…For example, alongside expenditure data, the OECD and Eurostat have long published information about numbers of ALMP programme participants. These could be used in conjunction with expenditure data to develop better – if still imperfect – proxies for ALMP ‘policy logics’, which can be argued to include not only how much money is spent on a measure but also how many people benefit from it (see also De Deken and Clasen, 2013). Moreover, as Oldervoll (2014) has pointed out, comparative analysts could make better use of the more disaggregated ALMP data published annually by Eurostat (e.g., Eurostat, 2012) and particularly the associated ‘qualitative reports’ (e.g., Eurostat, 2014).…”