This thesis deals with the take-up of social security benefits in Britain. It is well documented that not everyone who is entitled to benefits actually claims them. Nontake- up of benefits has been found to be a problem especially for benefits which are means-tested. So, throughout this thesis, we concentrate on Income Support, the main means-tested benefit in Britain. The latest official estimates on the extent of non-takeup (for 1993/94) suggest that up to 1.4 million persons are not receiving close to £1.7 billion of IS in spite of being entitled to it. The main question this thesis addresses IS what are the factors which determine whether an individual will or will not take-up their benefit entitlement? We consider the problem from an economic perspective by constructing suitable models set in both static and dynamic environments. These models provide some interesting insights about the nature of non-take-up. In tum, they also form the basis to a series of econometric models. Previous empirical evidence has shown that the entitlement level itself is one of the key determinants of whether or not an individual will take-up. In addition, it has long been recognized that - due to the complex nature of the benefit system - determining individual entitlements is, in many cases, error-prone with resulting benefit entitlements that are subject to measurement error. Hence, unlike any other studies thus far, we account for the presence of measurement error in the benefit entitlement when modelling the likelihood of take-up. Finally, we shed new light on the dynamics of take-up by using the information contained in our panel data set. In particular, we consider the effect claiming in the past has on the current decision to take-up and how future changes, expected or known with certainty, influence the decision to take-up or not
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:299337 |
| Date | January 1998 |
| Creators | Crenian, Robert A. |
| Publisher | University of Bristol |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1983/4fb0ffc0-cc0a-453e-8bf0-16f1a3af5b90 |
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