The problem of debt among low income families in the United Kingdom has received widespread attention in the media in recent months. In May 2003, Citizens Advice, which represents the 2000 or so Citizen’s Advice Bureaux around the country, warned that the number of people struggling with debt problems had risen by 47% over the past five years. The campaign group ‘Debt on our Doorstep’ argues that there are serious problems of default and of arrears recovery among low income families arising from excessive interest rates on loans, incomplete understanding of loan conditions, and ‘socially irresponsible lending’ by some high street lenders.
The evidence on the pattern of debt and, in particular, of debt-induced ‘financial stress’ for low income families underpinning these statements comes from a mixture of sources aggregate data from some classes of lenders, case loads and case studies from specialised agencies, and more detailed analysis of urban localities. To understand fully the prevalence of problems with debt among low income families, however, we need a suitably representative sample of ‘at risk’ households. Such data could be used to determine the general incidence of credit arrangements utilised by households, and to pin down the financial problems that may arise from outstanding debt. So far, most academic studies of the issue have also focussed on case studies of relatively small numbers of people (e.g. Dominy and Kempson, 2003) and/or largely qualitative data sets (Economic and Social Research Council, 2002; Kempson, 2002).
This paper describes the sources of credit utilised by low income families, the patterns of arrears in payments of outstanding debt, and default on household bills using a relatively new UK household micro data set. This is the Families and Children Survey (FACS) – a panel survey of low income families with children that was first established as the Survey of Low Income Families (SOLIF) in 1999. This is the first data set, to our knowledge, that provides a rich mixture of qualitative and quantitative information on these issues for a large sample of randomly sampled low income families. The primary focus of this analysis is on the first wave of this data (SOLIF, 1999), although we exploit the panel element to do some simple analysis of persistence in the use of particular forms of credit and, in particular, in the persistence of default and arrears.
The primary focus of the paper is descriptive given the dearth of information currently available on this important topic. We wish to understand what types of credit low income families use, and whether problems of arrears and default are pervasive. The paper focuses on five areas of household finances where problems of arrears and default might arise. These are credit-financed purchases, loans from financial organisations (ranging from banks to local moneylenders), loans from family, and arrears arising from non-payment for housing, and for utilities. We examine the associations between different types of default – for example, whether arrears in payment of rent and mortgages are associated with arrears in utility bills. We find strikingly different patterns of debt among one parent and low income couples with children, and between tenants and homeowners. We keep econometric techniques to a minimum in this paper, although in our background paper (Bridges and Disney, 2002) we use count models to show how there is greater heterogeneity across households in the incidence of default and arrears than there is in the use of credit facilities. Moreover we briefly examine persistence in the use of credit arrangements and in the reporting of arrears and other indicators of ‘financial stress’, using the panel element of the data.
Our results suggest that low income families indeed utilise a variety of credit arrangements. Moreover the proportions using different arrangements are rather different from those in the population as a whole, with greater use of catalogues and mail order schemes, relative to credit cards, and loans from sources other than high street banks. This may illustrate constraints on access to normal ‘high street credit’. Some evidence for this arises from differences in arrangement by type of household, whether delineated by family composition, employment status and housing status. We suggest that the absence of employment and home owning-related collateral may be an important factor in restricting access to credit for some low income families, but such families may also choose other sources of credit for a number of reasons that are unrelated to access. For example, temporary non-payment of regular bills such as utility bills, or loans from relatives, may be a less costly and cheaper alternative to bank loans or credit cards as a means of financing current expenditures.
What are the implications of these disparities in credit arrangements? A common perception is that, if low income households are excluded from prime credit outlets by adverse scoring from credit bureaux, such households will only get credit from secondary and unregulated markets where effective interest rates are much higher (for example, unregulated moneylenders) and/or less transparent (such as through mail order catalogues). In those circumstances, the threat of a ‘cycle of indebtedness’, in which excess interest rates exacerbate indebtedness and loans are never paid off, constitute a real social concern. We can, to some extent, examine this proposition by looking at the persistence of debt amongst the sampled individuals.
Overall, however, much of the public and media portrayal of the consumer ‘debt problem’ (whether of low income families or of families in general) is somewhat perverse to the economist. After all, the life cycle hypothesis of saving suggests that individuals will spend some parts of their life in debt whilst saving and decumulating assets in other parts of the life cycle. Even in low income households, persistent debt over a number of years may not be a concern if those households expect to improve their economic situation in future years. As with poverty analyses, a ‘snapshot’ of debt at a certain point of the life cycle gives only limited insight. Nevertheless it is important to understand the pervasiveness and nature of household debt among such families, not least because emphasis in public discussions on one particular source of household debt, such as the size of borrowing on credit cards, may be of less importance to these particular families. Moreover, the type of credit arrangements taken out by low income families may lead them to face cumulative debt problems that override life cycle considerations.
It is also important to note that individuals typically simultaneously incur debts and have some forms of wealth. SOLIF/FACS is incomplete in its provision of measures of household wealth to match the comprehensive information on debt, thus mirroring, in a perverse way, other data sets that report saving and wealth but which lower-censor measures of financial assets at zero. The survey does however provide some information on assets and saving behaviour. Crucially, we also know about home ownership and human capital in the sample and we find family types where it is fairly clear that debt is not offset by large amounts of other wealth. If, then, there truly is a UK ‘debt problem’, it is likely to be concentrated amongst the families sampled in this data set.
A final general point is to note that the analysis in this paper utilises a mixture of quantitative and qualitative responses. Indicators of credit arrangements used, and debts outstanding are fairly straightforward, but data on default and arrears are less so. In the context of a credit card, for example, reported arrears can mean failure to meet the minimum repayment, exceeding the ceiling (credit limit), or being unable to pay off the whole amount in the current period (which need not strictly be arrears, or even an indicator of ‘financial difficulties’ – see footnote 7). In turn, qualitative responses to questions concerning ‘difficulties’ in paying particular bills or ‘being behind’ on payments in others are almost certainly genuine indicators of financial stress but may mean different things to different respondents. Again, however, we assert that so little is known on a representative sample of the fraction of low income families that are suffering financial difficulties with repayment of debt, that the information here contains ‘valued added’ on all these issues.
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