Working Paper n. 2008-46

HOUSEHOLDS OVER-INDEBTEDNESS IN THE ECONOMIC LITERATURE

LUISA ANDERLONI

DANIELA VANDONE

Working Paper n. 2008-46 DICEMBRE

2008

DIPARTIMENTO DI SCIENZE ECONOMICHE AZIENDALI E STATISTICHE Via Conservatorio 7 20122 Milano tel. ++39 02 503 21501 (21522) - fax ++39 02 503 21450 (21505) http://www.economia.unimi.it E Mail: [email protected]

HOUSEHOLDS OVER-INDEBTEDNESS IN THE ECONOMIC LITERATURE

Luisa Anderloni†

Daniela Vandone‡

Abstract Overindebtedness is a multi-faced phenomenon with social, economic, legal and political aspects. In our study we present an analysis of the literature on overindebtedness. In particular, we look at all surveys which refer to over-indebtedness or financial difficulties of households with the aim to develop our knowledge about the nature and causes of over-indebtedness and to provide an answer to the research question: “who is likely to be over-indebted and what are the main variables that explain this risk”. Most of these studies are related to EU countries and have been published in the last decade.

Key Words: Household indebtedness, Over-indebtedness, Financial exclusion JEL Codes: D14, G20

†

State University of Milan, Department of Economics, Business and Statistics, Via Conservatorio 7, I 20122 Milan, Italy; e-mail: [email protected] ‡ State University of Milan, Department of Economics, Business and Statistics, Via Conservatorio 7, I 20122 Milan, Italy; e-mail: [email protected]

1. Introduction This analysis refers to studies – mainly empirical works or surveys - concerning overindebtedness. The definition it-self of over-indebtedness is not unique, but it varies across countries and areas of disciplines. In fact over-indebtedness is a multi-faced phenomenon with social, economic, legal and political aspects and there are a variety of over-indebtedness situations. In particular four different areas of disciplines, with various perspectives and questions, deal with this topic: - economics; - law and juridical studies; - sociology and social affairs. According to these diverse approaches the meaning of the term “over-indebtedness” may be different. Therefore in this analysis we try to adopt a wide perspective including the majority of them. Coherently with this “open minded” approach we do not choose at this stage a definition; however, in order to clarify the perimeter of our study, we should mention that, about all, approaches should agree – at a very broad level – with a definition that points out that people are considered over-indebted if they are having difficulties meeting or are falling behind with their payments obligations or household commitments. Nevertheless, problems arise when defining “payment obligations” or “household commitments”. Consequently, in outlining the perimeter of our analysis we consider that there are at least three different definitions: 1. definitions that focus only on “over borrowing”; 2. definitions that focus on all kinds of financial difficulties considering also the cases of difficulties caused only by payment of bills or rent or other non-financial debts; 3. definitions that consider jointly both the situations, that is people are considered over-indebted if they are having difficulties meeting or are falling behind with their household commitments – whether these relate to servicing secured or unsecured borrowing or to payment of rent, utility, insurances, taxes and duties or other household bills, but under the condition that financial debt is involved too. Therefore we look at all surveys which refers to over-indebtedness or financial difficulties of households with the aim to develop our knowledge firstly about the nature and causes of over-indebtedness deriving them mainly by the empirical evidence in Europe1, and only as a by product with the aim to identify the range of definitions that has been used in these surveys.2. The paper has been organised into four Sections. Furthering this introduction, in Section 2 we have examined reports related to original empirical studies that look at the nature and causes of over-indebtedness and have been published, for the most part, in the last decade. Most of these studies are related to EU countries, although we also include key researches undertaken elsewhere. These studies include some that have examined general over-indebtedness and others that focus on financial difficulties relating 1

According to the request of the European Commission, Directorate General for Employment, Social Affairs and Equal Opportunities for the project “Towards a Common Operational European Definition of Over-indebtedness” 2007-2008. 2 The studies summarised in Table I and IV are also classified according to the above mentioned definitions.

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specifically to the payment of consumer credit, mortgages, rent, utility bills and other household bills. The papers examined are summarised in the synoptic tables: aim of the survey, methodology and variables considered, main results are highlighted in the tables I-IV in the appendix. Considering the macro area of aims pursued and the methodologies adopted, these studies have been divided into 4 categories: 1) analysis based on empirical-descriptive methods, 2) empirical-econometric analysis, 3) the approach of credit scoring models, 4) qualitative researches. All the above mentioned approaches try to provide an answer to the research question: “who is likely to be over-indebted and what are the main variables that explain this risk”. However they make different assumptions and the results they provide have different meaning. In Section 3 we deal with the relationship between over-indebtedness and financial exclusion. Section 4 provides concluding remarks and suggestions for further analysis.

2. An analysis of surveys on over-indebtedness Empirical analysis aimed at studying the over-indebtedness phenomena with reference to individuals or families or households can be classified into four broad categories, as above mentioned: - empirical-descriptive methods; - empirical-econometric analysis; - the approach of credit scoring models; - qualitative researches. The first group includes studies that attempt to describe the phenomenon of overindebtedness after an in depth understanding of human behaviour based on interviews and personal data of representative samples of the population or of its segments, defined in an appropriate way according to the aim of the analysis3. Sometimes the data are not collected by interviews, but through re-elaboration of data available from files of utility services providers, banks and other financial institutions, consumer advice services where personal data and behavioural data are stored (examples of stored information are those concerning frequency and amount of arrears, levels and kinds of consumptions, etc.). The second group includes studies that use econometric methods, such as regression, time-series, cross-sectional analysis, to test working hypothesis on a large number of observations, sometimes based on database collected as in the previous group plus other macro-economic or social data. The third group includes studies based on a database constructed from a sample of applicants who have already been granted credit and fed with the credit history of each individual as to see whether they turned out to be a “good” risk or a “bad” risk. The fourth group includes qualitative researches aimed at an understanding of findings and behaviour of specifically targeted people. The data are collected by in depth interviews generally on small samples or are taken from files of cases handled by institutions dealing with this kind of problem. In this case the aim of the research in not to generalise the results but to interpret specific situations. The variables used in these four categories of studies are: 3

Possible examples of samples based on segments are those that consider only people living in a specific area, or young persons or elders, or unemployed or presenting other specific socio-economic characters.

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− individual factors; − institutional factors: − individual credit histories. Individual factors include: − household demographic characteristics, like age, gender, ethnicity, education, family circumstances, socio-demographic adverse events (i.e. negative health shock, family break-up, etc.); − household economic characteristics, like income earned and wealth, family dependants, home property or tenure, employment status, economic adverse events (i.e. unemployment shocks, negative income shock, incidents, unexpected rise in expenses and debts). Within this body of literature, the empirical studies we are considering are those which analyse the types of factors that affect the households level of indebtedness and their ability to repay. Institutional factors are aspects which are not linked to the personal or macro economic situation but to the institutional context. These factors may influence the willingness to repay and, in turn, may influence the amount of debt holding. We can detect institutional factors moving from this assumption: when deciding whether to repay, an individual (rational agent) weighs the gain of resources from non repayment against the punishment for default. The ability of the financial market to punish default is influenced by the level of information shared, legal restriction and judicial enforcement, and the level of development of the informal credit market. It is very difficulty to measure their impact. Often they explain country differences about the level of indebtedness and therefore of over-indebtedness and the related willingness to honour financial commitments after an adverse event occurred. A special case is that of fraud, i.e. open account, use overdraft facilities or apply for credit with no intention of paying on them. Data from individual credit histories are those stored, along with individual factors (both the above mentioned personal or household demographic characteristics and personal / household economic characteristics), into the files of credit scoring models. They include: − number, type and amount of credit granted and their use over time; − amounts owned (number of accounts with balances and percentage of available credit in use); - payment history (late payments, bankruptcies and other negative items); - search of new credit (applies for or opens new credit accounts distinguishing between a search for a single loan and search for many credit lines, in part by the length of time over which inquiries occur). Generally, both quali-quantitative analysis based on empirical-descriptive methods and qualitative researches use mainly individual factors to explain the types of behaviour of different groups of individuals. The second group of studies adds to individual factors the institutional ones and combines them in order to predict behaviour or events. Finally, credit scoring models link individual factors to individual credit histories in order to predict the risk of default. Therefore the variables exploited are often common, but they can be used differently according to the diverse approaches.

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2.1. Who are most likely to be over-indebted: the results of analysis based on empirical-descriptive methods As clearly shown in Table II, there is a wide body of literature that studies which groups in societies have the greatest likelihood of facing financial difficulties in meeting their financial commitments and other household payments and being over-indebted. Our collection of empirical studies concerning households over-indebtedness or more generally the difficulties of debt repayment has demonstrated how the attention for this kind of problem is differentiated among countries and how many different aims, approaches and available database there exist. This means that the results of different studies can not be easily compared, but only that a broad picture of different contexts can be drawn. 2.1.1. Age Age and level of income are the most common variables considered by the large majority of surveys. Generally speaking the most exposed to the risk of over-indebtedness are people in their thirties, which is generally the second or the third age group in the scale of age groups, followed by those groups that immediately come before and after4. A special case is that of Great Britain where young people tend to use more credit and loans and with debts increases the frequency of being over-indebted too. However the likelihood of being in financial difficulty exists mainly for young householders, while young people still living with parents were not found to have a higher level of risk5. Increasing age from 40-45 to 50 and over is usually accompanied by a decrease in demand for borrowing, either because incomes are sufficient to cover household expenses or because people are more conservative towards borrowing. 2.1.2. Family circumstances 4

Surveys in Belgium show that the highest frequencies are found in the age groups 25-34 (30.5%) and 35-44 (29,4%) [OCE, 2004 and Banque Nationale Belgique 2006], in France the age group 35-44 accounts for 30% and that of 45-54 for an other 26.6% [Banque de France 2005] similar to the evidence of 5.5% in the age group 35-54 of a previous analysis in the same country [Le Duigou 2000]. In Germany, in the old federal states, formerly West-Germany, people that more often are affected (age group 40-49) are older than those in the new federal states, formerly east Germany, where the higher concentration is in the class 20-39 years [Springeneer et al. 2006]. According to Reifner et alt. the age group with the highest percentage of over-indebted (17%) includes people aged 35-40 years, but significant percentages are almost evenly distributed in the groups ranging from 18 to 50. In Greece the most critical ages are those in the age groups 36-45 and 46-55 years [Mitrakos et. Al 2005] and in Italy the age group 41-50 accounts for 32,4% of the cases [Landi S. 2006)] while in Norway, exposed debt is relatively evenly distributed across all age groups over 25 years of age [Norges Bank 2006]. In Portugal according to the Observatório do Endividamento dos Consumidores the most affected are in the age group 36-45 accounting for 35.0%, followed by 32.0% in the age group 46-55, while according to Frade - the age group 30-39 accounts for 32,8% and the age group 40-49 for 28.1% (Frade et al. 2006]. Finally in the UK, according to the Bank of England-NMG Research 2003, adults who reported having “heavy burden” were concentrated in the age groups 34-44 (19%) and 25-34 (13%). As in the other cases this data should be weighted with the share of the population in the group. In this country the situation is really more complex and the surveys that consider more in depth all household commitments different from borrowing highlight a higher proportion of young households facing financial difficulties. 5 Berthoud R. and Kempson E. 1992.

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The marital status of the population is often analysed as a personal feature which may influence the risk of being in financial difficulties. Here the results are difficult to comment due to the different life styles and changing situations6. As a consequence of this, the criteria of classification of the marital status are not homogeneous across countries and even among different surveys in the same country. Furthermore, sometimes the marital status is declined together with the circumstances of having dependant children. From a methodological stand point, the latter is a very important element to consider analysing the over-indebtedness phenomenon, for its economic and social implications that render more serious problems, but in practice the statistics are not easy to read, and most of all to compare7. When we consider only the marital status and use the following main categories of civil status: “married or cohabiting couples”, “single”, “divorced or separated” and “widow”, we find that generally the highest percentage of over-indebted people (in absolute value8) is related to married or cohabiting couples9. As a complement to these percentages there are mainly singles10 and divorced or separated. As already mentioned the phenomenon of separated-divorced at risk of overindebtedness appears more evident in Belgium (35.2%), in France (32.7%) than in other countries. However, we have to point out that in these last mentioned cases the data is related to over-indebted persons who applied for specific procedure to rescheduling their debts and to managing the financial difficulties.

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The models of households and families (based on marriage, partnership, single parent, and so on) are changing quickly in some societies and sometimes the marital status reflects also institutional/ economic convenience, therefore sometimes the declared situation is different from the real one. As highlighted by Banque de France 2005, in France the trend between 2001 and 2004 is mainly due to the increase in relationship breakdowns. It is interesting to note that in the dataset of the surveys conducted by the Bank of England and NMG Research from 2002 to 2006, the variable “marital status” is available, but it has not been used in presenting the main results: the variables considered are instead “age”, “housing status”, “income group”, and “social class”. 7 Furthermore, the statistics should be compared with the different groups in the whole population. This approach has been adopted by Kempson & Atkinson 2006 and Reifner et. al. 2007 and by Bank of England with reference to the different variables analysed in that study. 8 As previously mentioned, we should compare correctly this value with the share of the population in each respective status. 9 This is clearly the case of Portugal with percentages as high as 66.5% and 61% [respectively Observatorio de envidamento dos consumidores 2002 and Frade et al. 2006], Italy with 60.4%[Landi 2006], Germany-formerly west–Germany [Springeneer 2007] and Germany with 42% [Korzach 2000]. In Great Britain the risk of being over-indebted or in financial difficulties is higher for families, but here the emphasis is – at the same time - on the presence of children [DTI-MORI 2005, Kempson 2002, Kempson et al. 2004, Kempson 2006]. In France the category “married or cohabiting couples” accounts for 36.5% [Banque de France 2005] while in Belgium it falls to 28.7% [Observatoire du credit et de l’Endettement 2006] 10 Very high percentages are found in Germany with 41% [Reifner et al. 2007] where the category likely includes also divorced/separated persons without children, while in an other previous survey singles account for 26%, divorced or separated accounts for 19% and single parents for 13% [Korczak 2000]. The risk of over-indebtedness seems to be rather high among single persons in Belgium showing 31.4% [Observatoire du credit et de l’Endettement 2006] and in France with 25% [Banque de France 2006], while in Portugal the probability falls to 14.8% in 2002 and 16% in 2006 [respectively Observatorio de envidamento dos consumidores 2002 and Frade et al. 2006] and in Italy to 15% [Landi 2006]. In Great Britain the link between single status – risk of over-indebtedness seems to be weaker, but becomes stronger and more evident when single are single parents [DTI-MORI 2005, Kempson 2002, Kempson et al. 2004, Kempson 2006].

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Among causes generating financial difficulties, changing family circumstances are also often mentioned. These may refer to having a baby or to family breakdown leading to separation and divorce. A cross country comparison can be done pointing out once again the severe limits of a very broad comparison made among different contexts analysed by studies that adopted different methodologies and used different samples: having said that, the link between life changes and financial difficulties seems to be more evident in France11, Germany12 while it seems to recur to a lesser extent in Great Britain13 and Portugal14. 2.1.3. Economic activity status and level of education The relationship between employment status and risk of over-indebtedness has been widely studied by most surveys and it is a point strongly considered in the credit scoring models. From a theoretical stand point we have to consider that, on the one hand, the possibility to obtain credit (consumer credit, personal loans and mortgages) is linked to the employment status and to the level of income. Therefore employed full time, with a stable job, well skilled and with a good job position can account for a wider selection of credit and can benefit from better economic (i.e. level of interest rates) and financial (length of loans contracts, flexibility on reimbursement) conditions15. In other terms, these categories have more opportunities of over-borrowing. Generally they are also more well equipped (financially and culturally) to face changing situations and managing difficulties. On the other hand, those with the worst creditworthiness and lowest credit scores are often forced to access more expensive credit conditions and to negotiate different lines of credit with different lenders. Both the two mentioned situations can cause, in the

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According to the Banque de France 2005, among “passive causes” the item “separation-divorce” accounts for 14.7%, the second more frequent cause after “job loss”. Also in previous times – according to Le Duigou 2000 – “separation” is the second cause of over-indebtedness after “unemployment” in two areas of the Commissions for managing situations of over-indebtedness with percentages as high as 17.6% and 11% respectively, and this follows the “job loss” item accounting for 34.6% and 37% in the same area, while in the third area studied “separation” is a less important factor with 8% while a stronger impact of economic factors is found (“unemployment” 43% and “income reduction” 13%). 12 Springeneer (2007) with reference to both new and old federal States quotes as the third cause “divorce-separation” which comes after the main causes “unemployment” and “permanent low income”, such as working poor in particular in the New Federal States. Also Korczak (2000) found “separation” the second cause of over-indebtedness (22%) which follows the main reason “unemployment” (38%), while other family changes such as “birth of children” accounts for 6%. The same ranking is shown by Reifner et al. (2007) where “separation or new engagement”, accounts for 15,2%, next to unemployment accounting for 29.9%. 13 According to the Bank of England-NMB Research (2006) “divorce or separation” is quoted with a minor frequency as a cause of debt problems (4%), the same percentage in the case of “one of the parents leaving work to have a child”, while DTI-MORI (2005) finds that those who have experienced a significant life event in the past 12 months are over represented on all over-indebtedness indicators: 5% of respondents had had a child in previous 12 months, but they accounted for approximately 11% of those in arrears. Separation from partner was over-represented in 3 out 5 of the five indicators, accounting for only 3% of the sample, 9% of those finding their borrowing repayment a heavy burden. Analogously, Kempson et al. (2004) found that the likelihood of arrears on consumer credit and household bills increased from 20% of those who did not experienced changes in that period to 32% of those who had a new baby or separated and that the impact on consumer credit was more marked than that on household bills. Yet in Kempson (2002), the two key life events mentioned were found both strongly associated with financial difficulties. 14 According to Observatorio do endividamento (2002) changes in the household composition had a frequency of 12.8% and is ranked fourth, after to low income (33.7%), illness (18.2%) and unemployment (14.6%). 15

Surveys on indebtedness prove that people with a higher level of borrowing or financial debts, in absolute terms and sometimes also on relative terms, are mainly those who have better employment and income positions.

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event conditions change (with reference to the family circumstances or to the economic status), the risk of facing difficulties which could increase even more. Consequently, the unemployment condition is more often a cause of falling into overindebtedness or, from a different perspective, the poverty it-self (that is inadequate income and poor or nil working conditions) is the main reason of financial difficulties. Generally households which are economically inactive due to retirement or with an unemployed head resort more rarely to borrowing. Cross country comparisons are in this field difficult or partially mis-leading due to the difference of social welfare in different countries and, again, to the fact that in some cases over-indebted persons studied are those who applied for debt-settlement procedures, while in other cases the results are related to a more general sample. Empirical evidence generally supports what is said above on a logical basis: overindebted people are more often employees (white collar or blue collar without a strong difference in our societies) rather than self-employed or pensioners and other inactive persons16. A share, sometimes large, is represented by unemployed people or those living on benefits, but as already highlighted, it is difficult to assess if this is on a present situation, while the job loss caused or jointly caused the financial difficulties. With regards to the level of education, this is a variable that is generally linked to the labour status (evidently a higher level of education is related to better jobs and economic positions) but is also important from a different stand point: a person better educated has both more opportunity to evaluate his/her financial position and the terms and conditions of the credit offered, and later, is better equipped to manage situations of difficulties dealing with banks and credit institutions, and other social institutions. 2.1.4. Income and labour conditions Income is another variable analysed in depth when studying the phenomenon of household over-indebtedness. There are at least three main points of interest. First of all, as for the above described variables, it is very useful in order to better understand and depict the profile of those who are more at risk of falling into financial difficulties. Secondly, it is often used in constructing objective indicators of overindebtedness as it is an economic parameter both of financial flows and, to some an extent, of the level of household wealth. Here it is important to outline how different definitions or measures can be taken, these varying from the nominal income, to the disposable income, to equivalised income (in order to take into account how many persons resort to those resources for living), to the earned income and so on. Finally, in conducting stress tests in order to predict the impact of changes in the economic situation of a country or of an area (i.e interest rates and level of income, generally 16

In France employees – of different categories– account for 54,9%, while self-employed executives and various kinds of practitioners reach together a share of 3.7%, pensioners are as low as 7.4% and unemployed and others out of work accounts for 34% [Banque de France 2005], while in previous times alongside the high share of employed in different categories on the same level at 54.9%, there was a large share of self-employed (craftsmen and professionals) 28,3% and a higher proportion of retired and inactive person 16.7% [Le Duigou, 2000]. In Italy, where the over-indebted people of the sample are persons fallen into the usury trap, it is easy to understand why most of them (55.3%) are employees, 17.9% are self-employed and professional men, and 18.1% are retired, while irrelevant is the share of unemployed [Landi 2006]. In Germany, according to Reifner et. al. 2007, the phenomenon is more frequently widespread among inactive people (unemployed short or long term, living on other benefits and retired). In Portugal, the unemployed people over-indebted are as low as 7.4 plus a 6.9% of persons attending training courses, and the largest share are employed in various jobs, sectors and positions.

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linked to evolving conditions in the labour market) one of the elements considered is the impact of these changes on the level of income and, therefore, on the affordability of the level of indebtedness. As it is easy to predict on a logical basis, the majority of surveys provide evidence that there is a strong link between household income and the likelihood to have financial difficulties. However, as above mentioned, if the highest levels of debt in absolute are found among the wealthy groups17, the risk of being over-indebted and facing financial difficulties is higher among the poorest groups. In many cases - in particular when all kinds of debts are considered, i.e. when arrears on household bills, rent and other household commitments are taken into account – the conclusion of the analysis is that poverty it-self18 is the main cause of financial difficulties. In these cases, when comparing expenses and financial outflows to the income, we could infer both conditions of over-borrowing and over-spending, indeed these are only the results of very low income so that everything is “over”. With reference to both variables “economic activity” and “income”, the changes other than the initial situation are of most relevance in motivating conditions of overindebtedness. Job loss or working hour reduction and income reduction are very often associated with the risk of over-indebtedness and mentioned as causes of financial difficulties. In the French context, where the concepts of “active” and “passive” situations are very common, job loss and other factors, all causing in different ways a reduction in the disposable income, are at the origin of passive over-indebtedness and passive conditions account for 72.2% of the cases, while active ones stand at 27.1%. Forgetting the distinction between active and passive over-indebtedness, as already mentioned above, in almost all countries changes in labour conditions, i.e. unemployment or forced severe reduction in working time, is the first reason for financial difficulties, generally outdistanced from the following reasons and accounting by itself for a share closer to forty percent than thirty percent19. 2.1.5. Other common variables Various studies consider also additional variables in order to identify the link between them and the likelihood of overindebtedness. The most common are: - housing tenure and real estate wealth; - savings; - attitudes towards payments, credit and money management; - degree of urbanisation of the area of residence; - health; - ethnicity. As far as housing tenure is concerned, when trying to do a cross country reading of the phenomenon, we should mention once again the need to consider the specific conditions 17

In Greece one of the main results of the study is that borrowing is concentrated among households with the highest level of income and the same is found by the periodical assessment made by the supervisory banking authorities in their financial stability reports when periodically analysing the impact of the development of the consumer credit markets on financial stability conditions for the whole banking and financial sector and estimating the risk of financial vulnerability [Mitrakos et. al. 2005). In Norway, the main difference among households with positive and negative margin after principal, is average income level. Differences on the expense side are less evident so that it is deduced that negative margins are largely the result of low income [Vatne B.H. 2006]. 18 I.e. inadequate income to survive and lack of any other kind of resources (savings, help from parents or friends, etc) 19

This is the case of France [Banque de France 2005] and Le Duigou 2000], Germany [Springeneer 2007, Korczak [2000] and to a lesser extent according to Reifner et al. 2007.

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of accommodation in each country and the different meanings, in economic and social terms, of different forms of accommodation20. Having said that, we can point out, in broad terms, living in rented accommodation is associated with a higher likelihood of being in financial difficulties21. If home ownership was identified as being associated with a lower risk of overindebtedness, there is also a logical reason for that: those who have real estate know that creditors may register a mortgage on the property in order to defend their right or can levy execution on it. Therefore they try to avoid, where possible, falling into overindebtedness and into severe financial difficulties. Similar reasons motivate a positive relationship among wealth (real and financial assets) and soundness and financial solvibility. As savings are concerned, generally the surveys which collect information on this aspect, all conclude that those who are over-indebted or at high risk of being in financial difficulty, lack this form of safety net, which is very useful in times of hardship22. As regards attitudes towards payments, credit and money management, it suffices to mention here that psychological features of the individuals and their attitudes towards payments, use of credit and deferment of payments often play an important role in influencing the level of debt and the risk of facing problems with reimbursement. Although generally these kinds of psychological attitudes are not studied in depth in surveys which analyse the phenomenon of over-indebtedness23, however some of them provide preliminary findings. It is easy to understand, those who generally have an attitude of avoiding debts and refraining from postponing payments, at the cost of going without other things, are much less likely to have problems with debt and arrears24. There is generally a relationship between the above mentioned attitude and age as older people tend to avoid debts and attach a higher importance on keeping up with payments. Considering degree of urbanisation of the area of residence, sometimes surveys take into account that attitudes, behaviour and financial management are also related to life styles and culture. Generally the finding is that those living in countryside are more conservative towards debt and often manage budgets where costs and expenses are more easily reduced in hardship. With regards to health, illness is a possible cause of overindebtedness also if it is generally statistically less important than others. In principle, aspects of health could be positively correlated with overindebtedness, similarly to age, economic activity and income. In other words, more fragile persons are to a larger extent exposed to hardship and, consequently, to the likelihood of passive overindebtedness. 20

As previously stated, the Bank of England-NMR Research and DTI- MORI (2005) correctly compare the percentages of different groups with those of the whole population. 21 In France only 3.7% of over-indebted people are owners and 6.3% are buying a house with a mortgage, while 78.2% are tenants renting in the social housing sector and 9.8% are free tenants. [Banque de France 2005]. Instead in a previous survey, the picture drawn showed a higher proportion of owners and mortgagors accounting for 48%, and tenants renting in the social housing were 21.3% and free rent tenants 30.7% [[Le Duigou 200]. In Great Britain, various surveys from the Bank of England-NMG reveal that people whose debts are “a heavy burden” are over-represented by renters (both private and local authorities) and this finding is confirmed by other surveys (DTI-MORI 2005, Berthoud R. and Kempson E. 1992, Kempson 2002 and Kempson et. al. 2004). 22 Berthoud and Kempson, 1992 and DTI-MORI 2005. 23 Vice versa, a body of literature, behavioural finance, studies more in depth the issue and provide useful comments on attitudes both toward investment and debts and their management. 24 See Berthoud R. and Kempson E. 1992 and DTI-MORI (2005).

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As far as ethnicity is concerned, in most European countries, minorities are overrepresented in the low-income groups and in the category of more unsecured working positions, living in rented housing, therefore, they are, in principle, more at risk. Little empirical evidence is available in this field for two main reasons. Firstly, in order to limit the risk of feeding and disseminate discrimination, statistics on overindebted people do not show the variable “ethnicity”. Secondly, often surveys include in their samples only the native population, while migrants and ethnic minorities are eventually the target of specific analysis and, in this case, the focus is generally on the difficulty of access or financial exclusion rather than matters related to oveindebtedness. The evidence of these studies25 is that it would be wrong to consider migrants or minority as a homogenous category, because their access to financial services, behaviour and needs are very diverse. Personal features, ethnic groups as well as the stage in the migrant life cycle, are all relevant elements in explaining the level of access to financial services and the difficulties faced. 2.2. Multivariate analysis: what explain household non performing loans ? Econometric empirical studies on households’ debt arrears and financial fragility are aimed to understand to which extent the current increase in households’ indebtedness constitutes a movement towards a new equilibrium or, rather, is related to a riskier financial position for the sector. Typically, these studies use institutional database that are publicly available and are taken from the statistical publications of national central banks. The studies can be divided in two groups, accordingly to the type of variables affecting debt arrears taken into account: the first group focuses on individual factors and the second on institutional factors (table III). 2.2.1 Analysis based on individual factors The research question of these papers is to identify what factors affect the affordability of debt, that is which are the major elements influencing arrears and households’ financial fragility. These models adopt a set of variables (i.e. income, wealth, type of employment, home property, education, age, marital status) that tend to explain a good proportion of the variation of arrears, indicating that these models captures quite well the factors behind arrears’ development. The results, in general, agree on the fact that the main statistically significant factor predicting debt problems is the level of debt to income ratio. Del Rio and Young (2005) find that, although there is no clear point at which debt becomes a problem, there is a strong link between the level of debt to income ratio and the probability of debt being somewhat of a burden or a heavy burden. Similarly, Rinaldi and Sanchez-Arellano (2006) find that an increase in the ratio of indebtedness to income is associated with higher levels of arrears. However, they also find that if the rise in the debt ratio is accompanied by a rise in real disposable income, the negative effect is more than offset. Some of these models include variables for adverse events, such as unemployment shocks, negative income shocks and health shocks. The propensity to fall into arrears is 25

Anderloni (2003) with reference to Italy, Anderloni and Carluccio (2007) and Anderloni (2007) with reference to Italy, France and Spain.

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affected by adverse events, but the extent to which they matter varies across countries and depends crucially on institutional factors. 2.2.2 Analysis considering institutional factors The research question of this second group of papers is to investigate the effect of institutional factors on borrowers’ arrears and repayment behaviour. Empirical analysis find that, although the set of individual variables affecting households’ overindebtedness is the same, there are significant differences across countries in households’ propensity to arrears and households in different countries respond differently to adverse shocks: households in similar circumstances fail to repay their loans on time in some institutional environments but keep up with their repayments in others. These differences are explained by institutional factors, among which the most important are: the information sharing structure, the efficiency of the judicial system, the existence of informal credit markets. The analysis of institutional factors is important because they affect not only the ability to repay after an adverse event occurred but also the willingness to do this. In fact, when deciding whether to repay, a rational agent weights the gain of resources from non repayment against the punishment and the cost of default. Consequently, these studies introduce explicitly a default option into a model of life-cycle consumption to explain how the possibility of default influences the level of consumption, and thus the level of indebtedness, and its sensitivity to income. The ability of the financial market to punish default is influenced by the cost and efficiency of judicial enforcement, the level of information sharing and the importance of informal credit markets. 1. Judicial enforcement As far as the quality and cost of judicial enforcement, Duygan and Grant (2006) find that households are more likely to be in arrears and to default when cost of enforcement increases and when it takes long time for the court to enforce the contract. They also find that negative earnings shocks are more likely to result in missed repayments where creditor rights are poor. Grant and Padula (2006) specify that the effect of judicial enforcement is significant for housing credit since it affects decision to lend through its effect on the value of the collateral but it is economically small and statistically insignificant for unsecured debt. This do not surprise given the small size of the typical loan and the fact that these loans are uncollaterized. 2. Information sharing Jappelli and Pagano (2006) analyse the effect of information sharing on borrowers’ characteristics and indebtedness and find that information sharing reduces borrowers’ incentive to become overindebted by drawing credit simultaneously from many banks without any of them realizing. A borrower’s default risk depends on the overall indebtedness of the borrower when his obligation toward that lender will mature; if this information is unavailable to the lender, however, the borrower has the incentive to overborrow. Similarly, Duygan and Grant (2002) find that households are less likely to default if other lenders can learn of their failure to repay their debts. They find that in all most cases unemployment shocks lead to a failure to repay loans on time, but this happens more frequently in countries with limited information sharing. 3. Informal credit markets Grant and Padula (2006) find that the effect of informal credit markets on whether the debt is repaid is both economically and statistically significant and negatively affect

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repayment behaviours. Household with access to informal credit markets view exclusion from the formal credit market less onerous since they can still borrow from friends and family should the need arrive. 2.3 The approach of credit scoring models Credit scoring models have been developed in order to identify default risk by companies granting consumer credit. Scoring is typically constructed from a sample of applicants who have already been granted credit. For each of these individuals the credit history is needed to see whether they turned out to be a ”good” risk or a “bad” risk26. Discriminant analysis, multiple linear regression, probit, logit or some other type of classificatory procedure are the techniques applied in order to construct these models. Two newer methods beginning to be used in estimating default probabilities include options-pricing theory models and neural networks. Due to their proprietary nature little is known about the specific content and structure of credit scoring models in order to predict the probability of personal default; however, a relatively large number of studies have been published on such models. The models utilize both socio-demographic characteristics27, economic features of the borrower and historical data on credit performance. These data are then used to calculate the predicted probability of default for each new applicant by combining the estimates coefficients from the probability of default regression with the applicant’s values of the explanatory variables, or in dividing borrowers into high and low defaultrisk classes. These models are estimates based not only on original variables, but also on transformations of these variables by weight of evidence and reduction of classes of weight of evidence. 2.3.1 Variables in the models As shown in table IV, the most common socio-demographic variables are: age, gender28, education, marital status, number of children or other dependants, ethnicity. To evaluate economic characteristics, the most important variables used are income (measured and considered in various dimensions), employment, labour agreement, housing tenure and other indicators such as time at address and time in employment(i.e. stability), telephone and postal code of the applicants and of his/her employer (for deriving economic indicators), credit insurance. The credit history consider not only the experience of defaults and of delinquencies and of dishonoured payment instruments or other unpaid, but also number of credits, guarantors and their actually use, credit card use, savings and other financial assets, and number of requests for information on the applicant that the credit agency received during the last months. 26

In the credit industry a “bad” risk customer is typically defined as someone who has missed three consecutive repayments. 27 The information that can be used to build a score model is often subject to regulation. In the U.S. for example the Equal Credit Opportunities Act (1974 and 1976) stipulates that scoremodels cannot include variables such as race, gender, or marital status. Similarly, in the UK the Sex Discrimination Act (1975) and the Race Relations Act (1976) makes it illegal to discriminate on grounds of gender and race when granting credit. 28 In countries where there are not restriction regarding the elements that can feed the credit scoring models.

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2.3.2 Problems with credit scoring The main problems that have been the subject of considerable debate in the literature are: - the reject inference; - the population drift; - the unobserved effects. One of the main problems is that since models tend to be constructed from the sample of individuals who have already been granted credit, the design sample will be biased with regards to the overall population of applicants. Consequently if the rejected applicants are thought of as being a 'bad' risk, individuals with similar characteristics will potentially be rejected from receiving credit in any scoring system based on this data, and so will never have the opportunity to prove their worth. Attempts to infer the true risk status of the rejected applicants in order to build a superior score-card is known as 'reject inference', and the issues is widely discussed in the literature29. Another problem that can arise when designing a score model is that of population drift. This takes into account the tendency for the distribution of the characteristics of the population to change over time. Consequently, the sample used to build the score-card maybe significantly different from the population that the score model will be used on, so reducing its performance. A way to move around this problem is to compare the statistical properties of the applicant population (at various times) with those of the sample population, and to build a new score-card when the differences between the two become too great. In addition, in the present credit-scoring system a 'bad risk' (i.e. a rejection) tends to arise from the behaviour of individuals with similar observable characteristics. However, credit default may be driven by unobservable characteristics. As mentioned earlier, for example, some observable characteristics cannot legally be used to build a score-card. It follows from this that individuals may be rejected from credit simply because they have similar observable characteristics to someone who is a bad risk as a result of their unobservable characteristics. Credit scoring systems thus need to begin to control for unobserved effects. We have to highlight these problems because people with a low credit score are refused by banks and other prime lenders and sometimes also by sub prime lenders and could be induced to address illegal lenders30. Therefore the ability of credit scoring models to distinguish correctly between “good” risk and “bad” risk is of great importance also from a social stand point.

2.4 Surveys adopting qualitative researches Studies based on qualitative researches are aimed to in-depth analyse the behaviour of small sample of specifically targeted people. Although the results are difficult to 29

See, for all, Crook J., Banasik J. (2002), Hand D.J. et al. (1994). Researches demonstrate that use of illegal lenders is greatly driven by a lack of legitimate credit options, with borrowers turning to illegal providers only after all other potential sources of credit supply have been tried or exhausted (Elisson A. Collard S. Forster R. 2006).

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generalize, these researches are relevant since they give a valuable contribute to better understanding the situation of people in financial difficulties and their behaviour. The studies reported in table V focus on random sample of people who lost their job in a specific economic sector (Frade 2004) or people who apply for assistance from citizen associations (Frade 2004, Edwards 2003, Observatorio do Endividamento dos Consumidores 2002) or households that defaulted on their utilities debts (Herbert and Kempson 1995). In such a situation, unemployment, low income, money mismanagement and illness are the main causes of default. Financial problems may also arise from their consumption and indebtedness patterns - the ant and the grasshopper, Frade 2004 - which generate distinct sustainability of families in the face of unemployment. 2.5 A synthesis of causes of over-indebtedness As previously stated, individual factors, institutional factors and previous experiences in the credit market are all elements that explain the probability for a person in a certain context to fall into financial difficulties and to become over-indebted. In many cases, adopting descriptive and qualitative methods of analysis, it is possible to rank the situations that characterise over-indebted households or persons, but it is difficult to discern whether a factor is really a cause, i.e. it is a determinant, or it is a consequence or a simple accessory circumstance31. Indeed, it is more likely that risk factors will work in combination with others and with other unexpected events in leading to overindebtedness For this, multivariate analysis as well as credit scoring models are more appropriate to interpret the situations and to predict the probability. Differences shown in different countries and in the same country by various surveys reflect also a bias due to the fact that the causes of financial difficulties may be deduced in different ways. Sometimes they are derived by files of organisations in charge of providing assistance to persons in financial difficulties. This kind of activity may have to follow specific legal procedures as part of court activities. Therefore, the listed causes are – to some extent – filtered by the objective evaluation of the situation from an expert while, in the other cases, they are simply self-reported by the persons directly involved in the financial difficulties and interviewed about their position and feelings. Furthermore, we should consider that sometimes the survey is addressed to the whole population and consequently the questions and the reported answers tend to be more generic, otherwise when addressed to more specific targets both questions and answers tend to be more detailed and the analysis of causes goes more in depth. Summarising the results of the surveys considered in our review of the literature, we found that among the causes at the top of the rank by frequency there are low income, unemployment or poor working conditions and changes in these conditions (unemployment or forced reduction in hours worked) as well as changes in family status ( family breakdowns and birth of a new child)32. These main causes are followed by other facts that generate unexpected additional expenses (illness, …) as well as reduction in earned income (illness and permanent 31

For example, Farinha 2004, with reference to Portugal, shows that income and age are more significant than school and income. 32 Se footnotes n° 12-13-14-15.

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injuries).Furthermore it is worth mentioning attitudinal causes linked to money management, credit use, payments and arrears. However, we should recall what was previously mentioned: as with most social phenomena, more often it is not a single simple cause that leads to overindebtedness. Rather, it is more likely that risk factors such as low income, unstable job and precarious financial conditions will work jointly and trigger (such as changes in circumstances) sparking off the difficulties. Therefore, we find attitudinal causes related to money management, styles and ability linked to financial literacy and financial capability, and over-commitment as a consequence of over-borrowing or over-spending or, simply, poverty among the reasons that motivate the financial difficulties of households. Researches also point out the growing phenomenon of working poor. Generally surveys conducted by or on behalf of consumer associations or debt and family budget counselling agencies pay more attention to these elements and highlight the link between them and the risk of overindebtedness. Consequently, they overemphasise the role of promoting financial literacy and financial advice to consumers as a tool to prevent overindebtedness. Surveys in a number of developed countries suggest that financial literacy levels are particularly low amongst the less educated, minorities and those on lowest income, while the trend towards the liberalisation of markets with a proliferation of providers and distribution channels, together with increasing product innovation increases the risk of mis-selling and of contracting unsuitable credit and loans, on the one side, and investments and savings, on the other.

3. Over-indebtedness and financial exclusion: a complex relationship Although overindebtedness is generally considered a phenomenon separated from the rest of financial exclusion, indeed there are cause-effect links between them. The relationship between the two conditions and also with social exclusion are complex. On one side, we have to consider the link between over-indebtedness – as a cause – and financial exclusion – as a consequence. On the other side, the relation can be reversed: financially and socially excluded people can result in becoming the most exposed to the risk of over-indebtedness. In both the hypotheses, the analysis should be conducted considering the supply side and the demand side. As far as the supply side is concerned, adopting the first hypothesis above mentioned, we should consider – in principle – two main reasons why over-indebedness may cause financial exclusion. Firstly, there is the circumstance that banks consult both credit bureaus registers and other special registers where payment incidents and dishonoured cheques are recorded not only when a credit application is submitted, but also when a request of opening a bank account is made. In some countries33 they can also consult files where persons involved in procedures concerning management of over-indebtedness situations are recorded. It is easy to understand that over-indebted people, who have likely been

33

Like in France.

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included in the above mentioned registers, face the risk of seeing their request refused by banks and are, consequently at risk of financial exclusion. This may happen also with reference to the opening of a current account which includes payment facilities involving a trust relationship. In some countries, basic banking accounts, with limited functions, have been introduced in order to avoid the risk of banking those persons that are less trustworthy. Secondly, when a situation is not already clear of financial distress, but the applicant presents too many elements of economic and financial weakness (low income, unstable job, poor financial management ability, family relationship problems and so on) commercial banks are not interested in serving them. Consequently this kind of customer is induced to resort to alternative financial providers that offer credit services that are inconvenient due to their high interest rates and charges, their limited amount that often multiply the number of different contracts signed, and the short terms for the reimbursement. This feeds a vicious circle where the sequence of over-indebtedness, payment difficulties, insolvency and financial exclusion is often found34. On the demand side, those who experience over-indebtedness conditions may be induced to quit the financial market, i.e. become financially excluded, for various reasons. Negative experience in managing debts and dealing with banks may generate fear of loss of control, and preference to manage the family budget only by cash35 and, when income are low, to do without a relationship with a deposit institution. In other cases, as above mentioned considering the supply side, sometimes banks refuse to open a full transaction bank account to certain groups of people such as those with a poor credit history or those who failed credit scoring systems because their characteristics meant they were assessed as a high risk. But there is evidence that people may be deterred from opening an account if it does not offer overdraft facilities to ease access to money paid on it. Furthermore, delays in clearing cheques paid into an account meant that people could not have instant access to any money paid in. Consequently, considering the offer inadequate to their needs, some persons may develop a negative attitude towards the banking system and refuse a relationship limited to basic banking services. In other words, they show lack of interest in opening a saving account. Otherwise, it is the risk of seizure of also the so called “guarantee minimum income” if paid on a bank account, that can cause self-exclusion, i.e. preference to do without a bank relationship. However, in most countries nowadays to receive a salary and social benefits it is necessary to have a bank account, therefore this financial self-exclusion can lead to social exclusion. Considering therefore the reverse link, i.e. social exclusion can cause overindebtedeness, we should take into account two main phenomena. First, those who are socially more fragile, suffering many hardships, living without a stable job and an adequate and stable income, have poor family budget - both on the side of the inflows and of the outflows for costs and expenses - because they have reduce margin to absorb even minimum shocks. Therefore, without a net of public 34

In France many people are denied access to an account [Gallou R., Le Queau P. 1999]. A survey conducted in Italy , France and Spain on access to banking accounts and payment services, credit and savings by low-income people at risk of financial exclusion revealed that in Italy and France it is not infrequent the case of persons who decide to return to the bank their credit card as a way to avoid spending more than they can afford [Anderloni L., Braga D., Carluccio E.M., 2007].

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welfare, social assistance and debt counselling, they are exposed to the risk of falling from a position of indebtedness to one of overindebtedness, also for only minor liquidity problems when they are not faced promptly and in an adequate manner: this may trigger a spiral of financial difficulties growing the amount involved and legal implications. Second, social excluded people, facing difficulties in proving their identity in some context36 and sometimes with complex positions (with reference to residence, job positions, marital status, and so on) and poor literacy are not attractive customers for banks. Therefore they are exposed to the risk – as above mentioned with reference to those already over-indebted - of being forced to use alternative financial providers – sometimes illegal lenders - that, due to their terms and condition, can - in this case -lead to over-indebtedness and financial difficulties, while in the previous case they reinforced a pre-existing situation of over-indebtedness and rendered more severe consequences. Besides its links with financial exclusion in general, the issue of over-indebtedness of households has given rise to two particular concerns at EU level. The first is the impact on consumers of the enlargement of the credit market, and increased competition and innovation. This is in the context of European Union moves towards a single harmonised market for financial services, progress with the Financial Service Action Plan37 and the proposal for modifying the Directive on consumer credit38. The priority is to find a balance between the goals of maintaining accessible and affordable credit together with the promotion of the internal market, while ensuring at the same time, a high degree of protection for consumers throughout the European Union. This debate highlights a discrepancy between the objective of offering financial service providers legislation to allow them to operate in the same way in all the Member States, through full harmonisation of key legislation and, at the same time, the goal of not reducing levels of consumer protection, leaving space for regional problems and combating the increase in over-indebtedness. A major concern is that, in some contexts, aggressive policies to promote the use of credit via revolving cards could lead to an intolerable increase in indebtedness, including over-indebtedness amongst those who are most economically and culturally fragile and who would be most exposed to the risk of taking on too big commitments too quickly. The increase in card-based payments undeniably presents a number of policy problems, the most serious of which is the likelihood that the use of cards will contribute to an unjustifiable level of consumer credit and that borrowing on the cards will contribute to an increase in the level of consumer bankruptcy39. Secondly, preventing and dealing with different forms of over-indebtedness represents, in some countries, an important part of the common objective to fight against poverty and social exclusion. The Lisbon European Council has established a political 36

This is a debated case in Great Britain and Ireland See http://ec.europa.eu/internal_market/finances/policy/index_en.htm 38 See Modified proposal for a Directive of the European Parliament and the council on credit agreements for consumers amending Council Directive 93/13/EC COM (2005) 483 final and the following Council of the European Union, DS258/06 of April 4th 2006. The importance to amend the Directive is reaffirmed in White Paper, Financial Services Policy 2005-2010. 39 Because increasing financial distress imposes externalities on the economies in which it occurs, the global rise of the credit card poses serious policy questions. 37

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framework, including the fight against exclusion in the Union’s overall strategy40. This is to be achieved through an open method of co-ordination combining national action plans and a Commission’s initiative for co-operation in that field. In accordance with its mandate, the Treaty of Nice endorsed the fight against social exclusion and all forms of discrimination, within its European social agenda41. Furthermore, it has included the fight against exclusion within art. 137 of the Treaty establishing the European Community. Based on this, the Council has invited the Member States to elaborate a common approach by preparing two-year National Action Plans on Social Inclusion42. In this context it should be pointed out that, amongst initiatives aimed at preventing the risk of exclusion, several national plans have included specific initiatives to confront over-indebtedness and financial exclusion. In particular, as over-indebtedness has increased it has had unfavourable implications for poverty and exclusion amongst individuals and households (for example, they were discouraged from looking for or accepting a job)43. Initiatives taken to combat the rise in over-indebtedness include the promotion of information and the development of educational activities44. In addition, some countries45 have also adopted measures to improve access to banking services and to provide free financial advice services. On top of this, the reports presented by United Kingdom46, Netherlands, France, Finland, Belgium and Germany highlight the measures taken to combat financial exclusion, such as easier access to bank accounts, simplified soft loans and face-to-face counselling to cater for the needs of people on low incomes. In these cases, financial exclusion is seen as part and parcel of social policies to fight poverty and promote social inclusion. Other initiatives taken to prevent and manage over-indebtedness include services that offer advice and guidance for people with debts47 and legislation on the regulation of debt48.

40

See Lisbon European Council, Presidency Conclusion, March 23rd and 24th, issue “Promoting social inclusion”. 41 See Nice European Council Meeting, December 7th, 8th and 9th 2000, Presidency conclusions, Annex I, European Social Agenda, III Fighting Poverty and all forms of exclusion and discrimination in order to promote social integration. 42 See NAPS/Inclusion 2003-2005 and updated reports on 2004-2006 NAPs/ Inclusion. 43 The situation and level of attention is different in the various countries, since there is no official or academic shared definition, it is difficult to compare the available data. This phenomenon seems to be relevant in Austria, Belgium, Germany, France, Ireland, Netherlands, the UK, Portugal where the NAP on Social Inclusion point out that the phenomenon has reached worrying levels and in Spain where a report of the Bank of Spain underlined the problem that 34.5% of the poorest families had debts which were three times more than their annual income. See Commission of the European Communities, Commission Staff Working Document, Implementation and update reports on 2003-2005 NAPS/Inclusion and update reports on 2004-2006 NAPS/Inclusion, COM (2006) 62 final. 44 Examples of that are Austria, Belgium, France, Luxembourg, Portugal that include these initiatives within the 2003-2005 NAPs on Social Inclusion. 45 France and Belgium in the first case, the UK in the second case. 46 The experience is particularly articulated in UK: generally, also afterwards, the government sets out the goal to reduce by 50% the number of people that do not have any bank account; to this purpose, it has created a special fund for financial inclusion. Some regions (Northern Ireland, Wales and Scotland) have taken specific initiatives. 47 See the experiences of Austria, Belgium, Germany, Finland, France, Hungary, Netherlands, Ireland and the UK. 48 With reforms introduced in Germany, France and presently under discussion in Belgium, Finland and Netherlands.

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4. Conclusion In the last two decades the interest for the issue of households over-indebtedness has rapidly grown in many European countries. Until relatively recently, excessive consumer debt was rare and largely a marginal problem in Europe, as credit was all but unavailable to most consumers and other forms of lending, such as mortgages, required adequate guarantees and stable and not low income so that this prevented, on one side, banks to take too much risk and, on the other side, households to be highly exposed to the risk of falling into over-indebtedness. Changing economic situations, labour market dynamics and volatility, competition in the financial sector exposed a growing number of people to this risk. According to the results of empirical evidence, the phenomenon of overindebtedness seems to affect only small segments of the population, so it is not important for its dimension, but for its nature. In other words, we should point out the circumstance that it disproportionately affects persons who are weak from a social and economic stand point, often deserving special attention due to various factors, such as presence of children, or of multiple disadvantages. Our overview found more attention was paid to this phenomenon in United Kingdom, Germany and France. These countries pioneered both the analysis of the phenomenon and its monitoring over time, and the answers given in order to deal with the problem, once over-indebted people declared their inability to meet their financial obligations and other household commitments. Other countries followed very soon with a great body of literature, statistics and initiatives to tackle the problem. We mention here, in particular, the cases of Belgium and Portugal. In more recent years also Sweden, Norway, Greece and Italy seem to become aware of the phenomenon and started to concentrate on it. Generally the first to pay attention are the supervisory authorities, concerned about the effects of consumer credit growth on the financial stability of intermediaries and markets49. The research questions more often addressed by the literature are: - How many people are at risk of over-indebtedness? - Is the situation getting worse? - Does the situations have implications for the financial stability of the financial system or are the consequences limited and mainly affecting the over-indebted households? - Who is over-indebted? - What are the main causes? - How to deal with the problems? How to prevent them? and How to deal with them when the situation get worse? How to balance the different interests at stake (creditors, debtors and society)? To answer these questions a preliminary issue has to be dealt with: “How can we identify over-indebtedness and measure it” ? Our analysis of the literature provides evidence that different studies, according to the their specific goals propose methodologies and indicators, but a common definition still lacks. 49

In fact that, with reference to these countries, the literature quoted in our review is mainly from Financial stability reports of the central banks.

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References Anderloni L., Carluccio E.M. (2007), Access to Bank Accounts and Payment Services, in New Frontiers in Banking Services. Emerging Needs and Tailored Products for Untapped Markets, Springer, Berlin. Anderloni L., Braga D., Carluccio E.M. (2007), New Frontiers in Banking Services. Emerging Needs and Tailored Products for the Untapped Market, Berlin Heidelberg, Springer-Verlag. Anderloni L. (2007), Migrants and Remittances, in New Frontiers in Banking Services. Emerging Needs and Tailored Products for Untapped Markets, Springer, Berlin. Anderloni L. (2003), Il Social Banking in Italia. Un Fenomeno da Esplorare, Giuffrè, Milano. Andreeva G. (2004), European generic scoring models using survival analysis, CRC – University of Edinburgh, WP 04/3. Andreeva G., Ansell J., Crook J.N., Modelling the purchase propensity: analysis of a revolving store card, in “Journal of the Operational Research Society”, Volume 56, Number 9, September 2005, pp. 1041-1050. Atkinson A., McKay S., Kempson E., and Collard, S. (2006) Levels of financial capability in the UK: results of a baseline survey. London: Financial services Authority.(Consumer Research 47). Avery R.B., Caleman P.S .,Canner G.B. (2004), Consumer credit scoring: do situational circumstances matter?, Bank for International Settlement, BIS Working Papers, n° 146. Bank of Greece (2003), Greek households’ borrowing and indebtedness: evidence from a sample survey of the Bank of Greece, in “Monetary policy 2002-2003”, pp. 8896. Banque de France (2005), Enquête typologique 2004 sur le surrendettement, Banque de France, Paris. Banque Nationale Belgique (2006), Statistiques – Centrale des credit aux particuliers 2006, Banque Nationale Belgique. Berthoud, R. and Kempson, E. (1992) Credit and debt: The PSI report. London: Policy Studies Institute. Betti. G., Dourmashkin, N., Rossi, M.C., Verma, V., and Yin, Y. (2001) Study of the problem of Consumer Indebtedness: Statistical Aspects. Contract No. B51000/00/000197. Final Report. Bridges, S. and Disney, R. (2004) Use of credit and arrears on debt among low-income families in the United Kingdom, in “Fiscal Studies”, Vol., 25, no., 1, pp. 1-25. Camões F., Hill M. (2000), Prediction of loan defaults using a credit card scoring model incorporating worthiness, paper presented at The Twentieth International Symposium on Forecasting, Lisbon, 21st to 24th June. Chen G.G., Astebro T. (2001), The Economic Value of Reject Inference in Credit Scoring, Department of Management Sciences, University of Waterloo, Canada. Crook J., Hochguertel S. (2006), Household debt and credit constraints: comparative micro evidence from four OECD countries Crook J., Banasik J. (2002), Does Reject Inference Really Improve the Performance of Application Scoring Models ?, Credit Research Centre, The School of Management, University of Edinburgh, Working Paper, n° 02/3.

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Della Pellegrina L., Macis G., Manera M., Masciandaro D., (2003) Il rischio usura nelle province italiane. L’usura nelle province italiane: un’analisi econometria, Roma, Ministero dell’economia e delle finanze. Del-Rio A., and Young, G. (2005a), Unsecured debt in BHPS: determinants and impact on financial distress, Bank of England Working Paper n° 263, London, Bank of England. Del-Rio A., and Young, G. (2005b), The impact of unsecured debt on financial distress among British households, Bank of England Working Paper n° 262, London, bank of England DREES (2003), Endettement et surendettement : des ménages aux caractéristiques différentes, in Etudes et Résultats, n° 251, August. Duygan B., Grant C. (2006), Household debt and arrears: what role do institutions play?, Preliminary draft presented at the Finance and Consumption Internal seminars, European University Institute. Elliott A. (2005) Not waving but drowning. Over-indebtedness by misjudgement, Center for the Study of Financial Innovation, London. Edwards S. (2003), In too deep .CAB clients’ experience of debt, CAB, Citizens Advice Scotland. Farinha L. (2004), Households debt burden: an analysis based on microeconomic data, in “Economic Bulletin”, Banco de Portugal. Farinha L. (2003), The effect of demographic and socio-economic factors on household’s indebtedness.in “Economic Bulletin”, Banco de Portugal. Fay S., Hurst E., White M. (2002), The Household bankruptcy decision, The American Economic Review, vol.92, n.3. Ford, L., Kempson, E., and Wilson, M. (1995) Mortgage arrears and possessions: Perspectives from borrowers, lenders and the courts. London: Department of the Environment. Frade, K. (2004) The fable of the grasshopper and the ant: a research project on overindebtedness and unemployment in Portugal. Coimbra: University of Coimbra. Gallou R., Le Queau P. (1999), Les Personnes Interdite de Chequiers, Paris, Bank de France. Gloukoviezoff G. (2006), Surendettement des particuliers en France: quels roles pour les particuliers ?, Document de Travail, n° 43, ILO, Geneva. Grant C., Padula M. (2006), Informal credit markets, judicial costs and consumer credit: evidence from firm level data, preliminary draft. Haas O.J. (2006), Over-indebtedness in Germany, International labour office Geneva, WP n.44 Hand D.J., Henley W.E. (1994), Inference about rejected cases in doscriminant analysis, in Diday E., Lechevallier Y. Shader M., Bertrand P. Butschy B. (eds), New Approaches in Classification and Data Analysis, Berlin, Springer-Verlag, pp. 292-299. Herbert, A., and Kempson, E. (1995) Water debt and disconnection. London: Policy Studies Institute. Jappelli T., Pagano M. (2006), The role and effects of credit information sharing, in Bertola G., Disney R., Grant C. (edited by) The economics of consumer credit, Cambridge, MIT Press. Kempson, E. (2002) Over-indebtedness in Britain. London,Department of trade and Industry.

22

Kempson, E. and Atkinson, A. (2006) Over-stretched: people at risk of financial difficulites. Bristol: University of Bristol Kempson, E., McKay, S., Willitts, M. (2004) Characteristics of families in debt and the nature of indebtedness. London: Department for Work and Pensions (Research Report No 211). Korczak D. (2000), Over-indebtedness in Germany at the edge of 21th century, Abdruck aus money matters No.3/00. Landi S. (2006), Il sovraindebitamento: analisi dei casi pervenuti al Fondo di Prevenzione Usura Adiconsum, Adiconsum, associazione difesa famiglia e ambiente Le Duigou, J-P. (2000) Endettement et surendettement des menages. Paris: Conseil Economique et Social Mitrakos, T.M., Simigiannis, G.T., and Tzamourani, P.G. (2005), Indebtedness in Greek households: evidence from a survey. in “Bank of Greece Economic Bulletin”, , n° 8/05, pp. 13-35. May O., Tudela M., Young G. (2004), British Household Indebtedness and Financial Stress: a Household-level Picture, Bank of England, Quarterly Bulletin, Winter. MORI (2003) Financial over-commitment survey. London: Citizen's Advice. MORI (2005) Over-indebtedness in Britain: A DTI report on the MORI Financial Services survey 2004. London: Department for Trade and Industry. Observatoire du Crédit et de l’Endettement (2005), La consommation et le crédit aux particuliers, Rapport annuel 2005. Observatoire de l’Endettement des Ménages (2007),L’endettement des Ménages en Novembre 2006, 1ère partie: La photographie des ménages endettés, Rapport n° 19, February. Observatoire de l’Endettement des Ménages (2007),L’endettement des Ménages en Novembre 2006,Seconde Partie: Les évolutions intervenues entre décembre 1989 et novembre 2006,, Rapport n° 19, February. Observatorio de Endividamento dos Consumidores (2002), Evidamento e incumprimento no crédito bancario ao consumo. Um estudo de caso, Centro de Estudos Sociais da Faculdade de Economia da Universidade de Coimbra. Observatorio de Endividamento dos Consumidores (2002a), O sobreendividamento dos dos consumidadores: um estudo de caso, Centro de Estudos Sociais da Faculdade de Economia da Universidade de Coimbra. Observatorio de Endividamento dos Consumidores (2002b), O Sobreendividamento em Portugagal, Centro de Estudos Sociais da Faculdade de Economia da Universidade de Coimbra. Oxera (2004), Are UK households over-indebted?, Report prepared for APACS, BBA, CCA, and FLA. Phipps, J; Hopwood Road, F.(2006), Deeper in debt. The profile of CAB clients, CAB – Citizens Advice Scotland. Reifner, U.; Knobloch, M.; Laatz, W.; Cantow, M. (2007), Iff uberschuldungsreport 2007, Private uberschuldung in Deutschland, IFF, Hamburg. Riiser M.D., Vatne B.H., Developments in household debt. An analysis of microdata for the period 1986-2003, in “Economic Bulletin”, Norges Bank, n° 2/06, pp. 72-79. Rinaldi L., Sanchis-Arellano A. (2006), Household debt sustainability. What explains household non-performing loans? An empirical analysis, European Central Bank, Working Paper Series, n.570.

23

Roszbach K. (2003), Bank Lending Policy, Credit Scoring and the Survival of Loans, Sveriges Riksbank, Working paper series, n° 154, November Rowlingson, K., and Kempson, E. (1993) Gas debt and disconnections. London: Policy Studies Institute. Springeneer, H. (2007) Schuldenreport 2006. Berlin, BWV Berliner WissenshaftsVerlag Sveriges Riksbank (2005), Swedish households debt-servicing ability 1997-03, in “Financial Stability report”, n. 1/2005, pp. 27-29. Sveriges Riksbank (2004), Swedish households’ indebtedness and ability to service debt – an analysis of household data, in “Financial Stability report”, n. 1/2004, pp. 61-84. Sveriges Riksbank (2004a), Swedish households debt-servicing ability 2000-02, in “Financial Stability report”, n. 2/2004, pp. 33-35. Tudela, M., Young, G. (2003), The distribution of unsecured debt in the United Kingdom: survey evidence. Bank of England Quarterly Bulletin, Winter. London: Bank of England. Vatne B.H. (2006), How large are the financial margins of Norwegian households ? An analysis of microdata for the period 1987-2004, in “Economic Bulletin”, Norges Bank, n° 4/06, pp. 173-180. Whitley J., Cox P. (2004), An empirical model of household arrears, Bank of England, Working paper n. 214. Whyley, C., Kempson, E. and Herbert, A. (1997) Money matters: approaches to money management and bill-paying. London: Policy Studies Institute.

24

APPENDIX TABLE I AND IV- LEGENDA: Concept of financial difficulties used.

A. ANALYSIS

BASED ON SAMPLES OF PERSONS WHO EXPERIENCED FINANCIAL DIFFICULTIES AND ASKED ADVICE OR PROCEDURES FOR DEBT RESTRUCTURING Financial difficulties related to : A.1 - borrowing (financial debts) A.2 - other commitments (rents, payment of utilities, …) A.3 - financial and non financial debts

B. ANALYSIS BASED ON PANELS

REPRESENTING THE WHOLE POPULATION (financial difficulties may be detected as self declared financial difficulties, people showing a high percentage of financial debts to income, people showing other ratios signalling financial difficulties). Financial difficulties related to : B.1 - borrowing (financial debts) B.2 - other commitments (rents, payment of utilities, …) B.3 - financial and non financial debts

C. DATA COLLECTED BY CENTRAL BANKS OR OTHER BUREAU FOR CREDIT ASSESSMENT Financial difficulties related to : C.1 - borrowing (financial debts)

When the concept is ambiguous, the classification follows the criterium of the general aim of the analysis

TABLE I - ANALYSIS BASED ON EMPIRICAL-DESCRIPTIVE METHODS OR STATISTICAL SOURCES OF CASES Country Authors Belgium

Banque Nationale Belgique 2006

Belgium

Observatoi re du Crédit et de l’Endettem ent 2005

Belgium

Statistiques “Des faites et des chiffres” 2006

France

Title

Dataset Data source Time period Statistiques Banque 2002– Centrale Nationale 2006 des credit de Belgique aux particuliers 2006

Objective

Methodology

Main evidence: who are the over-indebted people (main variables explaining the risk), what are the causes

Central de 2005 Crédits aux Particuliers, Observatoir e du Crédit et de l’Endetteme nt Banque de Belgique

Combien de personnes sont-elles surrendettée s en Belgique ?

Observatoir 1995e du Crédit 2003 et de l’Endetteme nt

Analyses based on data from Observatoire du Crédit et de l’Endettement – (Wallonie area)

Analyses of persons which registered payment defaults relating to instalment sales, instalment loans and personal instalment loans. Concept of financial difficulties C.1 Analysis of statistics of the Credit Bureau Analysis of household’ overindebtedness in the Wallonie area Indicator of risk of facing financial difficulties Percentage of over-indebted persons asking for a legal procedure for re-scheduling their debts Concept of financial difficulties A.3 Analyses of persons which asked for debt restructuring

Demographic characteristics (2006) Age: 18-24 years: 5.4%, 25-34 years, 26.9%, 35-44 years : 29.4%, 4554 years: 22.8%, 55-64 years: 10.9%, > 65 years: 4.6% Geographical region: see detailed statistics

Rapport général sur la consummati on et le crédit aux particulier 2005

Statistics from files of the Central Individual Credit Register. This registration aims to strengthen the means of preventing the excessive indebtedness of private individuals Analyses based on data from Observatoire du Crédit et de l’Endettement – (Wallonie area) and statistics from Central de Crédits aux Particuliers, Banque de Belgique

Whole population of overindebted persons en France

The study is conducted every three years and is aimed at improving the procedure of the treatment of overindebtdness and at highlighting the main shifts in their quantitative, sociological

Banque de Enquête France typologique 2004 sur le 2005 surrendettem ent + Barometre du surrendettem

Concept of difficulties A.3

financial

Analysis based on the data of the cases handled by the Commissions de surrendettement Concept of difficulties A.3

26

financial

Demographic characteristics of persons registered in the Credit bureau Register (see above) Demographic characteristics of over-indebted persons: See detailed statistics in the rapport.

Socio-demographic characteristics – Source OCE (2003): Age: 55 years: 11.6% Marital status: married, couple: 28.7%, single 31.4%, divorced: 22.6%, separated 12.6%, widow, 4.7% Household composition: single 36%, married or living together without children: 14.3%, married or living together with children: 26.4%, lone parent: 23.3% The study analyses: Sociological profile of over-indebted: - marital status:couples 36.5% in 2004 compared to 42.2% in 2001; divorced- separated, 32.7% (265% in 2001), unmarried: 25% (26% in 2001), widower, 5.8% (5.3% in 2001). This trend is mainly due to the growth of divorced/separated persons. - number of dependants: 0 dependants 47.4% in 2004 compared to 42.5% in 2001; 1 dependent 20.7% in 2004 ( 21.5% in 2001), 2 dependents 17.1% (29.0%), 3 dependents 9.5% (6.5%) and 4 or plus

ent à fin de septembre 2006

France

DREES 2003

Endettement et surendettem ent: des ménages aux caractéristiq ues différentes,

and aspects.

Survey INSEE « Patrimoin e»

19971998

geographical

dependents: 5.3% (6.5%) - age: less than 25 years 3.3% in 2004 (5.0% in 2001, 25-34 years: 22.2% (26.4%), 35-44 years 30% (31.4%), 45-54 years 26.6% (24.6%), 55-64 years 12% (8.3%), more than 65 years 5.9% (4.3%) - employment status: self-employed 0.3% in 2004, executives, intellectual practitioners 1.1%, other practitioners 2.3%, employed 32.6%, blue collar 22.3%, pensioners 7.4%, unemployed or other out of work 34.0% Economic profile of over-indebted - income: see detailed statistics - nature of income: see detailed statistics - house tenure: owners 3.7%, mortgagors 6.3%, tenants 78.2%, free tenants 9.8%, others 2.0% - real estate wealth ≤76.200 € : 41.0%, 76.200 -152.400 €: 4.4%; 152.400€-228.600: 11%, > 228,600: 5.6%) - savings: ≤1.500€: 56.6%, 1.500 € - 7.600 : 36.3%, > 7,600€: 7.1% - car value: see detailed statistics Nature of debts: Causes the analysis distinguishes between active and passive - ACTIVE 27.1% - PASSIVE 72.9%

The survey analyses households wealth and savings and studies, among other aspects, the characteristics of overindebted households Definition

of

Analysis based on INSEEE data (survey “Patrimonie”) It distinguishes between personal (household) and business (professional) indebtedness. Then it analyses in depth only the of personal over- cases

27

- Active: too much debts: 14.6%, poor management 6.4%, expensive rent 1%, too much expenditures 1.4%, others 3.5%) - Passive: job loss 30.8%, separation-divorce 14.7%, illness-accident: 10.8%, income reduction 6.2%, others 8%. Nature of indebtedness Situations involving ONLY arrears on household expenditures 3.3% Situations involving ONLY financial / credit debts: 9.8% Situations involving BOTH credit and non financial debts: 86.9% Weigh of different kind of debts - Credit > 75% : 63.9% - Arrears on household expenditures > 75%: 11.6% Kind of credit: see detailed statistics Kind of household arrears : see detailed statistics The phenomenon of indebtedness refers mainly to young households, occupied in the working market and which benefit of a standard of life rather high. The phenomenon of over-indebtedness refers mainly to households with a standard of life rather low, and financial situation is fragile as a consequence of unemployment or of too much different debts.

Etudes et Résultats, n° 251, Aoŭst 2003

indebtedness: it adopts an indirect indicator and defines it as a high level of indebtedness, i.e. an amount of annual commitment (principal and interests) higher than 30% of the annual incomes.

indebtedness.

Percentage of over-indebted households (estimates) Threshold of Number of % of indebted Descriptive Statistic and annual households households Logistic Dichotomous Model financial over-indebted (considering commitment only personal Concept of financial over annual indebtedness) difficulties income A.1 > 30% 1,541,750 16 > 33% 1,135,001 12 > 35% 918,051 10 >40% 549,602 6

% of all households

6.5 4.8 3.9 2.3

Households characteristics, according to the kind of over-indebtedness Over-indebted households ( Household Overs with indebted > 30%) personal househol Mortgage Different Both debts ds s from mortgages N° households 9,836,938 1,541,750 683,656 152,008 706,0 86 Age of the “head” of household (%) < 30 years 11 7 12 6 7 30-39 years 27 32 28 34 32 40-49 years 30 34 25 35 34 50-59 years 19 18 16 21 19 60-69 year 9 7 14 3 6 > 69 4 2 5 1 2 Total 100 100 100 100 100 Economic activity of the head of over-indebted household: Farmers: 1%; Craftsmen and Salesmen: 7%, Self-employed: 1%, Executives: 8%; Cadre: 17%, Other White collars: 13%; Skilled Blue collars: 27%; Unskilled blue collars: 8%, Unemployed: 7%, Other inactive: 3%; Retired: 8% Composition of over-indebted households: Couple, 2 active without children, 6%, Couple 2 active with children: 30%, Couple 1 active without children: 1; Couple, 1 active, with children: 27%, Couple, 2 unemployed, without children: 4%, Couple, 2 unemployed, with children: 3%, Single parent: 7%, Single: 19%, Other: 2% Home tenure: Renter: 9%, Free renter: 2; Owner 88%, Other: 1%

28

France

Le Duigou 2000

Rapport Banque presente au France nom de la section des Finances (Conseil economique et social)

de Variou s years 19951997

Rapport au Conseil economique et social analysing the phenomenon of overindebtedness

See detailed statistics with reference to: level of income and wealth Main conclusion Les populations touches ne sont pas nécessairement des populations défavorisées au depart. Le surrendettement est alors la consequence d’une mobilité sociale descendente liée à la materialisation de risques (chômache, divorce ou séparation, malarie). Les baisse brutales de ressources conséutives à limportance du chômage de loungue durée, a l’augmentation du travail précaire et aux ruptures de situation matrimoniales expliquent en grande partie l’ampleur du surrendettemet. Les données statistiques disponibles montrent que le dèsèquilibre budgétaire de plus en plus souvent d’un financial choc éeconomique qui ne permet plus d’honorer les engagements financiers contractés dans le passé. Causes of over-indebtedness - Source: Banque de France - Maine and Loire Commission 1997 Unemployment 34.6%, income reduction 5.5%, illness 6,4%, separation 17.4%, level of initial debt 30.9%, reduction of benefits or social allowances 3.2%, others 2.0% Causes of over-indebtedness - Source: Banque de France - Meuse Commissions 1997 Unemployment 37%, illness 6%, Level of initial debt 33%, divorce11%, others 13% Causes of over-indebtedness - Source: Banque de France - Loire Atlantique Commissions 1997 Unemployment 43%, divorce-separation 8%, illness 5%, widowhood 2%, Level of initial debt 9%, income reduction 13%, accident ehen working 1%, others 19% Socio demographic characteristic - Source Observatoire de l’endettement ménages 1998- Over-indebtedned persons Age oh head of household: 55 years: 20,6% Occupational status: blue and white collars 54,9%, self-employedcraftsman 13%, self-employed-professional 15,3%, retired-inactive 16,7% Geographical area: Ile de France 21,6%, other areas 78,4% Underage dependants : no one : 65%, 1-2 dependants: 26,9%, 3 or plus dependants: 8,1% Home tenure: owner or becoming owner (mortgagor) 48%, rent tenants (local authority): 21,3%, free rent tenants: 30,7% Financial Profile - Source Observatoire de l’endettement ménages 1998 – Over-indebtedned persons - Share using banking overdrafts : 68,6% - Opinion about their budget: Easy or enough except enexpected events: 13,3%, fair or hard to manage: 46,2%, debts are necessary

Analyses of the caused of over-indebtedness based on the cases dealt by the Commissions

Concept of difficulties A.3

29

France

Observatoi re de l’Endettem ent des Ménages 2007

L’Endetteme nt des Ménages en Novembre 2006

SOFRESNove Observatoire mber de 2006 l’Endettemen t des Ménages

19th wave of a survey on households’ indebtedness in France The focus of the survey is mainly on the indebtedness. However it is possible to have information about difficulty of repayment

Postal questionnaire based on a representative sample of French households: 8,034 participants out a panel of 12,005

Concept of difficulties A.3

financial

40,5% - Opinion about debt burden: none repayment 12,3%, passable or very passable 9,9%, hidh oor very high : 19,0%, too much high: 58,8% - Recent changes in the financial conditions: improved 5%, unchanged 30,3%, deteriorated: 64,7% Nature of debts: only financial debts 30%, only non financial debts: 3%, both financial and non financial debts :67% A preliminary framework: the diffusion of indebtedness (%): House tenure % of Weight Share cases among Renters Renters Owners using indebted (market (social) or overdr people ) aft mortgago faciliti rs es on current accoun ts All 100.0 -27.1 13.0 59.9 24.4 households -indebted - without debts Of which - mortgages only both mortgages and other loans - other loans only

50.9 49.1

100.0 --

21.9 32.5

10.1 16.1

68.0 51.5

36.2 12.2

18.3

36.0

5.6

1.0

93.4

23.4

11.9

23.3

7.7

1.5

90.8

42.7

20.7

40.7

44.5

22.9

32.6

43.7

For detailed statistics on the profile of households with debts see the report. The burden of debt is: Excessiv Very High but Endurabl Easy to e high endurabl e manage e Indebted 4.5% 9.3% 33.3% 38.8% 14.1% househol ds The fragile households Very OverDebt is Debt is Financia precariou indebted indispen useful l burden s househol sable for for the high financial ds the family

30

Share of all househol ds Germany and comparis on with other countries

Elga Springenee r et al. 2007

Schuldenrep ort 2006, Verbraucher zentrale Bundesverba nd, Deutsches Rotes Kreuz, Deutscher Caritasverba nd, Diakonische s Werk der EKD (Editor), Berliner Wissenschaf ts-Verlag,

No own data collection, but analysis of : 1) Data from the 2nd Report on Poverty and Wealth, 2005 (Editor: German Federal Ministry of Family Affairs, Senior Citizens, Women and Youth)) 2) Sample survey of income and expenditure, (German Federal Statistical Office) 3) The German SocioEconomic

19992005 (period of exami nation)

Reporting the quantitative and socioeconomic development of overindebtedness and indebtedness (with the focus on borrowing) between 1999 and 2005.

situation

(reschedu ling procedure )

5.5%

1.3%

family budget

budget

1.8%

4.9%

2.35

See details in the report Secondary analysis based on I. Who are the over-indebted people? different sources 1) Main affected Age class: a) 30 to 39 years (New Federal States, former East-Germany) Concept of financial b) 40 to 49 years (Old Federal States, former West-Germany) difficulties 2) Main affected marital status: A.3 - B.3 a) Single (New Federal States, former East-Germany) b) Married (Old Federal States, former West-Germany)

Analysis of the main reasons and the main critical factors (such as the conditions of access to financial services) for overindebtedness.

3) Main affected household size: a) one person household (New Federal States, former East-Germany) b) three person households and more (Old Federal States, former WestGermany) 4) Main source of earnings: a) earned income (Old Federal States, former West-Germany) b) unemployment benefit (New Federal States, former East-Germany)

Overview of the recent German legislative proposals concerning Insolvency Law, Garnishment of bank accounts, and Legal Advice. Overview of the recent German case law concerning financial services.

II. Main reasons getting over-indebted (New and Old Federal States) Unemployment Permanent low income (such as working poor in particular in the New Federal States) Divorce/Separation Collapsed Self-employment Lack of financial competences such as budgeting Disease

Comparison with the factual and legal development in other countries.

III. Critical factors influencing the process of getting over-indebted 1) High priced consumer credits and high priced credits for small entrepreneurs 2) High priced conversion of debts 3) Risky Mortgaging for consumers with no or less equity and average income

31

Germany Korczak, D.

2000

Panel (German Institute for Economic Research) 4) Statistics of the German Bundesbank 5) Statistics on insolvency proceedings Eurostat 1999 Overindebtedness 1998-1998 in Germany Survey with at the edge German of 21th debt century. Abdruck aus counselling agencies money 2000 matters No.3/00. 2000

4) Being unbanked: No access to a bank account

Assess the differences in over-indebtedness between East and West Germany giving socioeconomical reasons because of the increase of over-indebt households especially in East Germany

Secondary analysis based on data from Eurostat

An increasing phenomenon: West German: in 1988: 4.2% of households were overindebted, in 1994: 5.1%; in 1997 the percentage increased, passing to 7.2%. East –Germany, adopted the social market economy since 1990 and there was an immediate increase of credit taking and the use of hire Concept of financial purchase, but in the same time unemployment increased highly. In 1994 the overindebted in east Germany were 7%. difficulties Estimation of the figures in 1999 account for 7,1% of overindebted in A.3 - B.3 whole Germany, but West-Germany rate went slightly down to 6.2%; whereas East Germany rate reached 11.5% Causes of over-indebtedness: Unemployment 38%; separation 22%; unexperience concerning credit taking 20%; persisting low income 19%; discrepancy between credit an income 14%; addiction 10%; diseases-accidents-death 9%; addictive consumption behaviour 7%; birth of children 6%; missed social security 3%. (source: Survey with German debt counselling agencies 2000).

Germany Haas O. J. 2006

Overindebtedness in Germany. Geneva International labour office

No own data collection. Analysis of the

2004

Marital status: (source: Erhebung bei Schuldenerberatunsstellen 2000: cases 24,639) Married : 31% (23% without children, 8% with children) , couple 11% (7% with children, 4% without children), single 26%, divorced/separated: 19%, single parent: 13% - Small excursus about Second analysis based on In 2004 about 33,000 over-indebted households declared themselves the definition of overempirical data insolvent (1% of all over-indebted) indebtedness Concept of financial Structural and personal causes of over-indebtedness Social factors: difficulties - Identification of the - Job loss and durable unemployment A–B–C main social and personal - Business failure 1 and 3

32

Geneva. WP n.44 2006

factors for overindebtedness

empirical data by the GP Forschungs gruppe

- Role of debt counselling and prevention as tools to tackle over-indebtedness

This study combines data from Social economic Panel, Client data provided by debt counselling agencies, infos from the Central Credit Registration .

Germany Reifner, U.; Knobloch, M.; Laatz, W.; Cantow, M. 2007

Iff uberschuldu ngsreport 2007. Private uberschuldu ng in Deutschland 2007

Sample of 3000 overindebted person that is built using data from debt advisor and debt agencies during the period 2005-2006

- Income poverty working poor - Separation or divorce - Illness

20052006

The aim of this work is to analyse the main socio-economical aspects of overindebtedness among German people.

Personal factors: - Insufficient financial literacy - Excessive consumption - Inappropriate financial services - Addiction Causes of overindebtedness (source Springeneer, H. Shuldenreport 2005) West New Germany Lander 46% 23% Unemployment 29% 8% Working poor /income-poorness 19% 23% Separation/divorce 16% 20% Business failure 21% 27% Excessive consumption/ uneconomic 6% 13% housekeeping 5% 1% Illness, accident, death 5% 3% Insufficient financial awareness 4% 0% Collapsed Mortgaging 4% 2% Surety due 0% 1% Addiction Foundation of a family/household Statistical analysis of data Who are over-indebted? Households’ net income (monthly): under 500€: 7%; 500-625: 9%; 625-750: 14%; 750-875: 9%; 875-1000: 8%; 1000-1250: 8%; 12501500: 7%; 1500-2000: 12%; 2000: 25% Concept of financial Average of equivalent net income: over-indebt 786€; average nonover-indebted 856€ difficulties Sample distribution of inactive: 2% students; 4% social assistance; 6% A.3 unemployment benefit I; 6% non active; 7% retired; 24% officer/workers; 50% unemployment benefit II Age of over-indebted: under 18: 2%, 18-20:12%,20-25: 14%,25-30: 13%, 30-35: 15%, 35-40: 17%, 40-45: 12%, 45-50: 8%, 50-55: 5%, 5560: 3%, 65-70: 0,3% Marital status single: 41% (compared to 38% of the population); married with children 25% (22% population) ; married without children 11% (29%)%; single parent 23% (5%) Causes Life events: Unemployed, forced part-time 29.9%, Separation or

33

Greece

Mitrakos, T.M., Simigianni s, G.T., Tzamouran i, P.G. 2005

Italy

Landi, S. 2006

Analyses of indebtedness by regional and demographic characteristics. Analysis of financial pressure + Regression analysis to investigate the extent to which geography and economic characteristics seem to play a role in household’s decision to take out a loan Concept of financial Socio-economic and financial characteristics considered are : difficulties 1. education B.1 2. employment status of the household head (employed/unemployed, employee/self-employed, etc.; public/private sector) 3. the number of household members employed 4. the household’s income and its net wealth. Regarding the overall level of indebtedness, the survey results suggest that borrowing is concentrated among households with the highest level of income and wealth. Period - This work would be a Statistical analysis on the 12 Who presented request in order to take advantage of the found? - 626 Il - Male 64,2%, female 35,8% betwee portrait of households areas of the self-drawn up sovraindebit persons n that presented request at questionnaire who amento: - Age 18-30 (5,4%); 31-40 (22%); 41-50 (32,4%); 51-60 (25,4%); 612003- Adiconsum in order to presented analisi dei 70 (10.5%); 71-80 (3.4%) 2006 take advantage of request in casi Concept of financial - Marital status: married 58.0%, single, 15%, divorced/separated: Prevention Usury Found difficulties pervenuti al order take 18.9%, couple 2.4%, widow 5.5, divorced/separated with a new family: advantage Fondo Di 0.2% A.3 - As directly follows; in Prevenzione of: - number of sons: 24% one son, 27,8% two sons, 9,3% three sons, could be an investigation Prevention Usura 0.5% four sons; 0.2% more then four sons, 34% no sons about the links between Adiconsum. and usury - work: 55,3 factory worker or clerk, 9% professional man, 18.1% over-indebtedness and Adiconsum, found retired, 8.9% craftsman usury associazione (Fondo - Income: 1.3% no income; 4,1% 1-499; 24.2% 500-999; 41,7% 1,000Prevenzione difesa 1,499; 18.9% 1,500-1,999; 5.7% 2,000-2,499; 2.9% 2,500-2,999 e Uusura) famiglia e Indebtedness in Greek households: evidence from a survey.’ Bank of Greece Economic Bulletin, 0 (25) 2005

6,007 2002households 2003 aged 25 and over With 2,303 full household responses

engagement 15.2%,Illness: 6.6%, Death of partner 1.2%, Accident : 0.1% Bad management: Consumer good: 13.2%, mismanagement: 3.1%, criminal record: 1.5%, others: 0.2% Other causes: poverty : 9.4%, special reasons: 8.3%, having financing: 4.6%, Mortgages: 3.2%, birth of a child: 1.6%, Too high credit 1.1%, others: 0.7% The demographic characteristics considered are : 1, the degree of urbanisation of the area of residence 2. the composition of the household and the presence of children 3. the age of the household head : variable measured :Average debt-to- income ratio %: Below 35 years: 79,6% ; 36-45 years: 101,2% , 46-55 years : 85,5%, 56-65 years: 63,3%, 66-75 years: 46,4%, 76 and over: 44,1% Variable measured: debt service ratio (debt service cost to income ratio %) Below 35 years: about 28%; 36-45 years: about 27% , 46-55 years : about 32%, 56-65 years: about 22%, 66-75 years: about 25%, 76 and over: about 23%

To investigate the level of household indebtedness and its relationship to households’ income and wealth. It analyses also distribution of financial pressure.

34

ambiente. 2006

Guarantor: - In 86% of cases is not disclosed

- Selfdrawn up questionnair e

Home and other proprieties: - ½ of the households has got an home of propriety - 22.2% has got a second propriety Monthly fixed costs analysis: see detailed statistics in the study Households’ balance: - 37.9% 0-500€ - 18.2% till 1,000€ - 5.6% till 1,500€ - 3.3% till 2,000€ - 33.5% negative Bank debt: - 89.9% has got credit from banks - 61.5% has got credit from finance companies

Norway

Norges Bank Economic Bulletin (Biorn Helge Vatne) 2006

How large are the financial margins of Norwegian households? An analysis of micro data for the period 19772004

Data set of 1987approximate 2004 ly 3,000 households for 1987 and an increasing number in subsequent years. In the late year. More than 10.000 observation s Selfemployed persons are excluded because it is

To estimate the financial margin, i.e. an indicator of the resilience of household finances to changes in economic conditions such as an increase in interest rates or a reduction in income.

Other debt: - 24.4% suppliers - 24.1% bills (water debt, gas debt..) - 19.3% state, taxes Analysis of microdata Analysis of exposed debt by groups: Age: exposed debt is relatively evenly distributed across all age group Concept of financial over 25. The age25-34 holds less than 24% of total debt, but 26% of exposed debt. Households over 55 also hold a relatively large share of difficulties exposed debt, 18% of total debt and 22% of exposed debt. The largest B.1 increase in the share of exposed debt is in the age group of over 45 (in the period 1987-2004 the share of exposed debt has doubled for this group. On the other hand, households under the age of 45 have reduced their share of exposed debt. The age group 25-34 reduced its share of exposed debt from more than 40% to less than 30% during the period under review. Income: (dividing population into five equal-sized groups by increasing income after tax): the 20% of households with the highest income hold 43% of total debt, but only 12% of exposed debt. The two lowest income groups hold 14% of total debt, but 51% of exposed debt. In the lowest income group, nearly all debt is exposed debt. The main difference between households with a positive and negative margin after principal payment is average income level. Differences on the expense side are less evident. Roughly speaking, negative margins are largerly a result of low income rather than high interest and

35

Portugal

difficult to differentiate between business activity and private finance. Farinha, L. Households Micro data 1994 and debt burden: from the 2000 2004 an analysis Survey of households’ based on microecono Wealth and indebtednes mic data. s (IPEF), Banco de conducted Portugal. by INE with Economic support of bulletin. Banco De 2004 Portugal in 1994 and 2000

principal payments.

This study is based on the thesis that the development in aggregate debt burden ratio depend on the individual ratios of the households’ themselves

Descriptive analysis on data. Characterisation of debt burden ratio of indebted households using average and 75th percentile. The burden ratio of indebted is calculated for several subsample defined according to pairs of households’ characteristics: 1) income and age 2) income and education Concept of difficulties B.1

Comparative analysis on the sample of 1994 and 2000 considering the average debt burden and age-income: Main evidences are: Below 500€: 31-40 years old the average of debt burden ratio was 68% in 1994 and 24% in 2000 (data underrepresented) 51-60 years old the average of debt burden ratio was 48% in 1994 and 12% in 2000 (data underrepresented) from 500 to 1,000€: under 30 years the average of debt burden ratio was 45% in 1994 and 18.75% in 2000 (data underrepresented) 31-40; 41-50; 51-60 the average of debt burden in higher in 1994 (28%) than in 2000 (20%)

financial from 1000 to 1500€; 1500 to 2500; above 2500: it cab be noticed the same trend for each range of age; in 1994 the average of debt burden is higher than in 1994. In 1994 the range of age with the highest debt burden ratio is “les than 30 years”. In 2000 the sub-samples with the highest ratio are 31-40; 41-50 Comparative analysis on the sample of 1994 and 2000 considering the average debt burden and education-income. Main evidences are: Below 500€ Third cycle school has got a debt burden ratio of 70% in 1994 and 3/4 % in 2000 (underrepresented data) From 500 to 1000; 1000 to 1500; 1500 to 2500 and above 2500 and for each schooling level it clear that the average of debt burden ratio is higher in 1994 than in 2000. In 2000 it is nearly 20%; in 1994 nearly 30% (approximations) Comparative analysis on the sample of 1994 and 2000 considering the

36

75th percentile of debt burden and age-income;75th percentile of debt burden ratio an school-income: Analysing the 75th percentile globally it can be assert that there aren’t considerable differences from the average, with some rare exception that aren’t representative in the lower class of income. Portugal

Observator io do endividame nto dos comsumido res

O sobreendivid amento em Portugal

Sample of 2000 – 203 cases of 2002 overindebtednes s collected by DECO

The aim of this work is to underlined the main characteristics of households that decided to turn to DECO hopping to improve their debt conditions.

Concept of difficulties A.3

2002

Portugal

Frade, C.; Lopes, C.; Nogueira, C.; Magalhaes, S.; Brinca, P.; Marques, M.M.L. 2005

Desemprego e sobreendivid amento dos consumidore s : contornos de uma « ligaçao perigosa ». CES

Interviews 2005 with 406 overindebted households, using the advisory services of DECO (7 regional branches)

This report is divided into two parts: theory of over indebtedness, empirical studies In the empirical part the scope is to analyse the socio-demographic characteristics of overindebt consumers, the motivations for a

Income and age are more significant than school and income Individual profile: Gender: Male: 40.4%, Female: 31.5%, n.a. 28.1% Age: 55: financial 7.9%. n.a. 1%. Marital status: Married: 66.4%, Divorced: 14.8,6%, Single: 8,7%, Widow: 2,2%, partners: 6,5%, separated (of fact): 2,2% Education: elementary: 33.5%, secondary: 53.7%, higher level: 10.8%, n.a. 2.0% Occupational status: Technician high level public sector : 2.5%, cadre private sector: 3%,teacher: 7.4%, administrative employee: 17.7%, unqualified workers: 4.4%, skilled workers: 0.5%, workers of agriculture and fishing sector: 0%, blue-collars: 11,8%, trader and vendor: 11.8%, student 0%, housemaid 1,5%, in training 6.9%, unemployed: 7,4%, other, 23.6%, n.a. 1,5% Income (of the household) monthly: < 748.20: 32,2%, 748.20-1246.99 €: 26.6%, 1246.99-1995.19 €: 13,8%, > 1995,19 €: 3.0%, n.a. 24.6% Number of debts: 1= 13.3%, 2= 10.8%, 3= 10.3%, > 3: 62.1%, n.a.: 3.4%

Descriptive analysis on variable of the sample

Causes: Unemployment: 14.6%, low income: 33.7%, poor management of family budget: 8.1%, illness: 18,2%, change in the household composition: 12.8%, expenses for education: 8.7%, other: 1.2%, n.a. 2.7% Descriptive analysis coming Who are the over-indebt? from interviews elaboration. Geographic distribution:12.2% Coimbra; 6.2% Evora; Faro 0.7%; Concept of financial Lisboa 44.9%; Porto 18.9%; Santarém 15.6%; Viana do Castelo 1.5% Age: 16.7% 20-29; 32.8% 30-39; 28.1% 40-49; 14.1% 50-59; 7.8% 60difficulties 60; 0.5% 70+ A.3 Marital status: married 61%; divorced 19 %; single 16%; widow :4% Households’ composition: 1 4.2%; 2 28.4%; 3 40.2%; 4 19.2%; 5 5.8%; 6 1.8% Children dependants: none 29.7%; one 39.8%; two 23.6%; three 5.8%; four 0.8% Education: illiterate 1%; fist cycle 16.1%; second cycle 18.2%; third

37

for re scheduling of debts.

Sweden

Sveriges Riksbank Financial Stability report 2005

Swedish household’ indebtedness and ability to service debt – an analysis of household data

Statistics Sweden’s HINK/HEK survey 17,000 households in the respective years

disproportionate debt; the motivations of denied credit.

20002001

20002002

To analyse households’ indebtedness and ability to service debt of individual indebted households to ascertain whether this leads to a different conclusion regarding the household sector as a whole.

cycle 25.2%, high school: 26.2%; Monthly income: above 375€ 15.6%; 376-500€ 20.8%; 501-1000€ 40.1%; 1001-1500€ 16.3%; 1501-2000€ 5.5%; 2001-2500€ 0.7% Source of income: salary 64.8%; pension 17.9%; temporary benefits 20.4%; self earnings 5.7% Unemployment situation: 24.4% jobless; 10.6% consort’s jobless; 3.7% couple jobless; 50.2% with work; 11.3% experienced unemployment

Analysis based on wealth and income data and estimating the effects of increase in interest rates and unemployment. Concept of difficulties B.1

financial

Analysis on the sub-sample (202) of unemployed: Sex: female 46%; male 36.6%; couple 17.1% Age: 12,9% 20-29; 33.7% 30-39; 28.7% 40-49; 13.9% 50-59; 9.9% 6069; 1% 70+ Civil status: 4% widow, 17.9 single; 18.9 divorced; 59.2 married Number of households’: one 6.3%; two 23.0%; three 35.6%; four 25.1%; five 7.3%; six 2.1%; seven 0.5% Number of sons: no children 29.3%; one 33.5%; two 27.8%; three 7.3%; four 1.6%; five 0.5% Education: illiterate 0.5%; first cycle 14.2%; second cycle 15.3%; third cycle 26.3%; high school 26.8%; further education: 5.8% Monthly income: under 375 29.5%; 376-500 27.6%; 501-1000 30.8%; 10001-1500 11.5%; 1501-2000 0.6% Income before deterioration of work condition or job loss: under 375 12.8%; 376-500 19.9%; 501-1000 30.1%; 1001-1500 25.0%; 15012000 6.4%; 2001-2500 3.2%; 2501+ 2.6% Number of debt contracted: none 23.8%; one 23.3%; two 17.8%; three 16.8%; four 5.9%; five 3.5%; six 4.0%; seven 3.0%; eight 3.0% Reason of debt: 57.5% essential goods; 8.4% helping familiars or friends; 34.6% financial difficulties of the moment; 11.7% obtain credit is quite easy; 3.4% improving lifestyle; 14.0% paying other debts Numbers of debt in arrears: none 78.7%; one 11.9%; two 5%; three 2%; four 1%; five 1.5% The population is divided into 5 Income categories equally large according to the level of their disposable income( cat. 1 the lowest income category, cat. 5 the highest income category) Cat 1 Cat.2 Cat.3 Cat. 4 Cat. 5 Households without margins 20 4,7 1.1 0,0 0,0 Indebted households without margins % 100 19 3,3 0,3% 0,0 Category 1 is a group difficult to distinguish since it consists of individuals with very different finance and life situations. The statistics

Swedish

38

households’ debtservicing ability 20002002

19972003

show that a major part of these households or individuals have neither employment income nor asset or liabilities It is mainly the households in category 2 that can be viewed as potentially vulnerable. The most vulnerable households – those that have no margins for unexpected expenses each month – are largely debt-free.

Swedish households’ debtservicing ability 19972003

Effects of rising interest rates : the conclusion of the exercise is that the household ability to service debt would not be affected to any great extent by even relatively steep rises in the interest rates Effects of increased unemployment: : the effects on the proportion of vulnerable households and the banks’ exposure to them are less than in the case of rising interest rates. In updating the study for 2002, it is said that “according to the statistics, virtually all the individuals in category 1, whether or not they have debts, have an annual disposable income that is exceeded by their estimated expenditures, so that the latter encroach on their margins.” Therefore not any further assumptions have been made. From 2001 to 2002, however, the proportion of households with no financial margin rose in both these income categories. This deterioration applied, not to all indebted households but mainly to those that already lacked financial margins initially.

UK

Bank of England – NMG Research 2006

The state of British household finances: results from the NMG Research Survey Waldron M. Young G., Quarterly Bulletin 2006 Q4 + 2005 Survey

Representati Septe ve sample mber of 1,844 2006 people

To understand if the rapid increase in household debt in recent year has consequences on the ability of people to repay what they owe and therefore on monetary policy and for financial stability

Questionnaire (22 questions added to the monthly omnibus survey) Focus on Households facing payment difficulties: households asked directly whether they have problems paying for their debts. Ass those with unsecured debt were asked whether they found it to be a burden on their household and those with mortgages were asked whether they had

39

In the 1997-2003 study, the analysis again focuses on income categories to 5., as a large majority of households in category 1 have no earned income and no assets or debts. The proportions of financially vulnerable households in income categories 2 to 5 show a continuous decrease since 1997 (DA VERIFICARE) With reference to the issue of facing payment difficulties, i.e. question about the burden : - distinction between homeowners and renters: unsecured debts were more likely to be considered a problem by renters than homeowners (15% of renters with debt said their unsecured debt was a heavy burden compared with 5% of homeowners) - distinction by income: the average income of those who said their unsecured debt was a heavy burden was £ 23,932 against £ 26,550 for those who said it was somewhat a burden and £ 32,178 for those who said it was not a problem. [Overall, the income of households for whom their unsecured debt is a heavy burden accounted for less than 5% of the total income of all households. So any impact that these problems might have had on aggregate spending is likely to have been small. +

experienced problems in With reference to the issue of facing payment difficulties, i.e. question paying for their about the frequency of having problems in repaying debts: distinction between homeowners and renters: accommodation. Never Occasionall Most Every Concept of financial y months month difficulties Whole 83 % 10% 3% 3% B.3 sample Homeowners 87% 8% 3% 3% Renters 76% 15% 5% 4%

2004 and 2003 Survey

Causes of debt problems: frequency of reasons (Question : What are the main reasons for the problems you have in repaying your debts ?) - “lack of cash flow that has been or will be resolved in the future” 32% - “overspending” 29% - Higher than expected household bills 13% - Unemployment : 10% - Loss of income through reduction or cessation of overtime 10% - Illness : 6% - Credit card and other loan offers were too tempting : 4% - Divorce or separation : 4% - You or your partner leaving work to have a child 4% - Redundancy : 2% - Debt legacy from being a student 2% - Other: 6% - don’t know: 10% Action to resolve debt problem: (Question: What action would you consider taking to resolve your debt problems ?) - Cut back on spending 60% - Take out another loan: 5% - Take out another mortgage on your house: 4% - Declare yourself insolvent (i.e. bankruptcy or IVA): 3% - Sell your house: 2% - Other: 6% - None of these: 20%

UK

Bank of England – NMG Research

British household indebtedness and

Representati Septe ve sample mber of 1,838 2004 individuals

DATASET is available with gender, age, region, race, marital status, household size, number of dependent children, education, current labour force status, social class, annual household income, Questionnaire (24 questions Affordability of debt, both in terms of the amount of household added to the monthly income that is devoted to servicing debt (= Income gearing) and omnibus survey) households’ perception of whether their debts are a problem

40

2004

financial stress: a householdlevel picture May O. Tutela M. Young G, 2004

adults aged 18 years or over (NMG Research), BHPS (2002), Survey of Mortgage Lenders – SML

Concept of difficulties B.3

financial - Homeowner : income gearing between 50-% and 100%: 1,6% of all households, 100% or more: 0,9% - Renters: income gearing between 50-% and 100%: 0,2 % of all households, 100% or more: 0,2% Unsecured debt is a burden : percentage of those with unsecured debt that have problems: - whole sample: 38% Household income Homeowner Renters s Up to £ 4,499 68% £ 4,500-9,499 20% 47% £ 9,500 – 17,499 37% 50% £ 17,500 – 24,999 30% 50% £ 25,000 – 34,999 35% 21% £ 35,000 – 59,999 46% 41% £ 60,000 and over 15% 25% DATASET is available with gender, age, region, race, marital status, household size, number of dependent children, education, current labour force status, social class, annual household income.

UK

Bank of England – NMG Research 2003

The distribution of unsecured debt in the United Kingdom: survey evidence Tudela M. Young G. Quarterly Bulletin Winter 2003

Representati Octobe To analyse the type of ve sample r 2003 debts they had, the of 1,950 amounts they owed and adults whether they considered the debt to be a burden to their household

Questionnaire (3 questions The characteristics of adults with different degrees f debt problems added to the omnibus survey) Self-reporting perception % Share % Share of debt to be a heavy burden reportin of reportin population g popul g Concept of financial heavy ation heavy difficulties burden burden B.1 Age group Income group 15-24 11 15 Less than £ 24 4 4,500 25-34 13 19 £ 4,50015 14 £9,499 34-44 19 18 £ 9,50013 14 £17,499 45-54 9 16 £ 17,5007 6 £24,999 55-64 5 13 £ 25,0007 5 £34,999 65 plus 5 20 £ 35,000-£ 0 5

41

Housing status With Mortgages Own outright Rented local A.. Rented private Housing Ass. UK

Bank of Financial England pressures in the UK household 2003 sector: evidence from the British Household Panel Survey

2002 British Household Panel Survey (BHPS) Nationally representati ve sample of adult members in around 5,500 households

UK

MORI 2003

Casual sample composed by 1,896 adults.

Financial overcommitment survey. London.

2003

To highlights some stylised facts relating to three standard indicators of financial health and to analyse: a) how financial stress is distributed across households; b) how this distribution has changed between 1995 and 2000 c) the types of household – by age, income and wealth – in the most indebted financial position To analyse qualitative information on the extent to which debt is considered a burden by individual households (subjective measure) - Measure the level of financial debt among the sample that could be representative for the all population.

BHPS is an annual survey

4

33

5

26

60,000 £ 60,000 plus Missing income Social class

20

23

AB

6

19

17

10

C1

7

25

18

7

C2

8

23

CDE

17

34

-

11

2

9

50

Indicators of financial pressure in the BHPS: Quantitative- Flow measures (Income, Saving, and Mortgage income gearing) Quantitative – Stock measures (Unsecured debt, Secured debt, Savings, Other financial investments, Housing wealth) Qualitative measures (Housing payment problems, Unsecured debt payment problems, Pension schemes)

- Interview face to face using Households financial state: CAPI - 56% claims not to have any difficulties keeping up with financial commitments - Revision of obtained data - 26% struggles fro time to time for each question in order to - 11% has serious problem

42

2003 Male/Femal e Range of ages: - 16 to 24 - 25 to 44 - 45+

give a right interpretation of - Asses the use of CAB different evidences as a source of advice and information about debt. Concept of financial difficulties B.3

the discriminant variables are: sex, age, education, unemployment; -91% of 54-64 years old has no or few difficulties problem to keep up with bills and credit commitments, compared with 71% of those in the class 15-24 years in the main situation -16% of households with children is more likely to struggle financially Possession of loans and credits: - 74% has at least one type of loan or credit (54% of it is represented by credit card, 42% by bank or building society overdraft, 24% store card, 16% personal loan, 11% mail order/catalogue loan, 9% hire purchase agreement, 9% secured loan/re-mortgage)

Working status: - full time - part tome - not working

- People with personal loans or secure loans are more likely to struggle constantly to pay bill and credits that those with have credit or store cards - financial situation does not appear to worsen among those with a large number of credit cards. 875 of them with more than 5 credit cards say they have no or few financial problems, compared with 82% of those with less than 5. - Is to reveal that 23% of these who posses loans and credit do not know the amount that they owe - Of those who know the total value of their debts only 64% have an outstanding balance, the average is 3,900£ -12% of British public have taken on additional credit in the last year (24-34 years old 19%, with children (15%), work full-time (18%), have a household income of 30,000£ or above (20%). Overdraft facility (42%): - 36% of them never used it and 29% had used once or twice a year - 19% is overdrawn on a monthly or permanent basis - sub groups that tent to be overdrawn all the time or once a month are 15-24 years old (23%), single people (25%), living in private rented accommodation (24%), council rented accommodation(25%) Posses of credit or store card: - 41% pays less than the full balance an their cards each month -Full payment of the monthly balance increases with age, over 65s (67%), 15-24 years old (32%) -people working full time (48%) are more likely than average to pay less than the full balance -repayment of household in full increase with households’ income, 55% of them with an household income of 30,000£ and above pay off their balance in full, 37% under 9,500£

43

UK

CAB: Nearly 30% of the sample had sought the help from CAB in the past, 39% of them are 35-44 years old CAB is the third source of advice and information that people would go if they ha d financial difficulties in the future after family and bank/building society advisor Objective indicators: Consumer credit indicators: August As part of the strategy Interviews face-to-face in DTI-MORI Overindebte MORI Financial launched on July 2004 their homes. Question asked 1- Those individuals spending more than 25% of their gross monthly dness in Services Decem “Tackling overrelate to individuals’ 2005 Britain: a income on unsecured repayments; (MFS) ber indebtedness: Action personal situation, with the DTI report 2- Those individuals who spend more than 50% of their gross 2004 plan 2004”, the DTI is exception of the question on the MORI survey monthly income on total borrowing repayments (secured and including committed to monitoring regarding burden of debt Financial unsecured) 9,892 the level and profile of where individuals were asked 3- Those individuals with 4 or more credit commitments Services consumer overrespond on behalf of their survey 2004 individuals Arrears indicator: greater than indebtedness household. 4- Those individuals in arrears on a credit commitment and/or Department 18 years. domestic bill for more than 3 months Five indicators are used in of Trade & Subjective indicator: order to measure overIndustry 5- Those individuals declaring their household’s borrowing indebtedness, specifying a Consumer repayment to be a “heavy burden” threshold and Characteristics of individuals satisfying the over-indebtedness (4 that are objective and one indicators (legenda: see the above) Competition that is subjective in nature). Policy % 1 2 3 4 5 Directorate Answ ering 2005 Concept of financial sampl difficulties e B.1 All 100 8% 9% 6% 3% 4% Age 18-20 5% 3%* 2% 2% 6%* 8% 21-24 6% 8%* 5% 10% 7% 11% 25-34 20% 27% * 29% 27% 30% 35-44 20% 25% 30% 22%* 24% 29 45-54 17% 19%* % 19%* 27% 18%* 8% 9% 4% 55-64 13% 11%* 29 2% 3% 4% >65 19% 5% % 22 % 10 % 3% Family type

44

Single (retired) Retired couple Single, not retired without children Single, not retired with children Couple, not retired without children Couple, not retired with children Housing tenure Mortgagor Outright owner Social tenant Private outright

UK

Berthoud, R.; Kempson, E. 1992

Credit and debt : the PSI report Policy Study Institute.

2,212 households Central Statistical

1989 compa ring some emergi

The aim of this work is to: - identify spending commitments and methods of budgeting

Elaboration of the face to face interviews. Statistical and econometric analysis of the sample.

45

12% 11% 21% 9% 21% 28%

36% 27% 27% 10%

3% 6% 16% 8%* 21%* 47%

1% 1% 3% 4% 2% 1% 7% 18% 23 4% 15% % 25 21%* 24 % 43% % 18 58 % % 31 %

53% 15% 21% 10%*

82 % 7% 6% 4%

51% 7% 29%* 12%*

Economic activity Full time work 42% 37% 28% 60% Part-time work 12% 20% 23% 16% Unemployed 5% 6%* 5%* 4%* Retired 23% 8% 5% 3% Housewife 11% 19% 31% 11% Gross income < £ 9,500 45% 62% 71% 33% £9,500-£17,499 29% 26% 18% 33% £17,500-£24,999 9% 8%* 4% 13% £25,000 - £ 39,999 11% 4% 5% 15% Over £ 40,000 5% 0% 1% 6%* Life changes over the last 12 months New baby 5% 7%* 9% 7%* Separation 3% 3%* 2%* 7% Individual or their partner made 2% 4% 5% 6% redundant 52% 68% 66% 71% Any life change Household spending: Average net income of households in 1989 is 205£ p.w. Average income p.w. households by age: Age

-20

2025

2530

3035

3540

4045

4550

5055

5560

6065

3% 1% 28 % 31 % 12 % 25 %

36%* 7% 44% 13%

13 % 4% 62 % 19 %

40% 11% 13% 4% 18%

28% 11% 18% 4% 24%

56% 64% 26% 27% 5% 5% 9%* 3% 4%* 1% 7%* 11% 9% 6% 6% 6% 58% 56%

6570

7075

7580

8’85

London

Office

ng aspects to previo us period

among households - analyse credit use information about characteristics of indebtedness and households in debt

In some cases analysis of sub-samples. Comparison with other studies in the past in order to highlights differences and new trends (1979-1989) Concept of difficulties B.3

Inco me

150 220 240

260

270

265

270

250

210

150

95

100

80

Savings: no savings at all 29%; savings less than 11£ 9%; savings 1011,000£ 20%; savings 1,001-10,000£ 27%; over 10,001£ 15% 1/5 of account are in building society account; the others in bank accounts

financial 92% of households currently employed has a current account; employees without an account are mostly weekly paid, they have low earnings; ¼ of pensioners hasn’t got an account. There is no systematic link between attitudes to money and level of income. Income is not the only variable that influence on consumerism: people in their thirties and forties are relatively heavy consumers than younger or older. Needed thinks but unaffordable because of cost: decoration or home repairs 34%; present for the family 33%; a holiday or family outing 23%; large items of home equipment 18%; clothing 14%; small item of home equipment 6%; car repairs 6%; food 4%; things for a new baby 3% Money left over at the end of their budgeting period: Money left Runs over Most weeks/months 19% 8% More often than not 15% 10% Sometimes 22% 20% Hardly ever 19% 16% Never 24% 44% There is no clear pattern of increasing or decreasing hardship over the life cycle; the fall of income associated with retirement don’t seem to lead to an immediate increase in budgeting problems . Households’ commitments: The volume of mortgage lending nearly trebled between 1980 and 1989; from 100 billion £ at 1989 prices to 270 billion. Average mortgage payment p.w. by age: Age -29 30-39 40-49 50-59 60-69 70+ £ 74 74 59 38 33 9

46

70

Mortgage holding by income: Income Up to 100- 150- 200100 150 200 250 Proportion 16% 36% 44% 60% with mortgage

250- 300300 400 70% 80%

400+ 80%

Rent: from obtained data it is evident that the highest concentration on tents is in the range of 30-39 and 70+. Patterns of borrowing: Attitudes to credit: a sensible way of buying 7%; a convenient way of buying 12%; occasionally necessary 37%; never a good thing 43% Sources of consumer credit: finance houses and other credit guarantors 45%; banks: loans on personal accounts 34%; bank credit cards 16%; retailers 5%; insurance companies 2%; building societies’ class 3 loans 2% Credit facilities: 60% has any credit commitment; 16% has three or more commitments; average number of commitments 1.2 Types of credit commitments; sources per hundred adults: overdrafts 9; credit cards 30; store accounts 17.5; mail order 20; instalments 12.5; loans 10 Extent of credit use; number of active sources: none 42%; one 23%; two 15%; three 10%; four or more 10% Sources of active credit: - revolving credit: mail order catalogues 31%; credit/charge cards 17%; banks/BS overdraft 13%; store cards 8% - one-off credit: instalment agreements 22%; loans 19%; informal borrowings 10%; mortgage extensions 4% Credit and age: up to 29 80%; 30-39 83%; 40-49 76%; 50-59 65%; 6069 33%; 70+ 20% Credit and income: -100 67%; 100-150 69%; 150-200 75%; 200-250 77%; 250-300 77%; 300-400 78%; 400+ 76% Credit use is most common in small and moderate households savings; high balances seem not need for credit. The group with largest number of credit commitments are couples with children: 2.4 average sources compared with 1.7 for non pensioner couples without children. The logical sequence according to this report might be: LOW

47

INCOME – HARDSHIP – CREDIT USE People with a strong consumer orientation and high incomes tent to have borrowed quite large sums; on the other hand households in hardship ere frequent credit users but have low income: there are two different pressure to use credit at opposite ends of the social scale Impact of credit on households budgets: Analysis of income and commitments: housing costs 19%; household services 8%; minimum personal needs 19%; total repayment commitments 7%; available income 46% Consumer credit in percentage of available income: -100 120%; 100150 27%; 150-200 19%; 200-250 16%; 250-300 12%; 300-400 15%; 400+ 9% Debt: Origins of debt: insufficient income 25%; reduced income 26%; other changes in circumstances 7%; over commitment 24%; unexpected bills 10%; overlooked payments 8%; withheld payments 4%; creditor action 7%; benefit problems 5%. 1/5 of households have been in arrears in the course of previous year, but 1/3 of those didn’t seem to be serious Number of debts: Number of debts 1 2 3 4 5+ %of all households 6.4% 2.5% 1.2% 0.7% 0.7% % of all debtors 55% 22% 10% 6% 6% Amount of debt in percentage of all current debts: -100 31%; 100-500 49%; 500-1000 12%; 1000-2000 5%; 2000+ 4% Type of debt: mortgage 6%; rent 22%; local taxes 10%; household services 18%; other commitments 9%; overdraft 10%; credit/store cards 6%; mail order 6%; one-off advances 12% People in their twenties have few commitments but more debts than those in their thirties, as can be visible in the risk measure (debt/commitments) twenties people have 7.1 and the other 4.5 Problem debts by age: Age -29 30- 40- 50- 60- 70+ 39 49 59 69 Any problem 24% 17% 14% 6% 5% 1% 3+ debts 6% 4% 3% 1% * * Problem debt; income p.w.: Income -100 100150

48

150- 200200 250

250- 300300 400

400+

UK

Kempson E. Atkinson A.

2006

Overstretche d: people at risk of financial difficulties University of Bristol PFRC, November 2006

Financial capability baseline Sample of 5,328 (4,905 general population survey + booster samples in Wales, Scotland and Northern Ireland +

Mid2005

To investigate how many people would be at risk should they face an economic shock

Cluster analysis to identify five groups exhibiting distinctly different levels and kinds of financial stress

Concept of difficulties B.3

49

financial

Any problem 33% 22% 13% 9% 10% 8% 2% debt 3+ debts 10% 4% 4% 2% 1% 1% * Problem debts by number of active sources of consumer credit: Active sources of none one Two three Four c.c. Any problem debts 4% 13% 16% 21% 21% 3+ debts 1% 2% 3% 6% 8% People who budget by week and/Or has nor current account, has more problems than those with a monthly cycle and an account. Debts to different creditors Incidence and risk of problem debts: Debt Incidence Risk (debt as (debts as % %of of household) commitments ) Mortgage 1.3 3.3 Rent 5.0 17.7 Local taxes 2.3 3.1 Household services 4.3 1.6 Other household bills 1.9 2.3 Overdraft 2.3 16.2 Credit/store cards 1.4 4.5 Mail order catalogues 1.3 3.3 One-off advances 2.7 4.3 With regard to BILLS and CREDIT COMMITTMENT 2/3 of people said that their household was doing so without any difficult and ¼ said that it was sometimes a struggle; However 1/10 reported they were facing a constant struggle or were actually falling behind with their payments, and 1/100 admitted to having real financial difficulties. With regard to REPAYING MORTGAGES: a small proportion (4% of all respondents faced constant struggle or were falling behind with their mortgage repayments COMBINING the replies: - 64% keeping out without difficulty - 26% keeping up sometimes a struggle - 7% keeping up a constant struggle - 3% falling behind Results of cluster analysis: 5 groups, with different profiles with regards to making ends meet: 1. Financially sound (3,115 i.e. 58.5%)

booster sample of 423 ethnic minorities) Thesis to be tested: - likely effects of recent fuel price increases on people’s ability to make ends meet; - possible consequences of a rise in mortgage interest rates from two perspectives: 1) how well mortgagors themselves felt they would cope if their repayments increased by 10%, 2) more objective assessment of the possible impact using a statistical model - what risks people would face of being unable to make ends meet if the main wage earner lost their job

2. Managing reasonably well (1,332, i.e. 25.0%) 3. Showing financial stress (478, i.e. 9,0%) 4. Struggling on low income (320, i.e. 6.0%) 5. Struggling and over-indebted (83, i.e. 1,5%) The evidence with regard to: Who is facing financial stress ? A) Economic circumstances Income The group n° 5 was disproportionately people on middle-incomes – equivalised (55%) and their median monthly incomes (£ 1,3099 were only slightly above the average (£1.179). It is worth mentioning that the group of financially sound shows values slightly below the national average (£1.000). Working conditions Although they included above-average proportions of people living in households headed by someone in work, they also included the secondhighest proportions of people not working through sickness or disability (10%) or caring full-time for a family (11%). They included above-average numbers of people living in a household headed by someone who was self-employed. Education They are particularly unlikely to be educated beyond A level (only 14% “none of above (national average 31%) Clusters: I= Financially sound, II= managing reasonably well, III=showing financial stress, IV = struggling on low income, V = struggling and over-indebted I II III Median equivalised £1,000 £1,700 £1,400 monthly household income Work status of main earner (%) Full time work 39 66 67 Part-time work 8 9 10 At home 4 4 3 Retired 34 10 3 Unemployed 6 4 5 Sick or disable 4 2 4 Full-time education 4 5 9 Household headed by self-employed person ? - Yes 7 11 9 - No 93 89 91

50

total IV V £780 £ 1,309 £1,179

27 8 19 9 21 12 3

57 12 11 0 2 10 7

48 9 5 23 6 4 5

5 95

10 90

8 92

Highest educational qualification Degree or above 16 27 24 8 14 19 HND/HNC 10 14 11 7 14 11 A level 12 18 22 12 33 15 Trade apprenticeships 6 5 4 4 4 6 GCSE 17 18 20 21 21 18 None of the above 38 18 19 48 14 31 B) PERSONAL and HOUSEHOLD CHARACTERISTICS - Average age : 35 years (mean) the youngest of the five group - Families with children (couple 30% and lone parent 23%, national average: 22% and 11%)) - Housing: Mortgage 48% (national average 35%); private rent 16% (10%) and local authority rent 28% (21%) Clusters: I= Financially sound, III=showing financial stress, IV = struggling and over-indebted I Average age 53 Family type % Single adult (not retired) 11 Single (retired) 14 Couple with no children 14 (not retired) Couple with no children 17 (retired) Lone parent with children 9 Couple with children 17 Other 18 Housing tenure % Mortgage 26 Private rent 9 Local authority rent 21 Own outright 37 Other 7

II= managing reasonably well, struggling on low income, V = II 44

III 38

IV 42

V 35*

total

11 3 22

10 1 20

17 4 10

12 0 19

11 9 17

6

1

3

0

12

10 33 16

12 30 26

31 19 15

23 30 17

11 22 18

54 11 14 14 7

48 16 18 5 13

22 16 52 4 7

48 16 28 0 8

35 10 21 26 8%

48

* 18-19 = 2%; 20-29: 33%,40-49: 26%, 50-59: 10%, 60-69: 0%, 70 +: 0%

UK

Kempson E. Mc Kay S. Willitts M. 2004

Characterist ics of families in debt and the nature of

Further analysis of the Families and Children

Variou s years since 1999 to

The study examines the characteristics of those families in debt and the nature of their financial difficulties.

The analysis uses a number of different dataset, both cross-sectional and longitudinal, to determine which type of families are

51

Key findings: - The average amount owed in outstanding credit more than doubled from £ 890 in 1995 to £ 2000 five years later. Lone parents had a much higher risk of being in arrear than two –parent families and were also more likely to have long-term financial difficulties. The overall

indebtedness DWP – Department for Work and Pensions

2002 Study (FACS) four surveys 1999-2002 and DTI overindebtednes s Survey 2002 Plus BHPS 1995 and 2000

incidence of arrears among families with children declined slightly between 1999 and 2002. - Families that were in arrears were more likely to have a head of household who was young (in their twenties) and not in paid work. Families were also more likely to be in arrears if they were living as tenants rather than home owners, have an income of between £7,500 and £ 15,000 per annum, not have access to a current account and have three or more children. - Many of the financial problem faced by families were quite longstanding, with four in ten families who were currently facing financial financial difficulties saying that they had done so for more than a year. Lone parents were expecially likely to have long-term financial difficulties. - Between 1999 and 2002, the proportion of lone parents who were in arrears fell from almost a half to just over a third. The largest reductions took place for arrears on household bills. - Moves out of employment (16+hours a week) resulted in 37% of lone parents, who had been up-to-date with commitments falling into arrears. However, moving into work of 16 or more hours a week did not improve the chances of a lone parent leaving arrears when compared with others who continued to not work. Likelihood of arrears on consumer credit and household bills by family characteristics and economic position Percentage of in arrears now: All households: 13% , all families: 22%, Lone parents 36%, two parents: 17% Age: 20-29: 35%, 30-39: 20%; 40 and over: 17% Household changes in the last 12 months: new baby or separation: 32%; no change: 20% Housing tenure: mortgagor: 15%, tenant: 36% Economic activity status: full-time work: 16%, not working 32% parttime work [33%, small numbers small to be used with caution] Gross household income: under £ 7,499: 26%;£7,500-14,999: 34%; £15,000-24,999: 21%; £25,000-34,999: 18%, over £ 35,000: 11% Changes in income in last 12 months: fall: 35%; rise: 19%; no change: 17% Current account holding: has account: 20%, no account: 33% Causes (all households in arrears – all families in arrears : Loss of income : 42% and 31% Low income: 15% and 17% Over-commitment: 9% . 10% Increased/unexpected expenses: 11% - 14% Overlooked or withheld payment 12% - 13% Third party error: 6% - 7%

most likely to be in debt and to identify any trend over time., By using longitudinal data, it looks also at movements into and out of debt, as well as which factors protect families from going into arrears and what events trigger indebtedness. Concept of difficulties A.3

52

UK

Kempson E. 2002

Overindebtedness in Britain. A report to the department of Trade and Industry PFRCUniversity of Bristol 2002

Interviews March The study aims to Concept of with a -May provide the information difficulties 2002 about the causes, extent nationally B.3 and effect of overrepresentati indebtedness. ve sample of 1,647 households in Great Britain (undertaken by MORI). A separate, but linked, survey was also undertaken with 189 young people, aged 18-24, 2/3 of these were “nonhouseholder s”

53

Arrears left by former partner: 2% - 2% Other reason: 3% - 6% financial Extent of financial difficulties: In past 12 months and Now (column %) No financial difficulties at all: 76% (past 12 months)- 80%(now) Financial difficulties, but not arrears: 6% - 7% In arrears: 18% - 13% Average number of arrears (those with any) : 2,4 – 1,9 Likelihood of financial difficulties by characteristics of households: Cell percentages In arrears in Difficulties In arrears the past 12 now no arrears now months All 18% 7% 13% Ages: 20-29 40% 7% 30% 30-39 27% 10% 19% 40-49 23% 10% 17% 50-59 14% 8% 8% 60 and over 6% 4% 3% Family type: Single pensioner 6% 3% 4% Pensioner couple 5% 4% 3% Single non pensioner 28% 15% 18% Non-pensioner 16% 5% 11% couple 48% 14% 36% Lone parent 25% 8% 17% Two parent family 19% 7% 12% Other Housing tenure: Mortgagor 17% 8% 12% Outright owner 7% 3% 4% Social tenant 30% 9% 22% Private tenant 31% 9% 21% Economic activity status 18% 6% 13% 23% Full-time work 30% 8% 28% Part-time work 41% 22% 19% Unemployed 30% 23% 7% 2% 4% Sick/disable Retired Changes in income in last 12 months:

Fall 32% 18% 23% Rise 16% 3% 10% Both rise and fall 36% 8% 26% No change 14% 6% 11% Causes of financial difficulties (all in arrears or financial difficulty in past 12 months: (householders and sample of young people) Loss of income : 45% householders; 23% young people Low income : 14% - 25% Over-commitment : 10% - 14% Increased / unexpected expenses : 12% - 11% Overlooked or withheld payment: 8% - 4% Third party error: 5% - 7% Debts left by former partner: 4% - 0% Other reason: 3% - 16%

54

Table II MULTIVARIATE ANALYSIS: WHAT EXPLAIN HOUSEHOLD NON PERFORMING LOANS A. INDIVIDUAL FACTORS Authors

Title

Whitley An empirical J., Cox model of P. (2004) household arrears, Bank of England, working paper n.214

Data source Council of Mortgage Lenders (CML) Associatio n for Payment Clearing Services (APACS)

Dataset Time Countries period Mortg United ages:1 Kingdom 9852000 Credit cards: 19902002

Objective

Methodology

Main results

To understand the factors accounting for the probability of default on secured and unsecured household loans by analysing the determinants of mortgages and credit cards arrears.

Mortgage: proportion of mortgage loans Major factors of arrears (in order of importance): - Mortgages: income, unemployment, amount of undrawn in arrears of six months or more. equity, loan to value ratio (positive effect) Independent variables: mortgage income gearing, unemployment rate, undrawn - Credit cards: income, number of credit cards in use loan to value ratio (negative effect – higher LTVs are equity, loan to value ratio for first-time associated with a better credit risk on mortgage loans, buyers but they might also suggest that households are more Credit card: credit card payment arrears of likely to be overextended and therefore will build up three months. arrears on credit card debt). No direct influence of Independent variables: total income unemployment. gearing, unemployment rate, number of active card balances, consumer confidence. Dependent variable: the self-reported indicator of financial distress (the variable takes value 1 when the household reports no problem in meeting debt commitments, 2 when the household reports debt to be somewhat of a burden and 3 when debt repayment are a heavy burden). Independent variables: unsecured debt, household income, age, employment status, mortgage income gearing, financial wealth, race, education, health, marital status. Independent variables: education, age, income, wealth, marital status, home property, type of employment, gender, number of children, mortgage status and level

Del Rio A., Young G. (2005)

The impact of unsecured cdebt on financial di stress among British households, Banco de Espana, working paper n.0512

British Household Panel Survey (BHPS)

19952000

United Kingdom

To quantify the level at which unsecured debt becomes a problem for the typical household and what factors affect this outcome

Del Rio A., Young G. (2005)

The determinants of unsecured borrowing: evidence from the British Household Panel Survey, Banco de Espana, working paper n.0511

British Household Panel Survey (BHPS)

19952000

United Kingdom

To clarify the type of factors that influence borrowing and whether the importance of these factors has changed over time (in order to understand whether unsecured debt has increased because the factors determining its use have changed or

55

There is a clear link between the subjective measure of financial distress and indicators of the affordability of debt. The main determinant of debt problems is the unsecured debt to income ratio; other important factors are the level of mortgage income gearing, the level of financial wealth, their health, ethnicity and marital status.

The main determinant of the participation decision is the age of the borrower. Other statistically significant factors are income, economic prospects, qualifications, job status, housing status and the mortgage gearing. The main determinant of the level of unsecured borrowing of borrowers is the level of individual income. Other statistically significant factors are economic prospects, qualifications, job status, housing status and the mortgage gearing. Age seems less important. There is no clear statistical evidence of a change in the determinants of participation in the unsecured credit market and in the amount of borrowing. The rise in unsecured

whether more debt is held for given circumstances, that is whether people are borrowing more because their economic circumstances have changed and they feel more confident about taking on additional financial commitment or not) To understand the determinants of low income families arrears and to describe the sources of credit utilised by low income families, the patterns of arrears in payments of outstanding debt and the default on household bills.

borrowing appears not to have been concentrated within poor risk groups but to have been a general phenomenon affecting all borrowers.

Independent variables: age, wage, marital status, home property, working, gender, number of children, housing or disability benefits

Most low income families utilises several credit arrangements. But there are sharp differences: low income homeowners use credit arrangements that are comparable with the rest of the population, while low income tenants rely on loans from family and friends, from finance companies and rely on non-payment of rent and utility bills. Arrears arise largely as a result of low incomes. There is evidence that these families minimise on borrowing costs by defaulting on family loans and by using utility non payments and rent arrears in the short run as means of deferring expenditures. There is some evidence of arrears rotation in utility bills. Arrears are usually not strongly persistent.

Regression analysis of the “managing money” domain, on the “planning ahead” domain, on the “choosing products” domain and on the “staying informed” domain

Managing money: the groups that were least likely to make ends meet were young, rented their home and managed a cash budget (did not use a current account). Planning ahead: capability is lower for older people, with lower income, for people socially or financially excluded. Choosing products: people were generally poor at choosing products: most of the time they do not collect information and make decisions without seeking any advice or information. This is also due to the fact that people learn through experience: those with more purchases are better able to choose products. Staying informed: capability is lower for low income people, lower education and young age. The most important factor is age, followed by household income. There is also a strong link with educational qualifications and therefore unskilled jobs. Tenants ran a

Bridges S., Disney R. (2004)

Use of credit and arrears on debt among low-income families in the United Kingdom, Fiscal Studies, vol.25 n.1

Survey of 1999 Low Income Families

United Kingdom

Financial Services Authorit y (2006)

Levels of financial capability in the UK: results of a baseline survey

Financial capability baseline survey

Mid2005

United Kingdom

To be able to describe the types of people most likely to display higher or lower levels of financial capability

Kempso Overstretched: Financial n E., people at risk of capability Atkinson financial baseline

Mid2005

United Kingdom

To identify which Regression analysis factors are the ones most closely related to

56

A. (2006)

difficulties, University of Briston, Personal Finance Research Centre, November Berthoud Credit and R. debt. The PSI Kempso Report, n E. University of (1992) Briston, Personal Finance Research Centre, November Farinha, Households’ L. (2004) debt burden: an analysis based on microeconomic data. Banco de Portugal, Economic bullettin, September

survey

Della Pellegrin a L., Macis G., Manera M., Mascian daro D. (2003) Farinha, L. (2003)

being unable to make ends meet following a drop in income

higher risk than home owners since they have fewer reserves they can draw on in a crisis.

Personal 1989 interviews in 2212 households

United Kingdom

To predict the probability of a household having any problem debt during the years

Probit equation which uses characteristics of a household such as age, income, tenure, etc. to find the best estimate the probability of a household having a debt

The probability of debt fell with age, income rose and for households who had been in employment throughout the pas three years. It is higher for families with children, with no savings, with increased consumer credit commitments and for tenants.

Survey of 1994 households and ’ Wealth 2000 and Indebtedne ss (IPEF)

Portugal

To analyse changes in individual debt burden ratios of indebted households

Dependent variable: households debt burden ratio (households debt burden / disposable income) Independent variables: Income, age, gender ,marital status, level of education, labour market situations, households’ number of elements

Strong increase in the overall level of the indicator in the second half of the 1990s. However, the empirical evidence obtained on the basis of IPEF find that this increase is mainly due a strong increase in the accessibility of households to credit during the same period, which sis not achieved at the expenses of the creating of highly critical situations. At the same time, the authors point out that in the IPEF the lowestincome class and the lowest age class are underrepresented in the sample and thus the results may underestimate the actual situation and introduces elements of vulnerability, in aggregate terms, to an increase in unemployment.

Il rischio usura nelle province italiane, Ministero dell’Economia e delle Finanze

Treasury 1999Departmen 2002 t Bank of Italy Istat

Italy

To obtain some forecasts about the incidence of usury in Italian provinces

Dependent variable: number of usury accusations for each province Independent variables: number of bank counters for each province, easy-term loans, bad loans, GPD, rate of unemployment, number of protests, numbers of mafia association crimes

There is a significant positive effect of easy-terms loans on the reduction of the number of usury accusations, while there is a very high negative impact of bad loans on usury credit demand. Positive impact of unemployment rate on the number of usury accusations PIL highlights that usury is more frequent in regions with a greater activity volume.

The effect of demographic and socio-

Survey of 1994 households and ’ Wealth 2000

Portugal

To evaluate the effect of some households characteristics on the

Independent variables: Income, family size, age, income age, gender, marital status, education, type of

The proportion of indebted households and the outstanding amount of their debt holdings increase with their income, wealth and with the level of education of the households’

57

economic factors on household’s indebtedness. Banco de Portugal, Economic bulletin, June

and Indebtedne ss (IPEF)

probability of holding work debt and on the outstanding amount of debt.

head.

58

B. INSTITUTIONAL FACTORS

Authors

Title

Rinaldi L., SanchisArellano A. (2006)

Household debt sustainability. What explains household non-performing loans? An empirical analysis, European Central Bank, Working Paper Series, n.570

Crook J., Hochgue rtel S. (2006)

Household debt and credit constraints: comparative micro evidence from four OECD countries

Dataset Data Time source period Statistical 1998publication 2004 s of national central banks

Survey of Consumer Finances SCF (US), Survey of Household Income and Wealth – SHIW (I), Survey if Household Finances – EFF (ES), DNB Household Survey – DHS (NL)

Countrie s Belgium, France, Finland, Ireland, Italy, Portugal and Spain

US, Italy, Spain, The Netherla nds

Objective

Methodology

Main results

To understand to which extent the current increase in the debt to income ratio of households constitutes a movement towards a new equilibrium or, rather, is related to a riskier financial position for the sector

Econometric analysis of household arrears on payment obligations. The model uses the ratio of non-performing loans as an indicator of households’ financial fragility. Independent variables: household debt/disposable income; real disposable income per household; household gross financial assets/disposable income; real lending interest rate; unemployment rate; inflation rate; house price index; owneroccupied dwellings.

To provide international comparisons of the determinants household debt holding.

Independent variables: income, wealth, age, number of kids, unemployment rate, employment status, race, education, health, marital status

The recent rise in the debt ratio has put the household sector a riskier financial position. The main attenuating impact on such risk is played by rises in disposable income, but in the countries considered the evidence is that income has grown less that the ratio of debt. In other words, the model suggests that, in the long run, an increase in the ratio of indebtedness to income is associated with higher levels of arrears; however, if the rise in the debt ratio is accompanied by a rise in disposable income, the negative effect is more than offset. This suggests that increases in real disposable income would allow – other things being equal – relatively higher increases in the debt to income ratio combined with the same level of the ratio of arrears. Differences between countries seem to be very important. These differences are likely to be related to institutional characteristics (legal and fiscal environment), which play a key role in determining the stability of financial conditions and, therefore, the equilibrium level of household debt. Institutional variables are very difficult to measure overtime; this is why it’s difficult to measure their impact directly. There are substantial differences among countries that are not easily explained by changes in the independent variables of the model. These differences are explained by institutional and structural factors such as Social Income Insurance, bankruptcy legislation, usury regulation, judicial enforcement, information sharing, mortgage market institutions, homeownership and house price development, financial system and financial liberalization.

59

Duygan B., Grant C. (2006)

Household debt and arrears: what role do institutions play?, preliminary draft presented at the Finance and Consumption Internal seminars, European University Institute

European Communit y Household Panel (ECHP)

19942001

Fay S., Hurst E., White M. (2002)

The Household Panel 1984bankruptcy decision, Study of 1995 The American Income Economic Review, Dynamics vol.92, n.3 (PSID)

US

Grant C., Padula M. (2006)

Informal credit markets, judicial costs and consumer credit: evidence from firm level data, preliminary draft

Italy

Findomesti 1995c Banca 1999 (the leading Italian lender of

EU and 15 member countries

To analyze the determinants of household debt arrears and, in particular, to understand the role of institutional factors (judicial enforcement, information sharing, informal markets) in household arrears by exploiting cross-country differences. To understand the determinants of household bankruptcy decision

Independent variables: education, age, interest rate, household income, marital status, home property, type of employment, country fixed effects, dummy variable for adverse events (unemployment shock, negative income shock, negative health shock). In order to understand the interaction between adverse events and institutional factors the model takes than into account the following other variables: judicial enforcement, information sharing, informal markets.

The propensity to fall into arrears is affected by adverse events. The responses to these adverse events vary across countries and depend on local financial and judicial institutions: - households are more likely to be in arrears when cost of enforcement increases - households are less likely to be in arrears if coverage is higher - the results on the effects of informal markets seem mixed.

Empirical model of the household bankruptcy decision. The independent variables test three hypotheses: - whether household are more likely to file for bankruptcy as their net financial benefit from filing increases; - whether they are more likely to file for bankruptcy when adverse events occur; - whether households’ bankruptcy decisions are influenced by average bankruptcy filing rates in the localities where they live.

Household are more likely to file when their financial benefit from filing is higher. Little support for the non-strategic model of bankruptcy which predicts that households file when adverse events occur which reduce their ability to prepay. Household are more likely to file for bankruptcy if they live in districts with higher aggregate filing rates (low effect of stigma).

To investigate the effect of institutional factors (namely judicial efficiency and

Independent variables: job seniority, income, home-owners, mortgage borrower (holding a mortgage is a signal to be a good borrower), self-employed, average length of civil trials,

The effect of informal credit markets on whether the debt is repaid is both economically and statistically significant. Household with access to these informal credit markets view exclusion from the formal credit market less onerous since they can still borrow from friends and family should the need arrive. In contrast, the effect of judicial enforcement is

60

unsecured credit to the household sector)

Jappelli T., Pagano M. (2006)

The role and effects of credit information sharing, in Bertola G., Disney R., Grant C. (edited by) The economics of consumer credit

of the reliance on friends, number of economically small and statistically insignificant. This do not availability of branches. surprise given the small size of the typical loan and the fact informal credit that these loans are uncollaterized (conversely judicial from family enforcement is significant for housing credit since it affects and friends) on decision to lend through its effect on the value of the borrowers' collateral). unsecured credit repayment behaviour. Literature review Comprehensive Information sharing can have important effects on credit overview of the markets activity. First, it improves the banks’ knowledge of economic applicants’ characteristics and permits a more accurate effects of prediction of their repayment probabilities. Second, it reduces informationthe informational rents that banks could otherwise extract from sharing their consumer. Third, it can operate as a borrower discipline systems, device. Finally, it eliminates borrowers’ incentive to become drawing overindebted by drawing credit simultaneously from many together theory banks without any of them realizing. and empirical evidence.

61

Table III SURVEYS ON CREDIT SCORING Authors

Title

Dataset

Data source Camoes F. Hill Prediction of loan 5,281 M defaults using a cardholders credit card randomly (2000). scoring model stratified incorporating by month worthiness of acquisition of credit card

Time Countries period April Portugal 1994 – February 1996

Avery R.B. Consumer credit Caleman P S scoring: do Canner G.B. situation circumstances (2004) matter ? BIS WP n° 146 2004

July 1997June 1999 (test period) Prior July 1997 (base period

Objectiv Methodology e

Variables

Seniority (years) in job Seniority (years) of bank account Seniority (years) in current address Seniority (years) in former address

The goal of the analysis is to draw inference s concerni ng the potential value of incorpor ating situation al data

Two empirical models are estimated that provide test of the potential value of situational factors in credit performance prediction The first model (“model 1”) tests the relation between local economic circumstances, as reflected in county-level unemployment rates, and payment performances on the new accounts

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Number of credit cards Employment (public service,private sector,selfemployed,unemployed,retired, no active) Employment (director, office staff, senior staff, technician, other category) Labour agreement (effective labour agreement, timed labour agreement, other labour agreement) Lodging (rent lodging, family lodging, own house, other lodging) Age (years) Education (technical/special degree, primary degree, secondary degree, high degree) Number of children Number of person in charge of Gender Marital status (married, divorced,joined, single, widower) Total charges Total income Default = dummy (0/1)variable = 1 if account became 60 days or more delinquent by June 1999 Unemployment = average unemployment rate over the two-year period 19971998 in the county where the individual resides Lag Unemployment =idem, in the two previous years Marital status = dummy (0/1) variable = 1 if : recent married, other married, new divorced, other divorced, never married) Delinquencies experience: dummy (0/1) variable = 1 if minor deliquencies all in the same month, within an identifiable two-to five month period, within an identifiable six- to 11 month perio; over 12 month or more Score = estimated historical credit score Kind of credit dummy (0/1) variable = 1 for revolving account, instalment accounts, mortgages, line-of-credit accounts Account age = number of month since account was opened; Age of individuals = individuals are classified as: under 40; 40-64, and 65 or

into credit evaluatio ns European generic scoring models using survival analysis CRC –University of Edinburgh, WP 04/3 - 2004 G. Credit scoring in Crook the context of the European integration:assessi ng the Performance of the Generic Models CRC –University of Edinburgh, WP 04/02 Does Reject Inference Really Improve the Performance of Application Scoring Models CRC –University of Edinburgh, WP 02/3 -2002

Andreeva G. 2004

Andreeva Ansell J. J.N. 2002

Crook J. Banasik J 2002

Data provided by a major internation al credit scoring consultanc y

October 1998Decembe r 200

Belgium Germany Netherland s

Idem

Idem

Idem

older Minority group= set of four dummy (0/1) variables classifying the census tract where the individual resides by percentage minority population: < 10%, 10-50%, 50-80% and > 80% - Home telephone - Residential status - Marital status - Occupation (full-time, part-time,self-employed, etc.) - Age - Time at address since 18 years old - Time in employment - Type of business (manufacturing, banking, catering, etc) - Employer’s phone - Card insurance - Credit insurance - Number of dependants - Spouse age - Goods code - Goods price - Payment date

UK (England)

The variables included in the Accept-reject and Good-Bad Equation are 26 and 16, respectively. In the Accepted-reject equation 10 variables are taken from the bureau and 5 are proprietary variables (not disclosed). To these are added the following: - Television area code - Age of applicant - Accommodation type - Number of children under 16 - Has telephone - Type of bank/building society accounts - Occupation code - Current electoral role category - Years on electoral role at current address - Number of searches in last 6 months In the Good-Bad Equations: 6 variables are taken from the bureau and 3 are proprietary variables (not disclosed). To these are added the following: - Time at present address - Weeks since last county court judgement (CCJ) - Television area code - Age of applicant

63

Rszbach K. 2003

Bank Lending Policy, Credit Scoring and the Survival of Loans Sveriges Riksbank Working Paper series n° 154, November 2003

13,337 application s for a loan that were processed by a major Swedish lending institution

- Accommodation type - Number of children under 16 - Has telephone Personal (area of residence, divorce/married, male/female); Financial (applicant has taxable income from capital, has taxable income from business, owns – part of – a house, income from wages, income of last years) Credit (applicant has a guarantor, has no collateral-free loans outstanding, collateral free credit facilities already outstanding, share of collateral free credit facilities already outstanding that is actually being utilized, amount of credit granted, number of collateral free loans that is registered, number of requests for information on the applicant that the credit agency received during the last 36 months.

Septembe Sweden r 1994August 1995

64

TABLE IV SURVEY ADOPTING QUALITATIVE APPROACHES Authors

Title Data source

Frade, C 2004

The fable of the grasshopper and the ant: A research project on over- indebtedness and unemployment in Portugal. University of Coimbra, working paper.

Interviews

Dataset Time period 2002

Objective

Methodology

Main results

To analyse the relationship between unemployment and over-indebtedness, that is to analyse financial sustainability of families in a situation of unemployment, especially where there are outstanding debts for consumption and housing.

Two sets of interviews based on different casual sample: - casual sample of workers from various industrial plants that have closed. Aim of the analysis: to look for any over-indebted individuals among the unemployed. - casual sample of individuals who had sought the help from DECO to renegotiate deals with creditors . Aim of the analysis: to find from the over-indebted to what extent unemployment had influenced their insolvency.

The results of the interviews indicate that among people who lost their job or who has overindebtedness problems, there are two general profiles – the grasshopper and the ant – who show different patterns of consumption and indebedness. These differences, in turn, show the distinct sustainability of families in the face of unemployment. The first set of interviewees is constituted by average 40 years factory workers, with low level of education, few professional skills and low salaries. As far as their consumer and indebtedness habits, they have a strong habit on savings although wages are low, the relationship with credit is nil or extremely limited, credit cards are not used, no intense or diversifies consumption. After job lost, these people had continued keep a rural or semi-rural lifestyle: they try to restrict their family expenditure as far as possible, they have almost all given up personal spending. This allow them to still maintain a low level of indebtedness, with a quite strong informal solidarity networks which sometimes helps them to stop entering into default. They also maintain a very strong ethical attitude in relation to their debt. The patterns of behaviour found makes it possible to classify these interviewees, symbolically, as the ants of society: generally speaking, although unemployed they are not overindebted. The second set of interviewees is constituted by 25-40 years, with a middle

Country Portugal

Concept of difficulties A.3

65

financial

Herbert, A.; Kempson, E. 1995

Water debt and disconnection, Policy Studies Institute, London

39 depth interviews of customers with water debt. Postal Survey water companies: 10 water and sewerage and 21 water only.

1994

UK

To point out the profile of households that defaulted on their water bills and to analyse the different ways that water companies use to manage households eater deb.

66

Interviews and qualitative analysis on existent data. Concept of difficulties A.2

financial

or high level of education, urban lifestyle, intense consumptions behaviour. Credit is commonly used and credit cards is a familiar financial instruments. Credit facilities and a lifestyle where having goods of a particular kind and personal image are of considerable social importance encourage a certain temptation to consume and to use credit. Not all are unemployed, but unemployment was the main cause of their defaulting. These people may be symbolically termed grasshoppers; they are more vulnerable to the financial consequences of job loss. This vulnerability is expressed in more frequent defaulting on debts, due to a more consumption pattern and higher indebtedness. The interviews conducted resulted from a random sample and the conclusion drawn from them cannot be further extrapolated for the universe of the families. In 1994 almost 2 millions of households defaulted on their water debts and 12,452 of them were disconnected. Households with water debt problems are under 39 years old, normally not in work or unemployed or looking for a job, with low income, with children. They fall behind their water bills because of their low income or an income reduction due to the substantial restructuring of the labour market, variations in earned income, long-term consequence of job loss and relationship breakdown. They also have disorganized money management or problem of can’t pay versus won’t pay In order to help them to overcome their inability to pay, many companies offer payment facilities, which are particularly relevant in order to help them to manage their finance, such as weekly payment or

Elliot, A. 2005

Not waving but droving

UK debt Advice Centre

Edwards, S. 2003

In too deep .CAB clients’ experience of debt, CAB – Citizens Advice Scotland

Over 900 people seeking debt advice from CABs

2001

UK

To analyse the behaviour of households the had sought the help of UK Debt Advice

Qualitative analysis Concept of financial difficulties A.3

UK

To portrait the characteristics of households who become cab’s clients because of their debt problems.

Qualitative analysis based on percentage frequency of the analysed sample. Concept of difficulties A.3

67

financial

pre-payment devices (swipe cards, water cards) As far as debt recovery, there are different approaches following different industrial policies adopted by water companies which can be summarized into to polarised approaches: short sharp shock approach and relaxed approach Households who had been disconnected were poor and predominantly in the cannot pay category (only few are categorized as households who won’t pay). Some people in default had become overcommitted through a drop of income, others were continually spending more than their income. The profile of CAB debt clients is: individuals poorer than the general population, who received income support, jobseekers allowance or tax credits. In general debt clients are more likely to be people of working age, between 25 and 59. There is a substantially higher proportion of single; among couples, it is higher the percentage of families with children. Most of them are tenants. About their debts, the average total debt per household was £10.700 (although almost half of the households old a debt less than £5.000) and the average debt to monthly income ratio was nearly 14 times the income. The average total debt generally increase according to age, with the highest levels of debt owed by people aged between 45 and 59. The three principal reasons why CAB clients are facing debt problems are overcommitment and money mismanagement, job loss and low income, although, of course, it has been generally accepted that there are a number of interrelated reasons.

Phipps, J; Hopwood Road, F. 2006

Deeper in debt. The profile of CAB clients, CAB – Citizens Advice Scotland

567 CAB clients

2004

UK

This paper updates the previous one “In too deep. CAB clients’ experience of debt”.

Qualitative analysis based on percentage frequency of the analysed sample. Concept of financial difficulties A.3

Observatório do Endividamento dos Consumidores 2002

Evidamento e incumprimento no crédito bancario ao consumo. Um estudo de caso

19982001

Portugal

To analyse retail credit in Portugal and arrears.

Qualitative analysis based on percentage frequency of the analysed sample. Concept of financial difficulties B.1

Observatório do Endividamento dos Consumidores 2002

O sobreendividamento dos dos consumidadores: um estudo de caso

20012002

Portugal

To point out the profile of overindebted households who had sought the help from DECO

Qualitative analysis Concept of financial difficulties A.3

Observatorio de Endividamento dos Consumidores 2002

O Sobreendividamento em Portugagal

Data collected by one of the most important bank in Portugal which are related to a portfolio of 146857 retail consumer credits. 46 interviews profile of overindebted households who had sought the help from DECO of Coimbra 9 case history of over-indebted households

2000 2002

Portugal

To highlights the paradoxes end differences that characterised the households that struggle with their debts.

Depth interviews and analysis of households’ income and arrears Concept of financial difficulties A.3

68

Compared to the previous report, CAB clients situation has worsen: the average total households debt increased approximately 30% between 2003 and 2006 (£13153 in 2006 against £10700 in 2003); moreover, the debt to income ratio was 17.5 in 2006, while it was 14 in 2003. Over half of the clients in the survey had nothing to offer creditors; on average it would take CAB debt clients who were able to make a repayment to their nonpriority creditors 77 years to repay the debts at the amount offered. The observed ratio of non-performing loans is quite low and default on consumer credit at the moment does not represent a problem. The two main variables which explain repayment problems are age(26-30) and marital status (divorced) Overindebted households who had sought the help from DECO are male, married, between 36 and 55 years, with a middle or high level of education. The three principal reasons why they are overindebted are unemployment, low income and illness. Consumer credits are used not only to buy goods but also to repay previous debts. Households try to be always solvent on mortgage repayment since home is considered one of most important goods to protect. Problems related to finance illiteracy: households are not able to prevent financial risks and have money management problems. High importance of informal markets, that is financial help from friends and family in order not to default.