Over-indebtedness in Italy: how widespread and persistent is it? Giovanni D’Alessio and Stefano Iezzi “The Bank of Italy’s Analysis of Household Finances” Fifty Years of The Survey on Household Income and Wealth and the Financial Accounts Banca d’Italia, Roma 3-4 dicembre 2015

Why to study over-indebtedness is important  Access to credit is a great benefit to most households as it enables to smooth short-term fluctuations of income and to finance long-term projects such as house purchase  However, some households might have problems dealing with debt  There was already some concern about rising levels of debt before the recent financial crisis and the situation of vulnerable households has been worsened by the additional pressure resulting from the economic downturn  Over-indebtedness is of interest for two main reasons: social issue  social issue (measurement should focus on the number of people involved and their condition of difficulty) stability of the financial system  issue for the stability of the financial system (emphasis on the size of the debt and the existence of collaterals) 22

Objective of the paper  Examine the measures of over-indebtedness proposed in the literature  Apply the measures to the Italian case from 2008 to 2014 by using the Bank of Italy’s survey on households (SHIW)  The wide set of indicators is critically analyzed from both a cross-sectional and a historical perspective  The panel component allows the analysis of transition into and out the condition of over-indebtedness  The issue of measurement errors that might affect both levels of over-indebtedness and transitions is taken into account  Over-indebtedness of Italian households are compared with that of other European countries by using HFCS data 33

Definition of over-indebtedness 44  Not a common consensus on the definition of over-indebtedness (Kempson, 1992; Bridges e Disney, 2004; Kempson, McKay and Willitts, 2004)  In Germany, over-indebtedness has been defined as a situation where household income “in spite of a reduction of the living standard, is insufficient to discharge all payment obligations over a long period of time” (Haas, 2006)  In France, an individual is considered over-indebted when, with well-meaning intentions, he/she is unable to meet the obligations coming from debts obtained for non-professional reasons  In the UK the focus has been put on being in arrears in paying regular bills (Oxera, 2004)  In Italy Law 3/2012 defines over-indebtedness as a situation in which there is a persistent imbalance between obligations and assets that can be easily liquidated, as well as an inability to fulfill the obligations regularly

Traditional indicators 55 CategoryIndicatorDescription Cost of servicing debt A1_30 Debt burden indicator Debt burden indicator: Households spending more than 30% of their income on total borrowing repayments (secured and unsecured) B_25Households spending more than 25% of their income on unsecured repayments C Debt poverty indicator Debt poverty indicator: Households whose spending on total borrowing repayments takes them below the poverty line ArrearsD1 arrears Households more than 3 months in arrears on a credit commitment D1B Households more than 3 months in arrears on a credit commitment or household bill Number of loans E4 Households with 4 or more credit commitments Subjective perception of burden F Households declaring that their borrowing repayments are a “heavy burden”

Extension of the traditional indicators 66  Traditional indicators typically ignore household assets: Households might bear debt burden higher than 30 per cent of income when they can rely on financial or real assets  Extension of A1_30 to A4_30: households spending more than 30% of their monthly income on total borrowing repayments after deducting financial and real assets except for the residual life estate of the household’s home (D’Alessio and Iezzi, 2013)  Extension of D1 to D2: Households more than 3 months in arrears and whose liabilities are above the assets that can be easily liquidated (Magri and Pico, 2012)

Over-indebtedness in Italy in 2014 Percentage of households  Similar result when considering only non-collateralized debts (B_25)  Households in arrears (D1) are 0.5%, but when considering also arrears on bills (D1B) the percentage rises to 8.4  Households being in arrears and having imbalance between liabilities and assets (D2) are 0.2%  Limited degree of overlap between some indicators  When dealing with measurement errors moderate changes in levels 77  Households spending more than 30% of their income to repay their debts (A1_30) are 2.3 per cent  When considering households assets (A4_30) the percentage drops to 0.6

Over-indebtedness indicators and self-reported financial distress (Association index)  Arrears indicators (D1, D1B and D2) more connected with subjective financial distress  Low association with traditional debt burden indicator A1_30  When accounting for household assets (A4_30), statistical association rises significantly  Low association for the remaining indicators 88

Over-indebtedness over time Percentage of households  For some of the indicators (A1_30, B_25, C) the percentage of over- indebted households increased between 2008 and 2010, and decreased afterwards  According to the arrears indicators (D1 and D2) and the debt burden indicator that includes assets (A4_30), over-indebtedness steadily increased between 2008 and 2012, and fell considerably only between 2012 and

Who is over-indebteded? Over-indebted households according to income quintiles  Over-indebtedness generally more frequent in the lowest class of income, although the share of indebted households in that class is lower  Traditional debt burden indicator (A1_30) declines slowly for the highest classes  When considering household assets (A4_30) over-indebtedness is very limited in the highest class of income  Relatively high prevalence of over-indebted households among the poorest class according to the indicator for arrears on debts and bills (D1B) 1010

Who is over-indebteded? Further results Further results:  Unemployment is associated with high levels of over-indebtedness, especially according to arrears indicators  High prevalence of over-indebted households among households with self- employed heads according to debt burden indicators  Households with a mortgage show the highest level of over-indebtedness according to most indicators  …with the exception of the arrears indicators for which the highest level is detected for social tenants 1111

How long does the over-indebtedness condition last? Percentage of over-indebted households in 2012 that remain over-indebted in 2014  13% according to arrears indicator (drops to 7% when taking into account household assets)  Share of households experiencing at least one instance of over-indebtedness from 2008 and 2014 is lower than 6%  The average duration of the condition of over-indebtedness is around one year and a half according to most indicators 1212  Degree of persistence generally low  Persistence is 33% according to the debt burden indicator (drops to 25% when considering assets)

Persistence and measurement errors  Some of the observed transitions might be spurious because of measurement errors that tend to under-estimate the degree of persistence  Latent Class Analysis (LCA) is a prominent tool to deal with measurement errors in transitions  The true variable of interest cannot be measured directly (latent); we only observe some imperfect indicators (manifest)  The LCA assumptions:  Transition probabilities of latent variable are allowed to vary over time  Measurement properties are constrained to be time-invariant  The true latent transitions only depend on the condition of over- indebtedness at the beginning of the period  The LCA model is estimated using Expectations-Maximization (EM) algorithm 1313

Persistence in over-indebtedness adjusted with LCA,  The corrected probability of persistence in over-indebtedness is significantly higher than that observed on the raw data  According to LCA an over-indebted household would remain in that condition for approximately 5 years on average (instead of 1-2 on unadjusted data) 1414

Cross country comparison of over-indebtedness HFCS data  Italy’s over- indebtedness generally lower than those for other European countries  Finland shows lower indicators; Austria, Germany and Slovakia approximately at the same level as Italy 1515

Conclusion - 1  Indicators address different aspects of over-indebtedness  Moderate levels of over-indebtedness in Italy, mostly below 4%  Indicators that take household assets into account fall below 2%  Italy’s over-indebtedness generally lower than those for other European countries  The indicators that best detect the condition of economic distress associated with over-indebtedness are those referring to the arrears on debts and bills and the debt burden indicator that includes assets  Over-indebtedness more frequent in the lowest class of income (although the share of indebted households in that class is lower), particularly according to the indicator of arrears on debts and bills  Debt burden indicator signals over-indebtedness also on higher classes of income and households with self-employed heads 1616

Conclusion - 2  Persistence in over-indebtedness is generally low according to all indicators, especially when indicators take account of household assets (1-2 average number of years in the condition of over-indebtedness)  When measurement errors are considered, over-indebted persistence is much higher (average number of years is approximately 5)  Future research will be focused on international comparison of persistence estimates using HFCS data 1717

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Over-indebtedness and measurement errors  Indicators could suffer from measurement errors affecting income, assets and liabilities in sample surveys  D’Aurizio et al. (2006) and D’Alessio and Faiella (2002) show that in SHIW under- reporting of debt values is considered to be significant and probably higher than that of income and assets  In order to assess the possible impact of such problems on over-indebtedness an adjusted dataset of SHIW prepared by D’Alessio and Neri (2015) has been used  Selectivity bias and under-reporting are treated  Adjustments: models and calibration techniques to fill the gap between sample estimates and National Accounts  The adjustments:  1: calibration of real and financial assets, financial liabilities and total income  2: calibration of real and financial assets, financial liabilities and income by type  available in 2008, 2010 and

Over-indebtedness and measurement errors, 2012 Percentage of households  Moderate increase in over-indebtedness for traditional debt-burden indicator A1_30 and and its extension A4_30  Moderate decrease for the debt poverty indicator C  No significant change for the arrears indicators (D1 and D1B) and the non-collateralized debt burden indicator (B_25) 2020