The determinants of households’ repayment difficulties on mortgage loans: evidence from Italian microdata

Abstract

This article investigates the main determinants of households' repayment difficulties on mortgage loans in Italy. We contribute to the empirical literature on household financial vulnerability by assessing the joint impact of socio-demographic factors, loan characteristics and institutional variables on the likelihood of mortgage insolvency and on the intensity of arrears. Using data from the Italian component of the 2008 European Union-Statistics on Income and Living Conditions (EU-SILC) survey, we firstly identify which types of households are more vulnerable to unexpected adverse events that may trigger repayment difficulties. Specifically, households whose head is young, unemployed or immigrant show a higher probability of arrears and emerge as those suffering more from the adverse economic conditions connected to the crisis. Moreover, household repayment behaviour is affected by mortgage characteristics and, in particular, having modified contract terms significantly increases current arrears probability. Finally, regional institutional and credit market factors mainly impact on the conditional intensity of arrears. This evidence suggests that, although repayment difficulties mainly arise from a genuine inability to repay, households are less likely to pay on time when institutions are less effective at punishing default, confirming the existence of some strategic behaviour.

Examining Statistical Methods in Forecasting Financial Energy of Households in Poland and Taiwan

“…Another branch of the literature focuses on forecasting the risk of consumer bankruptcy with the use of microeconomic factors. Most of the authors, e.g., Aristei and Gallo [14], Diaz-Serrano [15], Ghent and Kudlyak [16], Guiso, Sapienza and Zingales [17], Haughwout, Okah and Tracy [18], Hira [19], Jackson and Kaserman [20], Patel, Balmer and Pleasence [21], Worthington [22], and I-Cheng and Che-hui [32] use the following determinants: age, education level, gender, income level, mortgage expenditures, mortgage length, marital status, number of dependents, employment status, credit card expenditures, number of credit cards, and value of assets.…”

“…Majority of studies devoted to forecasting the financial standing of the household is based on traditional credit scoring methods that help banks decide whether or not to grant credit to consumers who apply to them [13]. Most of the scholars use the following determinants in the models, e.g., [14][15][16][17][18][19][20][21][22]: age, education level, gender, income level, mortgage expenditures, mortgage length, marital status, number of dependents, employment status, credit cards expenditures, number of credits, and value of assets. In other words, existing forecasting models available in the literature contain only individual financial and demographic information.…”

Evaluation of the Macro- and Micro-Economic Factors Affecting the Financial Energy of Households

“…They disrupt the sources of household income, which decreases households' ability to repay their debts. This condition gradually increases the probability of experiencing financial distress, causing foreclosures on the collateral used for securing bank credit, such as homes or cars [19][20][21][22]. The third macro-economic factor is the interest rate.…”

Mortgage arrears, regulation and institutions: Cross-country evidence

“…Although there is increasing evidence that macro-prudential policies affect housing credit growth and house prices ( Galati and Moessner, 2018 ), there is limited evidence on whether these instruments influence the incidence of mortgage defaults. Wong et al (2011) investigate the 5 An exception is the work by Aristei and Gallo (2012) who consider variables such as mortgage maturity in their analysis of Italian mortgage defaults. 6 Both theories suggest that macroeconomic factors (such as lower house prices, higher interest rates and higher unemployment) may increase mortgage defaults by reducing the ability of households to pay their mortgages.…”