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Risk Aversion and the Size of Desired Debt

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Abstract

We investigate the determinants of the level of desired total, secured, and unsecured debt for a panel of Italian households over the period 1989–2016, accounting for both left censoring and sample selection. In particular, we focus on the role of households’ attitudes towards risks, using both their observed behaviour in the financial market and the responses to a hypothetical lottery choice question. We find risk aversion to be a significant determinant of the desired amount of unsecured, secured, and total debt. Relatively more risk adverse households desire more debt, suggesting that Italian households may rely on debt to insure themselves against shocks.

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Notes

  1. The optimal consumption path is a function of the coefficient of risk aversion when, for example, preferences are represented by the popular isoelastic utility function or the Epstein–Zin–Weil recursive utility.

  2. Attitudes toward risk represent a relevant factor in several decision making processes, like those concerning financial investments and portfolio choice (Gomes and Michaelides 2005; Barasinska et al. 2012), health insurance (Anderson and Mellor 2008; Schmitz 2011; Gandelman and Hernández-Murillo 2013), migration (Jaeger et al. 2010), labour market (Ahn 2010; Dohmen et al. 2010; Dohmen and Falk 2011; Pollmann et al. 2020), education (Castillo et al. 2011; Caner and Okten 2010; De Paola and Gioia 2012; Checchi et al. 2013), and marriage (Schmidt 2008; Spivey 2010; De Paola and Gioia 2017).

  3. We prefer this to other panel data estimators robust to selection bias, such as Kyriazidou (1997) and Rochina-Barrachina (1999), because it does not require any known distribution of the errors in the equations of interest but allows them to be heteroskedastic and serially correlated. Although this estimator can be employed when some of the explanatory variables are endogenous, we do not exploit this advantage.

  4. Most financial institutions have an upper limit on age when deciding whether to grant a loan. Since 2005, the Italian National Institute for Social Security allows pensioners to access salary-backed loans, where the Institute is directly responsible for repayments that are never higher than one fifth of the pension. This has enlarged the Italian market for loans to senior people, but options for those aged 90 years old and higher are basically non-existent.

  5. The phrasing of the question in 2000 is as follows: “You are offered the opportunity of buying shares which, tomorrow, with equal probability, will be worth either 10 million or nothing. How much would you be prepared to pay to buy these shares?"

  6. This is based on the model of expected utility, which has been the standard approach in economics to capture risk-aversion consideration. See O’Donoghue and Somerville (2018) for a review of its pros and cons.

  7. Eisenhauer and Ventura (2003) underline that one has to choose between considering the positive outcome of the postulated gamble as a gross or a net value, i.e. before or after tax. We opt for the latter.

  8. Results are robust to limiting the sample to only risk averse individuals. Results are available on request.

  9. We present the results for OLS, CRE, and CRTE only, since the Mundlak effects are always jointly significant (the other results are available on request). We also report the results from the Semykina and Wooldridge’s (2010) estimator, but it should be noted that the liquidity constrained questions are not referred to any of the two forms of credit in particular.

  10. However, it is important to observe that net wealth may be affected by simultaneity bias: the amount borrowed in a year influences the current level of wealth. We checked the robustness of our results to two alternative specifications, the first where we substitute the current value with the lagged value of net wealth, and the second where we remove the regressor from the analysis. In both cases, the results for the remaining explanatory variables are not affected by the change.

  11. To increase the number of observations, when the answer is missing we do as follows: for each households, we assign a value of zero in all the waves preceding the first 0 observed (i.e. we assume that the household did not know the answer in the preceding waves if she did not know the answer in the current wave), and a value of 1 to all the waves following the last 1 answered (i.e. we assume that the household learned the correct answer after she first answered it correctly).

  12. The percentage of total households’ liabilities on GDP in Italy has always been lower than the European mean. However, between 1995 and 2012 this indicator has more than doubled and, after a slowdown due to the effects of the financial crisis, has been recently recording high growth rates again. See e.g. Eurostat data available at https://ec.europa.eu/eurostat/databrowser/view/nasa_10_f_bs/default/table?lang=en.18.

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Authors and Affiliations

  1. Department of Economics and Management and Centro di Ricerca Interuniversitario sull’Economia Pubblica, University of Padua, 35123, Padua, Italy

    Elena Lagomarsino

  2. Department of Economics, Ca’ Foscari University of Venice, 30121, Venice, Italy

    Alessandro Spiganti

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  1. Elena Lagomarsino
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  2. Alessandro Spiganti
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Appendix

Appendix

See Tables 3, 4, 5, 6, 7, 8, 9 and 10.

Table 3 Stepwise adjustment of samples and average number of waves
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Table 4 Variables and definitions
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Table 5 Summary statistics for the entire sample
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Table 6 Summary statistics for constrained sample
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Table 7 Summary statistics for unconstrained sample
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Table 8 Summary statistics depending on portfolio choices
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Table 9 Secured and unsecured Debt versus the Arrow–Pratt measure, AMEs
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Table 10 Total Debt versus financial literacy, AMEs
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Lagomarsino, E., Spiganti, A. Risk Aversion and the Size of Desired Debt. Ital Econ J 9, 369–396 (2023). https://doi.org/10.1007/s40797-021-00172-1

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