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On Italian Households’ Economic Inadequacy Using Quali-Quantitative Measures

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Abstract

Motivated by an interest in investigating factors associated with poverty risks in Italy, our study provides insight into the relationship between various socio-economic, demographic, and behavioural variables and a new measure of the economic inadequacy of households. We propose that a household is in a condition of economic inadequacy when it simultaneously has difficulty making ends meet and is in arrears with payments of commitments for more than 90 days. To analyse the determinants of economic inadequacy, we use cross-sectional microdata collected through a structured questionnaire from a 2012 survey of household income and wealth conducted by the Bank of Italy. The results of the analysis show that the probability of economic inadequacy for Italian households is higher when the household is located in regions in southern Italy, has a low equivalent income, registers a decrease in income compared with that of a normal year, has a low liquidity ratio, pays rent for the house of residence, is over-indebted, is indebted to friends and relatives, and has an unhappy and impatient household head. We also propose constructing a composite indicator at the regional level that combines the percentage of households in relative poverty, as measured by the Italian National Institute of Statistics, and the percentage of households that we identify as existing in a condition of economic inadequacy. The composite indicator allows us to take into account some aspects of household living conditions that are not included in the measure of relative poverty.

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Notes

  1. The poverty line is derived considering the distribution of income within the population (e.g., 60 % of the median income in Eurostat’s at-risk-of-poverty measure).

  2. This measure is given by the sum of bank deposits, postal deposits, government securities, bonds, equity in companies (traded or not traded on the stock market), investment trusts, and so forth, valued on the 31 December 2012.

  3. Following Rosenbaum and Rubin (1983), we employ the counterfactual framework to define the effect of the treatment (for example, household heads’ time preference) on the outcome variable (for example, economic difficulty). Each individual in the population has two potential values for the outcome: \({\texttt{economic}}\, {\texttt{difficulty} }_{{\texttt{time}}\, {\texttt{preference}}=1} \) and \({\texttt{economic}}\, {\texttt{difficulty} }_{{\texttt{time}} \, {\texttt{preference}}=0} \). Obviously, we are able to observe only one of these values for each individual; the other outcome is the counterfactual. The treatment effect is therefore defined as

    $${\mathbb{E}}({\texttt{economic}} \, {\texttt{difficulty}}_{{\texttt{time}} \, {\texttt{preference}}=1})-{\mathbb{E}} ({\texttt{economic}} \, {\texttt{difficulty}}_{{\texttt{time}}\, {\texttt{preference}}=0} ), $$

    where effect is for the entire population. However, we are interested in the effect calculated considering only individuals who received the treatment (in our case, an individual with a high time preference); hence, we are interested in the so-called ATT (Wooldridge 2010). Let \({\mathbb{E}} ({\texttt{economic}} \, {\texttt{difficulty}} _{{\texttt{time}} \, {\texttt{preference}}=1} |{\texttt{time}} \,{\texttt{preference}}=1)\) be the average outcome of individuals when they actually manifest a high time preference, and let \({\mathbb {E}}({\texttt{economic}} \,{\texttt{difficulty} }_{{\texttt{time}} \,{\texttt{preference}} =0} |{\texttt{time}} \,{\texttt{preference }}=1)\) be the average outcome of individuals with a high time preference who are assumed not to have a high time preference. Thus, the ATT is defined as

    $$\begin{aligned} {\text{ATT}} &= {\mathbb{E}} ({\texttt{economic}} \,{\texttt{difficulty}}_{{\texttt{time}}\,{\texttt{preference}}=1} |{\texttt{time}} \,{\texttt{preference }}=1)\\ &-{\mathbb{E}} ({\texttt{economic}}\, {\texttt{difficulty}}_{{\texttt{time}}\, {\texttt{preference}}=0} | {\texttt{time}}\, {\texttt{preference}}=1). \end{aligned}$$

    Since \({\texttt{economic}}\, {\texttt{difficulty} }_{{\texttt{time}}\,{\texttt{preference=}}0 }\) is not observed for individuals with a high time preference, the quantity \({\mathbb {E}}({\texttt{economic}} \, {\texttt{difficulty}}_{{\texttt{time}}\, {\texttt{preference}}=0} |{\texttt{time}} \,{\texttt{preference }}=1)\) must be estimated by using the proposed RBP model (4). For further methodological details, see also Radice et al. (2013) and Zanin (2014a, b).

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Acknowledgments

We would like to thank three anonymous reviewers for numerous suggestions that encouraged us to conduct further analyses and helped us improve the article’s presentation and quality. The opinions expressed herein are those of the author and do not reflect those of the institution of affiliation.

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  1. Prometeia, G. Marconi 43, 40122, Bologna, Italy

    Luca Zanin

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Appendix

Appendix

See Tables 4 and 5.

Table 4 Descriptive statistics reported in terms of the mean values of the binary variables
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Table 5 Parametric estimates of model (2)
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Zanin, L. On Italian Households’ Economic Inadequacy Using Quali-Quantitative Measures. Soc Indic Res 128, 59–88 (2016). https://doi.org/10.1007/s11205-015-1019-1

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