Are the in-work poor more disadvantaged in urban areas? An analysis of housing affordability in Italy

Abstract

In Europe, there is growing empirical evidence on the difficulties workers face in making ends meet. High housing costs may compound the picture. This study investigates the housing affordability problems of workers’ households. Drawing on 2019 EU-SILC cross-sectional data for Italy, it examines the extent to which working households’ income results in housing affordability problems, and the differences between cities and rural areas. It considers three groups: in-work poor, low-middle, and high-income households. Results confirm the relevance of the income level as in-work poor households face the lowest housing costs but the highest housing affordability problems. In terms of territorial differences, results show a widespread vulnerability of the in-work poor, especially for tenants: these households have considerable difficulties in coping with housing costs in both urban and rural areas, despite rents being higher in cities. In contrast, the place of living assumes more relevance for low-middle-income households: for them, renting in cities rather than in rural areas is substantially riskier.

Keywords:

• Housing affordability
• in-work poverty
• urban-rural divide
• Italy
• EU-SILC

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 In-work at-risk-of-poverty risk rate: persons aged 18–64 who are employed according to their most frequent activity status and are at risk of poverty. Income-based statistical indicators are labelled as ‘at-risk-of-poverty’ by Eurostat due to a lack of information on people’s effective living standards (Lohmann, 2018). This article uses the most common terminology in the literature and refers to ‘in-work poverty’ and ‘in-work poor’ (e.g. Lohmann & Marx, 2018). Source: Eurostat data https://ec.europa.eu/eurostat/web/products-datasets/product?code=tespm070

2 For example, according to the Eurostat definition of IWP, a person is considered in-work poor if she is more than 18 years old, has worked at least seven months in the previous year, and lives in a household with an equivalized income below 60% of the median income of the country (Source: EU Statistics on Income and Living Conditions, EU-SILC methodology – IWP. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=EU_statistics_on_income_and_living_conditions_(EU-SILC)_methodology_-_in-work_poverty).

3 Also, it is important to note that experiencing housing affordability problems might result from people’s deliberate choice to spend a considerable amount on housing.

4 Scholars have implemented different thresholds across the income distribution: e.g. a threshold of 40% for low-income households (Fahey et al., 2004); a threshold of 25% for low-income households in housing regimes with a consistent share of public housing (Dewilde, 2017). Eurostat instead implements a threshold of 40% for all. More generally, there is debate in the literature on how to measure housing affordability. Another approach to operationalize housing affordability is that of ‘residual income’. In this case, scholars deduct the housing costs from household income and investigate whether the remaining income is sufficient to meet the other everyday expenses. To do this, they either define a basket of goods and its costs or equivalize incomes and implement a relative poverty line. This measure considers the number of members and their ages, unlike the ratio approach. However, the difficulty lies in identifying a minimum standard of non-housing consumption (Fahey et al., 2004; Filandri, 2015).

5 The Covid-19 pandemic had major consequences on the labour market (e.g. loss or reduction of employment), but also on housing costs. It resulted in a general increase in utility costs, because people spent more time at home due to lockdowns, and higher risks of eviction, especially in large cities (Dreesen & Heylen, 2023). In EU-SILC, housing costs are measured in the current year; thus, the 2020 release is potentially subject to the effects of the pandemic.

6 In EU-SILC, components of housing costs are not available separately. Also, Eurostat’s definition of housing affordability problems excludes mortgage principal repayment. This aspect is further discussed in the section ‘Discussion and Conclusion’.

7 In line with Eurostat, household income is equivalized through the OECD modified scale, which confers a value of 1 to the first adult, 0.5 to additional adults, and 0.3 to children under 14 years old.

8 The original EU-SILC variable distinguishes among five categories: a) outright homeowners; b) homeowners with mortgages; and c) tenants i) at prevailing or market rates, ii) at a reduced rate, or iii) in free housing. The EU-SILC category ‘tenants at prevailing or market rates’ might include households in the private rental market who benefit from housing allowances. Also, in countries where the rental market is tightly restricted – and therefore, there is no de facto market rental– this category reflects all tenants (Hick et al., 2022). However, this is not much the case in Italy, where the rental market is unregulated, and housing allowances are minimal.

9 The choice of control variables was based on the literature (e.g. Filandri, 2015). The main models do not include control variables referring to dwelling characteristics since they are closely related to housing costs and, therefore, to the outcome of interest. Similarly, the household labour configuration (e.g. the number of workers) is related to households’ income. However, I ran robustness checks controlling for the number of rooms and household work intensity, and the results are consistent (see Supplementary Files Section II).

10 For more details: (King et al., 1994; Elwert & Winship, 2014).

11 The probability of facing housing affordability problems is missing for high-income homeowners (with and without mortgages) living in rural areas because there are no observations in the sample for this case.

Additional information

Notes on contributors

Claudia Colombarolli

Claudia Colombarolli is a research fellow in Economic Sociology and Labour Studies in the Department of Cultures, Politics and Society at the University of Turin. Her main research interests engage with social and territorial inequalities, focusing on the multidimensionality of poverty and labour market disadvantages. She mainly works with cross-sectional and longitudinal survey data.