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Poor and wealthy hand-to-mouth households in Belgium

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Abstract

We identify the population shares of poor hand-to-mouth households, wealthy hand-to-mouth households and non hand-to-mouth households in Belgium. We apply the methodology proposed by Kaplan & Violante (2014) and Kaplan et al., (2014) to the Belgian component of the Household Finance and Consumption Survey. We find that the fraction of hand-to-mouth households in Belgium is substantial and predominantly consists of wealthy hand-to-mouth households. We also compare the observable characteristics and marginal propensities to consume (MPCs) of the three household types. Belgian wealthy hand-to-mouth households have characteristics that resemble those of the non hand-to-mouth households, while their MPCs are often more similar to those of the poor hand-to-mouth households. This pleads for giving a unique place to each type of household when evaluating the effects of fiscal policy.

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Notes

  1. Jappelli & Pistaferri (2014) consider the Italian Survey of Household Income and Wealth (SHIW), while we make use of the Belgian component of the Household Finance and Consumption Survey (HFCS). Moreover, these authors do not specifically investigate differences in MPC between P-HtM, W-HtM and N-HtM households, which is a core focus of the current study.

  2. Two recent empirical studies that are closely related are Song (2019) and Du Caju et al., (2022). Song (2019) focuses on a similar research question by using South Korean data. A main methodological difference is that Song applies the structural approach of Blundell et al., (2008) to identify households’ MPCs (thus following Kaplan et al., 2014). As argued above, this empirical strategy is data-intensive, which restricts its applicability; we circumvent this in the current study by exploiting the specificity of the third (2017) HFCS wave. Similar to our study, Du Caju et al., (2022) also use the Belgian component of the HFCS. However, they specifically investigate the empirical relation between households’ indebtedness and their consumption, which is quite different from (and complementary to) our question of focus.

  3. A fourth wave of the HFCS was collected in 2020, but the data were not yet publicly available at the time of the current study. Moreover, we fear that the COVID pandemic that started in 2020 may have substantially impacted the patterns in these data, making it difficult to compare this fourth wave to the earlier waves.

  4. A more detailed description of the dataset cleaning procedure can be found at https://gregkaplan.me.

  5. We follow Kaplan & Violante (2014) by qualifying a hand-to-mouth household as “wealthy” as soon as it has any positive illiquid wealth. At this point, it is worth highlighting that these households are not necessarily rich.

  6. Properties stand for house, flat, apartment building, industrial building and warehouse, building plot, field, garden, woodland, farmland, garage, shop, office, hotel, and farm.

  7. Except for the regression results in Table 6 and Table 7, we have used population weights in our tables and figures. More precisely we use the variable HW0010 as household weight.

  8. The OECD modified equivalence scale attaches a value of 1 to the first adult in the household, a value of 0.5 to any other household member aged 14 or more and a value of 0.3 to household members aged 13 and below.

  9. More precisely, housing value is defined as the sum of the current price of the household main residence, other properties current value and additional properties current value at the time of the interview. The debt is defined as the sum of all mortgages with the home equity line of credit subtracted.

  10. Based on Lusardi et al., (2011), a household is considered financially fragile if it has liquid balances lower than the threshold of EUR 2000.

  11. Throughout this paper we present smoothed graphs. For smoothing the lpoly function of Stata was used that performs a kernel-weighted local polynomial regression.

  12. Other social transfer (HG0100): Did (you/your household) receive any government scholarships or income from public assistance or other welfare payments in (the last 12 months / the last calendar year)? Please do not include unemployment benefits, public pensions or special one-time payments.

  13. We assigned zeros to those who do not have any payment.

  14. The exact question is: Imagine you unexpectedly receive money from a lottery, equal to the amount of income your household receives in a month. What percent would you spend over the next 12 months on goods and services, as opposed to any amount you would save for later or use to repay loans?

  15. At this point, an important caveat is that this is not a ceteris paribus exercise. For example, the income of the youngest people is substantially below that of the prime age category.

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Author notes

  1. Maite De Sola Perea

    Present address: Department of History, Universiteit Antwerpen, Sint-Jacobsmarkt 13, B-2000, Antwerpen, Belgium

Authors and Affiliations

  1. Department of Economics, University of Leuven (KU Leuven), E. Sabbelaan 53, B-8500, Kortrijk, Belgium

    Laurens Cherchye

  2. ECARES, Université libre de Bruxelles. Avenue F. D. Roosevelt 50, CP 114, B-1050, Brussels, Belgium

    Thomas Demuynck & Mariia Kovaleva

  3. ECARES, Université Libre de Bruxelles and Department of Economics, University of Leuven (KU Leuven), Avenue F. D. Roosevelt 50, CP 114, B-1050, Brussels, Belgium

    Bram De Rock

  4. National Bank of Belgium, Bruxelles, Belgium

    Geoffrey Minne & Maite De Sola Perea

  5. Department of Economics, University of Leuven (KU Leuven), Naamsestraat 69, B-3000, Leuven, Belgium

    Frederic Vermeulen

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Cherchye, L., Demuynck, T., De Rock, B. et al. Poor and wealthy hand-to-mouth households in Belgium. Rev Econ Household (2023). https://doi.org/10.1007/s11150-023-09689-z

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