ZAI 4 “Refugios de quirópteros”

single number. If there was perfect equality the coefficient would be 0, whereas a coefficient of 1 indicates total wealth inequality. See CSO (2015b) for further information on how to calculate the coefficient.

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Total net wealth

Total debt

Financial assets

Real assets

Figure 6.3: Net wealth, by component and age Mean, (in EUR Households)

Source: HFCS (2013). -200 -100 0 100 200 300 400 500 75+ 65-74 55-64 45-54 35-44 18-34 0 200000 400000 600000 800000 1000000 0 50,000 Source: HFCS (2013). 100,000 150,000 200,000

Figure 6.4: Net wealth and gross income correlation, by age cohort

Income, mean (in EUR Households)

Net assets, mean (in EUR Households)

18-34 35-44 45-54 55-75+

Table 6.1: Gini coefficients for net-wealth, by country

Gini coefficient net wealth

Percentage of households that are

home-owners Germany 0.78 0.45 Austria 0.77 0.47 France 0.68 0.55 Netherlands 0.69 0.57 Euro-Area 0.69 0.60 Luxembourg 0.69 0.66 Finland 0.70 0.67 Ireland 0.64 0.71 Italy 0.62 0.69 Belgium 0.62 0.70 Portugal 0.65 0.71 Cyprus 0.69 0.77 Greece 0.56 0.72 Malta 0.61 0.77 Spain 0.58 0.82 Slovenia 0.55 0.81 Slovakia 0.45 0.90

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than is income, we would nonetheless expect there to be a positive correlation with income; a higher income will allow households to accumulate assets and/or pay down debts at a faster rate than would be possible for lower income households. Figure 6.4 shows that the strength of this correlation varies by age cohort, being much stronger for younger households than for older households. In fact, we do not see any overlap in the different coloured indicators of the age cohorts. There also appears to be greater variation in the relationship between wealth and income for the oldest group in particular, where assets have had more time to build up and also where there may have been a reduction in current income (if mainly pension related) compared to earlier income.

Given the importance of the HMR to net wealth for Irish households discussed earlier, it is possible that these different correlations across age groups are driven primarily by the paying down of the HMR mortgage. However, Figure 6.5 shows that even when the HMR is excluded, there is still a positive correlation between gross income and other net assets and that this correlation varies across age cohorts.

7. Conclusions

The main objective of this paper is to introduce researchers and other interested parties to the potential usefulness of the data on wealth, debt and income in the HFCS. In presenting the data we have concentrated on what we believe to be the most pressing policy areas. We have also focused on those aspects of the survey where there is comparable data for other countries. We have shown how the aggregate data on debt and assets can disguise major differences in the distribution of these characteristics across households.

This initial overview of the survey has shown that the composition of household balance sheets in Ireland differs from the Euro area average in some important respects. The contribution of property to total asset holdings and the extent of indebtedness of the median household stand out as important features of Irish households, as does the variation across age groups in debt and wealth. These patterns and more detailed breakdowns of the data could be used to examine the impact of economic shocks on household behaviour, and in particular how macro-financial linkages affect real economic outcomes. One obvious place to start is in the analysis of household consumption behaviour. Current estimates of the marginal propensity to consume (MPC) out of income and wealth by Irish households, as presented in Clancy et al. (2014) for example, pay little attention to the distribution of wealth. However, models of consumption that rely on a buffer stock of savings, such as those in Carroll et al. (2014), show that differences in aggregate MPCs across countries and over time can be attributed in large part to differences in the wealth distribution, and furthermore that the liquidity of that wealth matters.

The HFCS is also a rich source of information for analysing issues around debt sustainability. As well as providing information on household assets and liabilities, the data could also be used to analyse the impact of changes in interest rates, house prices and other asset prices on various groups of consumers and to assess the risks arising from the high levels of indebtedness of some households.

0 200000 400000 600000 800000 0 50,000 100,000 150,000 200,000 Source: HFCS (2013).

Figure 6.5: Net non-HMR wealth and gross income

correlation, by age cohort Income, mean (in EUR Households)

18-34 35-44 45-54 55-75+

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