Why Do Europeans Save? Micro-Evidence from the Household
Finance and Consumption Survey

Charles Yuji Horioka
Center for Computational Social Science and Research Institute for Economics and Business
Administration, Kobe University; Asian Growth Research Institute; Institute of Social andEconomic Research, Osaka University; and National Bureau of Economic Research
Luigi Ventura
Department of Economics and Law, Sapienza, University of RomeWorking Paper Series Vol. 2024-17
August 2024

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Asian Growth Research InstituteWhy Do Europeans Save? Micro-Evidence from the Household Finance andConsumption Survey
Charles Yuji Horioka*
Center for Computational Social Science and Research Institute for Economics and Business
Administration, Kobe University; Asian Growth Research Institute; Institute of Social andEconomic Research, Osaka University; and National Bureau of Economic Research
Luigi Ventura
Department of Economics and Law, Sapienza, University of Rome
August 2024
Abstract
In this paper, we analyze the saving motives of European households using micro-data fromthe Household Finance and Consumption Survey (HFCS), which is conducted by the European
Central Bank. We find that the rank ordering of saving motives differs greatly depending on
what criterion is used to rank them. For example, we find that the precautionary motive is themost important saving motive of European households when the proportion of households
saving for each motive is used as the criterion to rank them but that the retirement motive isthe most important saving motive of European households if the quantitative importance ofeach motive is taken into account. Moreover, the generosity of social safety nets seems to affectthe importance of each saving motive, with saving for the retirement motive being lessimportant in countries with generous public pension benefits and saving for the precautionary
motive being less important in countries with generous health systems. These findings suggestthat the retirement motive and the precautionary motive are the dominant motives for saving
in Europe partly because social safety nets are not fully adequate. Our finding that saving
motives that are consistent with the selfish life-cycle model as well as saving motives that areconsistent with the altruism model are important in Europe implies that the two models coexist
in Europe, as is the case in other parts of the world. However, our finding that the retirement
motive, which is the saving motive that most exemplifies the selfish life-cycle model, is of
dominant importance in Europe strongly suggests that this model is far more applicable inEurope than is the altruism model. Moreover, our finding that the intergenerational transfers
motive, which is the saving motive that most exemplifies the altruism model, accounts for only
about one-quarter of total household wealth in Europe provides further corroboration for thisfinding.
Keywords: altruism model, bequests, European Central Bank, Household Finance andConsumption Survey, households, household saving, household wealth, inheritances, intervivos transfers, intergenerational transfers, precautionary saving, retirement, saving, saving
motives, selfish life-cycle model, wealth, wealth-to-income ratio
Journal of Economic Literature classification codes: D12, D14, D15, D64, E21, and J14*Address for correspondence: Charles Yuji Horioka, Research Institute for Economics andBusiness Administration, Kobe University, 2-1, Rokkodai-cho, Nada-ku, Kobe, Hyogo, 6578501, JAPAN. Email address: horioka@rieb.kobe-u.ac.jp

1. Introduction
One of the key variables in economics is saving, and what is important is not just the amountof saving households do but also why households save (i.e., the relative importance of thevarious motives for which households save). Nonetheless, although a voluminous amount ofwork has been done on the determinants of the amount of saving, relatively little work has been
done on why households save. This paper attempts to fill this gap in the literature by analyzing
the saving motives of European households using micro-data from the Household Finance andConsumption Survey (hereafter referred to as HFCS), a large-scale household survey that is
conducted periodically by the European Central Bank.
To summarize our main findings, we find that the rank ordering of saving motives differs
greatly depending on what criterion is used to rank them. For example, we find that the
precautionary motive is the most important saving motive of European households when the
proportion of households saving for each motive is used as the criterion to rank them but thatthe retirement motive is the most important saving motive of European households if thequantitative importance of each motive is taken into account. Moreover, the generosity of social
safety nets seems to affect the importance of each saving motive, with saving for the retirement
motive being less important in countries with generous public pension benefits and saving forthe precautionary motive being less important in countries with generous health systems. Thesefindings suggest that the retirement motive and the precautionary motive are the dominant
motives for saving in Europe partly because social safety nets are not fully adequate.
Our finding that saving motives that are consistent with the selfish life-cycle model as well assaving motives that are consistent with the altruism model are important in Europe implies thatthe two models coexist in Europe (i.e., that both types of households coexist and/or that bothmodels coexist within the same household in Europe), as is the case in other parts of the world(see section 2). However, our finding that the retirement motive, which is the saving motivethat most exemplifies the selfish life-cycle model, is of dominant importance in Europe
strongly suggests that this model is far more applicable in Europe than is the altruism model.
Moreover, our finding that the intergenerational transfers motive, which is the saving motivethat most exemplifies the altruism model, accounts for only about one-quarter of household
wealth in Europe provides further corroboration for this finding.
The remainder of this paper is organized as follows: In section 2, we discuss theoreticalconsiderations; in section 3, we survey the previous literature on saving motives; in section 4,
we discuss the estimation model used in the econometric analysis; in section 5, we discuss thedata source and sample selection; in section 6, we present descriptive statistics; in section 7,
we present the estimation results concerning the determinants of the household wealth-toincome ratio; in section 8, we present our estimates of the composition of household wealth bymotive; in section 9, we conduct a number of robustness checks; and in section 10, we present
a summary, conclusions, and policy implications.

2. Theoretical Considerations
The simplest version of the selfish life-cycle model with no borrowing constraints and no
uncertainty predicts that households should be saving primarily for living expenses during
1retirement and that they should not be saving to leave intergenerational transfers (i.e., bequests
and inter vivos transfers) to their children. By contrast, if the altruism model applies and parents
harbor intergenerational altruism towards their children, households should be saving not only
for living expenses during retirement but also to leave intergenerational transfers to theirchildren. Furthermore, if households face borrowing constraints, they should also be saving in
preparation for the purchase of large-ticket items such as housing and consumer durables(because they know that they will not be able to debt-finance such purchases). Finally, ifhouseholds face borrowing constraints as well as various sources of uncertainty, they should
also be saving for precautionary purposes because they know that they will not be able toborrow when unexpected contingencies arise. Indeed, there is a voluminous literature on
precautionary saving, with theoretical papers tending to find that precautionary saving shouldbe important but empirical papers tending to find that it is not very important quantitatively(see, for example, the excellent survey in Jappelli and Pistaferri, 2017). Thus, assessing therelative importance of the various motives for which households save will shed light on whichmodel of household behavior applies in the world and on which assumptions concerning the
behavior of households and the environment facing households apply in the real world.

3. Survey of the Previous Literature on Saving Motives
In this section, we survey previous studies that have attempted to assess the relative importanceof various motives for saving and consider whether the findings are consistent with the selfish
life-cycle model, the altruism model, or both (see Horioka, 2021, for a more detailed
discussion).
Horioka and Watanabe (1997) and Horioka, et al. (2000) conduct comprehensive analyses ofsaving motives in Japan and the United States using data from the Survey of the Financial Asset
Choice of Households and the U.S.-Japan Comparison Survey of Saving, respectively. Both ofthese surveys were conducted by the former Institute of Posts and Telecommunications Policyof the former Ministry of Posts and Telecommunications of the Japanese Government, andboth are unique in asking respondents to provide information on the amount of saving,dissaving, new borrowings, and loan repayments for each motive. Horioka and Watanabe(1997) and Horioka, et al. (2000) analyze these data and obtain broadly consistent results forboth Japan and the United States. For example, Horioka and Watanabe (1997) find that theretirement motive ranks second (behind the precautionary motive) at 55.4% if the proportionof households saving for each motive is used as the criterion to rank them and ranks first (at62.5%) if the share of saving for each motive in total (net) household saving is used as thecriterion to rank them. Since the retirement motive is the saving motive that most exemplifies
the selfish life-cycle model, these findings strongly suggest that the selfish life-cycle model ishighly applicable in both Japan and the United States.
The saving motive that most exemplifies the altruism model is the bequest motive, and looking
at the results for this motive, Horioka and Watanabe (1997) find that, in Japan, the bequest
motive ranks 10th out of 12 (at 2.3%) if the proportion of households saving for each motive isused as the criterion to rank them and ranks 5th (at 3.2%) if the share of saving for each motivein (net) household saving is used as the criterion to rank them.

2

These results suggest that the selfish life-cycle model is much more applicable than the altruism
model in both Japan and the United States. It should be noted that saving for one children’s
education and marriage expenses involve intergenerational transfers from parents to children
so that they should be regarded as being consistent with the altruism model, but even if they
are taken into account, the life-cycle model remains far more applicable than the altruism modelin both countries (see Horioka, et al., 2000)
The literature on the importance of different saving motives is surveyed in detail in Horioka(2021), and as discussed by Horioka (2021), Gourinchas and Parker (2002), Schunk (2009),
Birkeland (2013), and Chao et al. (2011) analyze saving motives in the United States, Germany,
the Netherland, and China, respectively, and Yao et al. (2011) conduct a U.S.-China
comparison of saving motives.
In addition, some authors have analyzed saving for specific motives. For example, Ginama(1988) and Ogawa (1991) analyze precautionary saving, Horioka (1985) analyzes saving for
one’s children’s educational expenses, Horioka (1987) and Grossbard (2015) analyze savingfor one’s children’s marriage expenses, Horioka (1988) analyzes saving for housing purchase,and Horioka and Okui (1999) analyze saving for retirement.
The findings of previous studies generally support the selfish life-cycle model because theyshow that saving for motives that are consistent with the selfish life-cycle model such as theretirement motive are much more important than saving for motives that are consistent withthe altruism model such as the bequest motive in Japan as well as in other countries. However,previous studies also indicate that there are substantial differences among countries in therelatively importance of various saving motives, with motives relating to the selfish life-cycle
model being relatively more important in Japan (and perhaps also in China and theNetherlands) than they are in the United States and Germany (see Horioka, 2021, for moredetails).
The current paper is closest in spirit to Horioka and Watanabe (1997) and Horioka, et al. (2000),
but it makes an original contribution by analyzing saving motives in the major European
countries and comparing the results to those for other countries. Moreover, the current paper
makes a further contribution by analyzing the determinants of saving for individual motives
with emphasis on the impact of the generosity of social safety nets such as public pension andhealth systems. Finally, the current paper makes yet another contribution by analyzing the shareof saving for individual motives in a stock measure of saving as well as in a flow measure ofsaving.

4. Estimation ModelIn this section, we explain the estimation model we use to estimate the quantitative importanceof individual motives for saving.
Following Guiso et al. (1992), Carroll and Samwick (1995), Kazarosian (1997) and others, ourdependent variable is the natural logarithm of the wealth-to-income ratio, defined as the ratioof household net worth to annual household income, where household net worth is defined as
the sum of financial and non-financial assets minus liabilities.
3

The key explanatory variables we use are dummy variables for each of 11 saving motives: thehousing purchase motive (the wording in the survey is “to buy a home”), the other majorpurchase motive, the business motive (“to start a business”), the financial asset motive, theprecautionary motive (“for unexpected events”), the retirement motive (“for old age needs”),
the debt repayment motive, the travel/holidays motive, the inter vivos transfers motive (“tosupport children and grandchildren”), the bequest motive, and the government subsidy motive(“to profit from government subsidies”). Since the dependent variable is in log form, thecoefficient of the dummy variable for a given saving motive indicates the percentage amountby which the wealth-to-income ratio of a household saving for that motive exceeds the wealthto-income ratio of an otherwise identical household not saving for that motive.
Finally, we include a number of variables such as age, age squared, dummy variables pertaining
to educational attainment, a dummy variable for being male, household size, dummy variables
pertaining to marital status, and a dummy variable for homeownership as control variables andcountry dummies to control for unobserved heterogeneity.

5. The Data Source and Sample Selection
In this paper, we use micro-data from the Household Finance and Consumption Survey(hereafter referred to as HFCS), which is conducted by the European Central Bank. The HFCS
collects detailed information on the assets, liabilities, income, consumption, and saving
motives of households, and hence it is ideally suited to an analysis of household saving motives.
The survey is based on 84,000 interviews conducted in 18 euro area countries, as well as Poland
and Hungary. The first (2010) wave of the survey was conducted in 2010-11, the second (2014)
wave in 2013-15, the third (2017) wave in 2017, and the fourth (2021) wave in 2020-22. Moredetailed
informationon
thissurvey
can
be
found
at
https://www.ecb.europa.eu/stats/ecb_surveys/hfcs/html/index.en.html
We use the data from the third (2017) wave of the survey for our analysis. The 19 countries
included in our estimation sample were Austria, Belgium, Croatia, Cyprus, Estonia, Finland,
Germany, Greece, France, Hungary, Italy, Latvia, Lithuania, Luxembourg, Netherlands,
Poland, Portugal, Slovakia, and Slovenia (Austria is the reference country).
Turning to sample selection, we dropped all observations with missing values for any of thevariables used in our analysis. In addition, we dropped all observations for respondents who
did not circle any saving motives because it is implausible that they are not saving for any
motive even though they have positive wealth. Furthermore, we also dropped all observations
for responses who circled more than 6 saving motives because there are substantial differencesamong countries in the average number of saving motives circled, ranging from 1.59 in Finland
to 4.02 in Lithuania, and in the maximum number of saving motives circled, ranging from 3 inItaly to 12 in Hungary, Lithuania, and Slovenia.
In addition, we dropped all observations for which the wealth-to-income ratio is more than 100
because these are primarily respondents with very low incomes, which causes their wealth-toincome ratios to be unusually high.
Overall, our regression sample includes about 36,000 observations.

46. Descriptive Statistics
Tables 1-3 show the descriptive statistics for the variables used in the econometric analysis forthe full sample, the under-60 sample, and the 60-or-older sample, respectively. Looking firstat the results for saving motives for the full sample, if saving motives are ranked by the
proportion of respondents saving for each motive, the precautionary motive is by far the top
saving motive, with 63.1% of respondents saving for this motive. The retirement motive ranks
second, with 43.9% of respondents saving for this motive, followed by the inter vivos transfers
motive in third place (25.1%), the travel/holidays motive (25.0%) in fourth place, the majorpurchases motive in fifth place (17.8%), and the bequest motive in sixth place (10.7%).
Looking next at the results for the under-60 and 60-or-older samples, they are broadly similar
to those for the full sample, but with significant differences that reflect differences in life stage.
For example, the inter vivos transfers motive, the travel/holidays motive, the major purchases
motive, and the housing purchase motive are more important for younger respondents, whereas
the retirement and bequest motives are more important for older respondents. For example, theproportion of respondents saving for the retirement motive is only 36.6% in the under-60
sample but a full 53.3% in the 60-or-older sample, which is not surprising because one would
expect respondents to become more and more concerned about life after retirement as they age(this finding is consistent with the findings of Horioka and Watanabe, 1997, and Gourinchas
and Parker, 2002). Also, the proportion of respondents saving for the inter vivos transfers
motive declines with age, whereas the proportion of respondents saving for the bequest motive
increases with age, which is not surprising because one would expect the form of transfers fromparents to children to shift from inter vivos transfers to bequests as the respondent ages.
The detailed results are not shown due to space limitations, but we calculated a correlation
matrix among saving motives and found that correlations among saving motives were
surprisingly low. Thus, multicollinearity among the saving motive dummies is presumably not
a problem, implying that we can measure the contribution of each motive to wealthaccumulation with some precision.
If we look at the results for individual countries (not shown), the precautionary motive is the
top saving motive in virtually all countries in the sample. The ranking of the other saving
motives differs greatly from country to country, but in most countries, the next three mostimportant saving motives are the retirement motive, the inter vivos transfers motive, and thetravel/holidays motive, although the rank order of these motives differs greatly from country
to country.
However, just because the proportion of households who are saving for a given motive is large
does not necessarily mean that this motive is important quantitatively. It all depends on whether
the amounts of saving being done for that motive are large or small. It is to this issue that weturn in our econometric analysis.
Finally, the mean of the wealth-to-income ratio is 6.84, which indicates that the average
respondent’s wealth (net worth) is almost seven times his or her annual income.

5

7. Estimation Results concerning the Determinants of the Wealth-to-Income Ratio
The estimation results concerning the determinants of the wealth-to-income ratio for the fullsample, the under-60 sample, and the 60-or-older sample are shown in Tables 4-6, respectively.
Looking first at the results for the full sample in Table 4, all of the coefficients of the saving
motive dummies, except for those relating to the other major purchases, precautionary, andtravel/holidays motives are positive and statistically significant. The business motive dummy
has the largest coefficient (0.515), which implies that, ceteris paribus, those saving to start abusiness have wealth-to-income ratios that are a full 51.5% higher than the wealth-to-income
ratios of those who are not saving for this motive. This result is not surprising because startinga business typically requires a considerable investment. Moreover, the dummies of theretirement, financial asset, and housing purchase motives have the next largest coefficients(0.200, 0.196, and 0.195, respectively), which implies that, ceteris paribus, those who aresaving for these motives have wealth-to-income ratios that are a full 20.0%, 19.6%, and 19.5%
higher, respectively, than the wealth-to-income ratios of those who are not saving for thesemotives. Moreover, the dummy for the bequest and inter vivos transfers motives also haverelatively large coefficients (0.179 and 0.098, respectively), which implies that, ceteris paribus,
those who are saving for these motives have wealth-to-income ratios that are 17.9% and 9.8%
higher, respectively, than the wealth-to-income ratios of those who are not saving for thesemotives.
Looking next at the estimation results for the under-60 sample in Table 5 and those for the 60or-older sample in Table 6, they are broadly consistent with one another as well as with theresults for the full sample in Table 4 with respect to significance levels, magnitudes, and rankorder, but the magnitudes of the coefficients of the dummies for all of the major saving motives
are higher for the under-60 sample than they are for the 60-or-older sample.
These results contrast sharply with the results in the previous section pertaining to the
proportion of respondents saving for each motive. For example, the precautionary, inter vivos
transfers, travel/holidays, and other major purchase motives rank relatively high when the
motives are ranked by the proportion of respondents saving for each motive but not when the
motives are ranked by the quantitative importance of each motive because the proportion of
respondents saving for these motives is relatively large whereas the amounts involved are
relatively small. Conversely, the business, financial asset, and bequest motives rank relatively
high when the motives are ranked by the quantitative importance of each motive but not whenthe motives are ranked by the proportion of respondents saving for each motive because theproportions of respondents saving for theses motives are relatively small whereas the amounts
involved are relatively large. Finally, the retirement motive ranks high regardless of whichcriterion is used to rank the motives because the proportion of respondents saving for thismotive as well as the amounts involved are relatively large.
Turning to the estimation results for the other explanatory (control) variables, the coefficientsof age and age-squared are positive and negative, respectively, and statistically significant in
the full and 60-or-older samples, implying that the impact of age on the wealth-to-income ratio
has an inverted U-shape, as expected. As for the impact of educational attainment, the wealthto-income ratio tends to monotonically increase with educational attainment in all samples.
Moreover, the coefficient of the male dummy is positive and statistically significant in the fullsample and the 60-or-older sample, suggesting that male-headed households save more, ceterisparibus, than female-headed households. Household size and homeownership have a negativeand positive impact, respectively, on the wealth-to-income ratio, while marital status hardly
ever has a significant impact on the wealth-to-income ratio. Finally, the coefficients of the6country dummies (not reported in the tables) are all statistically significant, pointing to a large
degree of heterogeneity across countries.
Overall, the estimation results are highly satisfactory, with the majority of the explanatory
variables having coefficients that are statistically significant with the expected signs.

8. The Composition of Household Wealth by Saving Motive
In this section, we present estimates of the share of household wealth for each saving motive
in total household wealth, which is the most comprehensive measure of the importance of eachsaving motive. This measure can be calculated as the proportion of households saving for eachmotive, taken from Tables 1-3, multiplied by the share of wealth for each motive in total wealthfor households saving for that motive, and normalized so that the shares for all motives sum to100. The latter can be proxied for by the coefficient of the dummy variable for each motive inthe wealth-to-income ratio regressions in Tables 4-6 because this coefficient can be interpreted
as the percentage change in the wealth-to-income ratio that is attributable to that motive.
The results are shown in Tables 7-9 for the full sample, the under-60 sample, and the 60-orolder sample, respectively. Looking first at the results for the full sample in Table 7, theretirement motive is by far the most important motive for saving with a share of more than
one-half (53.8%). The inter vivos transfers motive ranks second, with a share of 15.1%,
followed by the housing purchase motive in third place (12.4%), the bequest motive in fourth
place (11.7%), and the precautionary motive in fifth place (9.3%). All other motives are farless important with a share of less than 5% or less.
Looking next at the results broken down by age in Tables 8 and 9, the retirement motive is themost important motive for saving in both the under-60 and 60-or-older samples, but its shareis higher in the 60-or-older sample than in the under-60 sample (61.1% vs. 48.2%). The shareof the bequest motive is also larger in the 60-or-older sample than in the under-60 sample(16.5% vs. 8.0%, respectively). By contrast, the share of the inter vivos transfers motive islarger in the under-60 sample than in the 60-or-older sample (19.7% vs.10.5%). The reversal
in the ordering of the inter vivos transfers motive and the bequest motive in the two samples is
not surprising given that bequests are, by definition, left later in life than inter vivos transfers,
and the increase in the importance of the retirement motive with age is also as expected.
Since the selfish life-cycle model assumes that the primary motive for saving is for retirement,
our finding that the share of saving for the retirement motive accounts for more than half oftotal saving in the full sample implies that the selfish life-cycle model is highly applicable inthe case of Europe.
Conversely, since it is primarily the saving motives relating to intergenerational transfers (theinter vivos transfers motive and the bequest motive) that are consistent with the altruism model,
our finding that the combined share of saving for these motives accounts for just over onequarter (26.8%) of total saving in the full sample implies that the altruism model is applicable
to some extent but not of dominant importance in the case of Europe. Moreover, it is possiblethat a part of these intergenerational transfers is motivated by selfish or strategic considerations
à la Bernheim, Shleifer, and Summers (1985) (for example, by a desire to induce one’s children
to provide care and attention during old age) and that the share of saving that is consistent withthe altruism model is even lower than suggested by the aforementioned figure. Thus, although7the selfish life-cycle model and the altruism model appear to coexist in the case of Europe, theselfish life-cycle model seems to be far more applicable than the altruism model.1

9. Robustness Checks
In this section, we discuss a number of robustness checks that we conducted.

9.1. Results based on Subsamples of Respondents
In this subsection, we report the results of analyses of the determinants of the wealth-to-income
ratio for various subsamples in order to try to shed light on what determines how importanteach saving motive is.
The Eurostat data base includes data on aggregate pension replacement ratios for all European
countries (see https://ec.europa.eu/eurostat/databrowser/view/ILC_PNP3/default/table?lang=en ), and as these data show, pension replacement rates were above the median in Austria,
Cyprus, Finland, France, Hungary, Italy, Luxembourg, Netherlands, Portugal, and Slovakia.
Table 10 shows the descriptive statistics for respondents from countries with relatively
generous public pension benefits, and as can be seen from this table, the proportion of
respondents saving for the retirement motive is 42.6%, which is slightly lower than it is for thefull sample (43.9%). This is as expected because those who expect to receive more generous
public pension benefits should be less likely to be saving for the retirement motive. Moreover,the proportions of those saving for the other 10 motives are also very similar in the full sample
and the sample of respondents from countries with relatively generous pension benefits.
Table 11 shows the estimation results concerning the determinants of the wealth-to-income
ratio for the sample of respondents from countries with relatively generous public pension
benefits, and as this table shows, the coefficient of the dummy for the retirement motive forthis sample is 0.149, which is more than 25% less than the corresponding figure for the fullsample (0.200). This result is as expected because those from countries with relatively generous
public pension benefits should be saving less for the retirement motive than those from othercountries. However, the coefficients of the dummies for the other saving motives are roughly
comparable in the full sample and the sample of respondents from countries with relatively
generous public pension benefits.
Table 12 shows the composition of household wealth by saving motive for the sample ofrespondents from countries with relatively generous public pension benefits, and as can be seenfrom this table, the share of the retirement motive is 43.2%, which is almost 20% less than thecorresponding figure for the full sample (53.7%). Thus, for respondents from countries withrelatively generous public pension benefits, the proportion of respondents saving for theretirement motive is only slightly less than that for the full sample, but the quantitative
Saving for one children’s education expenses and marriage expenses also involve intergenerationaltransfers, and they were found to be of some importance in Japan and (to a lesser extent) the UnitedStates (see Horioka and Watanabe, 1997, and Horioka, et al., 2000), but the survey we use for thecurrent paper does not ask explicitly about saving for these motives and it is presumably included insaving for the inter vivos transfers motive.
1

8

importance of the retirement motive is far less than for the full sample, as a result of which theshare of saving for the retirement motive in household wealth is much smaller than in the fullsample. This finding is as expected since saving for the retirement motive should be lessimportant in countries with more generous public pension benefits and conversely.
The detailed results will not be discussed due to space limitations, but we conducted a parallel
analysis for countries with generous health systems (defined as countries whose public
spending for inpatient and outpatient medical care as a percentage of total health spending ishigher than the median) and obtained similar findings. In particular, we found that, for
respondents from countries with relatively generous health systems, the proportion of
respondents saving for the precautionary motive is somewhat less than that for the full sample
and that the quantitative importance of the precautionary motive is far less than for the fullsample, as a result of which the share of saving for the precautionary motive in household
wealth is much smaller than in the full sample. This finding is as expected since saving for the
precautionary motive should be less important in countries with more generous health systems
and conversely.
9.2. Results based on the Accumulation Rate of Net Financial Wealth
Whereas in our benchmark econometric analysis in section 7, we analyzed the determinants of
the wealth-to-income ratio, which is a stock measure, in this subsection, we conduct an
econometric analysis of the determinants of the accumulation rate of net financial wealth (thechange in net financial wealth divided by initial net financial wealth, which is a flow measure)during the three-year period between the second (2014) wave and the third (2017) wave2. Notethat net financial wealth is defined as holdings of financial assets minus liabilities and that thechange in net financial wealth includes out-of-pocket saving as well as changes in asset values(i.e., capital gains and losses) because of the way it was calculated. When calculating thechange in net financial wealth, we convert nominal figures to real terms using the consumer
price index. We include the same explanatory variables we included in our econometricanalysis of the determinants of the wealth-to-income ratio.
The estimation results are shown in Table 13, and focusing first on the coefficients of the saving
motive dummies, which can be interpreted as the amount by which the accumulation rate of
net financial wealth of those saving for a given motive exceeds that of those not saving for that
motive, the dummy for the housing purchase motive has the largest coefficient, following by
the coefficients of the dummies for the travel/holidays motive, the inter vivos transfers motive,
the retirement motive, the government subsidy motive, and the precautionary motive. The
bequest motive dummy has a negative coefficient, but this could be due to the fact that bequests
tend to be left in the form of housing, which is excluded from the dependent variable that we
use in this section.3

2

Although the actual time between two consecutive interviews was variable across households in
different countries, we converted the accumulation rate of net financial wealth for each household to athree-year rate to achieve comparability.
3
We were not able to include the change in the value of housing wealth partly because we were notable to estimate the change in the price of housing across countries.
9

Recall from our discussion in section 7 that the results of the econometric analysis of thedeterminants of the wealth-to-income ratio, in which the coefficients of the saving motive
dummies can be interpreted as measures of the quantitative importance of the amount of wealthfor each saving motive, showed that the dummy for the business motive had the largest
coefficient, followed by the coefficients of the dummies for the business motive, the financial
assets motive, the housing purchase motive, the bequest motive, the government subsidy
motive, and the inter vivos transfers motive (see Table 4).
The results in Table 4 pertain to the stock of wealth for each motive whereas the results inTable 13 pertain to the accumulation rate of net financial wealth for each motive, and thus it is
not surprising that the ranking of saving motives varies greatly between the two tables, withsaving motives with longer time horizons such as the retirement motive and the bequest motive
being more important when it comes to the stock of wealth and saving motives with shortertime horizons such as the housing purchase motive and the travel/holidays motive being more
important when it comes to a flow measure of wealth accumulation.
Two other things to note are that the wealth accumulation regressions reinforce our earlier
findings that the retirement motive and the inter vivos motive are important and show that the
precautionary motive has a statistically significant impact even though it was not significant in
the wealth-to-income ratio regressions.
As for the impact of other explanatory (control) variables, only the coefficients of the variables
pertaining to educational attainment and marital status are statistically significant, with single
respondents and married respondents showing a higher accumulation rate of net financial
wealth than that of other respondents.

10. Summary, Conclusions, and Policy Implications
In this paper, we analyzed the saving motives of European households using micro-data fromthe Household Finance and Consumption Survey (HFCS), a large-scale household survey thatis conducted periodically by the European Central Bank.
To summarize our main findings, we found that the rank ordering of saving motives differs
greatly depending on what criterion is used to rank them. For example, we found that the
precautionary motive is the most important saving motive of European households when the
proportion of households saving for each motive is used as the criterion to rank them but thatthe retirement motive is the most important saving motive of European households if thequantitative importance of each motive is taken into account. Moreover, the generosity of social
safety nets seems to affect the importance of each saving motive, with saving for the retirement
motive being less important in countries with generous public pension benefits and saving forthe precautionary motive being less important in countries with generous health systems. Thesefindings suggest that the retirement motive and the precautionary motives are the dominant
motives for saving in Europe partly because social safety nets are not fully adequate.
Our finding that saving motives that are consistent with the selfish life-cycle model as well assaving motives that are consistent with the altruism model are important in Europe implies thatthe two models coexist in Europe (i.e., that both types of households coexist and/or that bothmodels coexist within the same household in Europe), as is the case in other parts of the world10(see section 3). However, our finding that the retirement motive, which is the saving motivethat most exemplifies the selfish life-cycle model, is of dominant importance in Europe
strongly suggests that this model is far more applicable in Europe than is the altruism model.
Moreover, our finding that the intergenerational transfers motive, which is the saving motivethat most exemplifies the altruism model, accounts for only about one-quarter of total
household wealth in Europe provides further corroboration for this finding.
Turning to the policy implications of our findings, our finding that the retirement motive is so
important in Europe and our finding that the generosity of public pension benefits affects theamount of saving for the retirement motive suggests that it may be desirable to improve public
pension benefits for the elderly (and also other social safety nets for the elderly such as publichealth insurance and public long-term care insurance) in countries where they are inadequate.
Similarly, our finding that the precautionary motive is so important in Europe and our findingthat the generosity of the health system affects the importance of precautionary saving suggeststhat it may be desirable to improve health systems in countries where they are inadequate.
Second, our finding that the bequest and inter vivos transfers motives are of some importancein Europe suggests that wealth disparities are, to some extent, passed on from generation to
generation via bequests and inter vivos transfers and that it might be desirable for governments
to introduce and/or to raise estate, gift, and/or wealth taxes as a way of alleviating this tendency.

Acknowledgements
We are grateful to Stephen Jenkins, Yoko Niimi, and participants of the General Conferenceof the International Association for Research in Income and Wealth (IARIW) and the Lecture
at the Institute of Economics, Academia Sinica, Taipei, Taiwan, for their valuable comments
and discussions. This work was supported by JSPS (Japan Society for the Promotion of
Science) KAKENHI Grant Numbers 15H01950, 18H00870, 20H01513, 20H05633, and
23H00831 to Horioka.

11

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13

Table 1: Descriptive Statistics (Full Sample)
Variable
Mean
Std. Dev. Median Minimum Maximum
Wealth/Income
6.843
8.368
4.441
0
74.976Log(Wealth/Income)
1.171
1.524
1.491
-10.643
4.317
Age
56.30115.85357
1685
Age^2/100
34.21117.850
32.49
2.56
72.25
Primary education
0.147
0.354
0
0
1
Lower secondary education
0.134
0.340
0
0
1
Upper secondary education
0.363
0.481
0
0
1
First-stage tertiary education
0.167
0.373
0
0
1
Second-stage tertiary education
0.169
0.375
0
0
1
Doctoral education
0.019
0.135
0
0
1
Male
0.632
0.482
1
0
1
Single
0.190
0.392
0
0
1
Married
0.585
0.493
1
0
1
Widowed
0.120
0.324
0
0
1
Household size
2.397
1.236
2
1
14
Homeownership
0.762
0.426
1
0
1
Saving for housing purchase
0.104
0.306
0
0
1
Saving for other major purchases
0.178
0.383
0
0
1
Saving to start a business
0.017
0.129
0
0
1
Saving to buy financial assets
0.036
0.187
0
0
1
Saving for precautionary purposes
0.631
0.483
1
0
1
Saving for repaying debts
0.079
0.270
0
0
1
Saving for retirement
0.439
0.496
0
0
1
Saving for travel/holidays
0.250
0.433
0
0
1
Saving for inter vivos transfers
0.251
0.434
0
0
1
Saving for bequests
0.107
0.309
0
0
1
Saving to profit from government
subsidies
0.020
0.138
0
0
1
Source: Authors' calculations based on data from the Household Finance and Consumption
Survey (HFCS), which is conducted by the European Central Bank.

14

Table 2: Descriptive Statistics (Under-60 Sample)
Variable
Mean
Std. Dev. Median Minimum
Maximum
Wealth/Income
5.283
7.354
3.217
0
74.368Log(Wealth/Income)
0.862
1.528
1.168
-10.6434.309
Age
44.827
9.836
46
16
59
Age^2/100
21.062
8.413
21.16
2.56
34.81
Primary education
0.064
0.244
0
0
1
Lower secondary education
0.113
0.317
0
0
1
Upper secondary education
0.406
0.491
0
0
1
First-stage tertiary education
0.195
0.396
0
0
1
Second-stage tertiary education
0.204
0.403
0
0
1
Doctoral education
0.018
0.132
0
0
1
Male
0.642
0.480
1
0
1
Single
0.271
0.445
0
0
1
Married
0.580
0.494
1
0
1
Widowed
0.036
0.186
0
0
1
Household size
2.810
1.332
3
1
14
Homeownership
0.722
0.448
1
0
1
Saving for housing purchase
0.151
0.358
0
0
1
Saving for other major purchases
0.223
0.417
0
0
1
Saving to start a business
0.024
0.154
0
0
1
Saving to buy financial assets
0.046
0.210
0
0
1
Saving for precautionary purposes
0.626
0.484
1
0
1
Saving for repaying debts
0.107
0.309
0
0
1
Saving for retirement
0.366
0.482
0
0
1
Saving for travel/holidays
0.301
0.458
0
0
1
Saving for inter vivos transfers
0.293
0.455
0
0
1
Saving for bequests
0.069
0.254
0
0
1
Saving to profit from government
subsidies
0.026
0.158
0
0
1
Source: Authors' calculations based on data from the Household Finance and Consumption Survey(HFCS), which is conducted by the European Central Bank.

15

Table 3: Descriptive Statistics (60 or Older Sample)
Variable
Mean
Std. Dev. Median Minimum

Maximum

Wealth/Income

8.869

9.136

6.496

0

74.976Log(Wealth/Income)
Age

1.572
71.205

1.422
7.676

1.871
70

-9.278
60

4.317
85

Age^2/100

51.291

11.146

49.00

36.00

72.25

Primary education

0.256

0.436

0

0

1

Lower secondary education
Upper secondary education

0.160
0.308

0.367
0.462

0
0

0
0

1
1

First-stage tertiary education

0.131

0.338

0

0

1

Second-stage tertiary education

0.124

0.330

0

0

1

Doctoral education

0.020

0.139

0

0

1

Male

0.620

0.485

1

0

1

Single

0.084

0.277

0

0

1

MarriedWidowed

0.592
0.228

0.492
0.420

1
0

0
0

1
1

Household size

1.862

0.838

2

1

11

Homeownership

0.813

0.390

1

0

1

Saving for housing purchase

0.044

0.205

0

0

1

Saving for other major purchases

0.120

0.325

0

0

1

Saving to start a business

0.007

0.083

0

0

1

Saving to buy financial assets

0.023

0.149

0

0

1

Saving for precauitionary purposes
Saving for repaying debts

0.638
0.044

0.481
0.204

1
0

0
0

1
1

Saving for retirement

0.533

0.499

1

0

1

Saving for travel/holidays

0.185

0.389

0

0

1

Saving for inter vivos transfers
0.197
0.398
0
0
1
Saving for bequests
0.156
0.363
0
0
1
Saving to profit from government
subsidies
0.011
0.106
0
0
1
Source: Authors' calculations based on data from the Household Finance and Consumption Survey(HFCS), which is conducted by the European Central Bank.

16

Table 4: The Determinants of the Wealth-to-Income Ratio (Full Sample)
Log(Wealth/Income)
Coeff. Std. Error t-value
p-value
Age

0.028

0.006

5.02

0.000 ***

Age^2/100
Primary education-0.013-2.913

0.004
0.142

-3.10
-20.520.006 ***
0.000 ***

Lower secondary education-2.8000.162-17.230.000 ***

Upper secondary education
First-stage tertiary education-2.660-2.502

0.129
0.099

-20.60-25.180.000 ***
0.000 ***

Second-stage tertiary education-2.5250.113-22.390.000 ***

Doctoral education-2.4170.109-22.080.000 ***

Male
Single

0.037
0.227

0.006
0.147

5.96
1.55

0.000 ***
0.139

Married

0.196

0.162

1.21

0.243

WidowedHousehold size

0.204
-0.104

0.128
0.021

1.60
-4.97

0.127
0.000 ***

Homeownership

2.213

0.214

10.34

0.000 ***

Saving for housing purchase

0.195

0.052

3.75

0.001 ***

Saving for other major purchases

0.007

0.024

0.30

0.767

Saving to start a business

0.515

0.102

5.05

0.000 ***

Saving for buying financial assets

0.196

0.030

6.58

0.000 ***

Saving for precautionary purposes

0.024

0.018

1.29

0.214

Saving for repaying debts-0.2980.025-11.980.000 ***

Saving for retirement

0.200

0.060

3.31

0.004 ***

Saving for travel/holidays-0.002

0.063

-0.03

0.979

Saving for inter vivos transfers
Saving for bequests
Saving to benefit from government
subsidies
Constant

0.098
0.179

0.039
0.021

2.48
8.48

0.023 **
0.000 ***

0.156

0.048

3.22

0.771

4.28

Mean of dependent variable

0.180
1.171

0.005 ***
0.000 ***

R-squared
Number of observations

0.515
35889

Notes: *Significant at 10% level, **significant at 5% level, ***significant at 1% level.
Source: Authors' calculations based on data from the Household Finance andConsumption Survey (HFCS), which is conducted by the European Central Bank.

17

Table 5: The Determinants of the Wealth-to-Income Ratio (Under-60 Sample)
Log(Wealth/Income)

Coeff.

Std. Error

t-valuep-value

Age

0.018

0.017

1.05

0.310

Age^2/100
Primary education

0.001-3.858

0.019
0.261

0.04
-14.760.971
0.000 ***

Lower secondary education-3.5760.238-15.040.000 ***

Upper secondary education
First-stage tertiary education-3.440-3.225

0.238
0.195

-14.46-16.510.000 ***
0.000 ***

Second-stage tertiary education-3.2550.194-16.770.000 ***

Doctoral educationMale-3.250
0.012

0.227
0.022

-14.290.57

0.000 ***
0.577

Single

0.241

0.150

1.60

0.126

MarriedWidowed

0.166
0.239

0.182
0.139

0.91
1.71

0.374
0.104

Household size

-0.058

0.033

-1.77

0.094 *

Homeownership
Saving for housing purchase

2.004
0.193

0.231
0.033

8.68
5.88

0.000 ***
0.000 ***

Saving for other major purchases-0.002

0.022

-0.10

0.920

Saving to start a business
Saving for buying financial assets

0.561
0.242

0.111
0.034

5.05
7.12

0.000 ***
0.000 ***

Saving for precautionary purposes

0.022

0.034

0.64

0.530

Saving for repaying debts
Saving for retirement-0.288
0.217

0.048
0.046

-6.05
4.76

0.000 ***
0.000 ***

Saving for travel/holidays-0.004

0.095

-0.04

0.966

Saving for inter vivos transfers
Saving for bequests
Saving to benefit from government
subsidies
Constant

0.111
0.191

0.053
0.037

2.08
5.12

0.052 *
0.000 ***

0.184
1.717

0.045
0.333

4.08
5.16

0.001 ***
0.000 ***

Mean of dependent variable

0.862

R-squared
Number of observations

0.468
20278

Notes: *Significant at 10% level, **significant at 5% level, ***significant at 1% level.
Source: Authors' calculations based on data from the Household Finance and Consumption
Survey (HFCS), which is conducted by the European Central Bank.

18

Table 6: The Determinants of the Wealth-to-Income Ratio (60-or-Older Sample)
Log(Wealth/Income)

Coeff.

Std. Error

t-valuep-value

Age

0.181

0.092

1.96

0.065 *

Age^2/100
Primary education-0.121-0.789

0.063
0.131

-1.92
-6.03

0.071 *
0.000 ***

Lower secondary education-0.780

0.172

-4.52

0.000 ***

Upper secondary education
First-stage tertiary education-0.587-0.529

0.084
0.066

-7.01
-8.07

0.000 ***
0.000 ***

Second-stage tertiary education-0.549

0.077

-7.16

0.000 ***

Doctoral education-0.275

0.091

-3.01

0.007 ***

Male

0.073

0.024

2.99

0.008 ***

Single

0.203

0.126

1.60

0.126

MarriedWidowed

0.222
0.202

0.120
0.147

1.85
1.37

0.081 *
0.189

Household size

-0.180

0.025

-7.22

0.000 ***

Homeownership
Saving for housing purchase

2.530
0.052

0.186
0.092

13.60
0.56

0.000 ***
0.581

Saving for other major purchases

0.039

0.037

1.06

0.302

Saving to start a business

0.199

0.082

2.43

0.026 **

Saving for buying financial assets
Saving for precautionary purposes

0.036
0.030

0.108
0.029

0.33
1.03

0.743
0.319

Saving for repaying debts-0.167

0.043

-3.92

0.001 ***

Saving for retirement

0.167

0.094

1.78

0.092 *

Saving for travel/holidays-0.021

0.024

-0.85

0.407

Saving for inter vivos transfers

0.078

0.031

2.50

0.022 **

Saving for bequests

0.154

0.019

8.20

0.000 ***

Saving to benefit from government
subsidies

0.026

0.049

0.52

0.607

Constant
Mean of dependent variable-6.647
1.572

3.318

-2.00

0.060 *

R-squared

0.553

Number of observations
15611
Notes: *Significant at 10% level, **significant at 5% level, ***significant at 1% level.
Source: Authors' calculations based on data from the Household Finance and Consumption
Survey (HFCS), which is conducted by the European Central Bank.

19

Table 7: The Composition of Household Wealth by Saving Motive (Full Sample)
1
2
3
4

Saving motive
Saving for housing purchase

Percent change in Percent change in
wealth-to-income wealth-to-income
Proportion ofratio that isratio that is
respondents attributable to each
attributable to
Share ofsaving forsaving motive
each saving
wealth foreach saving (households saving
motive (alleach saving
motivefor each motive)
households)
motive(percent)(percent)(percent)(percent)
10.4
19.5
2.028
12.43

Saving for other majorpurchases
17.8
0.7
0.125
0.76
Saving to start a business
1.7
51.5
0.876
5.37
Saving to buy financial assets
3.6
19.6
0.706
4.33
Saving for precautionary
purposes
63.1
2.4
1.514
9.28
Saving for repaying debts
7.9
-29.8
-2.354-14.43
Saving for retirement
43.9
20.0
8.780
53.83
Saving for travel/holidays
25.0
-0.2
-0.050-0.31
Saving for inter vivos transfers
25.1
9.8
2.460
15.08
Saving for bequests
10.7
17.9
1.915
11.74
Saving to profit fromgovernment subsidies
2.0
15.6
0.312
1.91
Sum
16.311100.00Notes: The figures in column 1 are taken from Table 1, and the figures in column 2 are taken from
Table 4. The figures in column 3 are calculated as the product of the figures in columns 1 and 2
divided by 100. Finally, the figures in column 4 are calculated as the ratio of the figures in column 3
to the sum of the figures in column 3.
Source: Authors' calculations based on data from the Household Finance and Consumption Survey(HFCS), which is conducted by the European Central Bank.

20

Table 8: The Composition of Household Wealth by Saving Motive (Under-60 Sample)
1
2
3
4

Saving motive
Saving for housing purchase
Saving for other majorpurchases
Saving to start a business
Saving to buy financial assets
Saving for precautionary
purposes
Saving for repaying debts
Saving for retirement
Saving for travel/holidays
Saving for inter vivos transfers
Saving for bequests
Saving to profit fromgovernment subsidies
Sum

Percent change in Percent change in
wealth-to-income wealth-to-income
Proportion ofratio that isratio that is
respondents attributable to each attributable to
Share ofsaving forsaving motive
each saving
wealth foreach saving (households saving
motive (alleach saving
motivefor each motive)
households)
motive(percent)(percent)(percent)(percent)
15.1
19.3
2.914
17.67
22.3
2.4
4.6

-0.2
56.1
24.2

-0.045
1.346
1.113

-0.27
8.16
6.75

62.6
10.7
36.6
30.1
29.3
6.9

2.2
-28.8
21.7
-0.4
11.1
19.1

1.377
-3.082
7.942-0.120
3.252
1.318

8.35
-18.68
48.15
-0.73
19.72
7.99

2.6

18.4

0.478
16.4952.90
100.00Notes: The figures in column 1 are taken from Table 1, and the figures in column 2 are taken from
Table 4. The figures in column 3 are calculated as the product of the figures in columns 1 and 2
divided by 100. Finally, the figures in column 4 are calculated as the ratio of the figures in column 3 tothe sum of the figures in column 3.
Source: Authors' calculations based on data from the Household Finance and Consumption Survey(HFCS), which is conducted by the European Central Bank.

21

Table 9: The Composition of Household Wealth by Saving Motive (60-or-Older Sample)
1
2
3
4
Saving motive
Proportion of Percent change in Percent change in Share of
respondents wealth-to-income wealth-to-income wealth forsaving for
ratio that isratio that iseach saving
each saving attributable to each attributable tomotivemotivesaving motive
each saving(percent)(percent)(households saving
motive (allfor each motive)
households)(percent)(percent)
Saving for housing purchase
Saving for other majorpurchases

4.4
12.0

5.2
3.9

0.229
0.468

1.57
3.21

Saving to start a business
0.7
19.9
0.139
0.96
Saving to buy financial assets
2.3
3.6
0.083
0.57
Saving for precautionary
63.8
3.0
1.914
13.13
purposes
Saving for repaying debts
4.4
-16.7
-0.735-5.04
Saving for retirement
53.3
16.7
8.901
61.06
Saving for travel/holidays
18.5
-2.1
-0.389-2.66
Saving for inter vivos transfers
19.7
7.8
1.537
10.54
Saving for bequests
15.6
15.4
2.402
16.48
Saving to profit from
1.1
2.6
0.029
0.20
government subsidies
Sum
14.578100.00Notes: The figures in column 1 are taken from Table 1, and the figures in column 2 are taken from
Table 4. The figures in column 3 are calculated as the product of the figures in columns 1 and 2
divided by 100. Finally, the figures in column 4 are calculated as the ratio of the figures in column 3
to the sum of the figures in column 3.
Source: Authors' calculations based on data from the Household Finance and Consumption Survey(HFCS), which is conducted by the European Central Bank.

22

Table 10: Descriptive Statistics (Countries with Generous Public Pension Benefits)
Variable

Mean

Std. Dev.

Median Minimum Maximum

Wealth/Income

6.785

8.247

4.465

0

74.976Log(Wealth/Income)

1.141

1.558

1.496

-9.9484.317

Age56.51915.84257

1685

Age^2/100

34.45417.881

32.49

2.56

72.25

Primary education

0.176

0.381

0

0

1

Lower secondary education
Upper secondary education

0.155
0.352

0.362
0.478

0
0

0
0

1
1

First-stage tertiary education

0.152

0.359

0

0

1

Second-stage tertiary education

0.151

0.358

0

0

1

Doctoral education
Male

0.013
0.623

0.114
0.485

0
1

0
0

1
1

Single

0.194

0.396

0

0

1

Married

0.568

0.495

1

0

1

WidowedHousehold size

0.126
2.381

0.332
1.239

0
2

0
1

1
14

Homeownership

0.755

0.43

1

0

1

Saving for housing purchase

0.095

0.293

0

0

1

Saving for other major purchases

0.147

0.355

0

0

1

Saving to start a business

0.014

0.119

0

0

1

Saving to buy financial assets

0.029

0.168

0

0

1

Saving for precautionary purposes
Saving for repaying debts

0.629
0.073

0.483
0.26

1
0

0
0

1
1

Saving for retirement

0.426

0.494

0

0

1

Saving for travel/holidays

0.219

0.413

0

0

1

Saving for inter vivos transfers
Saving for bequests
Saving to profit from government
subsidies

0.239
0.118

0.427
0.322

0
0

0
0

1
1

0.017

0.131

0

0

1

Source: Authors' calculations based on data from the Household Finance and Consumption
Survey (HFCS), which is conducted by the European Central Bank. The sample is limited tohouseholds in countries whose average public pension replacement rate is higher than the
median.

23

Table 11: The Determinants of the Wealth-to-Income Ratio (Countries with
Generous Public Pension Benefits)
Log(Wealth/Income)Age

Coeff.
0.027

Std. Error
0.007

t-value
3.86

Age^2/100-0.011

0.005

-2.09

p-value
0.004 ***
0.066 *

Primary education
Lower secondary education-0.203-0.058

0.068
0.080

-3.01
-0.73

0.015 **
0.486

Upper secondary education

0.041

0.054

0.76

0.466

First-stage tertiary education

0.130

0.045

2.92

Second-stage tertiary education

0.120

0.052

2.30

0.017 **
0.047 **

Doctoral education
Male

0.250
0.036

0.115
0.007

2.17
5.08

Single

0.075

0.038

1.98

MarriedWidowed

0.026
0.060

0.051
0.031

0.50
1.93

Household size
Homeownership
Saving for housing purchase-0.083
2.433

0.008
0.181

-10.07
13.46

0.129

0.081

1.60

0.144

Saving for other major purchases
Saving to start a business

0.013
0.490

0.044
0.172

0.30
2.85

Saving to buy financial assets
Saving for precautionary purposes

0.214

0.093

2.29

0.772
0.019 **
0.048 **

Saving for repaying debts

0.032-0.245

0.017
0.026

1.81
-9.60

Saving for retirement
Saving for travel/holidays

0.149
0.089

0.064
0.074

2.31
1.20

Saving for inter vivos transfers

0.056

0.024

2.33

Saving for bequests

0.166

0.027

6.22

0.045 **
0.000 ***

Saving to profit from government
subsidies

0.083

0.073

1.14

0.285

Constant-1.945-15.040.000 ***

Mean of dependent variable

0.129
1.140

R-squared

0.565

Number of observations

28480

0.058 *
0.001 ***
0.079 *
0.628
0.085 *
0.000 ***
0.000 ***

0.103
0.000 ***
0.046 **
0.260

Notes: *Significant at the 10% level, significant at the 5% level, ***significant at the 1% level.
Source: Authors' calculations based on data from the Household Finance andConsumption Survey (HFCS), which is conducted by the European Central Bank. The
sample is limited to households in countries whose average public pension replacement
rate is higher than the median.
24

Table 12: The Composition of Household Wealth by Saving Motive (Countries with Generous
Public Pension Benefits)
1

Saving motive

2

3

4

Percent change in Percent change in
Proportion of wealth-to-income wealth-to-income
Share ofrespondents
ratio that isratio that is
wealth forsaving for attributable to each attributable toeach saving
each savingsaving motive
each saving
motivemotive(households saving
motive (all(percent)(percent)
for each motive)
households)(percent)(percent)

Saving for housing purchase

9.5

12.9

1.23

8.35

Saving for other majorpurchases

14.7

1.3

0.19

1.30

Saving to start a business
Saving to buy financial assets

1.4
2.9

49
21.4

0.69
0.62

4.67
4.23

Saving for precautionary
purposes

62.9

3.2

2.01

13.71

7.3
42.6
21.9
23.9
11.8

-24.5
14.9
8.9
5.6
16.6

-1.79
6.35
1.95
1.34
1.96

-12.18
43.23
13.28
9.12
13.34

1.7

8.3

0.14

0.96

14.68

100.00

Saving for repaying debts
Saving for retirement
Saving for travel/holidays
Saving for inter vivos transfers
Saving for bequests
Saving to profit fromgovernment subsidies
Sum

Notes: The figures in column 1 are taken from Table 1, and the figures in column 2 are taken from
Table 4. The figures in column 3 are calculated as the product of the figures in columns 1 and 2
divided by 100. Finally, the figures in column 4 are calculated as the ratio of the figures in column 3 tothe sum of the figures in column 3.
Source: Authors' calculations based on data from the Household Finance and Consumption Survey(HFCS), which is conducted by the European Central Bank. The sample is limited to households incountries whose average public pension replacement rate is higher than the median.

25

Table 13: The Determinants of the Accumulation Rate of Net Financial Wealth (FullSample)
The accumulation rate of net
financial wealth
Coeff.
Std. Error
t-valuep-value
Age
Age^2/100

0.008-0.007

0.013
0.011

0.63
-0.63

0.548
0.543

Primary education-0.850

0.128

-6.62

0.000 ***

Lower secondary education
Upper secondary education-0.762-0.814

0.158
0.125

-4.81
-6.49

0.001 ***
0.000 ***First-stage tertiary education-0.832

0.125

-6.64

0.000 ***

Second-stage tertiary education
Doctoral education-0.721-0.957

0.114
0.134

-6.30
-7.15

0.000 ***
0.000 ***

Male

-0.030

0.034

-0.88

0.404

Single

0.228

0.054

4.24

0.003 ***

Married

0.093

0.038

2.41

0.042 **

WidowedHousehold size

0.072
-0.001

0.071
0.017

1.02
-0.08

0.338
0.938

Homeownership-0.013

0.027

-0.49

0.637

Wealth in wave 2
Saving for housing purchase

0.000
0.206

0.000
0.106

-0.31
1.94

0.767
0.089 *

Saving for other major purchases
Saving to start a business

0.029-0.078

0.022
0.118

1.29
-0.66

0.235
0.530

Saving for buying financial assets

0.061

0.015

4.16

0.003 ***

Saving for precautionary purposes
Saving for repaying debts

0.076-0.063

0.032
0.031

2.36
-2.02

0.046 **
0.078 *

Saving for retirement

0.105

0.027

3.87

0.005 ***

Saving for travel/holidays
Saving for inter vivos transfers

0.194
0.115

0.095
0.022

2.04
5.32

0.075 *
0.001 ***

Saving for bequests
Saving to benefit from government
subsidies-0.057

0.019

-3.05

0.016 **

0.087

0.037

2.35

0.047 **

Constant

0.424

0.450

0.94

0.374

Mean of dependent variable

0.132

R-squared

0.046

Number of observations
7571
Notes: *Significant at 1% level, **significant at 5% level, ***significant at 1% level.
Source: Authors' calculations based on data from the Household Finance and Consumption
Survey (HFCS), which is conducted by the European Central Bank. The sample is a panel
constructed from waves 2 and 3 of the Survey.
26