The Saving Behaviour of Immigrants and Home-Country Characteristics: Evidence from Australia

The Saving Behaviour of Immigrants and Home-CountryCharacteristics: Evidence from Australia

Liliya Gatina*

Abstract

This article investigates the determinants ofsaving rates of Australian residents, determineswhether the saving behaviour of immigrants isdifferent from that of native-born Australiansand if it is affected by their country-of-origincharacteristics. Comparison of estimated sav-ing rates for 2006 using Australian longitudi-nal data reveals that immigrants save less thantheir native-born counterparts. Amid thedeterminants, a home country’s gross domesticproduct per capita and old-age dependencyratio are found to be positively correlated,while national household saving rate isnegatively correlated, with immigrants’ savingrates. The latter finding may be driven byunaccounted remittances or changes in savinghabits after immigration.

1. Introduction

The mobilisation of savings is one of theimportant functions of the financial sector. Theprovision of savings facilities enables house-holds to secure their investment future. Thismoney can then be loaned to businesses, thuscreating a favourable environment for capitalaccumulation and private sector development.Countries with well-developed financial sys-tems have greater investment and financialdepth, mainly due to higher savings (TheWorldBank 1989). Thus, understanding the determi-nants of saving rates is important for creatingsound policies for a country.

As total domestic savings are affected notonly by government savings but also bypersonal savings (Edwards 1996), culturaldiversity can play a major role in defining thelevel of domestic savings in a country. Thiseffect may be even more prominent in countrieswith diverse ethnic backgrounds, such asAustralia. Customs and traditions from thehome country that people bringwith themwhenthey migrate can affect their way of life inAustralia and their saving behaviour, inparticular. As at June 2010, 27 per cent ofAustralia’s population was born overseas(ABS 2011); hence, their saving behaviourhas a significant impact on the Australianeconomy. The first aim of this article is toinvestigate the determinants of saving rates ofAustralian residents and determine whether thesaving patterns of immigrants are different fromthose of native-born Australians. If there is adifference, then this article progresses byexploring whether saving behaviour of Austra-lian immigrants can be explained by cross-country differences in national saving rates andother country-of-origin characteristics.

* School of Economics, Finance and Marketing, RMITUniversity, Victoria 3000 Australia; email<[email protected]>. The author wishes to acknowledge ProfessorHeather Mitchell, Associate Professor Simon Feeny, EditorProfessor Ian McDonald and two anonymous referees fortheir contributions to this article.

The Australian Economic Review, vol. 47, no. 2, pp. 157–72

�C 2014 The University of Melbourne, Melbourne Institute of Applied Economic and Social ResearchPublished by Wiley Publishing Asia Pty Ltd

The results of this analysis reveal thatimmigrants in Australia have lower savingrates than their native-born counterparts. Thisvariation in saving patterns can be at leastpartially attributed to their home-countrycharacteristics, such as the national savingrate of their home country. The negativecorrelation between national household savingrate in immigrants’ home country and theirsaving rate in Australia can be explained eitherbecause remittances were not considered due tolack of data or by the change in immigrants’saving habits after migration. A sample of 14countries is used to illustrate the negativerelationship between saving rates of immi-grants to Australia and the national saving ratein their respective home country.

After a review of the literature and descrip-tion of the data and methodology, this articleproceeds as follows: first, it analyses whatdetermines the household saving rates ofAustralian residents and whether there is adifference in saving behaviour betweenAustralian-born and foreign-born individuals;second, the sample is limited to immigrants totest whether there is a home-country effect ontheir saving habits; and finally, the saving ratesof immigrants are compared to the saving ratein their respective home country.

Data from the Household, Income andLabour Dynamics in Australia (HILDA) Sur-vey are used to obtain personal characteristicsof individuals. The HILDA Survey has inter-viewed the same cohort of 7,682 households atannual intervals since 2001. Country data aresourced from the World Development Indica-tors of the World Bank (2010).

2. Literature Review

From Keynes onwards, income has beenconsidered an important determinant of saving.Apart from income, other factors affecting thelevel of savings have been proposed. The lifecycle hypothesis concludes that aggregatesaving will only occur when the saving ofyoung people completely offsets the dissavingof the old. This implies that the aggregatesaving rate will be higher for the economieswith higher long-run growth rates (Modigliani

1986; Deaton 2005). Hence, according to thistheory, productivity growth and populationgrowth are important determinants of theaggregate level of saving.

The current literature also stresses theimportance of wealth effects in determiningsaving behaviour. For example, Dreger andReimers (2006) claimed that wealth effects areessential when investigating consumptionbehaviour and the inclusion of wealth consider-ably improves their model. The importance ofwealth in private saving was also highlighted bySalotti (2010), suggesting a negative relation-ship between tangible or housing wealth andhousehold saving in developed countries in theperiod 1980–2005, which is partially explainedby the housing market boom. However, as sheargued, many studies fail to account forhousehold wealth due to lack of data.

Culture and the specific characteristics ofcountries of origin are also proposed as possibledeterminants of different economic behaviour.Culture was defined by Guiso, Sapienza andZingales (2006) as customary beliefs andvalues that are transferred within generationsof ethnic, religious and social groups. Theyinvestigated the effects of culture’s fundamen-tal aspects, such as religion and ethnic origin,on economic outcomes. In particular, theyfocused on how saving decisions vary betweenvarious religious groups and argued thatcultural variables are important in understand-ing differences in saving rates among countries.Similarly, Carroll, Rhee and Rhee (1999) testedhow countries of origin affect savings byanalysing the saving patterns of immigrantsto the United States. Their findings suggestedthat the saving patterns of immigrants to theUnited States, to a large extent, depend onwhich country they came from; yet, thesepatterns do not necessarily resemble the savingrate of their respective home country.

The relationship between people’s origin andsaving rates has been tested using data fromdifferent countries. For instance, Al-Awad andElhiraika (2003), using data on immigrants tothe United Arab Emirates, investigated theeffect of immigrants’ home countries andregions on their saving behaviour. Theirfindings confirmed that saving rates differ

158 The Australian Economic Review June 2014

�C 2014 The University of Melbourne, Melbourne Institute of Applied Economic and Social Research

between households with different ethnic back-grounds. Likewise, Sinning (2007) in a study ofthe saving behaviour of German immigrants,argued that, on average, immigrant householdheads in the country save 6–10 percentagepoints less than comparable natives if remit-tances are not considered.

Research on the indicators of the financialintegration of immigrants into Australiansociety has concentrated predominantly ontheir wealth. For instance, Cobb-Clark andHildebrand (2008) compared the net worth andasset portfolios of foreign-born and Australian-born families. They pointed out that the wealthgap between the two is still present in Australia,albeit much smaller than in other immigrant-receiving countries. Likewise, the findings ofDoiron and Guttmann (2009), who studied thedifference in wealth distribution of these twogroups, revealed a wealth disadvantage forimmigrant households in Australia.

This is in line with the argument of Islam,Parasnis and Fausten (2010) that differences inwealth are seen as the main reason for thedifferent saving behaviour of native- andforeign-born households. However, as theyasserted, immigrants’ wealth accumulation inAustralia is unlikely to provide a comprehen-sive view on immigrants’ wealth holdings asthey can have financial responsibilities andopportunities in other countries that are notnecessarily limited to their country of origin.For example, they may use their savings to holdassets in their home country, which couldcontinue to build up after migration if they planto return.

Consequently, Islam, Parasnis and Fausten(2010) explored whether there are systematicdifferences in the saving behaviour betweenimmigrant and native households in Australiaand what might be the potential determinants ofany observed differentials. By using data fromfour Australian Household Expenditure Sur-veys (HES), they explained the observed savinggap in favour of native households by labourmarket outcomes. At the same time, theysuggested that immigrant households tend tosave more across the entire savings distribution,with higher values of savings observed at theupper end of the distribution, after controlling

for demographic and other characteristics. Thisresearch, however, did not account for thecultural dimensions of the saving behaviour ofthe immigrant population and predominantlyconcentrated on household socio-economiccharacteristics, thus restricting the range ofpossible factors affecting the saving behaviourof Australian residents.

This article contributes to the researchdescribed above by investigating the determi-nants of the saving rates of Australian residentsby using a different dataset and goes further byinvestigating how the ethnic background ofAustralian immigrants affects their savingbehaviour. To address this question, theHILDA Survey, unlike the HES used by Islam,Parasnis and Fausten (2010), collects informa-tion about immigrants’ country of origin.However, average aggregate expenditures donot differ significantly across surveys: there is a1.6 per cent difference for the same items(Sun 2010), which enables comparison with theresults obtained by Islam, Parasnis and Fausten(2010).

A similar model to the one used by Al-Awadand Elhiraika (2003) was applied to the HILDASurvey data. Carroll, Rhee and Rhee (1999)argued that saving rates differ between differentimmigrant groups, suggesting the presence ofcountry-of-origin effects. Nevertheless, thepersonal saving rate obtained by these groupsdiffers from the national saving pattern of theirrespective country and thus the internationalsaving rates differential remains unexplained.The contribution of this study to the research onthe determinants of economic performanceincludes a comparison of the estimated personalsaving rates of Australian immigrants with thenational saving rate of their home country.

As discussed above, various factors affectingthe saving rate have been discovered, which hasled to the development of various approaches tomeasuring it. This study integrates theseapproaches and selects the life-cycle permanentincome hypothesis for consumption as afoundation for the saving model. This modelalone cannot explain all the variations in privatesaving rates across countries; hence, additionalvariables are added to the regression. Thus,private saving behaviour in this research is


Gatina: Saving Behaviour of Immigrants and Home-Country Characteristics 159

considered to be a function of followingvariables: permanent income; personal factorsaffecting permanent income, such as age andoccupation; dependency ratio; wealth andcountry-of-origin characteristics.

3. Data and Methodology

To the best of the author’s knowledge, no studyhas ever been carried out using actual measuredsaving rates. These have always been imputedusing other variables, depending on theavailable data. For example, because Islam,Parasnis and Fausten (2010) used cross-sectional Australian data, they focused onout-of-pocket saving, defined as the differencebetween consumption and disposable income.A similar definition was used by Al-Awad andElhiraika (2003) for their study of savings byimmigrants to the United Arab Emirates due tothe country’s laws not allowing foreigners topossess fixed assets and hence their wealthholdings data being irrelevant. A differentapproach was used by Carroll, Rhee andRhee (1999) for their US study. The absenceof information about consumption in their datadoes not allow an estimation of personal saving,as suggested above. Also, since their data fromthe 1980 and 1990 Censuses of Population andHousing were obtained from a sub-samplewhich is randomly selected every 10 years, itwas not possible to follow individuals acrossdifferent periods. As a result, they estimatedwhat the wealth level would have been in 1990for the people observed in 1980 and what thewealth level would have been in 1980 for thepeople surveyed in 1990. The imputed datawere then used for the estimation of anindividual’s saving as the change in wealthbetween two periods.

The method of defining saving in thisresearch is severely constrained by datalimitations. Despite HILDA Survey’s interviewperiod, commencing in 2001, information onhousehold wealth is only available for 2002 and2006. As suggested by Carroll, Rhee and Rhee(1999), the panel structure of these data allowsan estimation of personal saving as the increaseor decrease in wealth between 2002 and 2006.This change in household wealth was consid-

ered for defining saving, but application of themodel using saving defined in this way failed toproduce any significant results. The possibleexplanation is that the wealth variable inHILDA Survey includes increases in the valueof assets, such as the family home, and saving,defined as change in household wealth, mightbe highly influenced by changes in propertyvalues. Furthermore, as argued by Engelhardt(1996), self-measured values of housesreported by homeowners are not alwaysaccurate and tend to be overestimated. House-hold wealth also includes windfalls, such asinheritances, winnings and termination pay-ments, which arguably make its change a poormeasure of household saving.

Fortunately, HILDA Survey’s rich datasetincludes household-level data on income in eachyear surveyed and data on expenses since 2005.Hence, following the approach by Al-Awad andElhiraika (2003) and Islam, Parasnis and Fausten(2010), saving (S) in this study is equal to thedifference between total disposable householdincome (Y) and total household expenditure (E).Accordingly, the saving rate (s) used in this studyis calculated by using these savings divided bytotal household disposable income: s ¼ðS=Y Þ ¼ ½ðY � EÞ=Y �. Given the availabilityof data on expenses and household wealth, thesample is limited to observations from2006 only.

Household expenditure in this study isdefined as the sum of all household expendi-tures listed in Table A1. As information aboutremittances was not collected by HILDASurvey, there is a possibility that householdsavings of individuals who transfer moneyoverseas could be overestimated when thesedata are used.

Similarly to the usage by Carroll, Rhee andRhee (1999) and Al-Awad and Elhiraika (2003),observable household disposable income in thisresearch is treated as permanent disposableincome plus a transitory component. As arguedby Carroll (2001), in the presence of uncertaintyabout meaningful labour income, Friedman’spermanent income hypothesis describes theoptimal behaviour of moderately impatientconsumers better than the later maximisingversions. According to Carroll, Milton Fried-man’s definition of permanent income that



determines current spending is the mean ofexpected income in the near future. The measureof permanent income can also be obtained byusing past income plus income change from thepast to the current period (Ramrattan andSzenberg 2008). Transitory income, which isdefined as the difference between current andlifetime income, has a negligible effect onconsumption, as asserted by Ramrattan andSzenberg (2008). Since this study is limited tothe investigation of factors affecting savingbehaviour in 2006, the annual disposable incomefor 2006 is treated as permanent income.

Two models were employed to attain theobjectives of this research. The first model wasused for determining if Australian residentsborn overseas have lower saving rates than theirAustralian-born counterparts:

Si ¼ a0 þ a1X i þ a2Ri þ ei ð1Þ

where Si is a saving rate of household i that isdefined as the ratio of household saving to thetotal disposable income; Xi is a vector ofhousehold characteristics affecting savings,such as household income, wealth, age, gender,occupation and education of the householdhead and Ri is a dummy variable that is equal to1 if the household head was born in Australiaand 0 otherwise.

The application of the second model wasjustified because the saving behaviour ofimmigrant households was, in fact, found tobe different from that of native-born house-holds. This model tested the significance of thecultural effects in contributing to this variation,using the immigrant-only sample:

Si ¼ a0 þ a1X i þ a2Zi þ ei ð2Þ

where, as before, Si is the saving rate of animmigrant household i and Xi is a vector ofhousehold characteristics and Zi is a vector ofcountry-of-origin characteristics, includinggross domestic product (GDP), national savingrate, the dependency ratio and the quality ofinstitutions. Both models were estimated usingSTATA 11 (StataCorp LP, Texas, USA).

A two-stage least squares (2SLS) procedurewas used because of the endogeneity of

personal income and household wealth. TheHausman test, carried out to test if there is acorrelation between the explanatory variablesand the error terms, confirmed the endogeneityof these two variables in agreement with thestudy of Al-Awad and Elhiraika (2003). Hence,the estimation of models (1) and (2) using theordinary least squares method will be biasedand inconsistent, unlike the more reliableinstrumental variable estimations. The instru-ments used are the lagged value of personaldisposable income in 2005, the previous year,and the lagged value of household wealth in2002, as this is only surveyed every 4 years.Although there are concerns about the credibil-ity of these instrumental variables, such as thepossible correlation of lagged income withunobservable determinants of the saving ratethat are endogenous to current income, thesewere the best possible instruments withinexisting data constraints. The STATA post-estimation test measuring the relevance of theexcluded exogenous variables was carried outand the results confirmed that these are goodinstruments.1

3.1 Personal Data

The data on individuals were taken from theHILDA Survey and limited to observations in2006 as this is the only year that has questionson household expenditure and householdwealth. Data collected in this year consist of17,454 respondents, or 7,139 households. Allpersonal variables with definitions are pre-sented in Table A1.

Saving models were applied to the sample ofindividuals aged 15 years or older. Althoughusing a household-level sample that is limited tohousehold heads is common in studies investi-gating saving behaviour (Carroll, Rhee andRhee1999; Al-Awad and Elhiraika 2003; Sinning2007; Islam, Parasnis and Fausten 2010), thisstudy analyses the saving behaviour of allhousehold members. As reported by Deatonand Paxson (2000), a household-level approachmight not reflect a true relationship betweensaving rate and individual parameters, such asage. For example, household income andconsumption of multi-generational household



with a mixture of savers and dissavers combinedata for people at different life stages, and notjust that of the household head. Individualparameters of a household head also depend onthe way the household headship is defined.Subsequently, analysing saving behaviour of allhousehold members may provide results whichare more consistent with the life-cycle model.Nevertheless, more specific analysis of thesample that includes only household headswas also considered in the author’s subsequentresearch.2 Most independent variables used inboth approaches were similar. They includedwealth, financial income, education, gender,marital status, major statistical region and thenumber of members in the household.

Other independent variables, however, werespecific to this study. They included twodummy variables: the first dummy variablerepresented whether or not an individual wasconsidered as a household head3 and the seconddummy variable represented whether or not thisindividual was the spouse of a household head.The amount contributed to total savingsdepends not only on the income of eachhousehold member but also on the householdresponsibilities of each member. Being a parentwho is the household head or the spouse of thehousehold head, for instance, entails theresponsibility of providing for children andhence they could be expected to have lowersavings.

As discussed above, the saving rate in thisstudy is equal to the share of net householdincome after paying all household expensesfrom total disposable income. For meaningfulestimates, however, income and expenditurevariables needed to be modified. The highproportion of missing responses under house-hold expenditure suggested a diversifiedapproach to handling these variables. Allmissing values of household expenditureswere treated as zero, except for inevitableexpense items, such as groceries, publictransport and taxis, electricity bills and gasbills. Similarly, missing values of annual rentand mortgage payments were treated as zero,assuming that those respondents who did notpay rent were houseowners and vice versa.Personal income was also subject to certain

restrictions. Observations with negative valuesof personal disposable income were deleted as,in this case, consistent saving rates could not becalculated.

After these manipulations, the saving ratesthat were then derived were taken on theextreme values at either end of the distribution,such as –21,948 per cent as the minimum valueand 100 per cent as the maximum value. Thisimplied the need for an additional trimming ofthe sample since expenses that are thousandstimes greater than income, on the one hand,and zero expenditures, on the other hand, arevery unlikely and can cause misleadingresults. Thus, the sample was winsorised to96 per cent, with the new lower and upperlimits of –130 and 79 per cent, respectively,and the mean value of 30 per cent. Furthertrimming of the sample to individuals aged 15and over with non-missing data on country oforigin reduced the sample size to 10,196residents.

The characteristics of the immigrant andnative-born individuals surveyed in 2006 arecompared in Table 1. The average immigrant is8 years older, has slightly fewer children in thehousehold and is better educated than theaverage person born in Australia. Compared toindividuals born in Australia, immigrants havea similar percentage of men and women but ahigher percentage of married individuals, alower employment rate and a higher income.However, the difference in the mean value ofwealth between immigrant and native-bornhouseholds is not significant.

The difference in household saving rates isan area of particular interest in this research.Hence, the mean values of the saving rates offoreign-born and Australian-born householdsare also compared. The results reveal adifference in saving rates in favour of native-born households (31.38 per cent per annum asopposed to 28.19 per cent saved by an averageimmigrant household).

About 23 per cent of respondents migrated toAustralia before 1964. The remaining three-quarters spread over the following period from1965 to 2006, with the lowest number migrat-ing in 1975–1979. The highest proportion ofimmigrants are older than 20 years (53 per cent)



and the lowest are children aged 11–15 years (8per cent) The majority of the sample membersoriginated from Europe and about one-quarterof all respondents was born in Asia.

3.2 Country Data

The personal variables mentioned above affectthe capacity to save by Australian households,whereas their willingness to save is affected bycountry-of-origin attributes, analogously to theexisting studies (Hussein and Thirlwall 1999;Al-Awad and Elhiraika 2003). Other possibledeterminants of the willingness to save, such asthe interest rate and inflation, are the same forall households. These variables includedimmigrants’ home-country characteristics,such as average per capita GDP, the dependencyratio and the national saving rate, which weretaken from the World Development Indicators(The World Bank 2010), and the householdsaving rates were calculated using data from theUnited Nations’ National Accounts OfficialCountry Data (United Nations StatisticsDivision 2012).4

Average per capita GDP is included to reflectthe relationship between household savings andhome country’s income. Immigrants from richcountries supposedly had a reasonable incomebefore migration and had accumulated somewealth. This can provide them additional

income in the form of bank interest or dividendsand hence their ability to accumulate moresavings.

This research also tested the relationship ofhousehold saving rates with the home country’sdependency ratio. According to Keynes, citedin Modigliani (1988), the ‘foresight’ savingmotive includes provision for the anticipatedfuture expenses of an individual or their family,which are different from the current costs andinclude expenses related to old age, educationand provision for dependants. Hence, the homecountry’s dependency ratio, reflecting theproportion of the dependent population tothe total population of working age, can alsoaffect saving habits. A relationship between thehousehold saving rate and the proportion of olddependants, in particular, can confirm the life-cycle hypothesis, according to which consump-tion in old age with accompanying lack ofsaving motivates current saving. This old-agedependency ratio varies from a minimum of4.16 per cent in Oman to a maximum of 30.98per cent in Japan, with the average value being19.17 per cent among 12,811 respondents from105 countries. The old-age dependency ratio inAustralia is 19.40 per cent. Three measures ofthe home country’s dependency ratio wereincluded: general age dependency ratio, young-age dependency ratio and old-age dependencyratio.

Table 1 Characteristics of Foreign- and Australian-Born Individuals Surveyed in 2006a

Characteristics Australian-born Foreign-born

Age 42.39 (18.09)b 49.60**c (16.18)% Male 47.21 47.61% Married (or de facto) 62.32 73.28**% Employed 67.21 60.34**Number of resident children 14 years old or younger 0.51 (0.94) 0.46* (0.87)Disposable income for financial year ($) 30,472 (24,935) 31,688* (26,097)Household wealth ($) 663,406 (1,093,007) 664,701 (1,116,218)Level of highest education achieved (%)No post-school qualification 50.02 41.09**Bachelor degree or higher 20.47 28.35**Other post-school qualification 29.50 30.56

Households saving rates (%) 31.38 28.19**Number of individuals 10,130 2,723

Notes: (a)Mean values are reported unless otherwise stated. The sample is restricted to individuals aged 15 years or older whohave non-missing country-of-origin data.(b) Standard deviations are in parentheses.(c) * and ** indicate a significant difference from a native-born Australian at the 5 and 1 per cent levels, respectively.



An additional attribute was a country’shousehold saving rate, which was included totest whether household saving habits depend onthe home-country saving rate. The nationalhousehold saving rate in this article is definedas the ratio of gross household savings to grosshousehold disposable income and is availableonly for 58 countries, varying from –82.70 percent for Kuwait and 36.01 per cent for China.Hence, by analogy with work done by Carroll,Rhee and Rhee (1999) for the US data andAl-Awad and Elhiraika (2003) for the UnitedArab Emirates, gross adjusted saving rate as apercentage of gross national income (GNI) wasalso included. According to Bolt, Matete andClemens (2002), gross national savings used foradjusted net savings calculation is defined as thedifference between GNI and the sum of publicand private consumption. Consequently, thegross adjusted saving rate (hereafter, referred toas the ‘national saving rate’) represents theproportion of gross national savings from GNIand is available for 94 countries, with 12,707respondents. National saving rates could be usedfor comparisonwith the results obtained for othercountries and to find evidence of the importanceof country-of-origin effects in explaining thedifferential of national saving rates. The Austra-lian national saving rate is equal to 29.97 percent, which is close to the national saving ratemean value of 28.22 per cent. Fiji has theminimum saving rate of –3.17 per cent and thehighest saving rate of 72.42 per cent is reported inEquatorial Guinea. Due to the fact that nationalsaving rates may vary greatly from year to year,the average national saving rate of the country forthe period 2004–2006was used in addition to thenational saving rate for 2006. The effect of eachcountry’s attribute on the household saving ratewas studied separately due to a high correlationbetween these measures.

4. Empirical Results

The first goal of the research was to identifywhat determines the saving behaviour ofAustralian residents and whether this behaviourdiffers between residents born in Australia andthose who migrated from overseas. As differ-ences were detected, tests were carried out

to determine which immigrants’ country-of-origin characteristics, if any, could have causedthese differences. Finally, the domestic savingrates of immigrants in Australia and thenational saving rate in their respective countryof origin were compared.

4.1 Difference in the Saving Behaviourbetween Australian-Born and Foreign-Born Residents

Model (1), estimated using the 2SLS procedure,was applied to the sample of both Australian-born and foreign-born residents to determinewhich individual characteristics affect Australianhousehold saving rates and if there is a differencein the saving behaviour of these two groups.

Table 2 suggests that number of householdresidents and their personal income play asignificantly positive role and the number ofresident children plays a significantly negativerole on the contribution by household membersto total household saving. However, age andgender of the household members do not affectthe amount saved by households, suggesting thatpersonal income already accounts for the effectof these factors on the individual contribution tohousehold savings. The lower contribution byhousehold heads or their spouse is attributable totheir higher expenses including interest andmortgage payments. As household wealth inHILDA Survey includes equity and house value,these expenses will be higher in wealthierfamilies and this could account for the coefficienton wealth being statistically insignificant.

Married people have the ability to share theirhousehold expenses with their partner and savemore. This is consistent with the findings ofOsili and Paulson (2006), who argued thatbeing married has a positive impact on savingsaccount ownership. This saving level, ingeneral, does not decrease even if a householdmember becomes unemployed, possibly due tothe availability of unemployment benefit underthe Australian social security system, but thesaving level is lower for households withmembers who are not in the labour force.

Although it is generally expected that peoplewith a higher education earn a higher incomeand, accordingly, have higher savings, according



to Morisset and Revoredo (1995), they mightrequire less precautionary savings due to a lowerunemployment risk. This could explain thenegative effect of having a Bachelor or higherdegree on the saving behaviour of Australianresidents. If this group’s outlook can be calledoptimistic, then this is also consistent with theresearch byHarris, Loundes andWebster (2002),who argued that economic optimism is negativelycorrelated with household savings. Anotherreason for the negative link between educationand saving rates, as Morisset and Revoredoargued, is that income benefits might take timeto be realised due to the lagged effect ofeducation of approximately 5 years. However,the household members do not experience thelagged effect of obtaining post-school qualifi-cations lower than, and different from, aBachelor degree. This can be explained bythe lower cost of obtaining this type of post-school qualification such as trade qualification.

Themain conclusion drawn from the results inTable 2 is that saving rates are higher for

Australian-born residents. In particular, they save3.89 per cent more per annum than their foreign-born counterparts. This contradicts the findingsof Islam, Parasnis and Fausten (2010), whoobserved the tendency of immigrant householdsto save more than native households when theyused Australian expenditure surveys. On theother hand, the immigrants’ lower propensity tosave that was detected in this study is consistentwith the findings for immigrant households inGermany that, on average, save 6–10 percentagepoints less than native-born Germans (Sinning2007). However, once the remittances oftemporary immigrants are treated as savings intheir home country, the savings gap betweenthem and comparable German-born householdheads disappears. Due to the absence ofinformation on remittances from Australia, asimilar analysis cannot be applied in this study. Itis evident, however, that if immigrants’ remit-tances were accounted for, the differencebetween the savings of immigrant householdsand native-born households in this analysis,

Table 2 Factors Affecting Household Saving Rates of Australian Residentsa

Variable Coefficient

Born in Australia 0.03890000***b (0.00882000)c

Income 0.02560000*** (0.00350000)Wealth 0.00001530 (0.00004990)Age 0.00154000 (0.00133000)Age squared 0.00000377 (0.00001310)Gender (1 if male) 0.00618000 (0.00760000)Number of children –0.04940000*** (0.00574000)Number of persons 0.02920000*** (0.00393000)Head –0.20400000*** (0.01650000)Spouse –0.15200000*** (0.01750000)Marital status (married¼ base case)Previously married –0.06350000*** (0.01250000)Never been married –0.09060000*** (0.01360000)

Level of highest education (no post-school qualification¼ base case)Bachelor degree or higher –0.01810000** (0.00850000)Other post-school qualification 0.02440000** (0.00980000)

Employment status (employed¼ base case)Unemployed –0.03570000 (0.02210000)Not in labour force –0.06540000*** (0.01060000)

Constant 0.07630000* (0.04410000)Observations 8,779

Notes: (a) The dependent variable is the household saving rate, which is equal to the share of net household income afterpaying all household expenses from total disposable income. In addition to the coefficients reported above, the regressionsalso include major statistical region controls, which are not reported due to low significance. The sample is limited toindividuals who have non-missing country-of-origin data, with the household saving rates above –1.28 and below 0.79.(b) *, ** and *** indicate statistical significance at the 10, 5 and 1 per cent levels, respectively.(c) Standard errors are indicated in parentheses.



defined as the difference between their after-taxincome and consumption, would be even greater.

Despite the limitation described above,features of the data used in this study allow amore detailed analysis of the reasons for thissavings gap in favour of Australian-bornresidents. In addition to demographic character-istics, the possible influences of being born in adifferent country on immigrants’ saving behav-iour were investigated. The following analysislimited the sample to immigrants.

4.2 Country-of-Origin Effect on Saving Ratesof Immigrants

Home-country variables included the nationalhousehold saving rate, the national saving rate, acountry’s general age dependency ratio, young-age dependency ratio, old-age dependency ratioand GDP per capita. In addition to these home-country characteristics observed in 2006, theaverage national saving rate for the period 2004–2006 was used to account for the national savingrate fluctuations. As discussed earlier, thenational household saving rate in this article iscalculated as the ratio of gross household savingsto gross household disposable income, using datafrom the United Nations Statistics Division(2012), while the national saving rate isrepresented by the proportion of gross nationalsavings from GNI (The World Bank 2010).

The analysis of the country-of-origin effecton the saving behaviour of immigrants wascarried out using model (2). As before, 2SLSprocedure was used to control for endogeneityof individual income and wealth, with house-hold wealth reported in 2002 and individualincome in the previous year being used asinstruments. Even though, when tested, house-hold wealth appeared to be exogenous using thereduced sample, for consistency, it was treatedas endogenous throughout this article.5

The results in Table 3 reveal that all thehome-country variables, except the general agedependency ratio and the young-age dependencyratio, have significant effects on the savingbehaviour of individuals. There is a negativecorrelation between the saving rate of immi-grant households in Australia and the nationalhousehold saving rate, which is also evident for

the national saving rate and the average 2004–2006 national saving rate. In contrast, a higherpercentage of old dependent people and ahigher country’s GDP per capita in immigrants’country of origin result in a higher domesticsaving rate when they migrate to Australia.Among all statistically significant coefficients,the change in a country’s GDP per capita hasthe highest effect and the change in the averagenational saving rate has the lowest effect on thesaving rate of its emigrants to Australia.

An explanation for these results is as follows.Individuals from wealthy countries that arerepresented by a higher GDP per capita aremore likely to have higher financial wealthwhen they migrate to Australia. This canprovide them with additional income in theform of bank interest or dividends and hencetheir ability to accumulate more savings.The negative association of the aged dependentpopulation ratio in immigrants’ home countrywith their household saving rate in Australiaconfirms the foresight motive of the life-cyclehypothesis, according to which householdssave to pay for the inevitable expenses of thefuture. A higher percentage of aged populationthat is not in the labour force means thatindividuals are encouraged to save more toprovide for their retirement. Interestingly, theratio of dependent young and aged populationsto the working-age population and the ratiorepresenting only young dependants do notaffect immigrant savings. This could mean thathigher savings are particularly encouraged incountries that have an ageing population.

The negative coefficient on the nationalhousehold saving rate shows that immigrantsfrom countries that save more have a tendencyto save less than immigrants from countrieswith a lower saving rate. This phenomenoncould be explained either by the fact thatimmigrants change their saving habits oncethey settle in Australia or by the lack ofinformation on the remittances sent to the homecountries. One of the reasons that immigrantsfrom countries with high saving rates do notsave as much as they used to once they move toAustralia could be the high level of Australiansocial security. As opposed to living incountries with low social security provision,



Tab

le3Effects

ofHom

e-Cou

ntry

Cha

racteristics

ontheHou

seho

ldSa

ving

Rates

ofIm

migrantsin

Australia

a

Variable

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Nationalhouseholdsaving

rate

–0.00196*

b

(0.00114)c

Nationalsaving

rate

–0.001800**

(0.000880)

Average

natio

nalsaving

rate

–0.001660*

(0.000973)

Age

dependency

ratio

–0.000162

(0.000991)

Age

dependency

ratio

(young)

–0.000687

(0.000628)

Age

dependency

ratio

(old)

0.00204*

(0.00114)

Gross

domestic

product(G

DP)

0.02390***

(0.00696)

Constant

0.04270

(0.16600)

0.102000

(0.129000)

0.086300

(0.130000)

0.056700

(0.134000)

0.080700

(0.127000)

0.03360

(0.12500)

0.06490

(0.12200)

Observatio

ns1,147

1,749

1,761

1,795

1,795

1,795

1,778

R2

0.17500

0.121000

0.118000

0.120000

0.121000

0.12100

0.12400

Notes:(a)T

hedependentvariables

arethenatio

nalhouseholdsaving

rate,the

natio

nalsavingrate,the

averagesaving

ratefor2

004–2006,a

country’sgeneralage

dependency

ratio

,young-age

dependency

ratio

,old-age

dependency

ratio

andGDPpercapita.Inadditio

ntothecoefficientsreported

above,theregressionsalso

includemajorstatisticalregion

controls,w

hich

arenotreported

dueto

lowsignificance.The

sampleislim

itedto

immigrant

respondentsaged

15yearsor

olderwho

have

non-missing

country-of-origindata,w

iththehouseholdsaving

ratesabove–1.28

and

below

0.79.

(b)*,

**and***indicate

statistical

significanceat

the10,5

and1percent

levels,respectively.

(c)Standarderrors

areindicatedin

parentheses.



where they had to rely on their savings in anemergency, immigrants in Australia do notneed to save so much due to the availability ofsupport schemes such as age and disabilitypensions, unemployment benefit and paid sickleave. Guest (2010) also argues that policybiases in Australia, such as higher income taxrelative to consumption tax, discourage house-holds from saving and favour spending.Alternatively, the saving rate of immigrants isdefined as the proportion of their householddisposable income after all household expensesare paid from total disposable income, soremittances could be included in the totalsaving rate if a certain unreported share of theirincome is sent to their home country. In thiscase, a high household saving rate in Australiacouldmean that the recipient country’s economyis not stable and has low savings. A lack of datadoes not allow testing of both propositions,which might be of interest in the future.

A similar pattern in the saving rate ofindividuals from different countries is observedin Table 4, where their household saving rate inAustralia, averaged for each country of origin, is

compared with their respective country-of-origin national saving rate. This comparison islimited to individuals from 14 countries, whichare represented by at least 30 respondents. Ahigh negative correlation coefficient of –0.81between the national saving rate and the averagehousehold saving rate of migrants from those 14countries also confirms the findings.

5. Conclusions

The main goal of the analysis reported in thisarticle was to determine what characteristics ofhousehold heads and other Australian residentsaffect their household saving rates. Anothergoal was to see if ethnicity is one of thesedeterminants, thus contributing to the existingresearch on the importance of country-of-origineffects for economic outcomes. Home-countryproxies in this research were represented by thenational household saving rates, nationalsaving rates and countries’ dependency ratiosand GDP per capita, while economic outcomeswere represented by the saving rates ofimmigrants in Australia. The possible presence

Table 4 Comparison of Immigrants’ Household Saving Rates in Australia, Averaged byTheir Country of Origin, with the Respective Country-of-Origin National Saving Ratesa

CountryNo. of

respondents

Averagehouseholdsaving ratein Australia

Standarddeviation

Country-of-originnational saving rate

China 37 10.50 0.63 53.77Italy 61 21.95 0.42 20.03Sri Lanka 40 24.56 0.29 22.37Vietnam 48 25.42 0.40 37.08India 48 25.97 0.42 36.03Netherlands 65 26.23 0.38 29.38Malaysia 35 27.51 0.41 38.41Ireland 31 28.76 0.31 29.83Philippines 69 30.38 0.30 30.79New Zealand 219 30.94 0.28 16.11United Kingdom 682 30.83 0.32 15.38South Africa 56 33.88 0.28 14.77Germany 69 35.11 0.31 23.55United States 34 36.09 0.32 14.74

Note: (a) Household saving rates in Australia that were calculated by using Household, Income and Labour Dynamics inAustralia Survey data are averaged for every country of origin, with at least 30 representatives. The average rates arecompared with the immigrants’ respective country-of-origin national saving rates from The World Bank (2010). The sampleis restricted to respondents aged 15 years or older who have non-missing country-of-origin data, with the household savingrates above –1.28 and below 0.79.



of country-of-origin effects was investigated bytesting whether household saving rates differbetween native-born and foreign-born Austral-ians. The analysis of relationship betweenimmigrants’ saving rates in Australia and therespective saving rate in their home countrywas carried out to test whether the savingdifferentials across countries stem not onlyfrom economic factors but also from country-specific differences.

The empirical results reported in this articleshow that: (i) immigrants have lower householdsaving rates than native-born residents; and (ii)a country’s characteristics influence the saving-related decisions of its people who migrate toAustralia. In particular, a country’s old-agedependency ratio and GDP per capita arepositively associated, and the country’s nationalhousehold saving rate and national saving rateare negatively associated, with the saving ratesof its emigrants to Australia.

The initial step of the analysis identified thefactors affecting the saving rates of Australianresidents and detected different saving rates forforeign-born individuals. An average Austra-lian resident has a higher saving rate if they areemployed, have a higher income, fewerchildren and are in committed relationship.However, the highest income-earners—house-hold heads—and their spouse contribute less tohousehold savings than other household mem-bers. Furthermore, saving rates are lower forBachelor or higher degree-holders but higherfor those with other post-school qualifications.At the same time, saving rates are significantlyhigher for individuals born in Australia than forthose born abroad. Owing to the savingdefinition used in this research, the observedsavings gap would be expected to be evengreater should data on immigrants’ remittancesbe available and accounted for.

By limiting the sample to immigrants andincluding their home-country characteristics, itwas possible to identify the country-of-origineffects on their saving rate in Australia. Thesaving rates of immigrants to Australia arepositively correlated with the ratio of the ageddependent population and GDP per capita. Thenegative correlation between saving rates ofimmigrants in Australia and the national

household saving rate in their respectivehome country, which is also evident for theirnational saving rate, is another rather surprisingfinding of this research. However, this isconsistent with the empirical evidence(Carroll, Rhee and Rhee 1999) that has failedto find a resemblance between the savingpatterns of American immigrants and theirrespective national saving rate. Carroll, Rheeand Rhee explained these results by either thedifferent reasons for migration of individualimmigrants with different social backgroundsfrom different countries or a strong correlationbetween immigrants’ saving behaviour in theUnited States and their initial socio-economicstratum.

A further contribution of this study is theevidence of negative relationships between thedomestic saving rates of immigrants toAustralia and their home countries’ nationalsaving rates and national household savingrates. These results suggest that either thedomestic saving rates do not account for theamounts remitted to their home countries byAustralian immigrants or that their savingpatterns change when they migrate. Onepossible reason for this change could be that,due to the lack of social security in their homecountry, immigrants were forced to save morethere than they do once they migrate toAustralia. In addition, immigrants’ high sav-ings in Australia could mean that they remithigh amounts to their less-developed homecountry that has low national saving rate.These hypotheses, however, require deeperanalysis and could be the direction of futureresearch.

Although the present version of HILDASurvey does not allow changes in savingspatterns over time to be evaluated nor the effectof remittances, this study has produced someimportant findings on the saving behaviour ofimmigrants. First, they save less than native-born Australians, even after controlling forincome, wealth and other demographic char-acteristics. Second, these differences can in partbe attributed to country-of-origin effects.

First version received January 2013;final version accepted July 2013 (Eds).



Appendix 1: Definition of Personal Variables

All personal variables are defined in Table A1 below.

Endnotes

1. The endogeneity of personal income and householdwealth is determined by using Hausman endogeneity test (F(2,8748)¼ 7.98***) and relevance of the excluded exoge-nous variables is measured by the post-estimation test usingincome for 2005 (F(2,8750)¼ 296,783***) and wealth for2002 (F(2,8750)¼ 304,488***) as instruments. *** indi-cates p< 0.01.

2. Details are available from the author on request.

3. Household heads in this research are defined ashousehold members who earn the highest income.

4. United Nations System of National Accounts (UnitedNations Statistics Division 2012) use different seriesnumbers to store different time-series versions of nationalaccounts statistics (depending on the methodology,currency used or the source). The latest series are usedfor this article.

5. There is no significant change in the results of theregression even if wealth is treated as exogenous.

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Table A1 Definition of Variables: Individual Characteristics

Variable Definition

Age Age as at 30 June 2006Wealth Household net worth (assets minus debts for the household)/10,000Income Ln(financial year disposable incomeþ 1)Expenses Household expenses including annual expenses for: groceries, alcohol, cigarettes and

tobacco, public transport and taxis, meals eaten out, motor vehicle fuel, clothing andfootwear, communication, holidays, insurance, medical treatments and medicines,utilities, home and motor repairs and education plus 10% of capital expenses, such ascost of new or used vehicle, computers, televisions, whitegoods and furniture,a plusannual rent and mortgage payments

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The Saving Behaviour of Immigrants and Home-Country Characteristics: Evidence from Australia

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