Household Finances, Financial Satisfaction and Subjective. Prosperity: An Empirical Analysis of Comparison Effects

Household Finances, Financial Satisfaction and Subjective Prosperity: An Empirical Analysis of Comparison Effects Daniel Gray (d.j.gray@sheffield.ac.uk) Institute for Economic Analysis of Decision-Making (InSTEAD) University of Sheffield Abstract This paper explores the importance of the households financial position for an individual s level of financial well-being. Initially, the empirical analysis, based on a large nationally representative panel survey, aims to ascertain the impact of the households monetary financial position on both financial satisfaction and subjective prosperity. Taking into account monetary factors in addition to income, the results indicate that the household s level of net wealth, assets and debt are important determinants of both measures of financial well-being. The study goes on to explore whether the financial position of households in a comparison group influence an individual s own level of financial satisfaction and subjective prosperity. The results provide evidence that the financial position of household s in the comparison group are important determinants of an individual s own level of financial well-being, with information effects dominating comparison effects. In addition, these comparison effects are asymmetric depending on whether a household s financial position is above or below that of the reference group and are different at different stages of the life cycle. Keywords: Fixed Effects Ordered Logit, Household Finances, Financial Satisfaction, Subjective Prosperity JEL codes: D14, I31, J28 1

1 Introduction and Background Overall life satisfaction is frequently argued to be made up of a variety of domains, such as financial satisfaction, see for example, Easterlin (2006), Van Praag and Ferrer-i Carbonell (2007) and Layard (2006). In this setting, it is assumed that specific behaviours influence certain domains, and in turn these domain satisfactions determine an individual s level of overall life satisfaction. In the existing literature, however, there remains a limited number of studies which explore the determinants of financial well-being, where a particular focus is placed on the role of monetary financial measures beyond income. The analysis presented in this paper aims to ascertain the impact of a variety of household financial measures, including the level of household assets and debt, in addition, to the household income, on financial well-being in Australia whilst account for individual heterogeneity. The paper then goes on to explore whether the financial position in a specified comparison group influences an individual s own level of financial well-being. In this context, based on potential interdependence of preferences and the importance of relative position, the financial position of household s in a comparison group could have a significant impact on an individual s own level of financial well-being. Financial well-being comprises of both objective and subjective aspects of ones financial position, and captures how content an individual is with their material and non-material financial position (Joo and Grable (2004)). This paper explores two measures of financial well-being, namely, financial satisfaction and subjective prosperity, as they potentially capture different aspects of financial well-being 1. In line with overall life satisfaction, financial well-being is frequently found to have a U-shaped age pattern, see, for example, Hansen et al. (2008) and Plagnol (2011). This observation is potentially at odds with prior expectations as an individual s income often dramatically decreases in old age, and consequently, one may expect financial well-being to fall in line with the observed decreases in income. One possible explanation for this observation is that older individuals become accustomed to lower levels of financial resources, that is, individuals revise their expectations and so report higher levels of financial satisfaction, despite their changing economic position. An alternative explanation for this phenomenon is that financial variables, in addition 1 These variables are defined in details in Section 2. 2

to income, are important determinants to financial satisfaction and subjective prosperity (Plagnol (2011)). The financial position of households across the developed world has dramatically changed over the past three decades, with household debt levels dramatically increasing. In Australia, the debt to income ratio has increased by 28% over the past decade. Statistics from the Reserve Bank of Australia (RBA) indicate that, in 2013, the debt to income ratio stood at 148%, however, this has fallen from its peak of 156% in 2006 2. The changing financial position of Australian household s is likely to have a significant impact on an individuals level of financial well-being. In the existing literature, relatively few studies explore the influence of assets and debt on financial well-being. Headey and Wooden (2004), using data from the 2002 wave of the HILDA survey explore the impact household net worth has on both subjective well-being and ill-being. The variables, which capture well-being, are overall life satisfaction and financial satisfaction. Focusing on the determinants of financial satisfaction, the results reveal that both income and net worth are positively associated with financial satisfaction. The analysis also reveals no gender effects and a U-shaped age pattern is present in financial satisfaction. Analysing the German Socio-economic Panel Survey and the British Household Panel Survey, Van Praag and Ferrer-i Carbonell (2007) explore the relationship between financial satisfaction, savings and income. Using a probit adapted OLS estimation technique, they find that household savings and income have positive impacts on the level of financial satisfaction in both counties. The analysis presented in this paper builds on the work by Van Praag and Ferrer-i Carbonell (2007) by considering the impact of household debt on financial well-being. Hansen et al. (2008) explore financial satisfaction in old age in Norway. Analysing the first wave of the Norwegian Life Course, Aging, and Generation Study (NorLAG), the analysis aims to assess whether assets and liabilities can explain increasing financial satisfaction in old age. The findings suggest that financial satisfaction is influenced by a wide range of financial measures beyond simply income. Furthermore, the study reports that a large proportion of the increase in the level of 2 Data taken from www.rba.gov.au. 3

financial satisfaction in old age can be explained by an increased level of assets and decreased levels of debt held in later life. However, it is still found that, at low levels of income and wealth, older individuals tend to be more financially satisfied than their equally poor younger counter parts. Plagnol (2011) considers the impact of assets and debts on financial satisfaction across the life course, using data from the second and third waves of the National Survey of Families and Households (NSFH). The analysis reveals that financial satisfaction is steadily increasing between the ages of 30 and 78. The findings also indicate that income follows a concave pattern over the life course, suggesting that financial satisfaction is influenced by other factors besides income. In line with prior expectations, the regression analysis reveals that financial satisfaction is increasing in income. The analysis also indicates that the increase in financial satisfaction in later life can be explained by an increase in the level of assets and a decrease in the debt level of the household. In a related study, Worthington (2006) analyses the Australian Household Expenditure Survey and considers the relationship between debt and financial stress in Australia. Household stress captures the inability to do certain things due to insufficient funds, such as going on holiday. Financial stress, amongst other things, is found to be lower in households with higher levels of disposable income and those with higher house values. The study finds that possessing high levels of household debt does not influence the household s financial stress. This lack of relationship is attributed to historically low mortgage rates, and so the cost of incurring extra debt does not contribute to the financial stress an individual experiences. In addition to the financial position of an individual s own household, an individual s level of financial well-being is potentially influenced by the financial position of other individuals. Based on the theory of the interdependence of preferences, it is anticipated that an individual s level of utility is not only related to personal circumstances but also the circumstances of a comparison group. For example, an extensive literature relating to overall life satisfaction aims to ascertain the relationship between income and well-being. In this literature, several studies assert not only the importance of ones own income, but also an individual s own income compared to the average in a comparison group. In these studies, it is anticipated that there will be a positive own income effect and a negative comparison income effect, see for example, Ferrer-i Carbonell (2005), Luttmer 4

(2005) and Clark et al. (2008). Alternatively, an increase in reference income could potentially be associated with an increasing in utility. This phenomenon, is potentially capturing positive ambition effects and is dubbed the information effect by Senik (2008) but was also called the tunnel effect by Hirschman and Rothschild (1973) in the context of economic development. Consequently, a higher reference income could potentially be perceived as relative deprivation, or an indicator of better future prospects. Senik (2008) argues that both the comparison effect and information effects are present, however, an individual s personal economic circumstances will determine which effect dominates the other. In addition to income, comparisons also apply to wider aspects of individual circumstances. For example, Blanchflower et al. (2009) find that individuals care not only about their own weight but also their weight relative to a comparison group. Similarly, Luttmer (2005), as a robustness check explore the relationship between household income of a reference group on a variety of other satisfaction variables in addition to overall life satisfaction. These include both satisfaction with current financial situation and financial concerns. The results presented indicated that neither financial satisfaction nor financial concerns are influenced by earnings in the reference group, only by own household income. In summary, this paper builds on the existing literature in two distinct ways. Firstly, it provides a longitudinal analysis of financial well-being in Australia, as measured by financial satisfaction and subjective prosperity, whilst controlling for the household s level of assets, debts and net wealth. The existing literature which explores financial well-being in Australia only consider crosssectional data. The the analysis presented here employs panel data techniques in order to account for individual heterogeneity which has previously been shown to be important when analysing subjective well-being measures. Secondly, the empirical analysis explores the impact of comparison effects on both financial satisfaction and financial prosperity. Specifically, it explores the relationship between the level of net wealth, total assets, total debt and both unsecured and secured debt of household s in a specified comparison group on an individual s level of financial satisfaction and subjective prosperity. In line with Ferrer-i Carbonell (2005), this paper explores the relevance of the average household finan- 5

cial position of a comparison group and the potential asymmetry of the comparison effects, that is whether an individual s household financial position is above or below that of the comparison group. To my knowledge, this is the first time the financial position, beyond income, of a comparison group has been accounted for when exploring the determinants of financial satisfaction and subjective prosperity. In addition, it explores whether the reference measure has a different impacts depending on the age of the individual consider. Arguably, the information effect may dominate in earlier life, however, in mid to later life comparison effects may prevail. 2 Data The empirical analysis is based on data drawn from the Household, Income and Labour Dynamics in Australia (HILDA) survey. The HILDA survey commenced in 2001 and is financed by the Australian Government with the Melbourne Institute of Applied Economic and Social Research being responsible for its design and management. The HILDA survey is a nationwide panel survey that contains a wide range of social, demographic and socio-economic information. Further details of the HILDA survey are described in Wooden et al. (2002). This chapter focuses on the 2002, 2006 and 2010 waves as these waves contain a supplementary wealth module. This wealth module includes detailed information on the households wealth, including the monetary values of a variety of assets and debts held by the household. The analysis presented in this paper draws on an unbalanced panel of 27,530 observations of individuals aged between 16 and 93. Financial well-being captures a variety of aspects relating to ones current financial position, including both subjective and objective measures. This paper explores two different measures of financial well-being, namely, financial satisfaction and subjective prosperity as the capture potentially different aspects of a household s level of financial well-being. In line with Headey and Wooden (2004), and similar to Plagnol (2011) and Hansen et al. (2008), financial satisfaction is based on the question, I am now going to ask you some questions about how satisfied or dissatisfied you are with some of the things happening in your life... Your Financial situation. This is measured on a eleven point scale, with zero lower levels of satisfaction, and higher numbers indicating being more 6

satisfied. The mean level of financial satisfaction is 6.40. The level of subjective prosperity is based on the question, Given your current needs and financial responsibilities, would you say that you and your family are... This is originally measured on a six point scale ranging from very poor to prosperous. However, due to a lack of observations 3 the lowest two categories are combined and as a result subjective prosperity is measured on a five point scale. The summary statistics are presented in Table 1 with the mean level of subjective prosperity is 1.81. This measure has been used extensively in the previous literature, and has been argued to capture a variety of different aspects of an individual s financial position. For example, Siahpush et al. (2007) use this variable to capture a individual s level of material well-being, where as, Cole et al. (2009) argue it captures financial deprivation. Similarly, Qu et al. (2009) interpret the responses this question to capture an individual s level of perceived prosperity. A variety of measures are used in order to capture the household s financial position. These measures include the household s disposable income, the household s level of net wealth, the total level of assets, total debt levels and the level of unsecured debt and secured debt. These variables are based upon the derived variables contained in the HILDA survey, with a brief description provided here, however more extensive explanation of the variables are contained in the user documentation. The level of household disposable income is defined to be the household s gross income from all sources minus estimated taxes. In some instances this calculation returns a non-positive income and consequently, these are omitted from the analysis. The household s level of net wealth is defined to be the level of household assets minus total debt, where total assets is defined to be the summation of the household s financial financial and tangible assets and total debt is the summation of secured and unsecured debt. The level of secured debt refers to any debt secured against a property, whilst unsecured debt is all other debt held by the household. In line with Gropp et al. (1997) the empirical analysis includes the natural logarithm of each of the monetary measures which are inflated to 2010 levels 4. 3 0.66% of respondents reported very poor. 4 Where assets and debt take a positive value, the natural logarithm is simply taken. Where these variables are zero the natural logarithm is defined to be zero. When the value of net wealth is negative, the natural logarithm of net wealth is defined to be ln( nw ). 7

In order to capture potential relative effects, it is required to construct a comparison group for each individual to be compared. In this paper, similar to Ferrer-i Carbonell (2005), an individuals comparison group is based on a variety of characteristics including the respondents age, education level, gender, geographical region and wave they were surveyed. Education is divided into four categories according to the highest level of education obtained: below high school, high school, vocational degree and degree or above. In line with FitzRoy et al. (2013), individual s are argued to compare themselves to individual s 3 years younger than them and 6 years above them. The geographical region is based on major statistical region, which comprises of 12 different regions. In addition, the reference group is defined across each of the three years analysed here. The first specification is simply the average (mean) of the financial measures of household s in the comparison group. In line with Ferrer-i Carbonell (2005), the natural logarithm of financial measures of the reference group is included in the analysis. If the comparison effect dominates the information effect, it is anticipated that the higher the level of income, net wealth and total assets of the reference group the less satisfied and less prosperous an individual will feel. Similarly, the higher the level of total, secured and unsecured debt in the comparison group, the more financially satisfied and more prosperous an individual will feel. However, if the average financial position of the comparison serves to provide information to an individual, the the opposite relationships are potential expected. The next specification aims to capture whether the comparison effects are symmetric depending if a household s financial position is below or above that of the comparison group. Following Ferrer-i Carbonell (2005) and Duesenberry (1949), it is anticipated that an individual s level of financial wellbeing will be negatively affected if their financial position is worse than that of the comparison group, whilst, if there financial position is better than their reference group, then it is not expected to influence an individuals level of financial satisfaction. Let F M and F M r be the household own financial measure and the financial measure in the reference group, respectively, then in line with Ferrer-i Carbonell (2005), these measures are constructed as follows: if F M > F M r then P ositivef M = Ln(F M) Ln(F M r ), NegativeF M = 0. If F M < F M r then P ositivef M = 0, NegativeF M = L(F M r ) Ln(F M), and if F M r = F M, then P ositivef M = NegativeF M = 0. In this paper, having the income, net wealth, and total assets below that of the comparison group 8

will adversely affect financial well-being, whist having debts above the comparison group will be associated with lower levels of financial well-being. Alternatively, the opposite relationship could be displayed is the relative group provides information about the potential future position of an individual. In order to explore different effects across the age range, the analysis presents the results for two sub-samples of the data, these are namely, individual s less than 50 years of age and those aged 50 years and above. The summary statistics of the variables which measure the household financial position and those of the comparison groups are presented in Table 1. In line with the existing literature a variety of demographic and socio-economic variables are also accounted for in the empirical analysis. These include age and age squared, in order to capture the potential U-shaped age pattern. The highest education attainment is also controlled for via a series of dummy variables which capture if the highest level of education is high school, vocational degree and degree or above. The omitted category is defined to be below high school level. The number of people in the household is also accounted for as the number of people present in the household is closely related to the level of living expenses experienced by the household. This is anticipated to be inversely related to an individuals level of financial well-being. Compared to being married, whether the respondent is divorced or separated, widowed or never married is included in the analysis. The employment status is also included, these capture whether the individual is unemployed, retired or not in the labour force. These are compared to employed individuals. In line with Plagnol (2011), health status is captured by self assessed health. Table 1 presents the summary statistics relating to all the dependent and independent variables used in the empirical analysis. Due to a fixed effects specification being implemented in this paper, time invariant characteristics, such as gender are not accounted for in the empirical analysis. 3 Methodology The analysis of financial satisfaction and subjective prosperity employs the methodology proposed by Baetschmann et al. (2011), namely the fixed effects ordered logit model estimated via the Blow-up and Cluster estimator. This approach has been used to analyse overall life satisfaction a 9

variety of contexts, however, it is appropriate to analysed both financial satisfaction and subjective prosperity as they are both ordinal measures, where individual heterogeneity is likely to influence the results. Following Ferrer-i Carbonell and Frijters (2004), it is important to account for individual heterogeneity when analysing subjective well-being measures. The underlying model is based upon the latent variable model, y it = x itβ + α i + ɛ it, i = 1,..., N, t = 1,..., T (1) where yit is a latent measure of the ith head of household s financial satisfaction or subjective prosperity in period t, x it is the vector of observable characteristics, and β is a vector of coefficients to be estimated. α i is a time invariant unobserved component and ɛ it in a white noise error term. What is, however, observed is y it y it = k if µ k < y it µ k+1, k = 1,..., K. (2) Where the threshold parameters µ k are assumed to be strictly increasing for all values of k, and µ 1 = - and µ K+1 = +. It is assumed that the white noise error term, ɛ it is independently and identically distributed (IID) by the logistic distribution, it follows that the probability of observing outcome k for individual i in time period t is given as: P r(y it = k x it, α i = Λ(µ k+1 x itβ α i ) Λ(µ k x itβ α i ) (3) where Λ(.) represents the cumulative logistic distribution. To consistently estimate the coefficients of β, it is required that the K levels of y it are dichotomized, that is collapsed into binary outcomes. This estimation method is called the Blow-Up and Cluster (BUC) estimator. The estimator initially blows-up the sample size by replacing every observation in the sample by K 1 copies of itself, and then dichotomises every K 1 copy of the individual at a different cut off point. The conditional maximum likelihood logit estimate is then estimated using the entire sample, giving the BUC estimates 5. 5 The fixed effects ordered logit model is implemented in STATA using the bucologit command proposed by Dickerson et al. (2012). 10

One potentially limiting factor for the BUC fixed effects estimator is that it is not possible to calculate the marginal effects relating to each of the parameter estimates. It is possible however to comment on the sign and significance of each of the estimates. 4 Results 4.1 Life Time Patterns Initially, the descriptive statistics of the measures of financial satisfaction and subjective prosperity are further explored. Figure 1 plots the level of financial satisfaction against age whilst Figure 2 present the average level of financial prosperity. Both figures clearly show, in line with Plagnol (2011) and Hansen et al. (2008), a clear improvement in financial satisfaction and subjective prosperity in older age. This observation, is potentially counter intuitive as the level of income significantly drops in later life. Consequently, is is argued that monetary factors beyond income are important determinants of both financial prosperity and financial satisfaction. Figure 3 plots the average level of the household s level of household income, total assets and total debt by age. It clearly shows that level of household income slightly decrease into old age, as does the level of household assets. However, what is apparent is the significant drop in the level of debt held by the household, which dramatically falls beyond the age of 60. This potentially suggests that this reduction in debts could be driving up financial satisfaction and subjective prosperity in older age groups. In addition to financial variables, financial satisfaction and subjective prosperity will depend on an individual s financial needs. Consequently, various aspects of an individual s life will put a different stresses on an individual s financial position. For example, increases in the number of individual s and children in the household could increase the cost of living in the household, and as a result influence the level of financial satisfaction and subjective prosperity. Household size potentially falls in later life, due to children leaving, and consequently, this could be associated with higher levels of financial well-being, due to a reduction in living expenses. Similarly, it is likely that 11

Figure 1: Financial Satisfaction Figure 2: Subjective Prosperity 12

Figure 3: Financial Measures factors like health and relationship status will also be important determinants of financial wellbeing. Consequently, it is important to account for aspects other than financial measures when exploring the determinants of financial satisfaction and subjective prosperity. This is done in the subsequent regression analysis. 4.2 Financial Satisfaction and Subjective Prosperity Table 2 presents the coefficients of the determinants of financial satisfaction, whilst Table 3 presents the results relating to subjective prosperity. Both tables present four specifications which capture different aspects relating to the household s financial position. Specification 1 includes the household income, but no other monetary measures. Specification 2 includes the households level of net wealth with Specification 3 separating net wealth into total debt and total assets. Specification 4 further separated total debt into the household s level of secured and unsecured debt. Specification 1 of Table 2 indicates that financial satisfaction is inversely related to being unemployed and being divorced. Better health is associated with higher levels of financial satisfaction, 13

whilst a U-shaped age pattern is present as indicated by negative age coefficient and a positive age squared coefficient, however this relationship is not consistent across the different specifications considered. Once the net wealth is disaggregated into total assets and total debt, age is not found to be a statistically significant impact on financial satisfaction, potentially indicating the financial position of the household explains this U-Shaped age pattern. The results indicate that household income is positively related to the level of financial satisfaction. This result accords with the findings of both Plagnol (2011) and Hansen et al. (2008). Focussing on the financial variables included in Specifications 2, 3 and 4 show that all of the variables have the expected impacts on financial satisfaction. That is, net wealth and total assets are positively related to financial satisfaction. In addition, all types of debt (total, secured and unsecured) are inversely related to financial satisfaction. These findings show that the results presented in Headey and Wooden (2004) are robust to accounting for individual heterogeneity. Considering the determinants of subjective prosperity, presented in Table 3, provides evidence that, in line with Figure 2, a convex age pattern is present, as indicated by negative and positive coefficients on the age and age squared parameters, respectively. In line with prior expectations, the level of household disposable income increases perceived financial prosperity, whilst the number of people present in the household is inversely related to subjective prosperity. This result potentially captures the reduction in living expenses being associated with higher levels of subjective prosperity. Compared to being married, being divorced or separated and being a widow are associated with lower levels of financial prosperity. In addition, better health is also associated with higher levels of subjective prosperity. Specifications 2, 3 and 4 of Table 3 suggest that the results are consistent with the results of financial satisfaction presented in Table 2. Both household net wealth and total assets are positively related to subjective prosperity, whereas, all types of debt are inversely related to financial prosperity. Once again these findings reinforce the fact monetary financial variables beyond income are important determinants of subjective prosperity. The results from the empirical analysis presented in this section lend support to the results found 14

in other developed countries. In line with Plagnol (2011) and Hansen et al. (2008), who explore the determinants of financial satisfaction in the USA and Norway, respectively, we observed a significant increase in the level of financial satisfaction in later life. This phenomenon is also observed for an individual s level of subjective prosperity. On potential explanation for this is that people revise down their expectations and therefore adapt to lower levels of income. An alternative suggestion presented by Plagnol (2011), and supported here is that this increase in financial satisfaction and subjective prosperity is as a result of decreasing debt level so in later life. The analysis indicates it is important to account for monetary factors beyond income when considering the determinants of financial satisfaction and subjective prosperity. The next section goes on to assess whether the financial position of a comparison group influences either an individual s level of financial satisfaction or subjective prosperity. 4.3 Relative Financial Position This section explores whether the financial position of household s in a comparison group influences an individual s level of financial satisfaction and subjective prosperity. Tables 4 and 5 includes the basic measure of relative financial position, that is the natural logarithm of the mean of the specified comparison group for each monetary financial measure, for financial satisfaction and subjective prosperity, respectively. Tables 6 and 7 present the results for when a differential impact is allowed for whether the household s financial position is above or below of that of the comparison group. In line with the previous section, a series of four specifications are implemented as a consequence of the construction of the household s financial variables. In addition, these tables present the analysis for both the whole sample and both sub-samples aged above and below 50 years of age. This will allow the exploration of whether the relationships are different at different stages of the life course. Focusing on the financial variables for the whole sample, the results presented in Table 4 show that the inclusion of the relative financial position does not change the coefficients relating to the household s financial position, that is, total assets and net wealth are positively related to financial satisfaction, whilst all types of debt (total, unsecured and secured debt) are inversely related. The results indicate that the average income of household s in the comparison group does 15

not have a statistically significant impact on an individual s level of financial satisfaction. The results however suggest that financial satisfaction is increasing in the average level of net wealth in the reference group. This result potentially supports the idea of information or tunnel effects as it potentially suggests the level of net wealth an individual could potentially possess in the future. The sample split clearly demonstrates the difference between the two age ranges, with the net wealth of household s in the comparison group displaying a positive and statistically significant impact on financial satisfaction for younger individual s but is found to be a statistically insignificant determinant for individual s age 50 or above. Separating the net wealth into total assets and total debts, shows that the relationship between comparison net wealth and financial satisfaction is driven by the a household s level of assets in the comparison group opposed to total debt levels. Across the entire samples and both age ranges, the level of total debt held by household s in the comparison group fails to be a significant determinant of financial satisfaction. The level of total assets of the comparison group is found to increase financial satisfaction in the full sample, and it is apparent in the younger sub-sample, but not the older sample. Once again this result suggests that the average financial position of the comparison group potentially provides information to younger individual s. The level of secured and unsecured debt is not found to be a significant determinant of financial satisfaction. Table 5 presents the results relating to subjective prosperity. Similar to financial satisfaction, the household s monetary financial measures maintain the same relationship to subjective prosperity as in the previous section. In addition, the analysis for financial satisfaction, the average net wealth of household s in the comparison group have a positive impact on ones own subjective prosperity. The level of total debt of the comparison group is inversely related to subjective prosperity. This result is potentially unsurprising, as higher levels of debt of the comparison group, could provide information that a household will potentially have to incur higher levels of debt, and as a result will have a negative impact on subjective prosperity. Once again the level of total assets of the comparison group has a positive impact on subjective prosperity, once again lending support that the reference category providing information. The level of secured debt is inversely related to subjective prosperity, and it is apparent that this result is driven by individual s aged 50 or above. 16

Tables 6 and 7 present the results relating to the potentially asymmetric effects of the comparison group. Tables 6 indicates that having a household income above that of the comparison group has a positive impact on financial satisfaction, whereas, having income below the comparison group does not have statistically significant impact of financial satisfaction. This result is at odds with both Ferrer-i Carbonell (2005) and Duesenberry (1949). Interestingly, having a level of net wealth either below or above that of the comparison group are positively related to financial satisfaction. This could suggest that individual s with a level of net wealth below that of the average gain utility as it show potential information effects. In addition, if you have a a level of net wealth above that of reference group, individuals feel more prosperous. Considering the two age sub-samples reveals that these results are driven by younger individual s rather than older individual s. Specifications 3 and 4 of Panel 1 of Table 2 of show that having assets below that of the comparison group has a positive impact on financial satisfaction. Once again, this suggest evidence of the tunnel effect and as a result, one would expect this relationship to be more apparent in younger individuals. The younger sub-sample shows that having a level of total assets below the comparison group has a positive impact, where as it is statistically insignificant in the older panel. Table 7 suggests that having a level of income below the comparison group has a positive impact on subjective prosperity, once again potentially indicating information effects. Similarly, in line with financial satisfaction, having net wealth above or below that of the comparison group has positive effects on subjective prosperity, and once again these results are driven by the younger sub-sample. Having total debt below the average of the comparison group has a detrimental impact on subjective prosperity, and this result is apparent in individual s aged 50 or above. Once again this potentially indicates that the level of debt of the comparison group provides information of a individual s future debt levels. As a consequence an individual s level of subjective prosperity could be reduced if they anticipate they are to incur higher debt levels in the future. Having total assets below that of the comparison group has a positive impact on subjective prosperity, and this result is more prevalent in younger individuals. Having a level of secured debt below that average of the comparison group, has a negative impact on subjective prosperity. This result is driven by older individual s and perhaps indicates future debt older individual s potentially have 17

to incur into retirement, and consequently, have a detrimental impact on subjective prosperity. The analysis presented in this section shows that the financial position of household s, with arguably similar characteristics, influence an individual s own level of financial well-being. Furthermore, the empirical analysis lends support to the idea s presented by Hirschman and Rothschild (1973) and Senik (2008) with many of the comparison effects potentially providing future information about their own households financial position. In addition, the results suggest distinct differences between younger and older individual s when considering the effects the reference group. 5 Conclusion Overall life satisfaction has received considerable attention in the existing literature, however the exploration of the determinants of financial well-being remains relatively sparse. Initially, this paper aimed to ascertain the determinants of both financial satisfaction and subjective prosperity, where a particular focus was placed on the role of the household s financial position. The paper then explored the relationship between the financial position of household s in a comparison group on an individual s level of financial well-being. The empirical analysis analysed panel data drawn from the 2002, 2006 and 2010 waves of the HILDA survey. In line with the existing literature which explores financial well-being in other countries, the analysis presented in this paper indicates that both financial satisfaction and subjective prosperity are Ushaped over the life course, with it increasing in old age, despite a reduction of income in this period of life. This pattern potentially indicates that monetary factors beyond income are important determinants of both financial satisfaction of subjective prosperity. In a fixed effects framework, in order to account for individual heterogeneity, the empirical analysis presented in this paper found that the level of net wealth and assets are positively associated with both financial satisfaction and subjective prosperity, whilst all types of debt (total, secured and unsecured) are inversely related. These results outline the importance to account for financial factors beyond income when analysing financial satisfaction. In addition, it potentially suggests that 18

the level of household debt and assets are important determinants of both financial satisfaction and subjective prosperity, and consequently, are an important determinants of overall life satisfaction. Consequently, the high debt levels currently observed in Australia could be having a detrimental impact on individual well-being. The paper then explored whether the financial position of a comparison group influences an individual s level of financial well-being. In the existing literature, the relationship between comparison incomes and overall life satisfaction has been extensively explored. This study developed the existing literature by exploring the impact of the financial position of household s in a specified comparison group on an individual s level of financial well-being. Consequently, a variety of monetary variables, namely the level of income, net wealth, total assets and total debt and both secured and unsecured debt, of the comparison group were considered. The empirical analysis shows that comparison effects are present in financial measures other than income. More specifically these results supports the idea of information and tunnel effects, that is the financial position of the comparison group provide information on a household s potential future financial position. Further research could explore the impact of different specifications of the comparison group. More detailed geographical data could potentially allow more detailed specification of the comparisons group, and will potentially enable the identification of household s who individual s are more likely to compare themselves to. 19

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Table 1: Summary statistics Variable Mean Std. Dev. Min. Max. Dependent Variables Financial Satisfaction 6.404 2.255 0 10 Subjective Prosperity 1.809 0.764 0 4 Independent Variables Female 0.537 0.499 0 1 Age 46.206 17.039 16 93 Age Squared/100 24.253 16.823 2.56 86.49 Degree 0.229 0.42 0 1 Vocational Degree 0.308 0.462 0 1 High School 0.143 0.35 0 1 Ln(Household Size) 0.901 0.529 0 2.565 Never Married 0.181 0.385 0 1 Divorced/Separated 0.096 0.294 0 1 Widow 0.051 0.22 0 1 Not in Labour Force (NLF) 0.108 0.311 0 1 Unemployed 0.028 0.166 0 1 Retired 0.211 0.408 0 1 Excellent Health 0.108 0.31 0 1 Very Good Health 0.359 0.48 0 1 Good Health 0.361 0.48 0 1 Fair Health 0.141 0.348 0 1 Financial Variables Ln(Household Income) 10.985 0.739 3.219 13.234 Ln(Net Wealth) 11.894 4.279-14.908 16.47 Ln(Total Debt) 7.806 5.249 0 14.979 Ln(Total Assets) 12.765 1.861 0 16.51 Ln(Secured Debt) 5.389 5.954 0 15.05 Ln(Unsecured Debt) 5.312 4.86 0 15.187 Reference Group - Financial Position Ln(Reference Income) 11.139 0.4 4.7 12.628 Ln(Reference Net Wealth) 13.183 0.807-11.436 15.744 Ln(Reference Total Assets) 13.505 0.613 0 15.904 Ln(Reference Total Debt) 10.921 2.446-0.288 14.285 Ln(Reference Secured Debt) 10.22 3.402 0 13.945 Ln(Reference Unsecured Debt) 9.274 2.387-0.288 14.045 Positive - Income 0.149 0.257 0 2.368 Negative - Income 0.303 0.485 0 7.931 Positive - Net Wealth 0.241 0.436 0 3.095 Negative - Net Wealth 1.53 4.023 0 28.974 Positive - Total Assets 0.193 0.377 0 2.786 Negative - Total Assets 0.934 1.565 0 14.354 Positive - Total Debt 0.248 0.502 0 3.743 Negative - Total Debt 3.363 4.328 0 14.285 Positive - Secured Debt 0.248 0.501 0 3.892 Negative - Secured Debt 5.079 5.382 0 13.581 Positive - Unsecured Debt 0.225 0.557 0 3.889 Negative - Unsecured Debt 4.187 4.292 0 14.045 Number of Observations 27,530 22

Table 2: Determinants of Financial Satisfaction Specification Independent Variable 1 2 3 4 Ln(Household Income) 0.388*** 0.349*** 0.321*** 0.322*** (0.0432) (0.0430) (0.0436) (0.0436) Ln(Net Wealth) 0.0385*** (0.00494) Ln(Total Debt) -0.0488*** (0.00519) Ln(Total Assets) 0.220*** 0.220*** (0.0214) (0.0227) Ln(Secured Debt) -0.0208*** (0.00437) Ln(Unsecured Debt) -0.0386*** (0.00450) Age 0.0145 0.0112 0.00510 0.00161 (0.0144) (0.0144) (0.0143) (0.0143) Age Squared/100 0.0596*** 0.0599*** 0.0550*** 0.0585*** (0.0143) (0.0142) (0.0142) (0.0142) Degree -0.0400 0.0101 0.0438 0.0861 (0.167) (0.168) (0.167) (0.168) Vocational Degree -0.0633-0.0345-0.00538 0.0153 (0.119) (0.121) (0.122) (0.122) High School -0.371*** -0.323*** -0.265** -0.237** (0.116) (0.117) (0.119) (0.120) Ln(Household Size) -0.383*** -0.457*** -0.559*** -0.539*** (0.0600) (0.0608) (0.0641) (0.0644) Never Married -0.176** -0.216** -0.275*** -0.259*** (0.0851) (0.0854) (0.0858) (0.0858) Divorced -0.855*** -0.872*** -0.881*** -0.878*** (0.105) (0.105) (0.108) (0.108) Widowed -0.418** -0.445*** -0.437*** -0.444*** (0.171) (0.169) (0.170) (0.169) NLF -0.502*** -0.496*** -0.518*** -0.518*** (0.0661) (0.0665) (0.0669) (0.0669) Unemployed -1.332*** -1.337*** -1.332*** -1.336*** (0.105) (0.108) (0.109) (0.109) Retired -0.0241-0.0330-0.0656-0.0667 (0.0934) (0.0929) (0.0926) (0.0923) Excellent Health 0.933*** 0.926*** 0.926*** 0.947*** (0.135) (0.135) (0.135) (0.135) Very Good Health 0.590*** 0.573*** 0.584*** 0.596*** (0.121) (0.122) (0.122) (0.122) Good Health 0.394*** 0.388*** 0.397*** 0.409*** (0.118) (0.118) (0.118) (0.118) Fair Health 0.0855 0.0815 0.0938 0.106 (0.112) (0.112) (0.113) (0.113) Observations 62,020 62,020 62,020 62,020 Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 23

Table 3: Determinants of Subjective Prosperity Specification Independent Variable 1 2 3 4 Ln(Household Income) 0.721*** 0.679*** 0.606*** 0.609*** (0.0611) (0.0612) (0.0616) (0.0617) Ln(Net Wealth) 0.0486*** (0.00609) Ln(Total Debt) -0.0413*** (0.00622) Ln(Total Assets) 0.303*** 0.304*** (0.0261) (0.0278) Ln(Secured Debt) -0.0197*** (0.00502) Ln(Unsecured Debt) -0.0310*** (0.00523) Age -0.0769*** -0.0831*** -0.0991*** -0.101*** (0.0168) (0.0169) (0.0173) (0.0172) Age Squared/100 0.119*** 0.121*** 0.122*** 0.125*** (0.0170) (0.0170) (0.0173) (0.0172) Degree -0.241-0.184-0.0945-0.0798 (0.190) (0.194) (0.195) (0.196) Vocational Degree -0.261* -0.218-0.181-0.169 (0.139) (0.141) (0.140) (0.140) High School -0.584*** -0.531*** -0.460*** -0.446*** (0.132) (0.135) (0.142) (0.143) Ln(Household Size) -0.292*** -0.379*** -0.542*** -0.523*** (0.0714) (0.0722) (0.0751) (0.0751) Never Married 0.0861 0.0495-0.0259-0.0144 (0.0945) (0.0961) (0.0982) (0.0979) Divorced -0.846*** -0.880*** -0.869*** -0.866*** (0.124) (0.125) (0.127) (0.127) Widow -0.501** -0.561*** -0.595*** -0.600*** (0.216) (0.211) (0.209) (0.212) NLF -0.335*** -0.327*** -0.339*** -0.339*** (0.0737) (0.0747) (0.0749) (0.0751) Unemployed -0.770*** -0.756*** -0.746*** -0.749*** (0.123) (0.126) (0.128) (0.129) Retired -0.0549-0.0651-0.0885-0.0924 (0.109) (0.108) (0.108) (0.108) Excellent Health 1.374*** 1.361*** 1.357*** 1.383*** (0.163) (0.161) (0.165) (0.165) Very Good Health 1.122*** 1.093*** 1.087*** 1.107*** (0.148) (0.147) (0.150) (0.151) Good Health 0.801*** 0.787*** 0.780*** 0.795*** (0.143) (0.142) (0.145) (0.145) Fair Health 0.478*** 0.472*** 0.480*** 0.491*** (0.138) (0.136) (0.140) (0.140) Observations 16,852 16,852 16,852 16,852 Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 24