Financial Literacy and Retirement Planning in Australia

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Introduction

Financial literacy scores relate positively to numeracy skills. It is difficult for

individuals to make effective financial decisions if they are unable to apply basic

mathematical calculations to their situation. Decisions such as allocating assets in

retirement portfolios, determining saving rates, evaluating mortgage product

options, and/or managing credit card debt require individuals to possess an

understanding of how to calculate compound interest as well as an asset’s risk and

return. Individuals must also be capable of interpreting the results. Without this

ability, the decision maker cannot adequately consider his or her options. The link

between quantitative literacy and financial literacy is supported by research.

Gilliland et al. (2011) highlight the positive association in their recent analysis of

Michigan State University students. Furthermore, a close examination of one of

the most popular financial literacy measures—three survey questions that have

been dubbed the Big Three—reveals that mathematical calculations are necessary

to correctly answer two of the three questions. As a result, studies of the effect of

financial literacy on behavior should be of particular interest to researchers in the

field of numeracy.

This paper uses the aforementioned Big Three measure to learn more about

financial literacy and how it relates to retirement planning in Australia. As

changes in retirement systems around the world produce shifts toward more

personal responsibility for financial decision-making, research measuring

financial knowledge and assessing how it relates to financial decisions is

becoming increasingly important. Our paper extends research recently conducted

for a global project on financial literacy and contributes to the literature by

providing new results for Australia that are directly comparable to other country

studies. Notably, before this global initiative, it was often difficult to compare

financial literacy studies due to the various methods for measuring financial

literacy and for analyzing the resulting data. This paper also adds to the literature

by examining a country whose retirement system features many personal choice

elements, making it a compelling and relevant case to study in this context.

The Australian experience is important to study because Australia was one of

the first developed countries to introduce mandatory private saving as the main

earnings-related component of the country’s retirement income system.

Consequently, almost all adult Australians are required to interact with

increasingly complex private and public arrangements for retirement

accumulation and decumulation and are exposed to investment, inflation, and

Agnew et al.: Financial Literacy and Retirement Planning in Australia

Published by Digital Commons @ University of South Florida, 2013

longevity risks.

The mandatory private saving program is referred to as the

Superannuation Guarantee in Australia. This program requires employers to make

mandatory contributions to a retirement plan of the employee’s choice.

Currently, about 95% of full-time workers are covered by this program (ABS

2012). Generally, these plans are designed as defined contribution plans very

similar to US 401(k) plans. The mandatory contributions by employers are

substantial and are currently increasing from 9% of the employee’s salary to 12%.

When the system is fully mature, the balances in these plans will be the key

component of accumulated retirement savings. Australians may also make

voluntary contributions to these plans and contribute to other personal savings

accounts to prepare for retirement. Finally, Australians who meet certain income

and asset criteria are also eligible for retirement support from a government

program called the Age Pension, which is financed through general tax revenues.

The Age Pension provides basic financial support, and in most cases does not

replace pre-retirement standards of living.

While Australian retirement savers do not have to decide whether to

participate in retirement saving plans, as they are mandatory, they are responsible

for decisions relating to the plan in which superannuation savings are managed

and accumulate (including whether to create their own “self-managed

superannuation fund” [SMSF] plan), for plan management (such as consolidation

of multiple plans), for choice of investments (from increasingly long menus of

single- and multi-manager diversified and single options, and often individual

asset classes), for whether to make or increase voluntary contributions (for which

the tax rules differ by type and contribution amount), for whether to seek and use

financial advice, and for which benefit(s) to take at retirement. These decisions

can be overwhelming. While financial advice is readily available, it is not clear

whether ordinary Australians can afford advisor fees and have the skills and

experience to discern advice quality (ASIC 2012). Regardless, the efficient

functioning of the system depends on participants being well-informed and having

sufficient financial skills. This paper provides additional insight into whether this

is a valid presumption.

All of the above suggest that Australian workers and retirees face

considerable challenges navigating the complex financial products and policies

required for retirement planning. Previous literature has identified poor financial

literacy and lack of knowledge about superannuation across the Australian

population but has not specifically linked objective measures of financial literacy

A short description of the system can be found in Agnew (2013). A more detailed description can

be found in Bateman et al. (2013).

These plans are called superannuation funds in Australia. Given that the word fund may cause

confusion for non-Australians who often think of a fund as a single investment option, we will

refer to superannuation funds as plans in this paper.

Numeracy, Vol. 6 [2013], Iss. 2, Art. 7

https://digitalcommons.usf.edu/numeracy/vol6/iss2/art7

DOI: http://dx.doi.org/10.5038/1936-4660.6.2.7

with retirement planning (ANZ 2011). Croy et al. (2010) investigate how self-

assessed (rather than objective) financial knowledge relates to two financial

behaviors, specifically the intention to contribute extra to retirement plans and the

intention to change investment allocations. Bateman et al. (2012) measure

financial literacy consistent with our proposed approach but do not relate financial

literacy to financial behaviors, such as retirement planning.

In this paper, we use a new customized survey administered to a

representative sample of 1,024 Australians over age 18 from the Pureprofile Web

Panel of over 600,000 Australians to examine the relationship between financial

literacy and retirement planning. Overall we find that aggregate levels of financial

literacy in Australia are similar to comparable countries with the young, women,

those who are least educated, those who are not employed, and those not in the

labor force most likely to exhibit low financial literacy levels. Our age results are

somewhat difficult to interpret given a potential selection bias. We discuss

possible explanations for this in the text.

This paper is laid out as follows: In the next section we describe the

important features of our data set and present summary statistics related to

financial literacy. Following that, we examine how financial literacy relates to

retirement planning. Our final section concludes.

Data Overview and Summary Statistics

To study the relationship between financial literacy and retirement planning, we

commissioned a new survey of the Australian population. The survey used the

Pureprofile Web Panel and was fielded in June 2012 via the Internet. The

Pureprofile Panel includes over 600,000 Australians. Our final sample of 1,024

individuals was designed to be representative of Australia’s general adult

population. Survey respondents were required to be over 18. Pureprofile

compensated individuals completing the survey for their participation.

Respondents were not required to be the head of the household or the person

responsible for making financial decisions.

In terms of response rates, a traditional response rate measure could not be

computed because online surveys are administered in a different manner than

standard telephone and paper surveys. Therefore, we report the completion rate, a

commonly used metric for measuring responses to online surveys. For this survey,

Pureprofile sent survey invitations to individuals in their established pool who

met the study criteria. Out of the 1,245 who entered the survey, 1,024 (82.2%)

Gerrans et al. (2009) and ASIC (2011) provide useful summaries of research related to

Australian financial literacy undertaken in the past few years.

Agnew et al.: Financial Literacy and Retirement Planning in Australia

Published by Digital Commons @ University of South Florida, 2013

completed all the questions. A small number (6.1%) were screened out due to

non-consent or because the quota for the demographic they represented had been

filled. The remaining 11.7% started the survey but did not complete it.

While the focus of this paper is on retirement planning and basic financial

literacy responses, the survey also included questions to test the respondent’s

knowledge of Australia’s superannuation system. In addition, measures of

personality traits, numeracy skills, financial behavior, attitude toward and use of

financial planners, and perceptions of time until retirement were included. These

factors will be studied in future papers.

Findings Regarding Financial Literacy

In order to evaluate the financial literacy of Australians, we asked survey

participants three financial literacy questions that address basic economics and

finance concepts. The responses to these questions provide financial literacy

measures that are comparable with results from other papers.

The three

questions, called the Big Three, were developed by Lusardi and Mitchell (2011a)

and have been frequently used in other literature, including a series of papers

published in a special issue of the Journal of Pension Economics and Finance that

focused on financial literacy and retirement planning in eight countries including

Germany, the Netherlands, Sweden, Japan, Italy, the United States, Russia, and

New Zealand.

The wording of the questions is as follows (correct answers are indicated with

two asterisks):

Understanding of Interest Rate (Numeracy): Suppose you had $100

in a savings account and the interest rate was 2% per year. After 5

years, how much do you think you would have in the account if you

left the money to grow?

More than $102 **

Exactly $102

Less than $102

Do not know

Refuse to answer

Understanding of Inflation. Imagine that the interest rate on your

savings account was 1% per year and inflation was 2% per year. After

These basic financial literacy questions have been asked in other surveys conducted by the

authors using Pureprofile’s Web Panel. However, there is a low probability that individuals in this

sample have seen the questions before in one of these surveys.

See Alessie et al. 2011; Alemenberg and Säve-Söderbergh 2011; Bucher-Koenen and Lusardi

2011; Crossan et al. 2011; Fornero and Monticone 2011; Klapper and Panos 2011; Lusardi and

Mitchell 2011b; and Sekita 2011.

Numeracy, Vol. 6 [2013], Iss. 2, Art. 7

https://digitalcommons.usf.edu/numeracy/vol6/iss2/art7

DOI: http://dx.doi.org/10.5038/1936-4660.6.2.7

1 year, how much would you be able to buy with the money in this

account?

More than today

Exactly the same

Less than today **

Do not know

Refuse to answer

Understanding of Risk Diversification. Buying shares in a single

company usually provides a safer return than buying units in a

managed share fund.

True

False **

Do not know

Refuse to answer

The first two questions address economic topics related to saving for

retirement, including calculating interest rates and understanding the effect of

inflation on purchasing power. Correct responses to these questions require that

one has numeracy skills. The third question is related to investments and is

designed to measure understanding of the concept of diversification.

Table 1 provides a summary of respondents’ answers. Two stars denote again

the correct answers for each question. The sample is broken down into two

groups: the full sample, which includes retired and non-retired individuals age 18

to 85, and the working-adults sample, which also includes non-retired and retired

individuals age 25 to 65. The latter sample will be the main focus of the paper.

Demographics for the working-adults sample group compared to the national

population in this age group can be found in the appendix. Our working-adults

group is younger and slightly more educated than the national sample. Our

analysis uses unweighted data. Due to possible selectivity issues associated with

the participation of older people in online surveys, in Appendix Table A2, we

specifically compare the demographics for the over-65 sample with the population

of that same age. Here we find that our older sample is slightly younger and more

educated than the general population of the same age. Furthermore, our sample

has a greater proportion of males than the general population.

Overall, there is little difference between the working-adults sample and the

full sample. In both samples, more respondents answered the interest rate question

correctly compared to any other question. In fact, roughly 83% of the respondents

This question was slightly reworded for the Australian context from the original. The original

sentence read “Buying a single company’s stock usually provides a safer return than a stock

mutual fund.”

Agnew et al.: Financial Literacy and Retirement Planning in Australia

Published by Digital Commons @ University of South Florida, 2013

Table 1

Summary Statistics on Three Financial Literacy Questions (%)

Full Sample (%)

Age 25–65 (%)

(A) Interest Question

More than $102**

83.11%

83.09%

Exactly $102

4.10%

4.11%

Less than $102

5.57%

5.68%

6.45%

6.28%

0.78%

0.85%

(B) Inflation Question

More than today

9.77%

8.94%

Exactly the same

7.23%

7.13%

Less than today**

69.34%

70.77%

12.99%

12.44%

0.68%

0.72%

Correct (false)**

54.69%

55.07%

Incorrect (true)

6.74%

6.28%

37.60%

37.44%

Refuse

0.98%

1.21%

(D) Cross-question

consistency

Interest and Inflation

62.89%

63.65%

All correct

42.68%

42.87%

None correct

8.59%

8.09%

At least 1 DK

41.31%

41.06%

All DK

4.49%

4.35%

Number of Observations

1,024

828

Notes: DK indicates respondent replied with “do not know”; RF indicates

respondent refused to answer the question.

correctly recognized that their money would grow due to interest earnings to more

than $102. In terms of international comparison, rates of correct responses here

were similar to the Netherlands and Germany, and 10–15 percentage points above

Japan and the United States.

Respondents’ accuracy fell with the inflation

question to rates lower than those elicited from surveys in the Netherlands and

Germany. About 69% of Australian respondents answered this question correctly

and almost 13% responded that they did not know the answer. The most

challenging question for Australians to answer was the risk diversification

question. Over one-third of respondents indicated that they did not know the

answer to this question, and only slightly over half were able to give correct

answers. The rate of correct responses was comparable to the United States, the

Netherlands, and Italy, but well below Sweden and Germany. While the rate of

“do not know” responses was higher for Australia than for most countries (apart

from Japan), the similar rate of correct responses suggests that the Australian

sample disproportionately chose “do not know” compared with respondents from

other countries.

Considering the questions together, a positive correlation between the correct

responses to each question was found but these correlations were never greater

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than 0.35. The positive but low correlations are consistent with Lusardi and

Mitchell’s (2011b) findings. As suggested in their paper, the low correlations may

indicate that the three questions address different areas of financial literacy. In

total, only 63% of both samples correctly answered the interest and inflation

questions. This percentage falls to approximately 43% when responses to the risk

diversification question are incorporated. This response rate is similar to that of

the Netherlands (Alessie et al. 2011) and about ten percentage points higher than

that of U.S. respondents (Lusardi and Mitchell 2011b). Even more important,

nearly half of the respondents (approximately 41%) answered “do not know” to at

least one question. This is notable because Lusardi and Mitchell (2011a) find that

those individuals who tend to respond with “do not know” often know the least.

Who Is Financially Illiterate?

Table 2 breaks down the responses to the financial literacy questions by

sociodemographic characteristics. The table reports responses to individual

questions and overall responses. Obvious patterns emerge.

Table 2

Distribution of Responses to Financial Literacy Questions by Age, Sex, Education,

and Employment Status (%)

Interest

Inflation

Risk

Overall 3 measures

Correct

3 correct

>=1 DK

Age

35 and under

79%

55%

19%

42%

50%

31%

54%

359

36–50

85%

69%

13%

58%

35%

44%

39%

324

51–65

86%

62%

29%

52%

32%

239

Over 65

86%

82%

71%

22%

58%

26%

102

Sex

Male

85%

74%

11%

62%

29%

52%

31%

490

Female

82%

65%

14%

48%

46%

34%

51%

534

Education

High school or less

80%

63%

19%

53%

41%

38%

47%

283

TAFE (Certificate)

81%

66%

16%

43%

49%

34%

53%

238

TAFE (Diploma)

86%

71%

14%

55%

38%

45%

39%

122

Bachelor’s degree

87%

76%

65%

27%

52%

29%

238

Graduate degree

84%

73%

60%

30%

50%

33%

143

Employment Status

Self-employed

82%

80%

11%

56%

35%

48%

38%

Not employed

70%

15%

51%

30%

38%

51%

28%

57%

Not in labor force

85%

63%

16%

43%

49%

29%

54%

156

Working

83%

70%

11%

56%

37%

44%

40%

648

Retired

88%

81%

10%

70%

21%

57%

25%

146

Total Sample Size: 1,024

Note: The not in labor force category includes individuals who indicate that they are not in the labor force because they

are a caregiver, a student, or for some other reason. The working category includes part-time and full-time workers. It

also includes self-

employed workers. Therefore, the sum of all the employment categories will add to greater than the

sample size as 84 self-employed workers are double counted. Data are unweighted and DK

indicates respondent

answered “do not know.”

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For each question, younger individuals tended to respond less accurately than

their older counterparts. This is consistent with findings in other countries

(Lusardi and Mitchell 2011c). The pattern is most evident in the last column,

where the percentage of the sample answering all the questions correctly is

reported. Only 31% of individuals under 35 answered all the questions correctly

compared to 58% of those older than 65. This pattern reverses itself when

examining the “do not know” responses. Over half of the respondents under 35

answered at least one question with “do not know” compared to only 26% of the

oldest group. The differences between age groups are largest for the inflation and

risk questions.

Women also answered relatively fewer questions correctly than men. While

for the interest rate question the responses are fairly consistent between the sexes,

differences are more marked for the inflation and risk questions. In addition, and

mirroring other studies, women were more likely to respond with “do not know.”

In the full sample, over half of the women responded “do not know” to at least

one question, while only 31% of males did so.

We find that education is positively related to financial literacy. In Table 2,

we break our sample into several categories. The first category includes

individuals with a high school education or less. The next two categories include

individuals who have received education from a Technical and Further Education

(TAFE) institute or a similar school. TAFE institutes provide tertiary-level

vocational education and training in Australia and can also offer matriculation

courses for students who did not complete high school. Students can receive

certificates, as well as diplomas or advanced diplomas from these schools. The

next category includes individuals with bachelor’s degrees from a university or

equivalent school. The final category includes master’s and doctorate degrees.

Comparing across the three questions, the high school or less and TAFE

(Certificate) groups replied more often with “do not know.” The TAFE (Diploma)

group tended to perform just as well as the bachelor’s and graduate degree groups

when answering the first two questions, which happen to be the questions

requiring numeracy skills. These results naturally follow from the fact that

graduates earning TAFE certificates and diplomas encompass a wide range of

experiences and abilities, from self-employed, skilled tradespeople and designers

to individuals who did not graduate from high school and received only very basic

training for low-skill employment. Within this group, the prerequisite skills,

which can include numeracy, required to earn a TAFE diploma or advanced

diploma are far greater than those required for a certificate and this appears to

translate into the scores. As with the previous finding, respondents tended to

Respondents over age 65 are less representative of the general population than respondents of

working age. Males, younger respondents, and the better educated are oversampled in this group.

See Appendix Table A2.

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answer the interest question most correctly followed by the inflation question.

Interestingly, we find the non-numeracy–related third question provides the most

distinction between university degree holders and others. For this question, the

TAFE diploma holders perform like individuals with a high school education or

less and the TAFE certificate holders perform the worst. Across the board,

individuals in the university categories perform better overall and answer least

often with “do not know.”

Finally, we find that categorizing people by employment status highlights

groups with lower financial literacy. For example, respondents who demonstrate

the most difficulty answering the questions are those who are either not employed

and actively seeking work or those who are not in the labor force because they are

caregivers, students, or cannot participate for some other reason. We found that

only 28% (29%) of the not employed (those not in the labor force) group could

answer all of the questions correctly compared to 44% of workers, 48% of self-

employed workers, and 57% of the retired group.

In summary, financial illiteracy is more prevalent among certain demographic

groups. These groups are younger individuals, women, those with less education,

and those who are not employed or not in the labor force.

Planning for Retirement

In this section, we investigate whether financial literacy relates to retirement

planning in Australia. Prior research suggests that different measures of financial

sophistication and literacy relate to important investment behaviors. For example,

Calvet et al. (2009) find a relationship between demographic variables related to

financial sophistication and investment mistakes. Other papers suggest

connections between financial literacy and stock market participation, borrowing,

and mutual fund selection (Lusardi and Tufano 2009; Christelis et al. 2010; van

Rooij et al. 2011; Hastings and Mitchell 2011). Finally, a growing body of

research finds that financial literacy relates to retirement planning, which may

lead to greater wealth (for example, Ameriks et al. 2003; Behrman et al. 2010;

Lusardi 2009; Lusardi and Mitchell 2011a). It is these papers and recent findings

from other countries that provide the motivation for the following analysis.

In order to assess how financial literacy relates to retirement planning, we

asked participants the following question about their retirement planning efforts:

Have you ever tried to work out how much you need to save for

retirement?

This question has been slightly modified for the Australian context from the

retirement planning question posed in the U.S. Health and Retirement Survey

(HRS) and used in Lusardi and Mitchell’s papers (2011a, 2011b). The question

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requires a simple yes or no reply. For this analysis, we restrict our sample to

individuals who indicated that they are not retired and are age 25–65. This was

necessary given the focus on retirement planning and to allow comparability with

other studies.

We found that only 32% of the non-retired sample of 764 individuals have

attempted to work out how much they need to save. The patterns found within

each sociodemographic group seem to mirror the relationships observed with

financially literacy. While significance is not tested, males plan more than

females and individuals not working by choice or who are seeking jobs appear to

plan less. In terms of planning and age, a notable increase in planners is evident in

the 50- to 65-year-old age group (48%) relative to those under 50. For those under

50, the percentage who are planners ranges from 27% to 29%, depending on the

age category.

To determine whether planning relates positively to financial literacy, we

divided the nonretired sample into two groups: planners and nonplanners. Table 3

reports the percentage of planners and nonplanners who answered each financial

literacy question correctly. Planners were more successful at answering each

question compared to nonplanners. The largest difference we found relates to the

risk diversification question. For this question, 67% of the planners chose the

right answer versus 47% of the nonplanners. Similar differences are found once

all the literacy questions are combined. We found that just over half (55%) of the

Table 3

Financial Literacy of Planners and Non-Planners

Planners

Non-

Planners

Interest Rate Question

Correct

88%

80%

Inflation Question

Correct

77%

67%

16%

Risk Diversification Question

Correct

67%

47%

23%

47%

Summary

Correct: Interest and Inflation

71%

59%

Correct: all three

55%

35%

>=1 DK

25%

51%

Average number of questions correct

2.32

1.94

Average number of DKs

0.29

0.72

Sample Size

250

514

planners answered all three questions correctly versus only 35% of the

nonplanners. Furthermore, nonplanners seemed to be less confident or at least

more willing to reveal their lack of knowledge by responding “do not know.”

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Approximately half of the nonplanners answered at least one question with “do

not know” compared to only a quarter (25%) of the planners.

A Multivariate Model of Planning and Financial Literacy

In this section, we examine the relationship between financial literacy and

retirement planning using a multivariate regression framework. Using an indicator

variable for retirement planning as the dependent variable, first we estimate an

Ordinary Least Squares (OLS) model. The dependent variable equals one if

respondents answered affirmatively to our retirement planning question and zero

otherwise. Consistent with prior literature, we include numerous control variables

including indicator variables for homeownership, self-employment, and not

employed. We also control for each respondent’s household income. We include

age and age-squared to allow flexibility in the relationship between age and

retirement planning. Possible liquidity constraints and household income shocks

are captured by two variables: a dummy variable

that equals one if the

respondent or someone in the respondent’s family has ever experienced a drastic

and unexpected fall in savings or income and a variable representing the number

of children in the household. We define all of our variables in Appendix Table

A3, Panels A and B.

In Table 4 we report the results from four specifications using different

financial literacy measures. The financial literacy measure “all three correct” in

the first specification is an indicator variable that equals one if the respondent

answered all the financial literacy questions correctly and zero if not. The

measure in the second specification, “total number correct,” equals the number of

questions answered correctly. The third specification includes separate indicator

variables for each financial literacy question. The variable equals one if the

specific question is answered correctly. The final measure in the last specification

is the sum of the “do not know” responses of each respondent.

The regression results show there is a statistically significant relationship

between financial literacy and retirement planning which holds for each measure

of financial literacy. The first specification suggests that the probability of being a

planner increases by 12.3 percentage points if individuals can answer all three

financial literacy questions correctly. In the second specification, each question

answered correctly raises the chances of planning by nearly 6 percentage points.

In the third specification, only the risk question out of the three financial literacy

In empirical economics, binary (or indicator or categorical) variables are typically referred to as

dummy variables. These variables takes the value of zero or one to indicate the absence or

presence of some categorical effect.

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Table 4

OLS Estimates of Retirement Planning on Financial Literacy

Dependent Variable=1 if

planner (0 else)

(1)

(2)

(3)

(4)

All three correct

0.123***

(0.04)

Total number correct

0.059***

(0.02)

Inflation correct

0.054

(0.04)

Interest correct

-0.022

(0.04)

Risk correct

0.135***

(0.04)

Total number DKs

-0.113***

(0.02)

Age

-0.052***

-0.053***

-0.055***

-0.056***

(0.01)

Age squared

0.001***

(0.00)

Female

0.008

0.001

0.004

0.000

(0.04)

(0.03)

Education, TAFE (Certificate)

0.065

0.070

0.068

(0.04)

Education, TAFE (Diploma)

0.096

0.097

0.095

(0.06)

Education, bachelor’s degree

0.143***

0.142***

0.143***

0.119**

(0.05)

Education, graduate degree

0.134**

0.138**

0.122**

(0.06)

Single

-0.039

-0.038

-0.039

-0.031

(0.04)

Divorced or separated

0.086

0.091

0.090

0.093

(0.06)

Widow

0.332**

0.336**

0.347**

0.295**

(0.14)

(0.13)

Number of children

-0.005

-0.004

-0.000

(0.02)

Income $20,800–$41,599

-0.072

-0.063

-0.065

-0.053

(0.05)

Income $41,600–$67,599

0.024

0.026

0.021

0.018

(0.05)

Income greater than $67,600

0.053

0.060

0.050

0.057

(0.05)

Homeowner

0.083**

0.085**

0.083**

0.087**

(0.04)

Self-employed

0.016

0.022

0.019

(0.06)

Not working

0.026

0.039

0.034

0.048

(0.07)

Had income shock

0.015

0.016

0.010

(0.03)

Constant

1.073***

1.027***

1.081***

1.286***

(0.30)

Observations

751

R-squared

0.122

0.119

0.128

0.139

Notes: Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.

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This is consistent with Lusardi and Mitchell’s (2011b) findings for the United

States. Responding with “do not know” also has significant explanatory power. In

fact, the chances of being a planner decrease by 11.3 percentage points for each

“do not know” response. As a robustness check, we repeated the analysis with a

probit estimation. The relationships between the planning variable and the

different financial literacy variables remained qualitatively the same.

The regression results also suggest that certain demographic factors relate to

planning. For example, we find a nonlinear relationship between age and

planning, captured by the age-squared variable. The likelihood of planning,

measured by the marginal effect of age, increases near midlife. The marginal

effect of an additional year is positive from around age 40, suggesting a

gradually increasing interest in planning starting in midlife.

Earlier surveys show

that retirement planning is sporadic at best among Australian pre-retirees (Agnew

et al. 2013).

Education also relates to planning. Comparing individuals with a high school

degree or lower education to those earning a university degree, either a bachelor’s

degree or a graduate degree, increases the probability of planning between 12 and

14 percentage points. Homeownership, which is concentrated in the upper two-

thirds of the wealth distribution, also increases planning (by 8–9 percentage

points). As well as being wealthier, home-owning households have managed a

long-term financial contract with a mortgage provider and are likely to have built

up some financial competence that spills over into retirement planning. Overall,

the largest effect on retirement planning is widowhood status. Individuals who are

widowed are more likely to plan for retirement. This may be because, following

the death of a spouse, individuals are forced to carefully consider their finances if

they have not already done so. Interestingly, income was not statistically

significant, but does play a large role in the findings from other countries (for

example, Lusardi and Mitchell, 2011b).

In total, the results presented are similar to findings from other countries.

However, like the other studies, direction of causality is uncertain, whether from

financial literacy to retirement planning or the other way around. As noted by

others, individuals may become more financially literate because they plan, and/or

planning and financial knowledge may be driven by underlying characteristics.

This is an endogeneity problem that requires more sophisticated estimation

techniques. Other considerations include the possibility of measurement errors

(Lusardi and Mitchell 2011b, van Rooij et al. 2011). Since endogeneity problems

and measurement error can affect estimated coefficients in different directions, we

cannot forecast the sign of possible biases with any certainty.

We calculate this age turning point using coefficients estimated to eight significant figures. Due

to sensitivity to rounding, readers will not be able to replicate this age finding using the estimates

reported in Table 4 because they are rounded to three significant figures.

Agnew et al.: Financial Literacy and Retirement Planning in Australia

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To address these issues, we use an instrumental variables (IV) approach. The

challenge of using IV estimation is finding valid instruments that are correlated

with financial literacy measures but uncorrelated with the error term. Motivated

by Alessie et al. (2011), we constructed instruments based on the financial

experiences of respondents’ siblings and parents. Specifically, we asked if

respondents had siblings and then inquired whether their oldest sibling was in a

worse, better, or similar financial situation. From these responses, we created

indicator variables for siblings in worse and better financial situations. Alessie et

al. (2011) propose these variables as suitable instruments for financial literacy

because, while individuals cannot control a sibling’s financial situation, they can

learn from their siblings’ financial experiences. What they learn likely improves

their financial literacy but is not generated by their own planning behavior. In

addition, we include an indicator variable that equals one if the respondents

thought their parents had a good or intermediate understanding of financial

matters and another indicator variable that equals one if they have ever received

workplace financial education.

These instruments have been used in IV

modeling of financial literacy and retirement planning in other developed

countries (Alessie et al. 2011; Lusardi and Mitchell 2010).

Table 5 reports the results from the first and second stage regressions using

Generalized Method of Moments (GMM) estimation that allows for computation

of robust standard errors. We report only the estimates for one specification of the

financial literacy variable (all questions are answered correctly) because the

proposed instrumental variables were strongest in this case. As noted above, two

statistical properties are needed to ensure that our selected instruments serve their

purpose. The first is that the instrument is correlated with the financial literacy

variable of interest, and the second is that it is uncorrelated with the random error

in the model. Table 5, Panel B, tests for the predictive power of the instruments

We followed the exact methodology for constructing the instrumental variables used in Alessie

et al. (2011). Regarding siblings, we asked, “Would you say that your oldest [brother/sister] is in

worse than, better than, or about the same financial situation as you?” To measure parent’s

financial understanding we asked, “How would you assess your parent’s understanding of

financial matters? Think about the parent that is or was mostly responsible for the major financial

decisions.” Respondents ranked the parent’s knowledge using a 7-point scale (1 for very low; 7 for

very high). Consistent with Alessie et al. (2011), we created an indicator variable equal to one if

the parent was judged to have intermediate or high knowledge measured by a response of 4 or

greater. We also included an indicator equal to one if respondents did not answer or answered “do

not know.” Finally, following Lusardi and Mitchell (2010) we asked about workplace education:

“Did any of the firms you have worked for (including your current employer) offer financial

education programs such as retirement seminars?” An indicator variable was coded one if the

respondents answered yes.

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Table 5

Panel A: IV Estimates of Financial Literacy Impact on Retirement

Planning

Dependent Variable Equals

First Stage

Second Stage

All three correct

OLS

1 if planner (0 else)

GMM

All three correct

0.861***

(0.27)

Age

0.011

-0.057***

(0.01)

(0.02)

Age squared

0.000

0.001***

(0.00)

Female

-0.107***

0.094*

(0.04)

(0.05)

Education, TAFE (Certificate)

-0.006

0.065

(0.05)

(0.06)

Education, TAFE (Diploma)

0.041

0.053

(0.06)

(0.08)

Education, Bachelor Degree

0.140***

0.034

(0.05)

(0.08)

Education, Graduate Degree

0.075

0.069

(0.06)

(0.08)

Widow

-0.197

0.465**

(0.12)

(0.19)

Single

0.003

-0.037

(0.05)

Divorced or separated

-0.007

0.076

(0.06)

(0.08)

Number of children

-0.023

0.009

(0.02)

Income, $20,800-$41,599

-0.035

-0.056

(0.05)

(0.06)

Income, $41,600-$67,599

0.022

-0.007

(0.05)

(0.07)

Income, Greater than $67,600

0.133

-0.074

(0.05)

(0.08)

Homeowner

0.072*

0.025

(0.04)

(0.06)

Self-employed

0.026

0.035

(0.06)

(0.08)

Not working

0.001

0.038

(0.07)

(0.09)

Had income shock

0.068*

-0.051

(0.04)

(0.05)

Sibling in Worse Situation

0.053

(0.04)

Sibling in Better Situation

0.039

(0.05)

Parents are good financial

0.062

decision makers

(0.04)

Don't know if parents are good

-0.102

financial decision makers

(0.06)

Had workplace education

0.140***

(0.05)

Constant

-0.126

1.047***

(0.29)

(0.37)

Notes: Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.

Agnew et al.: Financial Literacy and Retirement Planning in Australia

Published by Digital Commons @ University of South Florida, 2013

Table 5

Panel B: IV Estimates of Financial Literacy Impact on Retirement

Planning

Dependent Variable Equals

First Stage

Second Stage

All three correct

OLS

1 if planner (0 else)

GMM

Observations

751

R-squared

0.1417

-0.410

F statistic

6.41

3.97

Test of Excluded Instruments

F(5, 727)

4.48

Prob>F

0.0005

Partial R-squared of Excluded

Instruments

0.0268

(the F-statistics for the joint significance of the instruments and the partial R-

squared of the instruments). While significant, the F statistic is small by

conventional standards and indicates that our instrumental variables may be weak.

Similarly the partial R-squared is low at 3%. When instrumental variables are

weak, the IV estimates may be biased and therefore offer little or no improvement

over the OLS estimates (Staiger and Stock 1997). Further, any bias correction

offered by the IV estimator is proportional to the explanatory power of the

instruments in the first-stage regression. While our instruments are only weakly

correlated with financial literacy, tests (Hansen’s J) show that they are

exogenous.

The second stage shows a positive and significant coefficient on the

instrumented financial literacy variable. The estimates are large. However, given

the potential weakness in the instruments mentioned earlier we recommend

caution in interpreting these results and want to be careful not to overstate our

findings. That said, our results support that financial literacy may lead to greater

retirement planning. Future work should focus on identifying stronger instruments

to confirm this result.

Discussion and Conclusions

Even though participation in the Australian retirement saving system is mandatory

for almost all workers, virtually everyone has the opportunity to make decisions

about important facets of their retirement savings plan. These include voluntary

additional contributions, changes to investment strategies, changes to insurance

provisions, and choice of plan provider. Even more choices confront retirees, who

have almost unlimited freedom to manage the decumulation phase of retirement.

For the rest of the world, Australia presents an interesting natural experiment

in whether making investment compulsory motivates higher financial literacy: it

We used the STATA module IVREG2 to perform the IV analysis (Baum et al. 2007).

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is a developed economy where the retirement savings system ensures that almost

all adults are long-term investors with the opportunity to choose their own

portfolios relatively easily.

Individuals need foundational numeracy, a basic understanding of finance

and some familiarity with the features of plans and products to make sound

financial decisions. An interesting question is whether compelling almost

everyone to join a defined contribution plan improves the population’s financial

literacy over time because people learn from their participation. The results

reported here can provide a benchmark for future comparison work in financial

literacy. So far, after 25 years of mandatory retirement saving, a large minority of

Australians does not know the relevant financial basics nor are they actively

preparing for retirement. In addition, the results highlight certain demographic

groups that are most at risk, including the young, women, the least educated,

those not in the labor force and those not employed. Results for Australia are not

markedly worse, but neither are they better than, other comparable countries

(Bateman et al. 2012) and “at risk” groups are similarly populated.

These results raise the obvious question: Why is financial literacy still

relatively low in Australia, and why does the mandatory system not motivate

more people to plan for retirement? Finding the answer to this question is a

challenge for future research. The solution will be essential to any efforts to

develop and test methods for improving financial awareness. While our study

does not provide the answers, we can propose several possible explanations that

should warrant attention in future research. While the observed lack of knowledge

could be a function of the mandatory nature of the Australian retirement system

and the system’s default structure, the fact that financial literacy is not markedly

worse in Australia than in other Anglosphere countries suggests that this is

unlikely to be the case. The existence of a compulsory employer contribution rate

may well encourage many Australians to feel that, since they are following

government policy prescriptions, their retirement is secure and therefore does not

need attention. On the other hand, subject to some caution due to sampling biases,

we find that both literacy and planning continue to improve as people age, unlike

some other similar countries where knowledge advances to middle age and then

begins to decay (Lusardi and Mitchell 2011c). This Australian result may indicate

that eventually people begin taking notice of issues surrounding and acquiring

some skills relating to retirement planning. This may not be surprising as the

interaction of a means-tested public Age Pension and individual choice of

retirement benefit necessitates many Australians of retirement age to navigate

product prospectuses and public benefit information.

Alternatively, individuals may not realize they have a knowledge gap. In our

survey, we asked individuals to assess their own knowledge of finance, and only

14% of our sample considered themselves below average. These findings are

Agnew et al.: Financial Literacy and Retirement Planning in Australia

Published by Digital Commons @ University of South Florida, 2013

consistent with the 8% figure reported in a large corporate survey conducted by

the Australia and New Zealand Banking Group Limited (ANZ 2011). The ANZ

survey also found that participants’ perceived need for further financial education

declined with their self-assessed knowledge. Thus, many Australians may not

realize they need more education when, in fact, they do.

While future research is required to determine whether these explanations are

valid, or if there is an alternative cause for the observed lower levels of financial

literacy, this paper does highlight important deficiencies, as well as reveal a

connection between financial knowledge and retirement planning. Our findings

are similar to those around the world suggesting that more research is needed

regarding methods for educating consumers so that they can make more informed

choices.

Acknowledgments

The authors are grateful for generous funding. Agnew acknowledges support from

the Wharton School’s Pension Research Council and the Global Financial

Literacy Excellence Center. Bateman and Thorp acknowledge financial support

under ARC DP1093842. The Chair of Finance and Superannuation (Thorp),

University of Technology Sydney (UTS), receives support from the Sydney

Financial Forum (through Colonial First State Global Asset Management), the

New South Wales government, the Association of Superannuation Funds of

Australia, the Industry Superannuation Network, and the Paul Woolley Centre for

the Study of Capital Market Dysfunctionality, UTS. In addition, the authors thank

Pureprofile and the staff of the Centre for the Study of Choice (University of

Technology Sydney) for their generous assistance with the development and

implementation of the Internet survey. Finally, the authors thank Mariya

Theiviasingham and Edward Wei for their excellent research assistance.

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Appendix

Table A1

Survey Sample versus Australian Population (25–64 years old retired and non-retired)

Respondent

Population

Australian

Population

Age 25–64

Gender

Male

47%

49%

Female

53%

51%

Age

25–29 years

16%

13%

30–34 years

16%

13%

35–39 years

15%

13%

40–44 years

13%

45–49 years

10%

13%

50–54 years

13%

55–59 years

11%

60–65 years

10%

11%

Work Status

Employed

71%

Not employed

Not in the labor force

15%

25%

Retired

not broken out

Marital Status

Never married

22%

27%

Divorced/separated

10%

14%

Widowed

Married or long-term relationship

66%

58%

Income

$1–$20,799 (i.e., less than $399 a week)

20%

19%

$20,800–$51,999 (i.e., $400–$999 a week)

31%

32%

$52,000–$103,999 (i.e., $1,000–$1,999 a week)

36%

27%

$104,000 (i.e., $2,000 a week) or more

Negative or nil income

Not stated

Highest level of Education

High school or less

24%

36%

TAFE (certificate)

23%

21%

TAFE (diploma)

12%

Bachelor’s degree

25%

17%

Graduate degree

16%

Not stated

Note: Source for population statistics: Australian Bureau of Statistics Census of Population and

Housing, 2011.

Employed includes full-time workers, part-time workers, and workers classified away from work.

Census records only specify those not in the labor force. Also, includes those not stating their labor

force status.

Includes those whose education was inadequately described

Numeracy, Vol. 6 [2013], Iss. 2, Art. 7

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DOI: http://dx.doi.org/10.5038/1936-4660.6.2.7

Table A2

Older Sample Population versus Older Australian Population (65 years old+)

Respondent

Population

Australian

Population

Age 65+

Gender

Male

60%

46%

Female

40%

54%

Age

65–69 years

61%

31%

70–74 years

27%

24%

75 years or over

12%

46%

Work Status

Employed

14%

11%

Not employed

0.3%

Not in the labor force

89%

Retired

80%

not broken out

Marital Status

Never married

Divorced/separated

15%

12%

Widowed

26%

Married or long-term relationship

75%

57%

Income

$1–$20,799 (i.e., less than $399/week)

38%

52%

$20,800–$51,999 (i.e., $400–$999 /week)

47%

27%

$52,000–$103,999 (i.e., $1,000–$1,999/week)

10%

$104,000 (i.e., $2,000/week) or more

Negative or nil income

Not stated

11%

Highest level of Education

High school or less

45%

54%

TAFE (certificate)

20%

13%

TAFE (diploma)

14%

Bachelor degree

12%

Graduate degree

10%

Not stated

19%

102

Note: Source for population statistics: Australian Bureau of Statistics Census of Population and

Housing, 2011.

Employed includes full-time workers, part-time workers, and workers classified away from work.

Census records only specify those not in the labor force. Also, includes those not stating their labor

force status.

Includes those whose education was inadequately described

Agnew et al.: Financial Literacy and Retirement Planning in Australia

Published by Digital Commons @ University of South Florida, 2013

Table A3, Panel A

Description of Variables

Variable Name

Description

Retirement planning question

Planner

Indicator variable that equals one if the respondent answered yes to the question

“Have you ever tried to work out how much you need to save for retirement?”

Financial literacy variables

All three correct

Indicator variable that equals one if all the financial literacy questions were

answered correctly, zero otherwise

Total number correct

Continuous variable that equals the sum of the number of financial literacy

questions answered correctly

Inflation correct

Indicator variable that equals one if the inflation question was answered correctly,

zero otherwise

Interest correct

Indicator variable that equals one if the interest question was answered correctly,

zero otherwise

Risk correct

Indicator variable that equals one if the risk question was answered correctly, zero

otherwise

Total number DKs

Continuous variable that equals the sum of the number of do not know answers

Demographic variables

Age

The age in years of the respondent

Age squared

The square of the age variable

Female

An indicator variable that equals one if the respondent is a female, zero otherwise

Education, high school or less

An indicator variable that equals one if the respondent’s highest level of education

is high school or less, zero otherwise (This is the omitted variable in the

regressions)

Education, TAFE (Certificate)

An indicator variable that equals one if the respondent's highest level of education

is a Technical and Further Education (TAFE) certificate, zero otherwise

Education, TAFE (Diploma)

An indicator variable that equals one if the respondent's highest level of education

is a Technical and Further Education (TAFE) diploma or advanced diploma, zero

otherwise

Education, bachelor’s degree

An indicator variable that equals one if the respondent's highest level of education

is a bachelor degree, zero otherwise

Education, graduate degree

An indicator variable that equals one if the respondent's highest level of education

is a graduate degree, zero otherwise

Married

An indicator variable that equals one if the respondent is married or in a

committed long-term relationship, otherwise zero (This is the omitted variable in

the regressions)

Single

An indicator variable that equals one if the respondent is single, otherwise zero

Divorced or separated

An indicator variable that equals one if the respondent is divorced or separated,

zero otherwise

Income less than $20,800

An indicator variable that equals one if the respondent earns an annual personal

gross income of less than $20,800, zero otherwise (This is the omitted variable in

the regressions)

Income $20,800–$41,599

An indicator variable that equals one if the respondent earns an annual personal

gross income between the two values, zero otherwise

Income $41,600–$67,599

An indicator variable that equals one if the respondent earns an annual personal

gross income between the two values, zero otherwise

Income greater than $67,600

An indicator variable that equals one if the respondent earns an annual personal

gross income between the two values, zero otherwise

Homeowner

An indicator variable that equals one if the respondent is a homeowner, zero

otherwise

Not working

An indicator variable that equals one if the respondent indicates they are not

employed, zero otherwise

Self-employed

An indicator variable that equals one if the respondent indicates that they are self-

employed, zero otherwise

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DOI: http://dx.doi.org/10.5038/1936-4660.6.2.7

Table A3, Panel B

Description of Variables

Variable Name

Description

Control variables for liquidity constraints and household income shocks

Had income shock

An indicator that equals one if the individual or someone in the respondent's family

experienced a drastic and unexpected fall in savings or income

Number of children

Number of children in the household

Instrumental variables

Sibling in Worse Situation

An indicator variable that equals one if the respondent answered that their oldest sibling

had a worse financial situation, zero otherwise

Sibling in Better Situation

An indicator variable that equals one if the respondent answered that their oldest sibling

had a better financial situation, zero otherwise

Parents are good financial

decision makers

An indicator variable that equals one if the respondent judged their parent to have an

intermediate or high understanding of financial matters (4 or greater on a 7 point scale).

Exact question in footnote 10.

Don't know if parents are

good financial decision

makers

An indicator variable that equals one if the respondent indicated that they did not know

if their parent had an understanding of financial matters. Exact question in footnote 10.

Had workplace education

An indicator variable that equals on if the respondent answered yes to the question "Did

any of the firms you have worked for (including your current employer) offer financial

education programs such as retirement seminars?"

Agnew et al.: Financial Literacy and Retirement Planning in Australia

Published by Digital Commons @ University of South Florida, 2013