Download Does Higher Education Pay ? Results from the Return to

DOES HIGHER EDUCATION PAY?
RESULTS FROM THE RETURNS TO
EDUCATION MODEL
Peter Johnson and Rachel Lloyd
The National Centre for Social and Economic Modelling developed the returns to education
model (RED99) for the Department of Education, Training and Youth Affairs (DETYA).
The views and opinions expressed in this paper are those of the authors and are not
necessarily those of DETYA or its Ministers.
Paper presented at the 29th Conference of
Economists
Gold Coast, 3-6 July 2000
Abstract
This paper examines private and public returns to higher education through the use of the
Returns to Education model, RED99, developed by the National Centre for Social and
Economic Modelling for the Department of Education, Training and Youth Affairs
(DETYA). A description of the model is presented and the private and public returns are
illustrated with an example. The example used compares the lifetime private and public
returns of a person who has a university degree with a person who has completed
secondary education.
Author note
Peter Johnson is a Research Officer at the National Centre for Social and Economic
Modelling (NATSEM) at the University of Canberra and Rachel Lloyd is a Research
Fellow at NATSEM.
Acknowledgments
The authors would like to thank all those at NATSEM involved in creating the Returns to
Education 1999 (RED99) model and its predecessor, the Hypothetical Returns to
Education Model (HREM). A great deal of gratitude is owed to Anthony King, Gillian Beer,
and Simon Lambert. Sincere appreciation is also extended to the staff of the
Commonwealth Department of Education Training and Youth Affairs (DETYA) who have
been involved with the development of the model for the past few years. The authors
would also like to thank Ann Harding and Anthony King for their helpful comments upon
this paper.
1
Introduction
Does higher education pay? Because people undertake further study, we expect that
there is a positive private return, and previous studies have demonstrated this (Maglen
1993). But who receives the returns, how much do they receive, and is there also a public
return to higher education? To help answer these and other questions the Commonwealth
Department of Education Training and Youth Affairs (DETYA) commissioned NATSEM to
create a model of private and public returns to education.
This paper describes the model (RED99) and its applications. Section 2 examines other
studies of returns to education. Section 3 describes the ‘returns to higher education in
Australia 1999’ (RED99) model. The flexibility of the RED99 model is explored in Section
4 and the way key parameters such as Labour Force Status and Earnings profiles are
constructed is discussed.
In Section 5 there are some illustrative simulations to
demonstrate the capabilities of and the type of output produced by the model.
2
Previous work on modelling returns to
education
The private rate of return to education at a level of education is given by the discount rate
that equalizes the stream of benefits to the stream of costs at a given point in time. For
example, the rate of return for a university graduate is the discount rate where the
difference between the stream of earnings for a university graduate and a secondary
school graduate is equal to the stream of foregone earnings and direct costs of university
education.
Rates of return to education have been comprehensively tracked, with estimated rates of
return to education available for almost any country, both developed or developing.
Wolter and Weber (1999) studied rates of return to education in Switzerland, a developed
country, and Siphambe’s study of Botswana is an example of a rate of return to education
study in a developing country (Siphambe 2000).
George Psacharopoulos has conducted reviews of rates of return to education in many
countries. Some of the general patterns that he found were:
•
Private returns are considerably higher than social returns because of the public
subsidization of education;
•
Overall, the returns to female education are higher than those to male education, but
at individual levels of education the pattern is more mixed; and,
•
Social and private returns at all levels generally decline with the level of a country’s
per capita income (Psacharopoulos 1993 p2).
The studies by Wolter and Weber and Siphambe generally concord with Psacharopoulos’
work, with the exception that Siphambe found that in Botswana rates of return rose with
level of education, rather than declining as seen elsewhere. Siphambe also determined
another general pattern:
•
Returns decline by level of schooling, reflecting diminishing returns to schooling (i.e.
returns to primary schooling are higher than secondary education, and the latter is
higher than returns to higher education - Siphambe 2000 p291).
Wolter and Weber’s study extended the general model for determining rates of return to
education by including other parameters such as unemployment, taxes, direct costs, and
dropout rates at university level.
Recent studies in Australia tend to be focused on competing theories, human capital
theory versus public choice theory (Quiggin 1999), and the relevance of these theories in
an Australian context. Preston in her study of the relevance of human capital theory for
the study of wage determination, found ‘education is positively associated with higher
earnings’ (Preston 1997 p54). Preston used the Mincer earnings function to obtain,
amongst other things, the rates of return to education. Chia, cited in Quiggin 1999, found
that obtaining a bachelor degree yielded a private rate of return of 9.6 for males, and 12.6
per cent for females. Maglen conducted examinations of rates of return to university
degrees at different points in time, using average earnings data, with adjustments for
average personal tax, and average levels of student assistance. Maglen found that the
private rates of return on a university degree have declined from the late 1960s to the mid
1980s, and that the rates of return for females were similar to those for males. The return
for males declined from about 18 per cent in 1968-69 to about 14 per cent in 1985-86.
(Maglen 1993)
3
Overview of the RED99 model
The major differences between RED99 and other methods of examining the rates of
return to education are:
•
RED99 examines private and government rates of return rather than private and
social rates of return.
•
RED99 determines a rate of return to higher education for individuals rather than an
aggregate rate of return to a level of study. However individual results can be
aggregated.
•
RED99 is able to investigate the effect of changes in government policy on the rates
of return to higher education.
RED99 is a detailed analysis of the financial costs and benefits of higher education in
Australia for individuals, couples, groups and the Federal government. The costs for
individuals and couples include tuition costs, Higher Education Contributions Scheme
(HECS) payments, and taxes (including income tax, indirect taxes, and tax on
superannuation). The benefits include earnings, government transfer payments
(unemployment benefits, student assistance, age pension etc.) and superannuation.
Costs to the government include the transfer payments, education subsidies, and tax
subsidies on superannuation, while the benefits include taxes and HECS contributions.
The model does not include the less tangible benefits of education, such as improved
employee productivity, enhanced innovation, or a more robust democracy.
While the studies discussed in Section 2 are at an aggregate level, RED99 is constructed
in such a way that it examines individuals, couples or groups of people with the same
characteristics. By examining rates of return to education at the individual level, the model
has a high degree of flexibility that enables changes to virtually all parameters.
By analysing the effect of higher education on income, taxes, and transfers, the model
can estimate the effect that changes in government policy may have on rates of return to
higher education.
The model has two streams, hypothetical and group. The hypothetical stream provides
outcomes for hypothetical individuals or couples. The group stream provides outcomes for
groups that are defined to represent the entire cohort of (initially) 18 year-olds, rather than
just ‘typical’ cases.
The model has three distinct phases: the data assembly, calculation and the presentation
of results phases. The data assembly is conducted in Excel, allowing parameters to be
specified. Calculations are performed using STINMOD. STINMOD is a general purpose
static microsimulation model developed by NATSEM. It models a broad range of Federal
Government programs. The programs currently modelled in STINMOD are Family and
Community Services pensions, allowances and family payments, Veterans Affairs
pensions, Medicare, and income tax. The incorporation of STINMOD into the model
allowed the effects of the Tax and Transfer system to be modelled in areas such as Youth
Allowance (YA), dependent spouse rebate, and maternity allowance. The results are
output in Excel to allow the presentation to be adapted to suit the needs of the user.
The model is highly flexible as there are over thirty parameters that can be specified to
meet the requirements of the user. These parameters are in the areas of personal details,
labour force participation, government policy options, and general economic factors.
Each hypothetical simulation involves parallel processing of two cases, a secondary
graduate and a university graduate, from the age of 18 until death. The output is
presented for both the secondary school and university graduates for the areas listed
below.
•
Education and labour force status
•
Private incomes
•
Government cash payments
•
Education costs/payments
•
Tax
•
Raw summary streams
•
Discounted summary streams
•
Difference between base and comparison individuals
The last element of the output ‘Difference between base and comparison individuals’ can
be used to determine and compare rates of return to different levels of education.
4
The flexibility of RED99
As mentioned above, RED99 has a high degree of flexibility, which allows almost all of the
parameters to be adjusted. The parameters fall into the following categories:
•
Personal characteristics
•
Education characteristics
•
Superannuation
•
Transfer payment parameters
•
Labour force profiles
•
Earnings profiles
•
Environment parameters
Personal Characteristics
Personal characteristics include the individual’s age at marriage, age at retirement, age at
death, and the individual’s gender. Age at marriage is only used in couple simulations.
Retirement age is used in the model as a switch to initiate superannuation calculations.
Age at death is based on average mortality rates, with less educated people being
allocated a slightly lower age at death and those with more education having a slightly
higher age at death.
Education Characteristics
An individual’s education parameters include their level of education, mode of HECS
payment (where applicable), and fee-paying arrangements. Possible education levels
range from incomplete secondary education to a post-graduate degree. HECS payment
options, where applicable, are up-front payment, and deferred (or loan) payments. The
fee-paying options include partial and full fees. The user can also specify the effect
fee-paying students have on the higher education sector (increasing or decreasing the
size of the sector etc).
Superannuation
Superannuation is addressed in the model by specifying the amount of superannuation
accumulated by an individual before the age of 18, and specifying the percentage of
income set aside to accumulate over the individual’s lifetime.
Accumulated superannuation cannot be accessed until retirement, when it is converted to
an annuity. The annuity is based on the number of years from retirement until death, and
it is an overestimation of the amount of income the individual would have in their
retirement years. In reality a retired person does not know when they will die and is likely
to retain as large an asset base as possible to generate an income to live on. We have
created an annuity that consumes all of the person’s superannuation to reduce the
complexity of the model as, in single simulations, there is nowhere for the residual to be
allocated. In simulations of couples the age of death is restricted to 65 or greater and the
annuity fully erodes each member of the couple’s superannuation by the age of death.
Transfer Payments parameters
There are three proxy parameters that are used in determining an individual’s eligibility for
certain transfer payments, such as Youth Allowance. These parameters are parental
means, private renter, and youth payment level. Parental means can be designated as
‘low’ to allow the individual to receive the relevant transfer payment, or ‘high’ to prevent an
individual from receiving a transfer payment altogether. The private renter parameter
identifies those individuals who are in scope to receive rent assistance. The youth
payment level is used to identify those individuals who ‘live at home’, and those who are
‘independent’. This is necessary to determine the level of transfer payments that the
individual will be paid.
Labour Force Profiles
The basic labour force profiles used in the model were derived in three steps, by
specifying:
•
labour force status while studying
•
the length of a person’s working life and the periods of time out of the labour force
•
the proportion of time in various labour force states (full time, part time employment
and unemployment) and the sequence of these states
By deriving the basic labour force profiles in this way we are able to base them on recent
Australian experience, rather than attempting to predict future work patterns. The other
major factor is that the profiles can be adjusted to suit any profile that may be required.
We assume that those studying full time are not in the labour force for the period that they
are studying. The length of working life differs depending on the education status of an
individual, with those with an incomplete secondary education having, potentially, more
years available to spend in the labour force. The workforce participation rate by education
status, based on data from the 1990 Income Distribution Survey, was used to determine
how many of the available years were spent in the labour force. The periods out of the
labour force, for reasons other than education, were allocated to the years immediately
before age 65. The remaining years of working life were allocated a labour force status:
full time employment, part time employment or unemployment. The sequence of labour
force statuses was guided by examining labour force status profiles by age, gender and
education attainment. This led to a general pattern of periods of unemployment followed
by full time employment, then part time employment and finally any unemployment before
retirement.
Earnings Profiles
The model allows complete flexibility for the user to construct and enter specific ageearnings profiles to attach to the hypothetical cases under examination. The section below
refers to the derivation of the default earnings profiles that are drawn from cross-sectional
income survey data.
The data sources for the profiles are the ABS unit record data from the 1990 Income
Survey (IS) and the 1994-95 Continuous Income Survey (CIS). The 1990 IS provided the
main source because it allowed distinction between various fields of study in the
classification of highest educational qualification.
The 1990 IS did not, however, allow distinction between the earnings of those with
bachelor and higher degrees, while such a distinction is available with the 1994-95 CIS
data. Consequently the 1994-95 CIS data were used to generate separate age-earnings
profiles for these two groups, so as to supplement the set of profiles derived from the
1990 IS. The earning profiles were all updated to reflect gross weekly earnings at 1999
levels.
It is important to note that these default age-earnings profiles include no attempt to isolate
that part of earnings differentials that can be attributed to education. The model does, of
course, allow the user to adjust the earnings profiles to reflect alternative assumptions
about the proportion of earnings differences due to education.
Environment Parameters
The Environment worksheet contains a list of possible courses, and characteristics of
those courses — including general education costs and the relevant HECS band. There
are eighty-two courses specified by the level of study and the type of course. There are
nineteen courses specified at the TAFE level, and twenty-one courses each specified at
the undergraduate, other postgraduate, and research degree levels. The general
education cost is the annual cost to government of providing a full-time place in the
course. The HECS band is based on the type of course, and does not apply to TAFE
courses.
Other environmental parameters include tuition costs, HECS repayment parameters and
charges, and Australian Postgraduate Award (APA) amount. Tuition costs includes annual
full time costs excluding HECS (for example, student union fees). The HECS charges,
HECS repayment rates and thresholds, and the APA amount are all the 1999 amounts.
Growth rates are provided for the general discount rate, real interest rate, real rate of
return on superannuation accumulations, real interest rate for superannuation annuities,
real earnings growth rate for each education level, and rates of indexation for income tax
scales and transfer payments.
5
An illustrative example using RED99
As an illustration of RED99 the following section details the simulation used and
discusses the output produced.
The cases that we will compare are from the typical cases provided with the model. The
secondary graduate is a male who has completed secondary school, and the university
graduate is a male who has completed a bachelor degree in science. The figure below
presents the earnings profiles for the base and university graduates used in the
simulation. The method for deriving these profiles is described in the section on the
flexibility of RED99. As would be expected the university graduate has higher earnings
over his working life. People who receive higher incomes are able to withdraw from full
time employment at an earlier age, and as the profiles were based on people employed
full time, the resultant pool of full time employees is comprised of people who earn lower
incomes. The effect of this pattern is that earnings profiles decline from the age of 43 for
secondary graduates and 53 for university graduates.
Figure 1
Age earnings profiles for cases in illustrative simulation
Earnings profiles (real $ pw)
1400
1200
1000
800
600
400
200
0
18
24
30
36
Completed Secondary
42
48
54
60
Bachelor of Science
Data source: Extracted from RED99 model
The other characteristics, labour force and education profiles for each case are given in
Table1 overleaf.
Table 1
Characteristics and profiles of cases used in RED99 simulation
Characteristics
Secondary graduate
University graduate
Gender
Male
Male
Age at marriage
N/A
N/A
Retirement age
65
65
Age at death
75
75
Completed secondary
Bachelor degree
N/A
Loan
Fee paying student option
Turned off
Turned off
Effect of fee paying student on
tertiary sector
Turned off
Turned off
0
0
0%
9%
2.5%
9%
Low
Not a private renter
Low - ‘At home’ rate
Low
Not a private renter
Low - ‘At home’ rate
18 to 55 Employed full-time
56 to 58 Employed part-time
59 to 62 Unemployed
63 to 74 Not in the labour force
18 to 20 Not in the labour force
21 to 61 Employed full-time
62 to 63 Employed part-time
64 to 74 Not in the labour force
N/A
N/A
N/A
N/A
Science
University
3 years
1 (Full-time study)
Personal Characteristics
Education Characteristics
Education attainment level
HECS payment option
Superannuation
Pre 18 superannuation
accumulation
Own contribution rate
Employer contribution rate
Transfer payments
Parental means
Private renter
Youth payments
Labour Force Profile
Ages are inclusive
Education Profile
Course
Level
Length of study
Full-time fraction
Education Costs
HECS charge
Tuition costs
General education costs –
borne by government
N/A
N/A
N/A
$4855 per annum
$770 per annum
$13640 per annum
Growth rates
Real earnings growth rate
Rate of indexation for income
tax and DFaCS payments
Real rate of return on
Superannuation and annuity
Source: Compiled from RED99 model
0.5%
0.5%
0.5%
0.5%
3%
3%
The major differences between these two cases are the education attainment level and
resulting education profiles, own superannuation contributions, labour force and earnings
profiles. In other respects the cases are very similar. The (secondary graduate) does not
make superannuation contributions, while the university graduate makes contributions of
two and a half per cent. The labour force profiles show that the secondary graduate has a
total of four years of unemployment, two years not in the labour force (before retirement
age), and three years of part-time employment. The university graduate is never
unemployed between the age of 18 and 65, spends only one year out of the labour force
and has only two years of part-time employment.
Private Returns
After the simulation has been run, the output is returned to Excel and the following figure,
showing the net undiscounted returns from education, is created. This figure is similar to
the standard representation of returns to university education (see for example
Psacharopoulos 1995). However Figure 2 illustrates net returns, that is earnings and/or
transfer payments less taxes, where the standard representation presents only earnings
and direct education costs
Figure 2
Net private returns for a secondary graduate and a university graduate
(undiscounted)
50000
Net return ($ raw)
40000
30000
20000
10000
0
18
24
30
36
42
Secondary graduate
a with a Science degree.
Data source: Compiled from RED99
48
54
60
University graduate a
66
72
Secondary Graduate Net Return
The secondary graduate obtains full time work at the age of 18 and his earnings less tax
increase until the age of 42 from where they start to decline. At the age of 56 he becomes
employed part-time, and has a drop in his net return. He loses this job and is unemployed
from the age of 59 and he leaves the labour force at the age of 63. During this time he
receives either unemployment benefits or Mature Age Allowance. When he is eligible
(under the rules of this model) to access his superannuation at the age of 65 he converts
his superannuation into an annuity that ceases when he dies at the age of 75.
University Graduate Net Return
The university graduate (the university graduate) receives student assistance from the
age of 18 to 20, and defers his HECS debt until he is working. When he completes his
study, at the age of 21 he obtains full time work and his earnings less tax increase until
the age of 53 where they start to decline. At the age of 62 he takes a part-time job. He
leaves the labour force at the age of 64 and receives Mature Age Allowance for the year
he is not in the labour force. He is then eligible (under the rules of this model) to access
his superannuation and he converts his superannuation into an annuity that ceases when
he dies at the age of 75.
At ages 18 to 20 the secondary graduate was employed full time and the university
graduate received student assistance. The difference between the secondary graduate’s
earnings and the university graduate’s student assistance is the net cost to the university
graduate, or foregone earnings. During that period this amounts to about - $40 000 in
undiscounted terms.
The net benefit for the university graduate is the difference between his income when he
joins the labour force and the income of the secondary graduate. The university graduate
earns more during his working life (from the age of 21 to 64) with an accumulated benefit
of about $438 000.
At the age of 64, both men are out of the workforce, and receiving an allowance from the
government, although they are still paying tax on their accumulating superannuation. As
the university graduate has been both making personal contributions and having a higher
amount of superannuation paid by his employer(s), the tax liability on his accumulating
superannuation is higher than the secondary graduate’s liability. The net effect is a slight
cost to the graduate.
The university graduate then benefits from his years of paying superannuation, by
receiving a higher annuity until his death at the age of 75, with a net cumulative benefit of
about $132 000.
By discounting the stream of costs and benefits so they are equal the private internal rate
of return to a Bachelor of Science degree was calculated to be 13.4 per cent. This return
is slightly lower than the private rate of return to university education for males in 1985-86
of 14 per cent, as calculated by Maglen in his 1993 study. This may mean that the
downward trend for rates of return to higher education that Maglen found is continuing.
However the following points need to be kept in mind when comparing the results form
RED99 to other studies of rates of return to higher education:
•
this simulation presented here is for a very specific case;
•
this simulation is not an aggregate return for all university education, which most other
studies tend to be.
Government Returns
This section presents the returns to the government from university education for our
university graduate. As noted earlier in this paper, this is not a social rate of return to
higher education, but rather the direct government costs and benefits from education. The
net undiscounted return to government are taxes received less any transfer payments
made, Figure 3 shows these returns from the simulation.
Figure 3
Net return to government for a secondary graduate and a university
graduate (undiscounted)
40000
Net return ($ raw)
30000
20000
10000
0
18
24
30
36
42
48
54
60
66
72
-10000
-20000
-30000
Secondary graduate
University graduate a
a with a Science degree.
Data source: Compiled from RED99
Secondary Graduate Net return
In Figure 3 it can be seen that the Federal Government has no costs for the secondary
graduate in the early part of his life. It does reap substantial benefit in the form of taxes,
on both income and superannuation, for the period he is working. The government pays
him a transfer payment from age 59 to 64. After his retirement the government receives
tax revenue on his annuity.
University Graduate Net return
The Federal Government has significant costs in the years that the university graduate is
studying, as it pays him student assistance and is subsidising his education by paying for
the majority of his course costs. However, once he begins work the government receives
substantial benefit in the form of HECS repayments, and additional taxes, on both income
and superannuation, for the period he is working. He is paid an allowance when he is
aged 64. After his retirement the government receives tax revenue from his annuity that is
similar, in undiscounted terms, to the revenue it received when he started his working life.
The net cost to the government for providing a university education to the university
graduate is the taxes that the secondary graduate pays, and it is assumed that the
university graduate would also pay had he not attended university, so the cost in
undiscounted terms was about $74 000.
The benefit to the government was that the university graduate had much higher earnings
and as a result of the taxation system he paid a greater proportion of his earnings in
taxes. The difference in taxes received from the university graduate and the secondary
graduate during the working life of 18 to 64 years of age inclusive was about $521 000.
The year the university graduate is 64 and receiving a payment from the government the
net return is still positive, albeit much smaller, because of the tax on his superannuation.
Over the retirement years the government receives $103 000 in taxes from the university
graduate over and above the taxes received from the Secondary graduate.
After discounting the stream of costs and benefits so they are equal, the Government rate
of return to a Bachelor of Science degree was calculated to be 9.9 per cent. This return
shows that it pays the government to educate people, as the taxes, including HECS,
income tax, indirect tax and tax on superannuation, paid during the working life of a
university graduate more than cover the costs of student assistance and the education
costs borne by the government.
While the government return is measuring only the direct government budgetary impact of
education, it is similar to a social rate of return in that it is lower than the private return. It
needs to be kept in mind that this is a return for a specific hypothetical individual, and their
set of circumstances, not an aggregate return for all university education, so the rate may
vary depending on the circumstances (for example the return to a different degree is likely
to be different).
6
Conclusions
The results from both of the simulations show that higher education does pay, and that it
pays both the individual student and the government. The results also show that higher
education pays a greater return to the individual than it does to the government. These
results are consistent with some of the general patterns found in previous work on rates of
return to education.
To confirm that these patterns hold across various types of study and for both males and
females and when aggregated, it would be prudent to utilise RED99 to examine,
aggregate and compare the results with contemporary studies in Australia that use
alternative methods.
7
References
Harding, A (1993), Lifetime Income Distribution and Redistribution: Applications of a
Microsimulation Model, North Holland, Amsterdam.
Maglen, L (1993), ‘Assessing the Economic Value of Education Expansion: A Preliminary
Review of the Issues and Evidence’, Education Issues: Two Papers prepared for the
Office of EPAC, EPAC Background Paper No. 27, June, pp1-67.
Preston, A (1997) ‘Where are we now with human capital theory in Australia?’ in The
Economic Record, Volume 73, No 220, pp51-78.
Psacharopoulos, G (1995); The Profitability of Investment in Education: Concepts and
Methods, Human Capital Development and Operations Policy HCO Working Papers,
World Bank. (http://www.worldbank.org/html/extdr/hnp/hddflash/workp/wp_00063.html
accessed 15 Jun 2000).
Psacharopoulos, G (1993); Returns to investment in education: a global update, WPS
1067, Policy Research Working Papers, World Bank.
Quiggin, J (1999) ‘Human Capital Theory and Education Policy in Australia’ in The
Australian Economic Review, Volume 32, No 2, pp130-144.
Siphambe, H K (2000) ‘Rates of return to education in Botswana’ in Economics of
Education Review, Volume 19, pp291-300.
Wolter, S C, and Weber, A (1999), ‘On the Measurement of Private Rates of Return to
Education’ in Jahrbucher fur Nationalokonomie und Statistik, Stuttgart, pp605-618.
Secondary Graduate
Private Return
Age
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Income
21736
23348
25012
26676
28340
29900
31408
32812
34320
35776
36608
37440
38272
39104
39988
40612
41288
41964
42692
43316
43836
44356
44928
45396
45916
45708
45500
45292
45084
Expenditure
5520
6265
7027
7741
8442
9097
9730
10281
11025
11643
11893
12242
12593
12943
13317
13581
13867
14177
14488
14768
15015
15262
15537
15759
16008
15892
15776
15661
15549
University Graduate
Government Return
Net
16216
17083
17985
18935
19898
20803
21678
22531
23295
24133
24715
25198
25679
26161
26671
27031
27421
27787
28204
28548
28821
29094
29391
29637
29908
29816
29724
29631
29535
Revenue
5520
6265
7027
7741
8442
9097
9730
10281
11025
11643
11893
12242
12593
12943
13317
13581
13867
14177
14488
14768
15015
15262
15537
15759
16008
15892
15776
15661
15549
Expenditure
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Private Return
Net
5520
6265
7027
7741
8442
9097
9730
10281
11025
11643
11893
12242
12593
12943
13317
13581
13867
14177
14488
14768
15015
15262
15537
15759
16008
15892
15776
15661
15549
Income
Expenditure
Net
Revenue
4545
4568
4590
37908
39832
41808
43836
45812
47840
49816
50908
51948
52988
54028
55172
55484
55848
56160
56576
56940
57304
57564
57928
58344
58708
59176
59696
60268
60788
1238
1240
1243
14270
15177
16441
17553
18637
19751
18256
18789
19755
20281
20808
21388
21544
21728
21886
22101
22290
22480
22613
22805
23026
23219
23470
23751
24061
24344
4077
4097
4118
23638
24655
25367
26283
27175
28089
31560
32119
32193
32707
33220
33784
33940
34120
34274
34475
34650
34824
34951
35123
35318
35489
35706
35945
36207
36444
468
470
473
14270
15177
16441
17553
18637
19751
18256
18789
19755
20281
20808
21388
21544
21728
21886
22101
22290
22480
22613
22805
23026
23219
23470
23751
24061
24344
Government Return
Expenditur
e
Net
18330
18499
18667
376
313
240
164
84
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-17862
-18028
-18194
13894
14864
16201
17389
18553
19751
18256
18789
19755
20281
20808
21388
21544
21728
21886
22101
22290
22480
22613
22805
23026
23219
23470
23751
24061
24344
APPENDIX Income and expenditure for a secondary graduate and a university graduate in illustrative simulation - RED99
Secondary Graduate
Private Return
Age
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
OTALS
Income
44824
44252
43784
43212
42640
42120
41288
40352
39468
11575
11310
11154
10256
11150
11206
11262
11318
11375
26235
26301
26368
26434
26502
26569
26637
26706
26774
26843
1844542
Expenditure
15447
15212
15022
14788
14554
14344
13979
13592
13229
2805
2739
2713
1939
2054
2082
2112
2142
2173
5941
5945
5949
5953
5957
5960
5964
5968
5972
5976
571610
University Graduate
Government Return
Net
29377
29040
28762
28424
28086
27776
27309
26760
26239
8770
8571
8441
8317
9097
9123
9150
9176
9202
20294
20356
20419
20482
20545
20609
20673
20737
20802
20867
1272932
Revenue
15447
15212
15022
14788
14554
14344
13979
13592
13229
2805
2739
2713
1939
2054
2082
2112
2142
2173
5941
5945
5949
5953
5957
5960
5964
5968
5972
5976
571610
Expenditure
0
0
0
0
0
0
0
0
0
0
0
0
10256
11150
11206
11262
11318
11375
270
337
403
470
537
605
673
741
810
879
72292
Private Return
Net
15447
15212
15022
14788
14554
14344
13979
13592
13229
2805
2739
2713
-8317
-9097
-9123
-9150
-9176
-9202
5671
5608
5545
5482
5419
5355
5291
5227
5162
5097
499317
Income
Expenditure
Net
Revenue
61256
62712
64064
65468
66820
68328
68172
68016
67912
67808
67704
66248
64792
63336
61880
18127
17644
11375
49415
49415
49415
49415
49415
49415
49415
49415
49415
49415
2922193
24600
25372
26114
26885
27630
28462
28387
28313
28269
28226
28184
27405
26628
25863
25172
5774
5583
3077
15815
15793
15770
15747
15725
15702
15678
15655
15632
15608
1121216
36656
37340
37950
38583
39190
39866
39785
39703
39643
39582
39520
38843
38164
37473
36708
12354
12061
8298
33599
33622
33645
33667
33690
33713
33736
33760
33783
33807
1803288
24600
25372
26114
26885
27630
28462
28387
28313
28269
28226
28184
27405
26628
25863
25172
5774
5583
3077
15815
15793
15770
15747
15725
15702
15678
15655
15632
15608
1118906
Government Return
Expenditur
e
Net
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
11375
0
0
0
0
0
0
0
0
0
0
68049
24600
25372
26114
26885
27630
28462
28387
28313
28269
28226
28184
27405
26628
25863
25172
5774
5583
-8298
15815
15793
15770
15747
15725
15702
15678
15655
15632
15608
1050857