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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