Kiss, Judit, T.

ANNALS OF THE ORADEA UNIVERSITY Fascicle of Management and Technological Engineering

University of Debrecen Electronic Archive

  
 
Abstract—According to the human capital theory, 
education can be seen as an investment into individual human 
capital. The profitability of human capital investment is partly 
determined by the individuals’ work-related earnings. The 
study examines how work-related earnings and the gap between 
gross earnings at different educational level changed in 
Hungary, between 2004 and 2013. An indicator is defined and 
presented to measure the change in gross earnings and net 
earnings caused by the education as human capital investment. 
Moreover we examine the change in earnings surplus by 
educational level, look for the answer to the question whether 
the gap between earnings for individuals with different 
educational attainment increased or decreased in Hungary from 
2004 to 2013. 
 
Keywords—educational level, marginal earning rate, 
investment in human capital, tax burden 
I. INTRODUCTION 
HE main topic of our examination was given by the 
human capital theory. According to the human 
capital theory, individual’s knowledge and skills can be 
referred to as capital and all activities which with present 
expenditures make future benefits while productivity of 
the individual grows can be interpreted as an investment. 
Many researchers have examined the significance and the 
main features of investments in human capital [1], [2], 
[3], [4], [5], [6]. Expenditures on health, training, 
education and migration can be seen as an investment in 
human capital. The profitability and the rates of return of 
education can be measured from the individual’s, the 
society’s and the state’s point of view. The individual 
rates of returns show how profitable for an individual to 
finish higher level of education. The main component of 
the profitability is the earning surplus achieved with the 
investment in human capital.  
The purpose of this paper is to examine the main 
characteristics of earnings surplus by educational levels. 
We examine how earnings differences between 
individuals with a given education level and ones with 
next lower educational level changed in Hungary, 
between 2004 and 2013. We define the marginal earning 
rate (MER) as an indicator to measure the impact of 
investment in education on gross and net earnings from 
employment.  
II. CHANGES OF GROSS EARNINGS BY EDUCATION LEVEL 
IN HUNGARY, BETWEEN 2004 AND 2013 
We examine the gap between gross earnings at 
different educational level in Hungary, between 2004 and 
2013. Data of gross earnings was provided by the 
National Employment Service [7]. “Gross amount of the 
regular earnings elements took into account in the 
reference month, plus 1/12
th
 of the total amount of non-
monthly bonuses, reward and 13
th
 month’s pay received 
in the previous year” [7]. The report of earnings includes 
full time and part-time employees. The survey covered 
enterprises with a staff of 5 or more as well as non-profit 
organizations, and public institutions without headcount 
limit [7]. Individuals’ gross earnings from employment 
rises with each level of education attained, except for 
primary school qualification [Fig.1.]. The largest increase 
of gross earnings occurred for individuals with 
apprentice vocational school and primary school (by 
69.5% and 60.9% respectively).  
 
 
Fig 1. Average gross earnings by educational attainment in 
Hungary, between 2004 and 2013 [7] 
 
The smallest increase of gross earnings occurred for 
individuals without primary school graduation (38.3%) 
ANALYSIS OF EARNINGS SURPLUS BY 
EDUCATIONAL LEVEL IN HUNGARY, 
BETWEEN 2004 AND 2013 
 
Judit T. KISS
1
,  
1University of Debrecen, tkiss@eng.unideb.hu 
  
T 
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ANNALS OF THE ORADEA UNIVERSITY  
Fascicle of Management and Technological Engineering 
ISSUE #1, MAY 2015, http://www.imtuoradea.ro/auo.fmte/ 
 
97 
 
  
and for individuals with university degree (40.9), as 
shown in Fig. 1.  
The gap between earnings at a given educational level 
and the lower level for employees increases by 
educational attainment, as shown in Fig. 1 and Fig 2. 
Earnings differences between individuals with apprentice 
vocational school and primary school increased by 
43.5%. The ratio of gross earnings at tertiary educational 
level and next lower educational level decreased in 
Hungary between 2004 and 2013, as shown in Fig 2. The 
largest decrease occurred for individuals with secondary 
upper school by 13.2 percentage points [Fig. 2.]. 
However, the earnings difference at primary school level 
as a percentage of earnings of the agents without primary 
school qualification was negative in 2004 and between 
2006 and 2012 (with exception of 2011). 
 
 
Fig 2. The change in gross earnings differences between 
individuals with a given education level and ones with next 
lower educational level in Hungary, between 2004 and 2013 
 
III. CHANGES OF GROSS EARNINGS AND NET EARNINGS 
CAUSED BY THE CHANGE IN EDUCATION ATTAINMENT IN 
HUNGARY, BETWEEN 2004 AND 2013 
We turn our attention to the alteration in the gross 
earnings caused by the change in individual educational 
attainment. We define an indicator to measure the 
mentioned change in earnings. The calculation of the 
indicator is based on the presumption that the labour 
market rewards the highest completed education level 
and an additional completed year of school. This 
assumption is a very strong condition since the change in 
earnings depends on many factors such as employment 
status, the productivity of an economy, the type of 
occupation, regions, work experience, and employee’s 
age and gender. However, the marginal earning rate 
(MER) measures the change in earnings in an 
environment determined by economic and social factors.  
Marginal earning rate on education shows how the 
individual’s average earning changes as individual’s 
educational attainment changes, with all other variables 
unchanged: 
1jj
1jj
EDAEDA
EE
EDA
E
MER







 ,     (1) 
where jEDA  is the sum of the years of schooling 
completed by the individual ( j -th level of education 
level), jE  is the average earning for an individual with 
j -th educational qualification. Marginal earning rate on 
education reflects the increase in gross earning (net 
earnings) when the years of schooling rises by one unit at 
given educational level.   
The largest gross proceeds from investment in 
education occurred in the case of tertiary education. One 
year of study at a university yielded 52 923 HUF in 2013 
(Fig. 3.). The value of MER for individuals with primary 
school was negative in 2004, because the average gross 
earning for individual with primary school qualification 
was less than that of individuals with a lower level of 
educational qualification (Fig. 1. and Fig 4.).  
 
 
Fig 3. The change in marginal gross earning rate on education 
by educational level in Hungary, in 2004 and 2013 
 
 
 
Fig 4. Marginal gross earning rates on education by educational 
level in Hungary, between 2004 and 2013 
 
The earning surplus gained from attaining one extra 
year of tertiary education increased by 40% between 
2004 and 2013. The participation rates in tertiary level of 
education decreased from 2004 to 2013. The number of 
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ANNALS OF THE ORADEA UNIVERSITY  
Fascicle of Management and Technological Engineering 
ISSUE #1, MAY 2015, http://www.imtuoradea.ro/auo.fmte/ 
 
98 
 
  
students enrolled in tertiary education decreased by 
9.81% from 2004 to 2013 [8]. According to the change in 
gross earnings, the value of the university and college 
qualification increased with a considerable measure. The 
change in MER was the highest for individuals with 
primary school qualification, the value of MER was -421 
HUF in 2004 and 1 943 HUF in 2013 (Fig. 3.). 
As a matter of fact, the marginal earning rate on 
education can be calculated in two ways. Gross earnings 
and net earnings can be taken into account when 
calculating the marginal earning rate. We can distinguish 
marginal gross earning rate (MGER) and the marginal net 
earning rate (MNER), depending on which earnings 
measure is used: 
 
1jj
1jj
EDAEDA
BTEBTE
EDA
BTE
MGER







 ,     (2) 
 
1jj
1jj
EDAEDA
PTEPTE
EDA
PTE
MNER







 ,     (3) 
where jBTE  is the before-tax earnings for individual 
with j -th educational qualification and jPTE  is the 
post-tax earnings for individual with j -th educational 
qualification.  
The gross earnings are determining factors in social 
costs and social benefits, contained in social rates of 
returns calculations. However, post-tax earnings are 
taken into account for private benefits and private 
indirect costs when calculating the private rates of return 
to education. In the following, we determine the marginal 
net earning rate that shows the change in post-tax 
earnings as the year of school increases by only one unit.    
The extent of taxes on labour income and the para-
fiscal charges (and tax wedges) are very high in 
international comparison in Hungary. The tax wedge 
shows how much the government collects revenues as a 
result of taxing the labour force. Tax wedge is the sum of 
personal income tax and employee plus employer social 
security contributions together with any payroll tax less 
cash transfers, expressed as a percentage of labour costs 
[9]. The largest tax wedge for a single person without 
children at 100 per cent of the earnings of an average 
worker could be found in Belgium (55.4%) and Germany 
(52.2%) in 2004 [10]. The value of the tax wedge in 
Hungary was the third highest value (51.7%) among 
member OECD countries. The lowest tax burden as a 
percentage of labour cost was in Chile (7%) and Mexico 
(17.9%).  
The main features of personal income tax system and 
para-fiscal contributions have changed in Hungary over 
the examined period (between 2004 and 2013). The 
progressive taxation on labour income was replaced by 
the flat income tax rate (16%) in 2011. The tax burden on 
labour income did not decrease significantly with the 
introduction of proportional taxation. The amounts of 
taxes on labour income, and tax wedges have remained 
relatively high mostly due to higher employee social 
security contributions and employer social contribution 
tax. The value of the tax wedge in Hungary was the 
fourth largest (49%) among OECD member countries in 
2013 [11]. The largest tax wedge occurred in Belgium 
(55.8%), Germany (49.3%) and Austria (49.1%) in 2013. 
The lowest tax burden as a percentage of labour cost 
could be found in Chile (7%) and New Zealand (16.9%) 
in 2013. 
We calculated tax liabilities for single individual 
without children at the income level of the average 
worker. Post-tax earnings, as actually realized value by 
the individual, are taken into account for earnings surplus 
when calculating the marginal net earning rate on 
education. The value of marginal net earning rate on 
education increases by educational level. The largest 
value occurred for individuals with university 
qualification, the MNER was 34 664 HUF in 2013, as 
shown in Fig. 5 and Fig 6. The market value of university 
qualification is very high, and it is accordance with the 
private rates of return to tertiary education. The private 
internal rate of return for a man attaining tertiary 
education was the highest in Hungary (25.6%) among 
OECD member states in 2009 [12]. The OECD average 
of private returns to tertiary education was 13% [12]. The 
private rates of returns for individuals with tertiary 
education completed in Hungary were the second highest 
among OECD member countries in 2010 (28.5% for men 
and 24.6% for women) [13]. The largest private rate of 
return occurred in Ireland (29.9% for men) and Estonia 
(29.7 for women) [13].  
 
 
 
Fig 5. The change in marginal net earning rate on education by 
educational level in Hungary, in 2004 and 2013 
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ANNALS OF THE ORADEA UNIVERSITY  
Fascicle of Management and Technological Engineering 
ISSUE #1, MAY 2015, http://www.imtuoradea.ro/auo.fmte/ 
 
99 
 
  
 
Fig 6. Marginal net earning rate on education by educational 
level in Hungary, between 2004 and 2013 
 
The college education is less lucrative in Hungary, 
compared to the university education, which is due to the 
lower earnings surplus of individual who has college 
educational level compared to the individual who has the 
next lower level educational attainment (Fig. 5, Fig 6).  
Negative values of MNER can be observed for 
individuals with primary school qualification (Fig. 6.). 
Negative MNER occurred in 2004 and between 2006 and 
2013 because the earnings of those with primary school 
qualification lagged behind to the earnings of those with 
lower than primary school qualification as shown in Fig. 
1. and Fig 6.  Consequently the private rates of return on 
primary education is probably negative, the earnings 
surplus is negative which cannot produce returns in a 
way that it cannot compensate the education costs 
compared to wages in the labour market. 
IV. CONCLUSION 
Our aim was primarily to gain insight into how the 
market values the knowledge and skills of individuals 
with given educational qualification. We examined the 
change in gross earnings and net earnings caused by 
attaining one year of school at different educational level. 
We defined and analysed the marginal net earning rate 
and marginal gross earning rate on education.  
The earning surplus shows the benefit that individuals 
can realise following their human capital investment in 
the labour market. According to our results, the earning 
surplus of individual who has j-th educational level is 
compared to the individual who has (j-1)-th educational 
increased over the 2004 - 2013 period. The marginal 
earning rate on education shows the change in 
individual’s average earning as an individual’s 
educational attainment increases. Both gross marginal 
earnings rates and net earnings rates on education 
increased in Hungary between 2004 and 2013. The 
marginal earning rates rose by educational level. This 
means that higher education as a human capital 
investment brings great returns for the individual in 
Hungary. The calculation of marginal earning rates can 
be improved with the correction of probability of 
unemployment. This means that we have to take into 
account the unemployment rates by educational level.  
Moreover the examination of calculation of marginal 
earning rates can be extended to take into account the 
earnings broken down by age.   
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ISSUE #1, MAY 2015, http://www.imtuoradea.ro/auo.fmte/ 
 
100 
 


Analysis of Earnings Surplus by Educational Level in Hungary, Between 2004 and 2013

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Analysis of Earnings Surplus by Educational Level in Hungary, Between 2004 and 2013

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