Reservations Wage of Young Workers in The Minimum Wage
Perspective
Mutiara Fadilla Muslimah, Yunisvita and Imelda
Faculty of Economics, Universitas Sriwijaya, Palembang, Indonesia
Keywords: Age, Education, Field of Study, Gender, Wages Reservations, Young Worker
Abstract: This study discusses the opportunities for young workers to choose a reservation wage between above the
Minimum Regional Wage (UMR) or below the UMR. Data used in this study are primary data with 100
respondents. Analytical technique used is binary logistic regression. The result of this study showed that
education variables have a positive and significant effect. Gender variables also have a positive and
significant effect, meaning that there is a difference in the opportunity to set a reservation wage between
male and female workers. Then the age variable has a negative and significant effect.
1 INTRODUCTION
Youth are described as human beings who are
high-spirited, energetic and intellectually in
accordance with the times, so they have a big role in
a large civilization (Rusmana, 2016). Youth in
economic demography is an asset to drive
development, but on the other hand youth can be a
burden (Mayella, 2017).
Labor conditions in the city of Palembang
illustrate that the number of young workers in 2015
amounted to 301.137 people. This number decreased
from 2014 which was 302.657 people. The number
of working population increased in 2015, which
661.192 people to 663.315 people. The increase in
the number of working population was followed by
an increase in the workforce, from 729.121 people in
2014 to 733.121 people in 2015. The rate of increase
in the labor force that was greater than the increase
in the number of workers (working population)
caused the percentage of unemployment rates also
increased during 2014-2015 is from 9.32% to
9.52% Central Bureau of Statistics of Palembang
City, 2015).
In contrast to the increase in the open
unemployment rate, the labor force participation rate
of Palembang City decreased slightly from 63.63%
in 2014 to 62.91% in 2015. According to
employment data and information center data, the
population working in Palembang City in 2014 was
more dominated by workers with education levels
High school with a total of 252.546 workers, then
148.314 people with primary education, followed by
133.097 university workers with university
education.
This is the same as in 2015, namely the workers
who dominate the labor market are workers with a
high school education level, then workers with
primary education levels, then workers with
university education levels. Thus, in Palembang City
young workers who control the labor market are
residents with high school level. This is because
many residents prefer to work after completing their
school years, with the reason of not having the cost
to enter university/college.
Existing labor offers can be formed using
reservation wages, the lowest wage rates where a
person still wants to work or the highest level of
wages where a person is still unemployed. The
supply of labor is represented by the characteristics
of reservation wages which is an important concept
in making a model of labor market dynamics
(Tajibu, 2012).
Reservation wages play an important role in job
search theory, labor supply and participation in the
labor market (Brown, Roberts, & Taylor, 2008).
Reservation wages are the highest wages for
someone who is unemployed to remain unemployed
or work/minimum acceptable wage(Killingsworth,
1983) in (Walker, 2003).
Reservation wages are a benchmark for someone
to accept a job. Many factors can affect reservation
wages. According to (Malk, 2014) personal
448
Fadilla Muslimah, M., Imelda, . and Yunisvita, .
Reservations Wage of Young Workers in the Minimum Wage Perspective.
DOI: 10.5220/0008441204480457
In Proceedings of the 4th Sriwijaya Economics, Accounting, and Business Conference (SEABC 2018), pages 448-457
ISBN: 978-989-758-387-2
Copyright
c
2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reser ved
characteristics, household income levels and
regional unemployment rates are important factors
that influence the determination of wage levels. In
addition, the duration of unemployment, gender and
age also affects the level of wages.
Age greatly affects the reservation wages
offered. Usually those aged 40 years and over will
consider their reservation wages. According to
research by (Humpert & Pfeifer, 2011) conducted in
Germany, the level of employment decreased with
increasing age after a maximum age of 30 to 50
years for men and 40 to 50 years for women. Hourly
wages increase as men and women age.
Workers of young age will set a high reservation
wage because the level of productivity of young
workers is considered to be higher compared to
older workers. Job opportunities in industries or
other jobs will be more limited for older workers
with longer unemployment compared to young
workers. This is caused by: 1) decreased
employment opportunities along with increasing
age, and 2) limited employment opportunities that
increase the length of unemployment for workers at
a young age (Dygalo, 2007).
In addition to age, reservation wages are also
very much determined by education. Education is
considered capable of producing high-quality
workforce, having a pattern of thinking and acting in
a modern manner (Khusyono, 2014). But there is a
tendency that the higher the education level of the
labor force the longer the waiting period is. The
waiting period of the workforce that has a high level
of education is also due to the high targeted
reservation wages.
Workers with a high level of education will also
set high reservation wages, because highly educated
workers are considered to have a more advanced
mindset so that they will be better able to make
decisions. According to (Astuti, 2013) higher
educated workers earn higher annual income and
increase faster than workers with low education
from the same age group as they increase their
employment.
Field of study can also affect reservation wages.
According to the Undang-Undang Republik
Indonesia Number 12 of 2012 is about Higher
Education. Higher education is a level of education
after secondary education which includes diploma,
undergraduate, master, doctoral, professional and
specialist education programs organized by
universities based on Indonesian culture.
Universities are providers of higher education for
vocational, academic and/or professional education.
Reservation wages can be influenced by the type of
higher education that has been taken by those who
want to work.
According to Maryani (2008) in (Khusyono,
2014) non-exact sciences majors are considered as
second class after the exact sciences department. In
addition, non-exact sciences are often considered as
departments that cannot guarantee the future and are
difficult to get a job. This is in accordance with what
has been assumed by the public that workers with
exact education backgrounds will find it easier to get
jobs. Thus, workers with exact education will set
their reservation wages higher than workers with
non-exact education. Furthermore, the workforce
with exact education background when continuing
their education to university level will choose
education with a scientific major.
The unemployed period or the duration of
unemployment is a description of a new problem for
the unemployment phenomenon that has never been
resolved. Unemployment duration can also affect
reservation wages. According to (Tarmizi, 2014)it is
common for individuals to choose a wage higher
than the reservation wage. There are two effects of
this choice, first individuals will receive higher
wages and reject lower-paying jobs. Secondly, this
rejection will result in the probability of getting
another job down and this will make the
unemployment period longer. More selective young
working in job searching their causes high potential
for the unemployed, and the problem is
characterized by the long duration of the labor force
unemployed young age (Putra, Zain, & Madris,
2014).
Work force that comes out or works again
according toMortensen and McCall (1976) in (Foley,
1997)is assumed to have a waiting time that is
affected by the probability of the possibility of
receiving the offered job and reservation wages.
Reservation wages themselves are determined by
costs when looking for work, unemployment income
if available, distributed of expected wage offers and
the possibility of receiving the next job in
accordance with education, skills, experience and
local demand conditions.
Brown, Taylor, Brown, & Roberts (2011)
conclude that there is a gap between intergender
reservation wages, especially with children under
five, playing an important role in this gap. Labor
without children, an unexplained component reaches
99 percent while for workers with children only
reaches 22 percent. This indicates that
discrimination in the labor market affects reservation
wages.
Reservations Wage of Young Workers in the Minimum Wage Perspective
449
Simanjuntak (2001) explains this because men
are considered as the main breadwinners for
families. This assumption is what makes men more
selective in choosing jobs that match their
aspirations both in terms of income and in terms of
position.
2 LITERATURE REVIEW
Reservation wages are wage rates that are only
sufficient for minimal living costs or the lowest
wage rates where workers will be willing to accept
certain types of work (Tarmizi, 2014). The definition
of reservation wages implies that the person will not
work at all if the market wage is less than the
reservation wage, and the person will enter the labor
market if the market wage exceeds the recurring
wage (Borjas, 2013).
Before the process of finding a job, job seekers
determine the lowest wage they are willing to
accept, which is called the reservation wage. When a
worker is unemployed they expect the
unemployment period to end immediately which is
possible when they receive the job offered. Workers
will accept job offers with consideration of the
minimum wage received. Workers take into account
the costs of searching, income from unemployment,
distribution of expected reservation wage offers and
the possibility of accepting other jobs (Foley, 1997).
Reservation wages are used in explaining job
search behavior through search theory (Job Search
Theory). Optimal search theory with the assumption
of stationary reservation wages predicting a positive
correlation between the two, namely workers who
have high reservation wages will tend to have a long
unemployment period and vice versa (Tajibu, 2012).
Job search theory explains that a prospective
worker does not get a job because there is a long
period of time between available work and
information obtained about the job (Tarmizi, 2014).
This is because every job vacancy must have the
terms, criteria and conditions that apply to
prospective workers. So that only workers who have
criteria in accordance with these conditions are
acceptable.
Job search theory is a model method that
explains the problem of unemployment from the
point of supply, namely the decision of an individual
to participate in the labor market based on the
characteristics of individual job seekers (Yani,
Hamidi, & Setiawan, 2014). Job search theory
hypothesizes that the determinant of the
unemployment rate is the cost of searching for a
reservation wage job, assuming that anything that
can increase the cost of seeking employment will
reduce the reservation wage. Thus, with the
increasing demand for labor, job seekers will find
jobs easier and mean lower costs of seeking
employment and increase reservation wages
(Sutomo, 1999) in (Khusyono, 2014).
Foley (1997) in (Astuti, 2013)explains that job
search theory predicts that the unemployment period
becomes longer when the reserve wages fall, the risk
of obtaining employment is high (called positive
dependence) and when the intensity of job search
falls, the risk of employment opportunities will
decrease (called negative dependency).
3 RESEARCH METHODS
This study discusses the decision of young
workers to set reservation wages in Palembang City.
The object of this study was the population with the
age range of 15-24 years who had worked in the city
of Palembang. The dependent variable in this study
is the reservation wage based on the South Sumatra
Regional Minimum Wage (UMR) in 2018 that is Rp.
2.595.995 and the independent variable in this study
is age, education level, field of study, unemployment
and gender
This study uses nonprobability sampling,
sampling technique by means of purposive
sampling, namely sampling techniques with certain
considerations (Sugiyono, 2013). The number of
population in this study was 301. 137 residents aged
15-24 working in Palembang City. Thus, the number
of samples taken was calculated using the Slovin
formula in this study as many as 100 people.
The data analysis technique used is a Binary
Logistic Regression Model an asymptotic function
(between 0 and 1) in the objective function.
Based on these equations, the models in this
study are as follows:
Where: RW = Wages Reservations (1 = above the
minimum wage, 0 = below the minimum wage); P =
Probability of respondents who have a reservation
wage above the minimum wage; 1-p = Probability of
respondents who have a reservation wages below the
minimum wage; βi = coefficient of variables; Age =
Age; Edu = Education; Fs = Field of study UnE =
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Duration of unemployment; Gen = Gender; μ = error
rate.
According to Yamin & Kurniawan (2014) the
results and the logistic equation cannot be directly
interpreted from the coefficient value as in ordinary
linear regression. Interpretation can be done by
looking at the value of Exp (B) or the exponent
value of the regression equation coefficient that is
formed.
Nachrowi & Usman (2002) describe the
interpretation of coefficients in a logistic model
carried out in the form of Odds Ratio (comparative
risk) or in an adjusted probability (probability
occurs). Odds are defined as
(risk), p represents
the probability of success and 1 - p states the
probability of failure. odds Ratio (Risk ratio) is a
value Odds ratio (risk) on the two individuals.
Odds Ratio is a comparison of the value of
Odds (risk) in two individuals.
Odds Ratio is writtenas:
Based on bivariate data (X, Y) where X is the
one-zero variable and Y is the one-zero response
variable, the Odds Ratio in the logistic model can be
presented in the general form as follows:
P = P (Y = 1) states the proportion of the score/
value of Y = 1 in the population among all possible
zero scores/values. The magnitude p = P (Y = 1) is
often also expressed as the probability or probability
of an event/case determined by a score of Y = 1, if a
/an individual is chosen randomly from a particular
population (Nachrowi & Usman, 2002).
3.1 Goodness of Fit Test
To assess whether the model is fit with the data
used in two ways (Sujarweni, 2014):
1. Hosmer and Lemeshow Feasibility Test, i.e. if
the probability value is>5%, it means that the
binomial logistic regression model is feasible
for further analysis.
2. Assessing the appropriate model, which is a
reduction in the -2Log value, possibly the initial
value in the next step will mean the hypothesis
of the model matches the data.
3.2 Variable Operational Definition
Table 1. Definition of Operational Variables
Variables
Definition
Indicator
Wages
Reservations
The first wage
received by
workers
Rupiah
(1 = above
UMR
0 = below
UMR)
Age
Age workers
Year
Education
Duration
education of
worker
Year
Field of Study
Duration of
unemployment
Gender
Educational
programs
undertaken by
workers
The transitional
period workers
wait for a first
job
Sex workers
1) 1 = Academic:
junior high,
high school
and
undergraduate
0 = Vocational
Education:
High school,
D1-D4, and
polytechnics
Month
1 = Male
0) 0 = Female
4 RESULTS AND DISCUSSION
4.1 Cross Tabulation Age and Wages
Reservations
Age is a factor that can affect the reservation
wage, the higher the person's age offered the
reservation wage will also be reduced or smaller
than the reservation wage offered on young workers.
This is because labor is considered a young are more
productive in performing tasks compared to those
who are elderly.
Table 2 shows that most of the respondents in
this study have reservation wages below the UMR.
This can be seen from the 3 highest groups of
respondents who are respondents aged 19-24 years
with a reservation wage level below the UMR. Then
there are 5 cells with a number of respondents that
are less than 12%.
Reservations Wage of Young Workers in the Minimum Wage Perspective
451
Table 2: Cross Tabulation Age and Wages Reservations
Age
(Year)
Wages Reservations
(Rp)
Total
above UMR
below UMR
17-18
2
3
5
19-20
1
14
15
21-22
11
37
48
23-24
4
28
32
Total
18
82
100
Source: Primary Data 2018
Then the lowest number is respondents aged 19-
20 at the reservation wage level above the minimum
wage, which is only 1%. This is because the
respondents in this study were young workers who
worked as salespeople whose average wages were
received below the UMR.
4.2 Cross Tabulation of Education and
Wages Reservations
Education can also be a determinant of a person's
wages. The higher one's education, the higher the
wages offered. This is because a person with high
education has its own added value where they are
considered to have better and more advanced
thinking patterns than those who have a low level of
education or who are not in school.
Table 3: Cross Tabulation Education and Wages
Reservations
Education
(Year)
Wages Reservations
(Rp)
Total
above
UMR
below
UMR
9
1
1
2
12
7
48
55
> 12
10
33
43
Total
18
82
100
Source: Primary Data 2018
Table 3 shows that there are the same number of
respondents and the lowest is 1% with a junior high
school education level (9 years) that has a
reservation wage level above and below the UMR.
The highest level of education with reservation
wages above the UMR is at the level of education
>12 years, which is 10%. But this number is still
very far compared to the number of respondents who
have a reservation wage below the UMR, at the level
of education >12 years the number of respondents is
3 times more that is 33% and at the 12 year
education level the number of respondents almost
reaches 5 times, namely 48% compared with the
highest number of respondents on reservation wages
below the UMR.
4.3 Cross Tabulation Field of Study
and Wages Reservations
Field of academic study is considered better and
higher than the vocational field of study. Public
perception of the academic higher education has
been embedded for a long time, so that workers with
academic education background will set a higher
reservation wages than workers who take vocational
education. Table 4 shows the level of the reservation
wage above the minimum wage with all kinds of
fields of study has a number of respondents who are
not more than 14%. It is inversely proportional when
seen in reservation wages below the minimum wage.
Can be seen on the reservation wages below the
minimum wage with a field of academic study are
those that have the highest number of respondents,
more than half of the total number of respondents
who precisely as much as 60%. While the field of
vocational study only 22%. The number of
respondents in concentration vocational science
majors is less than the concentration/majors in
academic science, which is only 26%.
Table 4: Cross Tabulation Field of Study and Wages
Reservations
Field of
Study
Wages Reservations
(Rp)
Total
above
UMR
below
UMR
Academic
14
60
74
Vocation
4
22
26
Total
18
82
100
Source: Primary Data 2018
4.4 Cross Tabulation Duration of
Unemployment and Wages
Reservations
Duration of unemployment person can affect the
reservation wage. The longer someone unemployed
then the reservation wage will also decrease. Unless
they were during idle receive severance pay or
benefits and family support, they will dare to set a
high reservation wage.
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Table 5: Cross Tabulation Duration of Unemployment and
Wages Reservations
Duration of
unemployment
(Month)
Wages
Reservations (Rp)
Total
above
UMR
below
UMR
0-11
13
66
79
12-23
2
8
10
24-35
2
4
6
36-48
1
4
5
Total
18
82
100
Table 5 shows the respondents with spells of
unemployment that are in the 12-35 month time span
has the same number of respondents i.e. 2% with the
reservation wage rate above the minimum wage.
This is the same when compared with the number of
respondents who are in the idle period with a span of
36-48 months at a rate below the minimum wage
reservation wage is 4%. While respondents with
unemployment 0-11 months old have the highest
number of respondents either the reservation wage
level above or below the minimum wage is as much
as 79%. That is, it can be concluded that the
majority of respondents in this study were old
unemployed respondents with no more than 11
months.
4.5 Cross Tabulation of Gender and
Wage Reservations
Gender or sex has long been embedded in mind
the public that there is always a difference between
men and women. Men are considered more capable
and shall be liable to the family so that the male
wage reservation will also be higher than the
reservation wage of women.
Table 6 illustrates that the number of female
respondents more than the number of male
respondents. At the level of the reservation wage
below the minimum wage, female gender of
respondents with more than respondents with male
gender is 59%. The reservation wage rate above the
minimum wage of respondents with male gender 2%
more than women.
Table 6: Cross Tabulation of Gender and Wage
Reservations
Gender
Wages Reservations
(Rp)
Total
above
UMR
below
UMR
Man
10
23
33
Woman
8
59
67
Total
18
82
100
Source: Primary Data 2018
4.6 Binomial Logistic Regression
Estimation Results
Log likelihood value in Table 6 there is a
reduction in the value of -2LL at step 0 is equal to
94.279 with a value -2LL in step 1 of 84.424. Thus,
it can be stated that the hypothesized models fit the
data.
Table 7: Log Likelihood
Step
-2 Log Likelihood
0
94.279
1
84.424
Source: Primary Data 2018
Based on the calculation value B Table 7, the
regression model that will be formed as follows:
Table 8: Results of Logistic Regression
Variables
B
Sig
Odds
Ratio
Odds
Ratio
Dummy
Age (Age)
-
0.349
0.091
0.705
-
Education
(Edu)
0.368
0.048
1.445
-
Field of study
(Fs)
0.163
0.809
1.177
0.54
Duration of
unemployment
(UnE)
0.019
0.480
1.019
-
Gender (Gen)
1.322
0.024
3.749
0.79
Constant
0.141
0.969
1.152
-
Source: Primary Data 2018
As well known, the coefficient value in logistic
regression is difficult to interpret directly. Thus, to
explain the logistic regression model the coefficient
Reservations Wage of Young Workers in the Minimum Wage Perspective
453
value needs to be interpreted as a probability value
called Odds Ratio (Nachrowi & Usman, 2002).
Age variables have a negative and significant
influence (at the 10% significance level) on the
reservation of young workers in Palembang City.
This can be seen from the coefficient value of -0.349
with the Odds Ratio value of 0.705. This Odds Ratio
value indicates that the more labor age increases the
probability or opportunity to set a reservation wage
above the 0.705 UMR is lower than the reservation
wage below the UMR. That is, when age increases,
the reservation wages offered will decrease and
when the age of the workforce decreases (young) the
wages offered will increase. This happens because it
is seen from their ability/productivity level at work.
Young laborers will set high reservation wages
because the level of productivity of young workers
is considered higher when compared to workers who
are not classified as young. This will affect the
employment opportunities of elderly workers to get
a job. The results of this study are supported by
research conducted by by (Humpert & Pfeifer,
2011)where the findings of their research stated that
the wages offered depend on worker productivity
and company decisions.
Besides that, when viewed from the income side,
when in the productive period in general the age
increases, the income will increase, depending on
the type of work done. A person's physical strength
to carry out activities is closely related to age.
Because when someone has passed the productive
period, then the level of productivity will decrease
and the income will also decrease (Putri &
Setiawina, 2013).
But on the other hand, based on the data
obtained in the field, in this study the most
participating respondents were respondents who
worked as salespeople. Therefore, Table 1 shows
that many young workers have low reservation
wages (below UMR). This is in line with the theory
described by (Borjas, 2013)that when workers are
young, the relative wages will be low. Because
working as a salesperson, when they decide to start
working with a minimum educational background of
high school will receive a low wage. Besides that,
usually the work as a salesperson is limited by age
because what is needed is a young and attractive
workforce. When their age increases, the wages
offered will be low. This contrasts with Borjas's
(2013) theory which explains when adult workers'
reservation wages will increase. Then, when
entering old age the relative wages will fall again,
because workers with old age are certainly no longer
attractive if they work as salespeople.
In the education variable, the results show that,
the higher the education level of a worker, the
probability or opportunity to set a reservation wage
above the UMR is 1.445 times higher than the
reservation wage below the UMR. This can be seen
from the coefficient value of 0.368 and the Odds
Ratio value of 1.445. This shows that the education
variable has a positive and significant influence on
the reservation wages of young workers in the city
of Palembang. When the workforce has a high level
of education, he can set the reservation wage above
the UMR. Workers with a high level of education
should get decent wages to support their lives to be
more prosperous.
The results of this study are in line with the
research of (Istekli & Senturk, 2016)that the factors
that influence someone's reservation wages are
education. When viewed from human capital,
increasing education causes an increase in
reservation wages. That is, the higher the level of
education pursued by a person, the higher the wages
of the reserve. Likewise, the opinion of (Becker,
1975)in the theory of Human Capital says that wage
rates are influenced by education, training, skills and
work experience. In other words, the level of wages
received is determined by the investment in human
capital itself.
According to (Miswar, 2018)education, type of
work, working hours and work experience have a
positive and significant effect. The length of school
one year will increase wages assuming other
variables are constant. That is, the length of a
workforce going to education will increase the level
of wages received by the workforce. Then in
research (Khusyono, 2014)also obtained the results
that education is considered capable of producing
high-quality workforce, having a pattern of thinking
and acting in a modern manner. Therefore, workers
with a high level of education will also set high
wages compared to workers who have a low level of
education.
The effect of field of study variables on the
reservation wages of young workers in Palembang
City shows that the field of study variable has a
positive and insignificant effect. This can be seen
from the coefficient value of 0.163 with an Odds
Ratio value of 1.177.
Because the field of study variable’s dummy, the
Odds Ratio value needs to be interpreted further, so
that the dummy Odds Ratio is 0.54. Thus, it can be
seen that workers with academic field of study have
the opportunity to set reservation wages above the
UMR of 0.54 times higher than workers with field of
vocational studies. Because the results were not
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significant, it means that in this study there was no
difference in the opportunity for reservation wages
above the UMR between workers and academic
fields of study and vocational training for young
workers in Palembang City. That is, both academic
education and vocational education are considered to
be the same as setting the reservation wage above
the UMR.
The views of the public so far have always
considered that the academic field of study is always
higher than the field of vocational studies, so they
assume that if taking academic education it will
increase the reservation wage. Therefore, vocational
education is still underestimated by society, while
the needs of the industrial world for graduates from
diplomas are high.
However, the Director General of Learning and
Student Affairs of the Ministry of Research,
Technology and Higher Education, Intan Ahmad in
2016 said the industry as an economic and
development driver requires workers who have
competence. As for skills and competencies, many
are produced by vocational education. This is
because in its curriculum, vocational education
provides a greater portion of practice than theory. In
terms of welfare, vocational education can also
emphasize educated unemployment. Because
graduates of vocational education are ready to use so
that it is needed by industry.
(Wilkins, 2001)said that vocational education is
one of the factors in ensuring economic
development, competitiveness and social stability in
all countries, both developing and industrialized
countries. This is due to a belief that the success of
vocational education in producing skilled labor is an
important part of the human resource development
strategy to provide the community with the
knowledge and skills needed in the world of work
and industry.(Wilkins, 2001)said that vocational
education is one of the factors in ensuring economic
development, competitiveness and social stability in
all countries, both developing countries and the
industrialized countries. This was due to a belief that
the success of vocational education to produce
skilled workforce is an important part of human
resource development strategy to provide the public
with a stock of knowledge and skills needed in the
world of work and industry.
Judging from the duration of unemployment
variable coefficient value of 0.019 with Odds Ratio
of 1.019 and the results of this logistic regression
explained that the unemployed old variable had a
positive and insignificant effect on the reservation of
young workers in Palembang City.Thus, it can be
seen that the duration of unemployed a workforce,
the probability oropportunity to set a reservation
wage above the UMR is 1.019 times higher than the
reservation wage below the UMR. That is, the
longer a person is unemployed, the higher the wages
will be. This is because the workforce gets some
kind of compensation during the period of
unemployment then after he gets a job, the
compensation given must be returned by the way the
income he receives must be deducted. This is in line
with (Cahuc & Zylberberg, 2004)opinion that the
average length of unemployment is influenced by a
number of compensation paid for those who are
looking for work.
The duration of unemployment variable does not
have a significant effect, because in fact when a
person maintains a high reservation wage, the
unemployment period will be longer, so that he will
reduce his wage level in order to get a job. This is
the same as the optimal search theory, assuming that
stationary reservation wages predict a positive
correlation between the two, namely that workers
who have high reservation wages will tend to have
long periods of unemployment and vice versa
(Tajibu, 2012).
But on the other hand there are several studies
that explain that the longer a person is unemployed
then the reserve wage will also increase. Like the
research conducted by (McConnel, Brue, &
Macpherson, 1999)that if someone chooses a higher
reservation wage and rejects a low wage, the
expected wage (when he works) will be greater. The
more refusing job offers will reduce the probability
of finding a job at the time, so this increases the
duration of unemployment or unemployment. An
unemployed person will choose the wage for his
reservation so that the marginal benefit equals the
marginal cost.
In addition, research (Foley, 1997)explains
before the process of looking for work, job seekers
will set the wage of the reservation. When a worker
is unemployed they expect the unemployment period
to end immediately which is possible when they
receive the job offered. Workers will accept job
offers with consideration of the minimum wage
received. Workers take into account the costs of
searching, income from unemployment (if any),
distribution of expected reservation wage offers and
the possibility of receiving another job. That is, they
will accept the job offered in consideration of the
costs they have incurred when they are looking for
work.
In this study gender are also variable’s dummy.
From Table 5, the coefficient value is 1.322 and the
Reservations Wage of Young Workers in the Minimum Wage Perspective
455
Odds ratio value is 3.749. Because the gender
variable’s dummy, the Odds Ratio value needs to be
interpreted further, so that the dummy Odds Ratio
value is 0.79. That is, the probability or opportunity
for male workers to set reservation wages above the
UMR is 0.79 higher than female workers. This result
shows that the gender variable has a positive and
significant influence, meaning that there is a
difference in the reservation rates of young workers
in the city of Palembang when viewed from gender.
Appropriate with previous theories and research
that there are differences in reservation wages
between men and women. Where men are
considered capable of setting higher reservation
wages than women because men are the backbone of
the family so men should get higher wages than
women.
According to (Brown et al., 2011)there are
differences in reservation wages between men and
women. This is intended because usually women
when after marriage then having children will
hamper their work. So, workers who do not have
children or do not have children have more
opportunities to set high reservation wages than
women who already have children. This indicates
discrimination in the labor market.
Another reason also mentioned by (Caliendo,
Lee, & Mahlstedt, 2017)differences in reservation
wages also arise from differences in productivity
between male and female workers. Male laborers
who are considered more agile, fast and flexible in
carrying out work, so that they will be given high
wages compared to female workers. In addition, the
research of (Bhattarai, 2017)also stated that gender
variables are the most significant factor in
influencing the level of wages received by workers
in the UK.
5 CONCLUSION
Based on the results of data analysis and
discussion, it can be concluded that in this study the
variables that positively and significantly influence
the wages of reservation for young workers in the
city of Palembang are education and gender
variables. While at the level of 10% significance
level the age variable has a negative but significant
effect.
Educational variables have a positive and
significant effect, meaning that the higher the level
of education in the workforce, the more likely it is to
obtain a reservation wage level above the UMR.
Then the gender variable also has a positive and
significant effect, meaning that there are differences
in the odds of reservation wages above the UMR or
below the UMR between male labor and female
labor.
Furthermore, the age variable has a negative and
significant effect on the significance level of 10%,
which means that the increasing age of the
workforce, the opportunity to set a wage reservation
above the UMR will be lower. While the field of
study and unemployment duration variables have a
positive but not significant effect. This means that
there is no difference in the chance of obtaining a
reservation wage above the UMR, both those who
have concentrations/majors in academic and
vocational sciences and the longer the
unemployment period of a laborer, the opportunity
to set a reservation wage above UMR will be higher
than the reservation wage below the UMR.
In further research, it is expected that researchers
use other variables to look at variables or variations
of other variables that can affect the reservation
wages of young workers. For example, using
variables such as health, skills or skills, marital
status and financial wealth.
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