S 3 H Working Paper Series Number 06: 2017 Efficiency Wages and Employee Work Effort: A Case Study of Pakistan’s Telecom Sector Maham Muneer Verda Salman December 2017 School of Social Sciences and Humanities (S 3 H) National University of Sciences and Technology (NUST) Sector H-12, Islamabad, Pakistan
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S3H Working Paper Series
Number 06: 2017
Efficiency Wages and Employee Work Effort:
A Case Study of Pakistan’s Telecom Sector
Maham Muneer
Verda Salman
December 2017
School of Social Sciences and Humanities (S3H) National University of Sciences and Technology (NUST)
Sector H-12, Islamabad, Pakistan
S3H Working Paper Series
Faculty Editorial Committee
Dr. Zafar Mahmood (Head)
Dr. Najma Sadiq
Dr. Sehar Un Nisa Hassan
Dr. Samina Naveed
Ms. Nazia Malik
S3H Working Paper Series
Number 06: 2017
Efficiency Wages and Employee Work Effort:
A Case Study of Pakistan’s Telecom Sector
Maham Muneer
Graduate, School of Social Sciences and Humanities, NUST [email protected]
Verda Salman Assistant Professor, School of Social Sciences and Humanities, NUST
School of Social Sciences and Humanities (S3H) National University of Sciences and Technology (NUST)
Sector H-12, Islamabad, Pakistan
iii
Contents
Abstract ...................................................................................................................................................... v
1. Introduction……………………………………………………………………………..1
2. Review of Literature ....................................................................................................................... 3
3. Theoretical Framework and Methodology .................................................................................. 6
3.1 Shapiro and Stiglitz’s (1984) Efficiency Wage Model .............................................................. 6
3.2 The Basic Model ............................................................................................................................ 7
3.3 Empirical Model ............................................................................................................................ 9
3.4 The Fair Wage Effort Hypothesis and Unemployment ........................................................ 10
3.5 Motivation for the Hypothesis .................................................................................................. 10
3.6 Empirical Model .......................................................................................................................... 12
Perceptions of Pay Fairness 0.770 Workgroups 0.677
Subordinate Evaluation 0.713 Management 0.785
Job Satisfaction 0.744 Job Switching 0.711
1 See this link for questionnaire design: http://discover.ukdataservice.ac.uk/catalogue? Sn%3D5368& source= gmail&ust=1488954135840000&usg=AFQjCNEardvKLDam8bm2z0mPdcNcuTj4ew.
Its values lie between 0 to 1. The value greater than 0.6 is usually considered acceptable
in social sciences. The Cronbach alpha for different variables is shown in Table 1:
4.3. Construction of Variables and Descriptive Statistics
The descriptive statistics of all the variables is done to obtain the clear picture of the
responses. There are 64 questions and the sample size is 203. The table in Appendix A shows
different variables and their frequency with percentages. For a clear picture of the data, the
proportion of categories for each variable are shown in the table. Here is the brief discussion of
how variables are constructed.
4.3.1. Construction of Variables
For Effort index, the variable is constructed by using 4 questions including one reversed
question with a five point Likert scale. The reversed question is transformed into different values
of (1=5 and 5= 1 and so on). Below are the questions:
1. The level of effort you put in your job.
2. How often you didn’t complete your tasks/targets within the allocated time?
3. How often you completed your tasks/targets before the allocated time?
4. How often you were above average in your performance evaluation report in the
recent past?
The responses of all the questions were added and then dived into two cut points. For
simplicity, values less than and equal to average, i.e., ‘14’ were assigned ‘0’ showed shirking and
‘1’ for values greater than mean showed full effort. Responses showed 22.17% employees are
shirkers while 77.83% employees are exerting full effort.
Monitoring variable consist of 4 questions. The questions are:
1. My work is monitored.
2. I have to report about the progress of my tasks/targets (i.e., how much I complete
daily/weekly, etc.).
3. It is easy for my supervisor to closely monitor my tasks/targets.
4. It is easy to falsely report about the completion of my daily/weekly/monthly/quarte-
rly tasks.
15
Questions 1 and 2 are binary and question 3 and 4 scaled from 1 – 5. For simplicity two
categories formed; no monitoring at all as ‘0’ and high level of monitoring as ‘1’. Values less than
and equal to average was assigned ‘0’ and ‘1’ for values greater than mean. 14.29% employees
are not monitored whereas, 85.71% employees are perfectly monitored.
The variable Efficiency wages consists of three questions are:
1. I received bonus due to my better job performance in the last one year or less.
2. I am promoted due to my good performance (for how many times?).
3. I received increment in my salary (for how many times?).
All variables were added and then 0 and 1 values were assigned. The employees who
report they didn’t get efficiency wages were coded as ‘0’ and 1 for the provision of efficiency
wages. 22.17% of the respondents reported they didn’t get and 77.83% received efficiency wages.
Job Search Time Variable consists of 2 questions based on scale 1 – 5 including one reversed
question:
1. It is easy for me to obtain a similar job at another company with comparable pay.
2. My job prospects will decrease, due to the probable merger of two mobile companies.
For simplicity, it was coded 0 and 1. ‘0’ for less time to find an alternative job and ‘1’ for
more time. 37.93% responses showed that less time is required to find a job whereas, 62.07%
reported that it would take more time to find an alternate job.
Perception of Fair Pay variable consists of 3 questions scaled on 1 – 5. The questions are:
1. My pay is fair, compared to Coworkers working in my company, with same kind of
work.
2. My pay is fair, compared to Workers working in other Companies, with same kind of
work.
3. I am compensated fairly relative to my local market.
Then these questions were coded 0 as unfair and 1 as fair. 40.39% and 59.61% employees
reported 0 and 1, respectively.
Management Relations variable consists of 4 questions scaled on 1 – 5, then coded as 0
and 1. The questions are:
1. In general, the relationship between management and the employees is very good.
2. Management has failed to create equity among employees.
16
3. All employees have equal chance of promotion.
4. The job performance evaluation system is objective.
Value 1 showed good and 0 bad relations with management. 22.66% reported badly and
77.34% reported as good relations with management.
Job Satisfaction variable consists of 5 questions scaled on 1 – 5, including 2 reversed
questions.
1. In general, I am satisfied with my job.
2. I am proud of my company's brand.
3. I do not willingly devote my free time to job.
4. I am satisfied with my overall job security.
5. In general, the work environment in my company creates stress.
For simplicity two categories were formed. Value 0 showed unsatisfied and 1 showed
satisfied.
Job Separation Rate variable consists of 1 question scaled on 1 – 5, is:
1. Thinking about the next year, there is a possibility I will lose my current job.
2. My job is at stake, when I see the present market conditions (i.e., the probable merger
of two Mobile companies).
The responses were added and divided into two cut points 0 being the no possibility to
separate from the job and 1 being the possibility to be separated from the job.
Peer Pressure variable consists of 4 questions based on scale 1 – 5. The questions are:
1. The level of effort my Coworkers (working in my department) put in their jobs.
2. My Coworkers didn’t complete their tasks/targets within the required time.
3. My Coworkers were above average in their performance evaluation report in recent
past.
4. My Coworkers meet their targets/ tasks/ objectives completion deadlines.
All responses were added and then dived into two cut point ‘0’ showed no peer pressure
and ‘1’ the presence of peer pressure. 46.80% employees reported no peer pressure and 53.20%
reported they took pressure.
17
4.4. Cross Tabulation
Tables 2 to 9 present the cross tabulation of effort along with independent variables. (The
direction of cross tabbed variables is horizontal) and highlight the association of independent
variables like monitoring, Job Search time and job separation rate etc. to the effort levels.
Table 2. Job Separation Rate and Effort Cross Tabulation
Effort Job Separation Rate
Probability of not losing job (0) Probability of losing job (1)
Shirking (0) 57.78% 42.22%
Full effort (1) 40.51% 59.49 %
Pearson chi2(1) = 4.2335 P value = 0.040
The cross tabulation of job separation rate and effort shows the significant relationship.
Job separation rate is the probability of separating or losing the job due to exogenous shock.
57.78% employees shirk when there is not the possibility of being separated from the job.
Whereas, 42.22% employees shirk with the possibility of being fired. This shows that lower
percentage of people shirk when they feel there is high probability of losing the current job.
59.49% employees exert full effort.
Table 3. Job Search Time and Effort Cross Tabulation
Effort Job Search Time
Less Time (0) More Time (1)
Shirking (0) 57.78% 42.22%
Full effort (1) 32.28% 67.72%
Pearson chi2(1) = 9.6730 P value = 0.002
Job search time shows the easiness to obtain a similar job in another company. Table 3
reveals that 57.78% employees feel it’s easy to obtain job with less amount of time and keeping
this in view they shirk. Whereas, 32.28% put full effort with less time to find a job. Similarly,
42.22% employees shirk when it takes more time to find an alternative job whereas, 67.72% are
more likely to provide high effort. The results show a clear picture of the relationship between
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these two variables. It can be argued that the people with more time to find an alternative job are
working at their peak levels.
Table 4. Effort and Efficiency Wages Cross Tabulation
Effort Efficiency Wages
No (0) Yes (1)
Shirking (0) 44.44% 55.56%
Full effort (1) 29.75% 70.25%
Pearson chi2(1) = 3.4217 P value = 0.064
Table 4 shows the relationship between efficiency wages and effort. When efficiency
wages are given 70.25% employees exert full effort. Whereas when there are no efficiency wages,
44.44% employees shirk. The percentage of employees is quite low who exert full effort in the
face of no efficiency wages.
Table 5. Effort and Perceptions about Fair Pay Cross Tabulation
Effort Perceptions about Fair Pay
Unfair (0) Fair (1)
Shirking (0) 68.89% 31.11%
Full effort (1) 32.28% 67.72%
Pearson chi2(1) = 19.4973 P value= 0.000
Table 5 shows that 68.89% employees shirk who take their wages as unfair. The
percentage of employees who shirk with fair wages significantly reduces to 31.11%. Only 32.28%
employees exert full effort with unfair wages, whereas the number raise to 67.72% when wages
are deemed as fair.
Table 6 reports that 57.78% employees are shirkers and unsatisfied with their jobs.
Whereas among unsatisfied 41.14% exerts full effort. Similarly, 42.22% employees are although
shirkers but satisfied with their jobs 58.86% employees are exerting full effort and satisfied with
their jobs.
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Table 6. Job Satisfaction and Effort Cross Tabulation
Effort Job Satisfaction
No (0) Yes (1)
Shirking (0) 57.78% 42.22%
Full effort (1) 41.14 % 58.86%
Pearson chi2(1) = 3.9205 P value = 0.048
Table 7. Management Relations and Effort Cross Tabulation
Effort Management Relations
Bad (0) Good (1)
Shirking (0) 37.78% 62.22%
Full effort (1) 18.35% 81.65%
Pearson chi2(1) = 7.5397 P value = 0.006
Table 7 shows that 37.78% employees who have bad relations with management are
shirkers and this percentage further decreases to 18.35% who put full effort. Similarly, good terms
with management rises the effort level to 81.65%.
Table 8. Monitoring and Effort Cross Tabulation
Effort Monitoring
No (0) Yes (1)
Shirking (0) 28.89 % 71.11 %
Full effort (1) 10.13% 89.87%
Pearson chi2(1) = 10.0691 P value = 0.002
Monitoring and effort cross tabulation in Table 8 indicates that 28.89% of shirking
behavior is influenced by lack of monitoring. Within no monitoring category the percentage of
full effort is 10.13% whereas within monitoring category, the percentage of full effort is 89.87%.
We see that highly monitored employees are almost 8 times more likely to put full effort than
with not monitored workers. It can be concluded that the monitoring positively affect effort.
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Table 9. Peer Pressure and Effort Cross Tabulation
Effort Peer Pressure
No (0) Yes (1)
Shirking (0) 66.67% 33.33%
Full effort (1) 41.14 % 58.86%
Pearson chi2(1) = 9.1671 P value = 0.002
A positive relationship between peer pressure and effort is revealed in Table 9. 66.67%
employees are shirkers with no peer pressure. Whereas, 58.86% employees are exerting full effort
with peer pressure. Similarly, the percentage of employees who are exerting full effort reduces to
41.14% when they don’t feel peer pressure. Peer pressure turns out to be an important
determinant of effort.
5. Results and Discussion
This section discusses the results of shirking model and fair wage hypothesis.
Monitoring is positively associated with effort in Table 10, Model A(1). Higher the
monitoring level, more likely it will be, that an employee put effort or work as compared to those
who are not monitored. The significance shows that the monitoring induces the workers to do
their tasks well. One unit increase in monitoring level increases the likelihood of exerting high
effort by 1.95 times. The increase in monitoring level, enhances the likelihood of being caught
as shirker and thus fired and thereby induces him to work hard (Chang & Lai, 1999).
Efficiency wage is the reward when performance is more than expectation. The positive
and significant coefficient of efficiency wage shows that, it is more likely the workers will put
high effort as compared to those who don’t receive efficiency wage (Goldsmith et al., 2000).
Efficiency wage motivates the workers to show good performance. The result is consistent with
the shirking model.
The positive relationship between job separation rate and effort shows that, the possibility
of losing the current job is high, induces the worker to put high effort as compared to those who
don’t think to be separated. With high probability of losing job stir up a worker to exert full on
21
the job effort, so that he may not be separated from the company. Firm considers him a valuable
employee, separating him will not be beneficial for the company.
Table 10. Regression Analysis for the Shirking Model
Variable Model A(1) Model A(2)
Coefficient Z-Score
Odds-Ratio
Coefficient Z-Score Odds-Ratio
Monitoringi 0.672* (0.249)
2.70 1.959 0.561** (0.263)
2.13 1.752
Efficiency Wagei 0.766*** (0.403)
1.90 2.152 0.820*** (0.453)
1.81 2.271
Job Separation Ratei
0.996* (0.386)
2.58 2.707 0.935** (0.387)
2.42 2.548
Job Search Timei 1.250* (0.380)
3.29 3.492 1.216* (0.389)
3.13 3.373
Peer Pressure 0.826** (0.393)
2.10 2.285
Career Level -0.0829 (0.277)
-0.30 0.920
Teamwork 0.267 (0.657)
0.41 1.305
Marital Status 0.180 (0.392)
0.46 1.198
Telenor -0.0465 (0.585)
- 0.08 0.955 -0.033 (0.595)
-0.06 0.968
Ufone -0.0506 (0.499)
- 0.10 0.951 0.042 (0.503)
0.08 1.048
Warid -0.383 (0.573)
-0.67 0.682 -0.401 (0.584)
-0.69 0.670
Zong 0.223 (0.635)
0.35 1.249 0.485 (0.669)
0.72 1.624
Constant -1.910** (0.778)
-2.46 0.148 -2.410** (1.105)
-2.18 0.090
Hosmer & Lemeshow Test
1.98 (0.982)
5.70 (0.681)
Number of observation = 203, LR chi2(8) = 27.94, Prob > chi2 = 0.0005, Pseudo R2 = 0.130
Log likelihood = - 93.419
Number of obs = 203, LR chi2(12) =32.52, Prob > chi2 = 0.0012, Pseudo R2 = 0.151
Log likelihood = -91.132
Effort is dependent variable and Logistic Regression is used for analysis. *, **, *** shows significance at 1%, 5% and 10% levels respectively. Standard errors are in parantheses.
Job Search Time is positively associated with the effort. With a greater amount of time,
to find an alternative job, it is more likely an employee put a higher level of effort as compared
22
to those whom required less time to find a job. The result shows that whenever a worker finds it
harder to acquire a job of same worth he is currently doing, or it takes a long time to find job, his
intention is to put much more effort on the current job. The longer unemployment duration,
higher is the effort (Cappelli & Chauvin, 1991; Wadhwani and Wall, 1991). One unit increase in
Job search time increases the likelihood of exerting full effort by 3.49 times.
In the company Telenor ,Ufone and Warid the employees are exerting less effort than
Mobilink. As the base category is Mobilink here. Zong employees are exerting much effort than
the Mobilink.
The Model A(2) produces results by incorporating some important variables in shirking
model as suggested by empirical researches.This model incorporates the 4 new variables namely,
peer pressure, teamwork, marital status and career level. By incorporating these variables, the
overall and individual significance of important variables is not disturbed. The effort of the
colleagues also effects one’s own effort levels. If one’s peers are working hard, ultimately one will
also put more effort. The positive significance shows that this variable is an important
determinant of one’s effort.
Teamwork shows that to be the part of a team enhances the morale of the workers,
encourages joint venture, and thus raises the effort levels (Chang & Lai, 1999). Marital status
shows the responsibility level of employees, married are exerting high effort than singles.(Fairris
& Alston, 1994). Career level is negatively related to the effort level. To be in a high position
shows the low level of effort. These three variables are turned out to be insignificant, but takes
the predicted sign as suggested by the literature. The model is overall significant at 15%, shows
that, by incorporating these variables. Hosmer and Lemeshow goodness of fit test shows that
model is a good fit, as the null hypothesis of good fit is not rejected here (P value in parantheses).
Perceptions about fair pay is positively associated with effort in Table 11, Model B(1).
The fairness in pay induces the workers to exert high effort as compared to those who take their
pay as unfair (Blinder & Choi, 1990). It is significant in case of Pakistan’s Telecom sector. The
employees know the worth of their jobs, and the compensation schemes all around the local
market. They give much considerations to the fairness of pay. The more the pay is fair, higher
will be the effort.
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Table 11. Regression Analysis of Fair Wage Effort Hypothesis
Variable Model B(1) Model B(2)
Coefficient Z Odds-Ratio Coefficient Z Odds Ratio
Perceptions about Fair Payi
1.753* (0.402)
4.36 5.77 1.485* (0.423)
0.00 4.415
Managemnet Relationsi 0.780*** (0.411)
1.90 2.182 0.575 (0.455)
1.26 1.777
Job Satisfactioni 0.705*** (0.384)
1.83 2.024 1.587* (0.424)
3.74 4.890
Monitoring 1.374** (0.555)
2.48 3.951
Job Search Time 0.977** (0.408)
2.40 2.656
Telenor -0.244 (0.606)
-0.40 0.783 -0.111 (0.678)
-0.16 0.895
Ufone 0.366 (0.507)
0.72 1.442 0.205 (0.561)
0.37 1.227
Warid -0.497 (0.575)
-0.86 0.609 -0.630 (0.628)
-1.00 0.532
Zong 0.739 (0.640)
1.15 2.094 0.542 (0.674)
0.80 1.719
Constant -0.619 (0.503)
-1.23 0.539 -2.551* (0.814)
-3.13 0.078
Hosmer & Lemeshow Test
7.59 (0.475)
9.65 (0.290)
Number of observation = 203, LR chi2(7) =32.12,
Prob > chi2 = 0.0000, Pseudo R2 = 0.149
Log likelihood = -91.333
Number of observation = 203, LR chi2(9) = 54.16,
Prob > chi2 = 0.0000, Pseudo R2 = 0.252
Log likelihood = -80.313
Effort is dependent variable and Logistic Regression is used for analysis. *, **, *** shows significance at 1%, 5% and 10% levels respectively. Standard errors are in parantheses.
Job Satisfaction is positively related to effort which shows that workers who are satisfied
with their job are going to exert more effort unlike those who are unsatisfied (Falk & Knell,
2004). Management relations show that the good relations among the workers and management
induces the employees to put high effort as compared to those who have bad relations with
management.Telenor and Warid employees are exerting less effort than Mobilink whereas Zong
and Ufone employees are putting more effort. All variables in the above regression are significant
suggests that fair wage hypothesis exist in case of Pakistan’s Telecom sector.
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The Model B (2) in Table 11 shows results by incorporating some important variables in
fair wage model as suggested by empirical researches. This regression controls some important
variables which captures the workplace characteristics. The most important are the job search
time and monitoring. The inclusion of these results makes the overall result significant. All of
them have predicted signs but the management relations coefficient turns out to be insignificant.
Good management relations are associated with increase in the level of effort exerted.
The insignificance shows that good relations with management, to somehow, compensate the
reduced effort by the employees. If an employee exerts low effort and at the same time, he has
good relations with management, will exploit it.
When an employee is being monitored and at the same time, there are longer duration of
unemployment spells, it compels him to put high effort. The results also show that local market
prospects are dim, employees have to spend more time to find an alternate job, if they lose it
today. The odds ratio interpretation is same as above.
6. Conclusion and Policy Implications
Companies believe that a change in the effort levels could bring a substantial change in
the profits of companies. Companies give strong incentives to uplift the effort. The study
concludes that efficiency wages play a significant role in Pakistan’s Telecom sector and motivates
the employees to raise their effort. Employees repeat those acts which have some positive
consequences. Higher effort gives them the positive outcomes in the form of efficiency wages.
At the same time, firms try to give that pay which is perceived as fair. Firms consider the concept
of pay fairness crucial to the labor market and for attracting best from the large pool of
unemployed workers. The fair pay hypothesis exists in case of Pakistan’s Telecom sector.
Employees give much importance to fair wages. They have some perceptions about the wages, if
the wages would not be fair, then there may be some issues or resentment among employees.
Companies align pay structure with their competitors, to make pay fair. Firms take the notion of
fairness serious while making the compensation policies.
Employers believe that pay influences effort by impinging on the employee’s attitude
towards job and the company. The more technically advanced firms, offer salaries which are
perceived as fair. By doing this, it is possible for them to bring a slight change in the effort level,
25
which could have even a much bigger effect on their profits. It can also be concluded from the
results, work environment like the peer pressure is a very powerful tool to elicit increased effort
and to model the human behavior is a complex phenomenon.
To sum, it can be implied from the study that the firms can elicit effort from employees
by giving them a good package of incentives. More work pressure can harm the objectives of the
employer. There is a need of friendly environment where the abilities can be best flourished.
Appendix A: Construction of Variables
Variable Categories
Effort Frequency Percentage
Shirking (0) ≤ 14 45
22.17
Working/ Full Effort (1) >14 158
77.83
Monitoring Frequency Percentage
No (0) ≤ 7 29
14.29
Yes (1) >7 174
85.71
Efficiency Wages Frequency Percentage
No (0) ≤ 5 45
22.17
Yes (1) >5 158
77.83
Job Search Time Frequency Percentage
Less Time (0) ≤ 5 77
37.93
More Time (1) >5 126
62.07
Job Separation Rate Frequency Percentage
Probability of not separated (0) ≤ 3 90
44.33
Probability of separation (1) >3 113
55.67
Perceptions about Fair Pay Frequency Percentage
Unfair (0) ≤ 8
82
40.39
Fair (1) >8
121
59.61
Job Satisfaction Frequency Percentage
Not satisfied (0) ≤ 16 91
44.83
Satisfied (1) >16 112
55.17
Management Relations Frequency Percentage
unsatisfactory (0) ≤ 10
46
22.66
Good (1) >10
157
77.34
26
Peer Pressure Frequency Percentage
No (0)
95 46.80
Yes (1)
108 53.20
Fear of Penalty Frequency Percentage
No (0)
97 47.78
Yes (1)
106 52.22
Team work Frequency Percentage
Yes (1)
188 92.61
No (0)
15 7.39
Supervisor Frequency Percentage
Yes (1)
146 71.92
No (0)
57 28.08
Subordinate Evaluation Frequency Percentage
≤ 3
38 26.03
3 < S ≤ 3.9
65 44.52
> 3.9
43 29.45
Experience Frequency Percentage
Less than 1-3 years 46
22.66
4- 10 years 105
51.72
More than 10 years 52
25.62
Company Frequency Percentage
Mobilink 55
27.09
Telenor 30
14.78
Ufone 57
28.08
Warid 30
14.78
Zong 31
15.27
Appendix B: Summary Statistics
Variable Obs. Mean Std. Dev Min Max
Effort 203 .7783251 .4164004 0 1
Monitoring 203 .8571429 .3507922 0 1
Job search Time 203 .6206897 .486415 0 1
Job separation rate 203 .5566502 .4980085 0 1
Perceptions of fair pay 203 .5960591 .491899 0 1
Management relations 203 .773399 .4196672 0 1
Job satisfaction 203 .5517241 .4985469 0 1
Peer Pressure 203 .5320197 .5002072 0 1
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Appendix C: Descriptive Statistics
Age Marital Status 20 – 29 30 – 39 40 – 49
44.83% 49.75% 5.42%
Married Single
58.13% 41.87%
Gender Job Classification Male Female
89.66% 10.34%
Administrative Non-Administrative / Technical
51.72% 48.28%
Education Career Level 14 years 16 years 18 or more