A PROJECT SUBMITTED TO
FAKIR MOHAN AUTONOMOUS COLLEGE IN
FULLFILMENT OF THE REQUIRMENTS FOR THE
DEGREE OF BACHLOR OF ARTS.
SUBMITTED BY: Sai Krishna Mohapatra
EXAM ROLL NO:21A10032
CLASS ROLL NO:BA21-046
REGISRATION NO:
UNDER THE SUPERVISION OF: Dr Sangram Panigrahi
F.M Autonomous college, Balasore
2021-24
DECLARATION
I do here by declare that the research presented in this project
entitled GENDER PAY GAP AND FEMALE UNEMPLOYMENT is
original and was carried out under the supervision of Dr Sangram
Panigrahi (professor at the department of economics at F.M
autonomous college)
This work is original and has not been submitted for any other
degree of this college or any other college or university.
Signature of the candidate
Date:
Exam roll no.21A10032
Registration no.
Class Roll no. BA21-046
Signature of the guide
Signature of head of department
ACKNOWLEDGEMENT
Any work of this magnitude requires the helping of
numerous. In this context I deem it my moral duty to
express my heartfelt gratitude to those people who directly
or indirectly helped me in the presentation of this project.
At the onset, I express my gratitude to Dr Sangram
Panigrahi. His constructive and valuable suggestions and his
timely assistance has helped me to prepare the project.
I am immensely grateful to the esteemed teachers in my
department Dr Sangram Panigrahi, Dr Subrat Kumar Rana
and Swarna Prava Mam. I would also like to thank all those
who directly or indirectly contributed to the success of this
endeavour.
Sai Krishna Mohapatra
Exam roll no.21A10032
Session:2021-24
CERTIFICATE
This is to certify that the project entitled “GENDER PAY GAP AND
FEMALE UNEMPLOYMENT” which is being submitted by SAI
KRISHNA MOHAPATRA, Exam roll no:21A10032, Regd. No:16905 in
fullfillment for reward of B.A Degree to Department of economics,
FM Autonomous college, Balasore, is a record of bonafide work
carried out by her under my guidance and supervision.
The project has not been submitted to any other college or
university for any other degree.
Signature of supervisor
Name: Dr. Sangram Charan Panigrahi
Asst. Professor of economics,
F.M Autonomous college,balasore
Date:11/5/24
CONTENT
CHAPTER I
1. Introduction
1.1 Meaning of gender pay gay and female unemployment
1.2 Types of gender pay gap
1.3 Causes of gender pay gap and female unemployment
CHAPTER II
2.REVIEW OF LITERATURE
3.OBJECTIVES
CHAPTER III
4.METHODOLOGY
4.1 Table
4.2 Analysis
CHAPTER IV
5.conclusion
6.suggestion
INTRODUCTION:
Gender pay gap and female unemployment is a significant socio-
economic issue in India and all over the world. Even though
women have increased their presence in high paying jobs
traditionally dominated by men, such as professional and
managerial positions, women as a whole continue to be
overrepresented in lower paying occupations relative to their
share of work force. This may contribute to gender differences in
pay. Other factors that are difficult to measure, including gender
discrimination may also contribute to the ongoing wage
discrepancy.
Around the world, finding jobs is tougher for women than it’s is for
men. The current global labour force participation rate for women
is just under 47%. For men it’s 72%. That’s a difference of 25%,
with some regions facing a gap of more than 50 percentage. This
problem is particularly marked in north African and Arab states.
The govt of India has implemented several programs and
initiatives to improve employment rates and quality of work for
women. The government initiatives ensure better opportunities
for women workers it includes social security programs, skill
development, better educational opportunities and legislative
reforms.
In this project we will examine the gender pay gap and female
unemployment situation in India and around the world. We will
take a deep dive into the reasons why such gender disparities
exist. The findings of this study will provide variations that exist
between male and female employment and also provide policy
makers with information and strategies needed to reduce female
unemployment and gender pay gap. Analysing gender pay gap is
critical to understanding women’s immediate and long-term
security.
1.1 meaning of gender pay gap and female
unemployment
Gender wage pay gap is the difference in the average gross hourly
earnings between women and men. The overall gender pay gap is
useful for understanding the impact of gender on women’s pay.
But there is no single gender pay gap since women of different
backgrounds have very different experiences and earnings.
However, across all racial and ethnic groups, women working full
time are typically paid less than men in the same group.
The lack of jobs for women who want to work at current wage rate
is called female unemployment. In India more educated women
are unemployed than before as the push factors for them to go
out and work is missing. According to NSSO survey 2017-18, in
urban areas unemployment among educated women was twice
their male counter parts.
1.2 Types of gender pay gap
• Unadjusted gender pay gap
The unadjusted gender pay gap is the difference in average gross
hourly earning between women and men excluding overtime. It is
based on salaries before income tax and social security
contributions are deducted. It does not take into account any
other factors potentially explaining the earnings, such as level of
education or work experience. By only focusing on gender, it
identifies any systematic differences in pay. The difference
between average wage of men compared to the average wage of
women is expressed as a percentage of average male earning. For
example, if the unadjusted gender pay gap is 10% this means that
on an average women earn 10% less than average male.
• Adjusted gender pay gap
Some of the reasons for the existence of gender pay gap are
structural and are related to differences in elements such as
employment tenure, level of education, work experience etc. If we
remove the parts that can be explained by these factors, what
remains is called or is known as adjusted pay gap. The adjusted
pay gap is the difference is pay between women and men taking
into account other factors that determine pay level such as job
level, seniority, experience, efficiency, performance etc.
Both the unadjusted and adjusted pay gaps together are a good
starting point to dig deeper into potential root causes of difference
in pay.
1.3 Causes of gender pay gap and female
unemployment
• Lack of experience: On average, women have less work
experience than men, and this contributes to gender pay gap.
Women are expected to temporarily exit the work force most
often to raise children or to take care of an older relative,
which leaves them with less work experience.
• Choice of College major: Women are more likely to major in
subjects such as humanities, education etc, and these majors
are associated with lower paying jobs after graduation. On
the other hand, fewer women graduate in the STEM subjects,
which are associated with the most lucrative jobs.
• Gender roles: gender role and the pressure to conform to
these roles for women is one of the major reasons for female
unemployment. In developed countries women who have
spouse with stable jobs are less likely to be employed in a
paid job. This can often arise from the from the economic
stability of the partner that can reinforce the “male
breadwinner” bias in marital arrangements.
• Under-representation in leadership positions: fewer women
are in management and leadership positions, especially at
higher levels. When women are managers, they tend to be
more concentrated in management support functions such as
human resources and financial administration than in more
strategic roles. This brings down the average salary of female
managers compared to that of male managers.
• Gendered jobs: Occupational gender stereotyping results in
certain jobs being held predominately by women, and that
leads to “female jobs” being undervalued. This brings down
wages across the board for women compared to men as
female jobs and occupations tend to pay less than those
occupations and industries dominated by men. Also,
enterprises that employ a majority of women tend to have
lower wages than businesses which employ men.
• gender bias: a job done by a woman is perceived as less
worth than a similar job done by a man. In the absence of
objective job evaluation methods and practices, gender bias
can easily occur in determining pay scales for women and
men.
• Motherhood: it is usually the women in a marital relationship
who are expected to quit their jobs to take care of their
family and kids. After marriage in a lot of conservative
household women are expected to quit their jobs, have
children and take care of their husbands.
• Priority to household work: even when women are allowed
to work after marriage there is rule that a woman’s first
priority should be her husband and household work. Women
are expected to work outside and also do all the household
chores with little help from their husbands. This holds women
back from achieving their full potential as they can’t give as
much time and attention to their professional work as men.
REVIEW OF LITERATURE
A brief review of some important studies done on this given
topic is given below
• Claudia Goldin (2023)
In her Nobel prize winning research work Claudia Goldin
exposed the causes behind deeply rooted wage and
labour market inequality between men and women. The
prize giving body said in their statement “her research
reveals the causes of change, as well as the main sources
of remaining gender gap”
• Equality and human rights report (2017)
This research report found that the overall gender pay
gap is exacerbated by the large number of women that
work park time and the many women in highly feminized
and low paying jobs. When it comes to exploring policy
solutions it is important to consider both ends of the pay
spectrum. This means tackling the ‘glass ceiling’ for high
achieving women but at the same time ensuring that
women are paid adequately and fairly for less skilled
work.
• Ministry of labour and employment of India (2023)
This report showed that the female labour participation
rate in India is rising. The female labour participation
force from the age 15 to 59 years has increased to 35.6%
in 2021-22 from 25.3% in 2017-18. In the journey of
employment for women, government assistance in terms
of policies, schemes, programs, etc are their companion.
the various government programs and schemes are
ongoing process to increase the female labour
participation along with safe working conditions.
• Imran khan and Darshita Gunwant (2024)
Imran khan and Darshita Gunwant in their research paper
REDUCING GENDER BASED UNEMPLOYMENT IN INDIA:
THE IMPACT OF SOCIAL INCLUSION AND FOREIGN FUND
INFLOW, found that both social inclusion and foreign
funds inflow are necessary for reducing unemployment
but this is only true in case of male unemployment. In the
case of female unemployment, only social inclusion factor
plays an important role, where as foreign fund inflows
have no role in reducing female unemployment.
OBJECTIVES
• To analyse the trend of gender pay gap around the world.
• To analyse the relationship between female unemployment
and various socio-economic factors.
• To study the impact of these socio-economic factors on
female employment.
• To study the unemployment rate among women.
• To analyse the various government policies and initiatives.
• Provide ways to reducing the pay gap between man and
women.
CHAPTER III
METHODOLOGY
The methodology used to calculate gender pay gap is
based on the paper published by AAUW. The male to
female earning ratio is calculated by women’s media
earning divided by men’s media earning and the gender pay
gap is calculated by subtracting women’s media earning
from men’s media earning, whole divided by men’s media
earning.
The study is descriptive in nature. This study is solely based
on the study of secondary data related to the problems of
gender pay gap and female unemployment. The request
data has been collected from ministry of labour and
employment in India, world of journal of advanced
research, the global economy, world bank etc.
TABLE AND ANALYSIS
Table and analysis are an important tool for economists to
understand, compare and make informed decisions about
economic conditions and policies.
Table data is useful to organize data that is too detailed or
complicated to be described adequately in text, allowing
the readers to see the results quickly. graphs are a common
method to visually illustrate relationships in data which are
too numerous or complicated.
Following there are some tables and graphs given which are
used for describing female unemployment and gender pay
gap.
• Given below is the average of female unemployment
for 2022, the average unemployment of these
countries is 8.92 %. The country with the highest
female unemployment is Palestine with an average
42.02%. The indicator is available from 1991 to 2022.
Source: world bank
Countries Female unemployment, 2022 Global rank Available data
Palestine 42.01 1 1991 - 2022
Djibouti 37.88 2 1991 - 2022
South Africa 31.43 3 1991 - 2022
Sudan 30.17 4 1991 - 2022
Countries Female unemployment, 2022 Global rank Available data
Gabon 29.41 5 1991 - 2022
Iraq 28.46 6 1991 - 2022
Libya 26.67 7 1991 - 2022
Swaziland 26.31 8 1991 - 2022
Yemen 26.3 9 1991 - 2022
Somalia 25.89 10 1991 - 2022
Jordan 25.04 11 1991 - 2022
Tunisia 23.59 12 1991 - 2022
R. of Congo 23.17 13 1991 - 2022
Botswana 22.76 14 1991 - 2022
Sao tome and Principe 21.91 15 1991 - 2022
Syria 21.42 16 1991 - 2022
Lesotho 20.38 17 1991 - 2022
Algeria 20.3 18 1991 - 2022
Namibia 19.7 19 1991 - 2022
Saudi Arabia 19.49 20 1991 - 2022
Saint Lucia 19.4 21 1991 - 2022
St. Vincent & ... 18.25 22 1991 - 2022
Iran 18.03 23 1991 - 2022
Haiti 17.75 24 1991 - 2022
Bosnia & Herz. 17.22 25 1991 - 2022
Montenegro 16.17 26 1991 - 2022
Greece 16.03 27 1991 - 2022
Lebanon 16.03 28 1991 - 2022
Egypt 15.93 29 1991 - 2022
Samoa 15.44 30 1991 - 2022
Costa Rica 15.1 31 1991 - 2022
Belize 14.83 32 1991 - 2022
Spain 14.66 33 1991 - 2022
Countries Female unemployment, 2022 Global rank Available data
Guyana 14.37 34 1991 - 2022
Rwanda 14.31 35 1991 - 2022
North Macedonia 14.28 36 1991 - 2022
Colombia 13.66 37 1991 - 2022
Cape Verde 13.06 38 1991 - 2022
Turkey 12.72 39 1991 - 2022
N. Caledonia 12.66 40 1991 - 2022
Nepal 12.6 41 1991 - 2022
Mauritania 12.44 42 1991 - 2022
Morocco 12.35 43 1991 - 2022
Suriname 11.99 44 1991 - 2022
Brazil 11.83 45 1991 - 2022
Albania 11.76 46 1991 - 2022
Domin. Rep. 11.65 47 1991 - 2022
Comoros 11.2 48 1991 - 2022
Armenia 10.59 49 1991 - 2022
Serbia 10.39 50 1991 - 2022
Mauritius 10.28 51 1991 - 2022
Bahamas 10.25 52 1991 - 2022
Georgia 10.03 53 1991 - 2022
Angola 9.96 54 1991 - 2022
Sri Lanka 9.87 55 1991 - 2022
Eq. Guinea 9.74 56 1991 - 2022
Honduras 9.74 57 1991 - 2022
Panama 9.73 58 1991 - 2022
Italy 9.45 59 1991 - 2022
Uruguay 9.41 60 1991 - 2022
Pakistan 9.27 61 1991 - 2022
Oman 8.74 62 1991 - 2022
Countries Female unemployment, 2022 Global rank Available data
Brunei 8.69 63 1991 - 2022
Paraguay 8.48 64 1991 - 2022
Chile 8.44 65 1991 - 2022
Sweden 7.92 66 1991 - 2022
Mongolia 7.8 67 1991 - 2022
Cyprus 7.76 68 1991 - 2022
Zimbabwe 7.67 69 1991 - 2022
Croatia 7.57 70 1991 - 2022
Eritrea 7.39 71 1991 - 2022
France 7.37 72 1991 - 2022
Argentina 7.3 73 1991 - 2022
Barbados 7.26 74 1991 - 2022
C.A. Republic 7.14 75 1991 - 2022
Bangladesh 7.08 76 1991 - 2022
Jamaica 7.01 77 1991 - 2022
Uzbekistan 7 78 1991 - 2022
India 6.67 79 1991 - 2022
• As per the latest PLFS (periodic labour force survey)
report, around 32.8% women of working age (15 years
and above) were in labour force in 2021-22 which was
just 23.3% in 2017-18. The major push came from the
rural sector than the urban sector, where it increased
by 12% and 3.4 percentage points, respectively. In rural
areas, female LFPR (labour force participation rate) has
increased to 36.6% during 2021-22 as compared to
24.6% in 2017-18, showing an increase of 12.0% points.
On the other side, female participation in urban areas
was significantly lower than the rural areas. Female
LFPR was 23.8% in 2021-22 as compared to 20.4% in
2017-18 in urban areas, showed an increase of just
3.4% points.
According to Annual PLFS Report, Figure 1, 2 and 3
shows the Female Labour Force Participation Rate for
age 15 years & above at usual status during 2021-22.
The following steps has been taken by the government to
increase female employment in our country
• Beti Bachao Beti Padhao (Save the Girl, Educate the
Girl): This flagship scheme aims to improve the Child Sex
Ratio (CSR) and ensure access to education for girls.
• Stand Up India: This initiative provides loans and support to
women entrepreneurs, encouraging them to set up businesses
and become financially independent.
• Skill India Mission: This mission focuses on equipping women
with industry-relevant skills, making them more employable and
competitive in the job market.
• Sukanya Samriddhi Yojana: This scheme encourages
parents to save for their daughters' futures by offering attractive
interest rates and tax benefits.
• Pradhan Mantri Mudra Yojana (PMMY): This scheme
provides easy access to loans for women microentrepreneurs,
enabling them to start and grow their businesses.
• Mahila Shakti Kendra (MSK): These centres act as one-stop
shops for women, providing them with information and support
on various government schemes and initiatives.
• Swadhar Greh Scheme: The Swadhar Greh Scheme is is being
implemented as a Centrally Sponsored Scheme for women who
are victims of difficult circumstances in need of institutional
support for rehabilitation so that they could lead their life with
dignity.
CHAPTER IV
5. CONCLUSION
One of the mounting concerns around the world is the problem of
unemployment among women in both the urban and rural
sectors. In urban sector, there is a huge problem of educated
unemployment and underemployment among the women.
Unemployment among women leads them to be dependent on
their husbands for financial stability, this leads to problems like
control and manipulation, domestic violence and abuse, women
not being able to fight back and leave toxic relationships etc.
financial independence among women is a must among women
for them to be able to lead a prosperous life.
6. SUGGESTION
Every country is trying to solve the problem of female
unemployment in their own establishment of vocational and
technical training institutes were also started for women. Big
factories should be attached to these colleges. Enabling female
entrepreneurship benefits future generation through the
multiplier effect. Investing in women build economic and social
prosperity by enabling a gradual social shift from high fertility, low
education and poor health to making more conscious reproductive
choices, higher education and better health for self and family.
Women entrepreneurs are fulfilling untapped customer needs
through innovative businesses.
