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~ 1 ~ Iweagu H. E., (2012) THE DETERMINANT OF LABOUR FORCE PARTICIPATION AMONG WOMEN IN NIGERIA BY IWEAGU HELEN E. REG. NO: PG/MSC/09/51347 An M.Sc dissertation submitted to the Department of Economics Faculty of the Social Sciences University of Nigeria In Partial Fulfillment Of The Requirements For The Award Of Master Of Science (M.Sc) Degree in Economics SUPERVISOR: ONYUKWU E. ONYUKWU JULY 2012
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Iweagu H. E., (2012)

THE DETERMINANT OF LABOUR FORCE

PARTICIPATION AMONG WOMEN IN NIGERIA

BY

IWEAGU HELEN E.

REG. NO: PG/MSC/09/51347

An M.Sc dissertation submitted to the

Department of Economics

Faculty of the Social Sciences

University of Nigeria

In Partial Fulfillment Of The Requirements For The Award Of Master

Of Science (M.Sc) Degree in Economics

SUPERVISOR: ONYUKWU E. ONYUKWU

JULY 2012

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Iweagu H. E., (2012)

TITLE PAGE

THE DETERMINANT OF LABOUR FORCE PARTICIPATION AMONG WOMEN

IN NIGERIA

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Iweagu H. E., (2012)

CERTIFICATION

This is to certify that Iweagu Helen Elowho, an M.Sc student of the University of Nigeria

Nsukka with registration number PG/M.Sc/09/51347 has successfully completed the

research required for the Award of Masters of Science Degree in Economics in the afore

mentioned institution.

Iweagu Helen Elowho Date

PG/M.Sc/09/51347

Supervisor Date

Onyukwu E. Onyukwu

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Iweagu H. E., (2012)

APPROVAL The research work titled: “The Determinant Of Labour Force Participation Among

Women In Nigeria” has followed due process and has been approved to have met the

minimum requirement for the award of the Master of Science degree in the Department

of economics, University of Nigeria Nsukka.

Approved

Supervisor Date

Onyukwu E. Onyukwu

Head of Department Date

Prof. C. C. Agu

Dean of Faculty Date

External Examiner Date

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Iweagu H. E., (2012)

DEDICATION This work is dedicated to my parents Mr. and Mrs. Young Iweagu, whose

unrelenting support saw me through the course of this study.

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Iweagu H. E., (2012)

ACKNOWLEDGEMENTS

It is tangible to note that this research work would not have been realized without

the direct or indirect contribution of some persons. Therefore, it is eminent that

acknowledgements be given first of all to GOD ALMIGHTY, for Knowledge, protection

and life itself throughout this academic pursuit. His strength has been sufficient for me.

My in-depth gratitude goes to my project Supervisor; Onyukwu E. Onyukwu for

his particular attention and significant contribution to this study, and to Dr Nwosu

Emmanuel for his unyielding support and deep encouragements. Appreciations also go to

all the lecturers in the Department of Economics - University of Nigeria Nsukka, who in

one way or the other contributed to my academic success. Special mention is made here

of Prof N. I. Ikpeze, Mr. Chukwu Jude and Mr Ukwueze Ezebilo. Your profound

contributions and dedication will always be remembered. I also want to acknowledge all

sources and authors of literature cited in this study.

The researcher also remains grateful to all family members and relatives whose

sincere encouragements and continuous prayers, strengthened and exhilarated me

throughout this study. I equally make mention of Mr. & Mrs. Young Iweagu, my husband

Mr Michael Ebele Ejogo, Henry I., Josephine I., Gladys E., Kenneth I., Evelyn I.,

Kingsely I., Alex I., Faith I., amongst others. I would not forget in a hurry the care and

love you showed me in the course of this study.

This list would not be complete if I fail to acknowledge; Yuni Denis, Nzekwe

Henrietta, Ifeanyi Okafor, Shelly E., Mr and Mrs Emeka Okoh, Rev Canoon Ita, Rev

Josiah, Obayuwana Godwill and all other friends to whom i remain very grateful to. My

heartfelt thanks also go to all my colleagues and most especially my Judge; Justice A O.

Akpovi for the support and love throughout this study. Your fervent prayers, moral

support and continuous encouragements saw me through this study.

May God richly bless you all for contributing to my success in life.

Iweagu Helen Elowho.

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Iweagu H. E., (2012)

ABSTRACT

Female labour participation has been relatively stagnant from 2004 till present and it is

therefore important to investigate the current determinants of female labour participation.

However, we note that cultural and traditional beliefs are the main forces behind

husband’s willingness to permit their spouse work and this motivated the researcher to

investigate the determinants of labour force separately in urban and rural sectors of

Nigeria. We employed the logistic regression on a house hold survey data of employment

to find out that the determinants of female labour participation are not the same in urban

and rural areas. Our findings suggests that marital status, religion, poverty rate and per

capita income are significant determinants in the rural sector, while in the urban sector

we have age and literacy rate. Surprisingly, household size was neither a significant

determinant in both urban and rural Nigeria. The fact that the determinants in the urban

regions are completely different from those in the rural sectors leads us to recommend

that, discriminate policies should be encouraged when designing policies to improve

female labour participation in Nigeria.

Key words: Female, Labour, Participation, Rural, Urban, Nigeria

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TABLE OF CONTENT

Cover

Page…………………………………………………………………………..…………....i

Title

page…………………………………………………………………………….…………...

ii

Certification Page

…………………………………………………………………….………….iii

Approval Page ………………………………………………………………………....

……….iv

Dedication

…………………………………………………………………………….………….v

Acknowledgements

…………………………………………………………………….…….......vi

Abstract……………………………………………………………………………………

…......vii

Table of Content

….……………………………………………………………………….........viii

List of Tables

…………………………………………...……………………………..………….x

List of

figures…………………….……………………...……………………………..………….

x

Appendix…………………….……………………...……………………………..………

…..….x

CHAPTER ONE: INTRODUCTION

Background to the

Study…………………………………………………………………………..1

Statement of the

Problem……………………………………………………………...……..........4

Objectives of the

Study……………………………………………………………………………6

Hypothesis of the

research.......…………………………………………………………………... 7

Scope of the Study

…….………………………………………………………………………….7

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Iweagu H. E., (2012)

Justification of the

Study………………………………………………………………….............7

CHAPTER TWO: REVIEW OF LITERATURE

Theoretical

literature……………………….……………………………………………..............9

The Neoclassical Theory......……

……………………………………………………………….11

The Theory of Allocation of Time and Human Capital Investment

………..…………………...13

Women’s Supply of Labour

...……………………………………………………………….......14

Empirical literature: Global

Evidence......……………………………………………………….15

Empirical literature: Nigerian

Evidence......……………………………………………………. 20

Summary of literature

Review...................................................................................................... 23

Limitation of the previous

study.............................……………………………………………..27

CHAPTER THREE: METHODOLOGY AND DATA

Methodology of the research

................………………………………..…………………….....28

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Iweagu H. E., (2012)

Theoretical Framework

..................………………………………………………………….......28

Analytical Framework

...................………………………………………………………….......31

Model specification

...............................................................................................……………...32

Model

1..........................………………………………………....................................................32

Model

2.......................…………………………………………………………………………...33

Estimation Methods

.........................................................……………………………………….33

Justification of the model

.......................................................………….......................................33

Source of data

...................………………………………………………………………………34

CHAPTER FOUR: EMPIRICAL RESULTS

Presentation of Results

..………………………................……………………………………....35

logit results for female participation in urban areas

.....………………………………………….35

logit results for female participation in rural areas

.......................................................................38

CHAPTER FIVE: SUMMARY, POLICY IMPLICATIONS AND CONCLUSION

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Iweagu H. E., (2012)

Summary

……………………………………………………………………………………..…42

Policy

implications………………………………………………………………………............43

Limitations of the Study

………………………………………………………………….……..45

Suggestions for further Study

…………………………………………………………….…….45

Conclusion

……………………………………………………………........................................46

References…………………………………………………………………………………

…….47

LIST OF TABLES

Summary of literature

Review...................................................................................................... 23

Table 1: logit regression for urban female participation

............…………………………………..35

Table 2: logit regression for rural female participation

......………………………………….….….38

LIST OF FIGURES

Figure 1: Female pop, labour participation and ratio of female to male labour force

participation………………………………………………………………………………

……….2

APPENDICES

APPENDIX 1: Stata

Results....…………………………………………………………..……...52

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CHAPTER ONE

1.0 Introduction

1.1 Background of the study

The debate on female labour force participation has been on stage for over three decades

in many countries around the world. One of the most striking phenomena of recent times

has been the extent to which women have increased their share in the labour force; in

both developed and developing countries, the increasing participation of women in paid

work has been driving employment trends and the gender gaps in labour force

participation rates have been shrinking. Especially in the 1980s and early 1990s, labour

force growth was substantially higher for women than for men for every region of the

world except Africa. In the developed industrialized countries, increasing female labour

force participation has been linked to the completion of the fertility transition. In many

developing countries, however, fertility decline has been slow or stalled (Lim, 2002).

Lawanson (2008) argues that women constitute more or less half of any country’s

population. However, he opined that in most countries, women contribute much less than

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Iweagu H. E., (2012)

men towards the value of recorded production both quantitatively in labour force

participation and qualitatively in educational achievement and skilled manpower.

In the last three decades, the global economy has witnessed the increasing visibility of

women, which is partly an outcome of social and political movements that have

championed women’s rights (Ruwanpura, 2004). He further argues that feminist scholars

have equally been in the forefront of making women’s contribution to the political

economy visible through related scholarship and research. Counting women into the big-

picture, therefore, is a fundamental first-step in recognizing their role in socio-economic

structures. Along with women’s increasing visibility, it is necessary to analyse the

constraints and conditions within which women contribute to the economy.

Improvements in the wellbeing of women are not measured merely in terms of access to

resources but also in terms of their sense of worth and dignity. Forms of employment,

quality of employment and access to social security conditions are also invariably linked

to welfare of women. Employment opportunities available to women need to realize their

potential capabilities (Ruwanpura, 2004).

The Nigerian situation shows that between 1971 and 2004, the percentage of women rose

from 12% to 70% of the work force due to women’s participation in further and higher

education (Women and Work Commission, 2005). However distinct differences exist in

the types of occupation entered by women and men. Women got more jobs in

administrative, clerical, personal services and sales occupation, Apart from moving into

law, medicine and accountancy, there was no similar movement into science,

engineering, ICT and the skilled trades. Women were not found in managerial

occupations: overall, women make up only 32% of managers and senior officials

(Women and Work Commission, 2005). Equally, Okoro (1991) notes that apart from

traditional humanist professions like nursing, teaching, catering and law, the percentage

of women who venture into professions like engineering, architecture are low compared

to men. In the same light Umar & Karofi (2007) observed that female employment in the

Nigerian civil service was historically tended to be lower than male.

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The trend or behaviour of female labour participation has been assumed to be increasing

at an increasing rate in many countries in Nigeria the illustration below shows us what it

looks like;

Source: Illustration drafted based on World Bank indicator data

The illustration above shows that as adult female population remains relatively constant

over the years, the ratio of female to male labour force participation kept increasing over

the years. However it remained relatively stagnant between 2004 and 2010. In the same

light, the labour participation rate for female dropped in 2000 but later increased to 40%

in 2002 and continued at the same rate till 2010. This figures buttress that, until 2004

there was visible progress to increase the level of female labour participation, but there-

after this effort subsided and the same predicament is facing the country today.

The Nigeria Bureau of Statistics publications (2010) show that despite the great

improvement over the years very few women relative to men secure jobs. Out of these

few, a sizeable number of them are temporarily employed. The female Labour

participation rate (% of female population ages 15 and above) in Nigeria was 38.90 in

2008, 39.20 in 2009, according to a World Bank report published in 2010. These figures

show that there has been great improvement yet much still needs to be done. The Federal

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Civil Service in Nigeria is regarded as the government employed staff in Nigeria and this

is being used as a proxy to depict the employment situation in the country. The analysis

also indicates that the number of males employed far outweighs the number of females

during the period under investigation.

The Federal Government of Nigeria started contemplating a sort of drastic reduction of

its workforce in 2001 to make public sector leaner and more effective in service delivery.

The reduction in the public sector workforce at the federal level has not been easy to

implement either due to its fiscal implications or the socio-political problems that such a

program can wreak on the country. In order to drum up support for the policy, a number

of frightening projections were made to underline the need to reduce the federal

workforce. A case in point was the projection that constituted the fulcrum of the alarm

raised by a team of Federal Government technocrats in January 2003. The alarm

bordered, in the main, on the urgent need to prune government personnel costs, with a

stern warning that a failure to do so may result in government spending 95 per cent of her

earnings on personnel by 2007 (Aminu,2010).

Oladejo et al (2011) also noted that several factors, both economic and non-economic are

responsible for low female participation. Traditionally, women are regarded as

homemakers, who oversee and coordinate the affairs and activities at home. (Oladejo et

al 2011) explained that previously in Africa, women remained at home while their

husbands and sons went out to the farm to work. But at home, however, they were not

idle as they engaged in manual processing of food crops and other farm produce in

addition to their housekeeping duties. This is generally induced by the cultural, religious

and traditional beliefs of most developing countries. This is evident in Chaudhry &

Nosheen (2009) who conclude that women empowerment is considerably influenced by

the socio-cultural norms of the community, job of women and household participation

rate.

This situation is worse-off in rural areas given that cultural beliefs are more intense in

rural areas with women seen as inferior beings. Our interest in this study therefore is to

ascertain the determinants of female participation in the rural areas and urban areas. The

advent of western education, industrialization and paid employment, has neutralised this

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cultural beliefs in urban areas and exposed them to the knowledge of men and women

both involved in the labour force.

1.2 Statement of the problem

A major problem confronting Nigeria and other African countries is how to sustain a

stable growth in output (Collier and Gunning, 1999). This preoccupation is important due

to declining state of the country’s per capita income with the growing number of the

female population. It shall therefore be to the nation’s advantage to increase the level of

female participation to boost total output in today’s competitive world.

Indeed, income inequality in Nigeria is high and not favouring the women, females lose a

large proportion of their lifetime income by taking time out of the workplace to have

children according to Ogwumike et al (2006). The labour market is a very important

source that offers explanation for earnings and income inequality. The structure of the

labour market has a significant consequence on employment status and it serves as an

important determinant of household income and welfare. Like most labour markets in

developing countries, the Nigerian labour market represents one of the major sources of

risk through which people fall into poverty (Ogwumike et al, 2006).

The labour market in Nigeria presents opportunities for participants to earn incomes and

determine their welfare; however, few women in Nigeria are engaged in top management

cadre of formal sector establishments. The last population census analysis of 2006

showed that most Nigerian women dwelled in rural areas, which makes them to lag

behind in terms of employment opportunities. Also, educational and health facilities in

rural areas are not increasing. In some places, women are confronted with socio-cultural

restrictions (such as marital status, cultural and religious characteristics) especially in

northern Nigeria as regards to their involvement in public labour participation. It is

therefore important for us to ascertain the rural-urban determinants of female labour force

participation.

There is a consistent partitioning of women into predefined jobs. For example, many

more women work in the service sector as compared to men. In addition, for numerous

developing countries, there has been a growing tendency for more women to be engaged

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in the informal sector than men. Though many women still find restrictions in attaining

some managerial jobs and others who even have these jobs have to contend with

maternity decisions and family trade-offs (Murray & Syed, 2007).

Although, women have shown a continued interest in employment in the state civil

service, men continue to out-number them. By population, the potential female labour

force in Nigeria is 50 per cent though the actual figure ranges between 31 and 36 per cent

in both the public and private sectors of the economy (Salaam, 2003; Africa Action,

2003). At the higher administrative and managerial levels, the figure is even smaller. For

example, of the 191, 329 federal civil servants in 1992, only 45,881 (24 %) were females.

In Kebbi State civil service, female employees constituted only 12% (1,396) of the total

employment as at 1999 (Federal Character Commission, Kebbi State Office,

2004).Women have been relegated to both productive and reproductive roles in the

household. Their contributions are often unpaid for, and yet do not allow them to fetch

other paid productive jobs especially in the formal sector (as cited by Muhammad and

Usman, 2007)

Although, the problem of employee turnover has received much attention from

researchers in organizational sciences, very few of these studies have focused on female

labour participation. Moreover, in Nigeria few authors examined the sector of female

labour participation like Aminu (2010), Baridam (1996) and Lawanson (2008) but none

of them used logistic regression to investigate the determinants. The motivation behind

this study is based on theoretical and empirical literature that projects husband’s

willingness to let their spouse work, as the prime determinant of female labour

participation. This is usually induced by the culture and religion background of the men,

and we agree that cultural and traditional beliefs are even more binding in rural areas.

That is why we investigated the relative determinants of labour force participation in

rural as well as urban areas. In addition to the limitations of previous studies, none of

these studies examined the determinants from rural and urban areas separately, as we

investigate in this study.

Thus, this study investigates the determinants of female labour force participation in

Nigeria from the opinion that labour market participation of women will improve their

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relative economic positions and also increase overall economic efficiency of the country.

And in order to improve female Also based on the changing demographic trends,

globalisation and westernisation, it is necessary to examine the determinants of female

labour participation in urban as well as rural areas.

The study seeks to provide answers to the following questions;

1) What are the factors that determine the female labour force participation decision

in urban Nigeria?

2) What are the factors that determine the female labour force participation decision

in rural Nigeria?

1.3 Objectives of the study

The broad objective of this study is to investigate the determinants of female labour force

participation in Nigeria. To achieve this objective we use the specific objectives below:

(1) To investigate the factors that determines the female labour force participation

decision in rural Nigeria.

(2) To examine the factors that determines the female labour force participation decision

in urban Nigeria.

1.4 Hypothesis of the research

In order to actualize the objectives enumerated, the following null hypotheses are

therefore tested:

1) There exist no determinants for female labour force participation of women in rural

Nigeria.

2) There exist no determinants for female labour force participation of women in urban

Nigeria.

1.5 Scope of the study

This study focuses on microeconomic analysis using house hold survey employment data

for 2010/2011. The study did not use macroeconomic or time series data, which therefore

makes this a static analysis. The researcher concentrated on the participation of women in

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Iweagu H. E., (2012)

the labour force on formal and informal activities, since we employed the use of primary

data. The study also separately investigated the determinants of female labour force

participation in urban areas as well as rural areas.

1.6 Justification of the Study

The justification of this study cannot be overemphasised as the study is based on the

determinants of female labour force participation. Figure 1 shows us that very little effort

has been done since 2004 to improve the level of female labour force participation in

Nigeria. There is therefore need to revisit our policies to change the status quo by

investigating the current determinants of labour force participation in Nigeria. However

we also reflect the fact that there could be a difference in these determinants given that

most of the forces behind female labour participation is based on cultural and traditional

beliefs.

The results of this study would therefore go a long way to provide policy implications of

the determinants in both the urban and rural areas for both government and non-

government agencies. It also serves as contribution to knowledge and a reference for

further studies by authors that may want to investigate further. In addition to this, the

significant difference between the determinants of the urban and rural areas, it only points

out that the impact of the cultural and traditional beliefs in rural areas are still very high

also meaning that the females are still highly marginalised. This should therefore lead the

government to put in place the mechanism to educate and enlighten the men resident in

rural areas to the importance and significance of female labour participation.

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CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 Theoretical literature

There is an immense literature available pertaining to women participation in economic

activities at the national and international level. Women represent a sizeable portion of

the population and require a lot of attention. They are considered as a supporting factor in

the economic development of the country and put a significant effect on overall business

and economic activities (Faridi, Chaudhry and Malik, 2011). According to Ruwanpura

(2004), “Economists explanations for the existence of segregated labour markets are not

new”. A review of the literature on women or gender in general indicates that there is

now a demand for a re-orientation of research and changes in the methodological

procedures used for the compilation and computation of national statistics so as to reflect

accurately the role of women and their labour input in the national economy. The trend is

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not only evident in the Third-world alone, but it is worldwide. The emphasis is now on

the productivity and efficiency of the labour input of women (Olukemi, 2008).

An analysis of trends in labour economics throughout the world reveals that sustained

increase in women’s participation in the labour force during the last century, particularly

during its second half. This fact has stimulated considerable interest in the economic

analysis of a woman’s decision to work (Rincon, 2007). The author noted that the

pioneering studies of Mincer (1962) and Cain (1966) in the United States have served as

a theoretical and empirical foundation for numerous studies of female labour force

participation. Ackah et al. (2009) were of the view that the increasing trend toward

women’s participation in the labour market in both developed and developing countries

has drawn both social and academic interest resulting in many insightful studies on

gender aspects of labour market issues.

A critical review of the large literature provides at least two general theoretical paradigms

to explain the changing patterns of female labour force participation in low-income

countries (Ackah et al, 2009). Equally, Nam (1991) categorizes the literature into two

perspectives, the modernization and the world system perspectives. According

modernization theorists, economic development is positively associated with female

labour force participation through change in the country’s occupational structure (i.e. the

increasing availability of service and white-collar jobs) and increased educational

opportunities, often accompanied by reduced fertility rates and household responsibilities

(Nam,1991).

The modernization process is associated with increased demand for labour, a general

social acceptance of women’s education and employment, as well as lower fertility

(Bauer and Shin, 1987). The relationship between education and female labour force

participation has been summarized by Standing (1981) under three hypotheses: the

opportunity cost hypothesis, the relative employment opportunity hypothesis, and the

aspiration hypothesis (Nam, 1991).

First, the opportunity cost argument conceives that to the extent that there is a positive

relationship between educational investments and earnings potential, education raises the

opportunity cost of economic activity, thereby giving people a positive incentive to seek

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Iweagu H. E., (2012)

employment (Bowen and Finegan, 1969). The relative employment opportunity

hypothesis posit that employers usually tend to have a positive bias towards a qualified

female work force rather than older male workers whose educational qualifications

increase their employment options (Oppenheimer, 1970).

Furthermore, the aspiration hypothesis is based on the human capital hypothesis that

women with higher levels of education are more likely to participate in the labour market.

From this view point that income aspirations and expectations of people are strongly

determined by levels of education, more-educated women are expected to have higher

income aspirations over their less-educated counterparts and therefore tend to be more

active in the labour market (Cain, 1966).

The world system perspective, on the other hand, explains the increasing labour force

participation in the context of traditional comparative advantage international trade

theory. From the perspective of the Stolper-Samuelson theorem, global trade

liberalisation would lead to a rise in the demand for unskilled labour in developing

countries (Ackah et al, 2009). In other words, since developing countries are more

likely to have a comparative advantage in producing unskilled labour-intensive goods,

one would expect international trade in these countries to lead to a rise in the demand for

and relative returns of the abundant factor; unskilled labour in the case of developing

countries (Harrison, 2005). Since more females than males tend to be unskilled and

female labour is usually cheaper than male labour, labour-intensive industries tend to be

relatively dominated by females, particularly those who are young and single (Grossman,

1979)

While a positive correlation between levels of education and female labour force

participation has been postulated theoretically, empirical findings in developing countries

are rather mixed (Standing, 1981). Studies have shown that female labour force

participation is another variable which appears to be associated with lower fertility rates

in different parts of the world (Kalwij, 2000). Empirical evidence from both developed

and developing countries confirm that female education is associated with a greater

incentive to participate in market activity.

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Iweagu H. E., (2012)

Neoclassical theory suggests that high levels of investment in human capital and greater

participation of women in the labour market are negatively associated with lower fertility

rates (Rincon, 2007). In general, however, the causal impact of female labour force

participation on fertility may occur along a number of complex pathways because both

female labour force participation and lower fertility may reinforce each other. The

relationships between female labour force participation and fertility have been studied

based on the maternal role incompatibility hypothesis, which states that an inverse

relationship occurs between women’s work and fertility only when the roles of worker

and mother conflict (Goldstein, 1972). According to the author, the implication of this

hypothesis is that a negative relationship between female employment and fertility exists

to the extent that they are competing uses of time. Otherwise, we should expect to find no

relationship, or even a positive relation between employment and fertility.

2.1.1 The neoclassical theory

The neo-classical economists’ interpretation of segregated labour markets is based on the

rationality of employers and workers. According to this argument, workers seek

appropriate employment after taking into account their endowment levels, constraints and

preferences; likewise as profit maximizing agents, employers will pay workers the worth

of their marginal product. Interactions of these two factors are argued to result in

competitive-efficient labour markets (Arrow, 1973). According to this theory, women

workers are paid lower wages because of lower human capital levels, truncated labour-

market participation, and minimal skill and training, acquired during employment. These

factors make women choose economic activities that reflect their constraints and

preferences, i.e. low paying jobs, flexible work, part-time work, etc. Lower monetary

rewards are also supposed to compensate for women’s “better” working conditions.

Becker (1957) argues that if an individual has a taste for discrimination, he must act as if

he were willing to pay something, either directly or in the form of a reduced income, to

be associated with some persons instead of others. The taste for discrimination is due to

individuals’ preferences and prejudices. Employers are prepared to sacrifice profit to

avoid female workers, by paying higher amounts to higher male workers due to the

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problems associated with employing women that include maternity leaves and inflexible

nature.

A key limitation of neo-classical theory, however, is that it does not move beyond to look

at the underlying mechanisms that hinder women from making different choices. Are

there social-cultural norms that impinge upon women affecting their human capital? For

example, women are unable to compete with men on an equal footing because usually

they have not acquired the appropriate education levels. This in turn is linked to

patriarchal norms and attitudes that factor into parents’ decision-making process, usually

with adverse consequences, against girls (Ruwanpura, 2004).

Similarly Anker (1997) explains that women have less skill and training experience than

men because,

(a) They do not have the same labour market opportunities as men, and

(b) Because family responsibilities lead them to exit-and-enter the labour

market

The explanation provided by neo-classical economists is a static account of the status

quo, but also its’ correspondence with labour market trends is debatable. Formal sector

employment is limited in low-income countries, but yet there are an equal proportion of

“highly” qualified educated men and women. According to neo-classical theory women

employees ought to be equally represented in formal sector jobs. Women are not,

however, adequately represented in formal sector employment. Does this imply the

existence of gender-based discriminatory practices in the labour market? A study done in

Peru notes that even with female education levels surpassing male education levels

during recent years, there has not been any change in gender wage-differentials

(Ruwanpura, 2004).

2.1.2 The Theory of Allocation of Time and Human Capital Investment

It is argued that the explanation for minority workers’ low relative pay and occupational

status lies in their relative deficiency in human capital. This theory, which relates an

individual’s investment in education and training with his or her lifetime earnings, was

developed by Mincer (1958) and Becker (1957). Two complementary theoretical

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approaches support the study of labour force participation of women. Both focus on

different aspects of the labour supply decisions. On one hand, the neoclassical model of

allocation of time deals with whether a woman will enter the labour market by comparing

the value of her time in the market to the value she places on her time spent at home and

if she decides to do so, how much time will be spent on market work. On the other hand,

the human capital investment theory stresses the relationship between the return on the

investment of acquiring valuable skills and the time the person expects to work during

his/her life (Becker, 1957). In other words, labour participation outcomes are related to

general skills acquired through education and training.

Indeed, those who are planning to participate in the labour market as full-time workers

are prompted to invest more in education and training (Altonji & Blank, 1999).

Moreover, the human capital model emphasizes the role of women's preferences and the

choices they may make to invest less in job-related education and training, as well as to

spend a smaller share of their adult years in the labour force (Blau et al., 2002). Other

factors include premarket discrimination, or societal discrimination, in which various

types of social pressures influence women's choices adversely.

2.1.3 Women’s Supply of Labour

Human capital theory suggests several reasons why women might decide to acquire

smaller amounts of formal education than men. Many scholars have emphasized the

traditional roles of women within the family of which childbearing is one of the most

important. Women know that bearing children might force them to leave the labour

market for a while. Again, the present value gives us the insight of the potential

behaviour of women. If a woman is planning to interrupt her participation in the labour

market, her investment in additional education might no longer be profitable since her

time out of the labour market results in a reduction in benefits since time would be

smaller (Rincon, 2007).

Moreover, a woman may decide against investment in the types of human capital that

require sustained, high-level commitment to the labour force because the investment

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depreciates rapidly during periods of work interruptions. The time out of the labour force

has cost her a reduction of earnings over the remainder of her working life. In this

example, the benefits of the investment in college education, the sum of the two shaded

areas, may not be large enough to make it worthwhile. Thus, a woman with an adherence

to the traditional roles in the family is less likely to pursue college and graduate study.

Anticipating time out of the labour force, she is likely to reduce her amount of

educational investment. Other kinds of human capital investments are those made after

one has started to work, in training received at the workplace. All forms of training,

whether formal training programs, informal training under the supervision of a more

experienced worker, or general training, are costly. If the training is specific to one firm

or employer, workers and the firm share the cost.

The role of education in determining women’s participation becomes stronger when we

consider women in urban areas only. Compared to illiterate women, those with higher

levels of schooling have progressively higher participation rates that peak for those with

higher education. Among rural women, illiterates and primary school graduates are not

any more likely to participate than illiterate women (Dayıoğlu and. Kırdar, 2010). The

authors noted that those with secondary and general high school education have a lower

likelihood of entering the labour market as compared to illiterate women, which may

stem from demand side factors: the unavailability of “socially appropriate” jobs for them

and the changing economic structure of rural households with the proportion engaged in

agriculture declining.

However, vocational high school graduates and those with university degrees have a

higher likelihood of entering the labour market. The effect is especially strong for

university graduates. Dayıoğlu and Kırdar (2010) was of the opinion that the age-

participation profiles are hump-shaped in both urban and rural areas, though age is a

stronger correlate of participation in urban areas. The authors assert that being married is

negatively associated with participation in both urban and rural areas, with a particularly

large effect in urban areas. Separated and divorced women are also less likely to

participate in rural areas but not in urban areas. In both places, it seems less likely for

widowed women to enter the labour market. The number of children in the household are

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also negatively associated with the participation probability of women in urban but not in

rural areas (Dayıoğlu and. Kırdar, 2010)

2.2 EMPIRICAL LITERATURE

2.21 Empirical literature: Global Evidence

Psachropoulos and Tzannatos (1989) pioneered the search for the female labour

determinants by examining the definitions and theories of female labour supply and relate

them to statistical evidence from 136 countries in the early 1980s. The research finding

support the view that, during the transformation from an agrarian subsistence economy,

the participation of women in the labour force initially decreases and picks up later after a

critical level of development has been achieved. They note that education is seen as a

potential booster of the officially recorded female labour supply in developing countries.

Jaumotte (2003) employed econometric analysis using a panel data of 17 OECD

countries over the period 1985-1999 to investigate the determinants of female labour

force participation. Their findings suggest that there is a positive impact of neutral tax

treatment of second earners on female participation. Unlike childcare subsidies, child

benefits reduce female participation due to an income effect and their lump-sum

character. And finally note that, female education, the general labour market conditions,

and cultural attitudes remain major determinants of female participation.

Ruwanpura (2004) examines themes related to quality of women’s employment in the

South Asian and African regions theoretically. The study explores the following issues:

What are the key determinants that influence the links between gender and employment

quality? Which institutional and economic factors increase women’s participation in the

labour force, and what is its relationship to quality of employment opportunities

available? the author notes that in the geographical areas under consideration this means

that an examination of informal sector activity is of paramount importance. He states that

addressing these issues will set the stage to investigate measures to reduce low-quality

employment, sometimes from unionised labour and at other instances from consumer

groups.

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Lisaniler & Bhatti (2005) investigate the determinants of female labour force

participation in North Cyprus for the year 2001. Analysis of data from the survey

“Gender Profile in Education and Employment in North Cyprus” suggests that women’s

education is the main factor increasing women’s likelihood of participation while age and

the residence are also significant factors influencing the women’s labour supply. Their

findings have also shown the effect of patriarchy and cultural factors on the labour supply

decisions of North Cypriot women.

Boca & Locatelli (2006) investigates the determinants of Motherhood and work status in

some European countries, and provide several interpretations of the differences across

countries. Their results suggest that most analyses indicate that social policies, taking into

account several variables (family background, the allocation of time within the

household, religion and culture), have a very relevant role in explaining different degrees

of incompatibility between employment and child rearing across different countries. The

incompatibilities between motherhood and careers find reconciliation in policies that

enhance employment flexibility and diminish the potential opportunity costs of children.

Ntuli (2007) uses survey data to examine the determinants of the low level and also of the

changes in African women’s labour force participation, during the first decade of

democracy (1995-2004) using decomposition technique devised by Even and

Macpherson (1990). The result shows that female participation responds positively to

education which has been the prime factor. The study finds that non-labour income,

marriage, fertility and geographical variations in economic development persistently

stifled participation.

Lawanson (2008) states that women constitute more or less, half of any country’s

population. The author notes that in most countries, women contribute much less than

men towards the value of recorded production both quantitatively in labour force

participation and qualitatively in educational achievement and skilled manpower. He

states that under-utilization of female labour has obvious implications for economic

welfare and growth. He notes several factors, both economic and non-economic

responsible for this. He concludes that the participation of women in the labour force

appears to depend much more on the social environment than is the case for men

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Pastore & Verashchagina (2008) investigates the determinants of female labour force

participation in 1996 and 2001 using data from the Belarusian Household Survey. The

selectivity corrected wage equation is estimated to compute an expected wage offer for

women. The latter is included, in the second step, as a regressor in the structural female

labour supply equation, estimated by probit. Several measures for the care of children and

elderly people, proxies for the opportunity cost of working, affect female participation,

but do not generate sample selection mechanisms. Their results suggest that the estimated

elasticity of female participation to wages is low, at about 0.45 in 1996 and 0.41 in 2001.

Moreover the data allows detecting poverty trap mechanisms, whereas women in low-

income households have much lower than average participation rates. At the same time

the elasticity of female labour supply with respect to the own wage appears to be much

higher for the low-paid groups of women.

Ackah et al (2009) investigate the determinants of female labour force participation in

Ghana at two points in time, 1991 and 2006, with the view that labour market

participation of women will improve their relative economic positions and also increase

overall economic efficiency of the country. The study utilizes data from the 1991/92 and

2005/06 Ghana Living Standards Survey. The OLS estimates result suggests that both

women’s educational attainment and fertility determine women's labour force

participation in Ghana. The study finds that women with primary school education or

above are more economically active than those with no education. They note that this

pattern is only found among women participating in wage employment. The study also

finds that high fertility acts as a constraint on female participation in wage employment;

and that the presence of children in the home significantly reduces participation in wage

work, controlling for age, education, ethnicity, religion and marital status.

Chaudhry and Nosheen (2009) explore the possible determinants of women

empowerment using regression analysis based on primary data from a district of Southern

Punjab. They construct a cumulative index for women empowerment using four indices

i.e. personal autonomy, family decision making, domestic economic decisions and

political autonomy. The empirical analysis shows some new and diverse results for three

different areas namely urban, rural and tribal areas. The results show that women

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empowerment is considerably influenced by education, access to media, socio-cultural

norms of the community, job of women and household participation rate.

Bbaale (2010) uses the Demographic and Health Survey 2006 to examine the relationship

between female education and labour force participation on the one hand, and fertility

rates on the other, for Uganda. His results confirm the hypotheses that female education,

especially at the secondary and post-secondary levels, reduces fertility and increases their

likelihood of being engaged in the labour force. He also finds that despite the near

universal knowledge of family planning methods in Uganda and the importance of

contraceptives in helping to reduce the number of children born, less than half of the

women were currently using them at the time of the survey. He suggests that efforts to

reduce fertility need to target measures that aim to educate women and to keep them in

school. The government programme to extend free education at the secondary level is

therefore an important measure that may help to reduce fertility.

Faridi et al (2011) investigate the factors which influence women’s participation in self-

employment in Pakistan. The study uses primary source of data for empirical analysis.

They employ Logistic regression technique to estimate the women self-employment

model. The study finds that age and experience positively affects women’s self-

employment. They also conclude that education, location and number of dependents

significantly reduce the women’s work participation as self-employed worker. The study

suggests that the government provide technical and vocational education to the women,

and also give old age benefits just to minimize the dependency burden.

Surjit & Kaur (2011) investigated the labour force participation of women in India and

found out that particular ethnic and socio-cultural groups tend to concentrate in various

sectors of the labour market. Studies in the area of gender and migration also point out

that marriage migration often leads to entry into the labour force and the two processes

are not mutually exclusive.

Ejaz (2011) analyzes the determinants of female labour force participation (FLFP) across

rural and urban Pakistan. Potential explanatory variables that determine FLFP include (i)

females’ own characteristics, (ii) household characteristics, and (iii) female

empowerment indicators. Endogenous explanatory variables, such as ownership of home

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appliances, fertility, and co-residence, can lead to biased and inconsistent results due to

reverse causality. They then use potential instruments which include (i) the average

number of home appliances owned in the locality, (ii) the gender of the firstborn child,

(iii) whether or not the first two children are of the same sex, (iv) proximity to a clinic,

(v) contraceptive use, and (vi) housing type. The probit model is used to estimate

variables, while the instrumental variable (IV) approach is used to tackle the issue of

endogeneity. In the first stage, the study’s results give estimates of endogenous covariates

separately, using the IV approach. In the second stage, the IV vector is used to show the

impact of explanatory variables on the dependent variable FLFP. Their results suggests

an inverse and significant relationship between FLFP and both fertility and the gender-

wage gap; and a direct and significant relationship between FLFP and ownership of home

appliances and co-residence.

Bibi & Afzal (2012) examines the factors which affect the decision of married women to

participate in the labour force. They found that education of the respondent, number of

off springs, number of dependents, family size, income of husband, monthly expenditures

of the family, positive attitude of husband and family towards the job of women, job

satisfaction, have a positive impact on the labour force participation of married women.

While age of the respondent, living with husband, strong relationship with spouse before

marriage, satisfaction of house wives with their current life, restrictions from family

regarding job, other earners in the family negatively affect the decision of married

women to participate in the labour force. They also suggest that the rate of inflation

prevailing in the economy of a country largely influences the labour force participation of

married women.

2.22 Empirical Literature: Evidence from Nigeria

Baridam (1996) pioneered the research in Nigeria by examining the determinants of

female labour force participation and family size using questionnaire and descriptive

statistics method. He sourced data from 300 female staff of Shell Petroleum, University

of Port-Harcourt and its metropolis shows that participation in labour force is due to

economic agents and love for children. The result also reveals that women avoid the

effect of their employment on their family size by employing house-helps.

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Ogwumike, et al (2006) analysed the distribution and structure of main job earnings,

determinants and income inequality in the Nigerian labour market. The study uses tabular

presentations, Gini Coefficient, Theil’s Entropy Index, Ordinary Least Squares technique,

Heckman’s two-stage selectivity bias correction procedure, Tobit analytical technique as

well as descriptive statistics for analyses. The results on labour participation show that

the aggregate data variables relating to age and education are all significant at 1per cent.

Age and education carry positive sign, which suggests that hours of labour offered in the

market increases with age and education of workers. All of marriage, divorce and loss of

spouse through death are all very significant and positive determinants of labour force

participation in the Nigerian job market. For married female, marriage affected

participation in 24 the labour market significantly, but negatively, suggesting that

marriage constitutes a source of restriction to female participation in the labour market in

Nigeria. He shows that the presence of children under-six also has significant negative

impact on the ability of women to participate in the labour market. Most of the variables

considered in disaggregated analyses in this empirical process are significant in

explaining time offered in the labour market in Nigeria.

Olusoji (2006) investigated the determinants of female labour participation in Nigeria,

using a Survey carried out between January and October 2001.They used regression

analysis to investigate the differences in hours put in by both women formal and informal

sectors separately. Their findings suggest that the number of hours worked were

determined by the respondents income, family size, relationship with household head,

sector of participation, education and location. The researcher also opines that women

with tertiary education work fewer hours than older and married women.

Umar and Karofi (2007) examine the impact of non-work factors on labour turnover

among female employees in Kebbi State Civil Service. The hypothesis of the study states

that the higher the perception of prevalence of certain non-work related factors, the

earlier the decision by female workers to disengage from the civil service. The study uses

administers questionnaire on 172 former female civil servants in Kebbi State. The result

indicates that non-work factors are statistically significant determinants of female labour

turnover. The finding also note that pressures from the matrimonial homes are very

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strong, standing out as the strongest of all the non-work factors responsible for female

labour turnover. The studies recommends that high-quality public childcare should be

provided at work places and that the government should also look at ways of making

work–environment reflect the culture of the society.

Aminu (2010) investigates the determinants of participation and earnings in wage

employment in Nigeria. He estimates Multinomial logit and Mincerian human capital

models for male and female employees across four wage employment segments

considered in the study. His results of the estimated multinomial logit model shows that

the probability of participation of employable household members in wage employment

segments is affected by the levels of education attained, possession of assets like own

homes, living in free accommodation and residing in urban areas. The probability of

participation in public sector wage employment increases with the level of education. He

finds that the main determinants of hourly wage are the levels of education, ages and the

location of residence of the employees. The returns to education and age differ for males

and females across the four segments of wage employment adopted for the study. He

finds that mean of hourly wage is highest in government ministries while it is lowest in

informal private sector organisations. Gender wage differential is lowest in government

ministries while it is highest in informal private organizations. He concludes that the

various segments of wage employment in Nigeria are not homogenous with respect to the

factors determining participation and earnings.

Chukuezi (2010) examines the participation of women in household labour in Nigeria . A

survey of married women in Owerri, Nigeria reveals that women do most of the

housework and childcare within the family. She explains that cultural expectations about

gendered responsibilities in the home despite their level of education and earnings are

mainly responsible for women doing more household work than men. She concludes that

both structured and cultural factors should be examined for an appropriate explanation of

gendered inequity in household labour in Nigeria.

Oladejo et al., (2011) analyse women participation in agricultural production in Egbedore

Local Government Area of Osun State, Nigeria. The study investigates the women’s

access to economic resources and examines the influence of selected socio-economic

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characteristics of women and access to economic resources on their participation in

agricultural production. Using multistage random sampling technique to select 50

respondents, it makes use of well-structured interview schedule to obtain the necessary

data. The study adopts both descriptive and inferential analytical tools. The study equally

uses probit analyses to investigate the determinants of women participation in agricultural

production in the study area. The results reveal that household size, marital status and

local taboos had significant impact on the women participation in agricultural production;

all at 5% probability level with a log likelihood of -96.160222, pseudo R2 of 0.0875 and

LR statistic of 18.44 which shows that the model has a good fit. They note that most of

the respondents were illiterate with non-formal educational status which directly

informed their participation in agricultural production. The study concludes that there is

high rate of involvement of women in agricultural production in the study area; hence the

role of some socio-economic variables as well as assets such as social capital, landed-

property, cash as well as savings are central in determining the participation level or

perception on agricultural production.

2.3 Summary of Literature

YEAR/AUTHOR LOCATION NATURE OF DATA METHODOLOGY FINDINGS

Psachropoulos and

Tzannatos (1989)

136 countries Time series data Panel analysis The participation of

women in the labour

force initially decreases

and picks up later after a

critical level of

development has been

achieved. And that

education is seen as a

potential booster of the

officially recorded

female labour supply in

developing countries.

Jaumotte (2003) 17 OECD countries Time series data 1985-

1999

Econometric panel

analysis

There is a positive impact

of neutral tax treatment of

second earners on female

participation. And that

female education, the

general labour market

conditions, and cultural

attitudes remain major

determinants of female

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Iweagu H. E., (2012)

participation.

Lisaniler & Bhatti (2005) North Cyprus 2001 cross-sectional

data

Binomial Logit Analysis Women’s education is the

main factor increasing

women’s likelihood of

participation while age

and the residence are also

significant factors

influencing the women’s

labour supply. And the

effect of patriarchy and

cultural factors on the

labour supply decisions of

North Cypriot women.

Boca & Locatelli (2006) some European

countries

cross-sectional data Structural model of

participation

that most analyses

indicate that social

policies, taking into

account several variables

(family background, the

allocation of time within

the household, religion

and culture), have a very

relevant role in explaining

different degrees of

incompatibility between

employment and child

rearing across different

countries

Ntuli (2007) Some African

countries

1995-2004 Decomposition technique Female participation

responds positively to

education which has been

the prime factor. The

study finds that non-

labour income, marriage,

fertility and geographical

variations in economic

development persistently

stifled participation.

Pastore & Verashchagina

(2008)

Belarus 1996 and 2001

Belarusian Household

Survey

Probit model The estimated elasticity of

female participation to

wages is low, at about

0.45 in 1996 and 0.41 in

2001. At the same time

the elasticity of female

labour supply with respect

to the own wage appears

to be much higher for the

low-paid groups of

women.

Ackah et al (2009) Ghana 1991/92 and 2005/06

Ghana Living Standards

Survey

OLS Technique Women with primary

school education or above

are more economically

active than those with no

education. And that high

fertility acts as a

constraint on female

participation in wage

employment; and that the

presence of children in the

home significantly

reduces participation in

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Iweagu H. E., (2012)

wage work, controlling

for age, education,

ethnicity, religion and

marital status.

Chaudhry and Nosheen (2009) Punjab primary data from a

district of Southern

Punjab

OLS method The results show that

women empowerment is

considerably influenced

by education, access to

media, socio-cultural

norms of the community,

job of women and

household participation

rate.

Bbaale (2010) Uganda Demographic and

Health Survey 2006

Probit model His results confirm the

hypotheses that female

education, especially at

the secondary and post-

secondary levels, reduces

fertility and increases

their likelihood of being

engaged in the labour

force

Faridi et al (2011) Pakistan Multiple Indicator

Cluster Survey 2007-08

data of Punjab

Heckman two step model

and Logistic regression

technique

Age and experience

positively affects

women’s self-

employment. They also

conclude that education,

location and number of

dependents significantly

reduce the women’s work

participation as self-

employed worker.

Surjit & Kaur (2011) India NSS data Tobit Particular ethnic and

socio-cultural groups tend

to concentrate in various

sectors of the labour

market. Studies in the

area of gender and

migration also point out

that marriage migration

often leads to entry into

the labour force and the

two processes are not

mutually exclusive.

Ejaz (2011) Pakistan Pakistan Social and

Living Standards

Measurement Survey

for 2006/07

Instrumental variable (IV) An inverse and significant

relationship between

FLFP and both fertility

and the gender-wage gap;

and a direct and

significant relationship

between FLFP and

ownership of home

appliances and co-

residence.

Bibi & Afzal (2012) Wah Cantt (Pakistan) Sample survey through

questionnaires

Descriptive analysis They found that education

of the respondent, number

of off springs, number of

dependents, family size,

income of husband,

monthly expenditures of

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Iweagu H. E., (2012)

the family, positive

attitude of husband and

family towards the job of

women, job satisfaction,

have a positive impact on

the labour force

participation of married

women. While age of the

respondent, living with

husband, strong

relationship with spouse

before marriage,

satisfaction of house

wives with their current

life, restrictions from

family regarding job,

other earners in the family

negatively affect the

decision of married

women to participate in

the labour force.

Baridam (1996) Port-Harcourt,

Nigeria

Data sourced from 300

female staff of Shell

Petroleum, University

of Port-Harcourt and its

metropolis

descriptive statistics

method

That participation in

labour force is due to

economic agents and love

for children. The result

also reveals that women

avoid the effect of their

employment on their

family size by employing

house-helps

Ogwumike, et al (2006) Nigeria General Household

Survey (GHS)

conducted in

1999 by the Federal

Office of Statistics

(FOS), Nigeria

Heckman’s selectivity bias,

Tobit analytical technique

as well as descriptive

statistics for analyses

Age and education carry

positive sign, which

suggests that hours of

labour offered in the

market increases with age

and education of workers.

While, marriage, divorce

and loss of spouse

through death are all very

significant and positive

determinants of labour

force participation in the

Nigerian job market.

Umar and Karofi (2007) Kebbi State, Nigeria Primary data through

questionaires

OLS Method The result indicates that

non-work factors are

statistically significant

determinants of female

labour turnover. The

finding also note that

pressures from the

matrimonial homes are

very strong, standing out

as the strongest of all the

non-work factors

responsible for female

labour turnover. The

studies recommends that

high-quality public

childcare should be

provided at work places

and that the government

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Iweagu H. E., (2012)

should also look at ways

of making work–

environment reflect the

culture of the society.

Aminu (2010) Nigeria General household

survey data (GHS)

conducted by NBS in

1998/99 and 2007/2008

Probit, Multinomial logit

and Mincerian human

capital models

The probability of

participation of

employable household

members in wage

employment segments is

affected by the levels of

education attained,

possession of assets like

own homes, living in free

accommodation and

residing in urban areas.

Chukuezi (2010) Owerri , Nigeria Primary data, Owerri Descriptive analysis That cultural expectations

about gendered

responsibilities in the

home despite their level

of education and earnings

are mainly responsible for

women doing more

household work than men

Oladejo et al., (2011) Osun State, Nigeria Primary data, Nigeria,

Osun state.

Descriptive and inferential

analytical tools and probit

analyses

The results reveal that

household size, marital

status and local taboos

had significant impact on

the women participation

in agricultural production.

Olusoji (2006) Nigeria Survey carried out

between January and

October 2001

OLS Regression Number of hours worked

were determined by the

respondents income,

family size, relationship

with household head,

sector of participation,

education and location.

2.4 Limitation of the previous study

From the literature review most of the works that sort the determinants of female labour

force participation relied on the assumption that there was no significant difference in the

region of residence of the individual, and just looked for the impact of rural urban

residency on female labour participation and therefore sort for the determinants generally.

We shall therefore capitalise on this to run regression analysis to test for the determinants

in the urban regions of Nigeria differently as well as those of the rural regions to ascertain

if there is no difference between them or there is need for separate policies to be carried

out in both regions to improve female labour participation if there is.

We also note that most of the works used methods like multi-stage random sampling

technique, OLS technique, decomposition techniques, descriptive statistics and other

regression analysis. However the closest of all these works is that of Faridi et al (2011)

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who used logistic regression but did his analysis based on primary data from Pakistan. In

Nigeria, Aminu (2010) used multinomial logit labour participation within 4 wage

brackets, while chukuezi (2010) examines the participation of women in household

labour participation and not general labour participation. Also we find, Baridam (1996)

who uses descriptive statistics to examine the determinant of female labour force

participation and family size in Nigeria and Lawson (2008) studied on the female labour

force participation: determinant and trend without applying any statistical techniques for

the estimation. We shall therefore use the logit approach to explore its odds ratio and

probability qualities in interpreting the results.

This study therefore attempts to fill the gap created in the literature by focusing on the

determinants of female labour force participation in Nigeria using logit regression in

urban Nigeria separately from rural Nigeria. The researcher employed the General house

hold survey employment data for 2010/2011, that we have employed has the advantage of

a very recent and national data unlike most works carried out in Nigeria.

CHAPTER THREE

3.0 Methodology of the research

3.1 Theoretical Framework

The theoretical framework of this study would be based on the Neoclassical Model of

Allocation of Time. Economists traditionally analyse labour supply through the use of the

neoclassical model of allocation of time or the model of labour-leisure choice, which is

an extension of the utility maximization problem of consumer theory. The model

analyses how individuals make choices in deciding how they will spend a fixed amount

of time. They must decide how many hours to work, and how many hours to spend

consuming a variety of goods, ranging from computers and cars to DVDs and theatre.

The study uses a standard participation model based on conventional theoretical

household models of time allocation (Mincer, 1962; Becker, 1965).

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In the simplest model, an individual has two uses for his/her time, either working in the

labour market at a real wage rate of W per hour, or “leisure”. According to this basic

model, individuals wish to maximize their utility or satisfaction (U) by purchasing goods

and services (C) in the marketplace and by consuming time in leisure activities

(L). amount of both consumed will depend on the individual’s market wage (W),

personal preferences, and the non-labour income (V) that person enjoys.

Becker (1965) while developing the model stated that the individual’s utility function will

be:

U = f(C, L) ……………………………………........................................................... (1)

where U is an index that measures the individual’s wellbeing, assuming people are able

to rank in order all possible situations from the least desirable to the most. Thus, a higher

index U means more C and/or L and more satisfaction.

Moreover, C and L are economic “goods” – that is, whatever economic quantities they

represent, we assume that more of any particular good is preferred to less.

Nicholson (1992) explained that when the individual seeks to maximize his/her utility

with respect to time in the period under analysis, he is bound by two conditions: first, he

must allocate the day’s discretionary time (T) – that is, 16 hours’ time, either to working

for pay (H) or to leisure (L). The other condition is related to the income he needs to buy

goods and services in the market place: Labour wages (W * H) and non-labour incomes

(V) are the only sources of the individual’s income. These constraints can be written as

the following:

L + H = T…………………………………………………………............................... (2)

C = (W * H) + V ……………………………………………………........................... (3)

The individual’s budget constraint is represented by equation (3). It tells us that

individual’s consumption expenditures must not exceed the total income. We can rewrite

(2) and (3) as follows:

C = W (T- L) + V

Setting up the Lagrangian expression to represent the individual’s utility maximization

problem yields

[ ]{ }( , ) ( )L U C L W T L V Cλ= + − + − ………………………………............................. (4)

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Iweagu H. E., (2012)

The first order conditions for a maximum are

0C

L UMU

C Cλ λ

∂ ∂= − = ∴ =

∂ ∂……………………………………….............................. (5)

0 LMUL UW

L L Wλ λ

∂ ∂= − = ∴ =

∂ ∂………………………..…………................................ (6)

Equating (5) and (6), we get

L

C

MUW

MU= ……………………………………………….……….................................. (7)

This expression can be interpreted as the utility-maximizing labour supply decision

principle. That is, in order to maximize utility, given the real wage, W, the individual

should choose to work that number of hours for which the marginal rate of substitution of

leisure for consumption is equal to W (Nicholson, 1992). The interior solution of the

model answers the question of the number of work hours to be supplied by the worker.

An increase in W, holding income constant, makes leisure more expensive.

Therefore, by consuming additional hours of leisure, the worker gives up more in forgone

wages, producing a negative substitution effect with respect to hours of leisure. On the

other hand, since leisure is a normal good, the income effect will be positive. That is, an

increase in the wage rate, W, will increase the consumption of leisure, L, since the person

now feels better off.

Since work and leisure are mutually exclusive ways to spend one’stime, these two

opposite reactions prevent the model from predicting the direction of the change in the

number of hours worked. The ambiguity cannot be solved unless one knows the worker’s

actual labour supply decision. If the substitution effect dominates, the result will be an

increase in the number of work hours supplied. On the other hand, if the income effect

dominates, the number of work hours supplied by the worker will decrease.

Nakamura A. & Nakamura N. (1994) noted that empirical studies have shown that the

income effect tends to dominate for men and the substitution effect, for women. When

non-labour income, V, changes, there is no ambiguity since the income effect operates

alone. Thus, an increase in V will cause an increase in leisure time and a decrease in the

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hours worked, and vice versa. A corner solution of the model will occur when the

individual has decided not to participate in the labour force. Economic theory explains

this case through the definition of reservation wage, W* as the measure an individual

places on his/her non-market time.

The reservation wage is the wage that would make a person indifferent between not

working and working that first hour. The value of W* is influenced by his/her tastes and

preferences, the level of non-labour income V, factors influencing the value of one’s time

at home such as the number of children, and marital status. This theory has been

successfully used to explain women’s labour force participation (Rincon, 2007). We

assume therefore that an individual maximizes a well behaved utility function (U) that is

defined over her within-period consumption of commodities (C) and leisure (L), the

model can be expressed formally as

( , , )U U C L X= …………......................................................................................…… (8)

where, X indicates individual and household characteristics such as age, marital status,

ethnicity, etc. The number of children and any other dependents are included in the vector

of individual and household attributes, X. Utility is assumed to be maximized subject to

the budget (income and time) constraint

C WL Y WT+ = + ………………………………………………...............................(9)

where W is the wage rate, Y is non-labour income and T is the total time available. The

individual maximizes a utility function subject to the constraint imposed by the fixed

time T and how to allocate her time to home production, market work and leisure. Thus,

the optimal allocation of time to market work will be determined by the personal and

household attributes as well as on the labour market characteristics. The labour market

conditions determine the costs of a job search and the remunerations of the market work.

The solution to the optimization problem results in the familiar first-order conditions

( , , ) , ( , , )C L

U C L X U C L X Wλ λ= ≥ …………………………................................…(10)

where λ is the marginal utility of income and equation (3) involves, on the one hand, the

demand function for the utility-generating commodities, and, on the other hand, the

optimal allocation of time among leisure, market work, and home production. If the

inequality in equation (3) holds strictly then the individual is not working and L=T, the

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Iweagu H. E., (2012)

wage, RW, such that ( , , )L R

U Y T X Wλ= is the reservation wage below which the

individual will not work; i.e., the individual participates in market work if and only if the

expected market wage is greater than the reservation wage.

3.2 Analytical Framework

The logit function is based on a binary random variable, say Y having a Bernoulli

distribution. We shall therefore relate is as stated by as follows;

Y~ B(1, ᴨ(x)).................................................................................................................(11)

That is, the variable Y takes either the value 1 or the value 0 with probabilities ᴨ(x) or

1- ᴨ(x) respectively. X ϵ Rp is a vector of p exogenous variables and ᴨ: Rp → [0,1] a

real-valued function. In fact, ᴨ(x) represents the conditional probability P(Y=1/x) of

Y=1, given x.

Let r = Y- ᴨ(x), which allows us to rewrite our model as

Y = ᴨ(x) + r.................................................................................................................... (12)

Where r has an expectation of

E(r) = E(Y - ᴨ(x)) = E(Y) - ᴨ(x) = ᴨ(x)- ᴨ(x)=0........................................................... (13)

And a variance of

Var(r) = Var(Y) = ᴨ(x)(1- ᴨ(x)).................................................................................... (14)

For the forthcoming analysis we are going to define the so-called logistic transformation

designated as;

............................................................................................. (15)

Which allows us to specify the probability function ᴨ as

ᴨ(x) = L(xTβ)...................................................................................................................(16)

with a vector β ϵ R of unknown parameters. This specification yields the logistic

regression model with parameter β.

If we denote the inverse function of L, referred to as the logit transformation, by

Logit ᴨ = ln ............................................................................................... (17)

3.3 Model Specification

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Iweagu H. E., (2012)

Since a female is participating in the labour force or not, labour force participation is a

yes or no decision. Hence the response variable, can take only two values. 1, if the

woman is in the labour force and 0 if she is not, Guajati, (2009). Following Afaredi et al

(2011) the study will employ the logit model for both objectives.

The logit model equation takes the following form:

FLF =Xi β + ui, ∀ i =1....n, .......................................................................................(18)

Where FLF represents the female labour force participation, X is a vector of explanatory

variables given as follows: ageyrs1 for age of respondent above 18 years old, martat for

marital status, religion, hhsize for Household size, pov for Poverty rate, lit for Literacy

rate, state, pcexp for Per capital expenditure, and lowage for Lowest wage willing to start

up work with, while β is a vector of parameters or coefficients to be estimated and µ is

the error term.

3.3.1a Model 1: This is for objective one; the logistic regression to ascertain female

participation in rural areas.

logit (yt) = ln 1

=

D

D .β0 + β1 ageyrs1 + β2 marstat + β3 religion + β4 lhhsize + β5 pov +

β6 lit + β7 state + β7 pcexp + β7 lowage + µ...................................................................(19)

3.3.1b Model 2: This is for objective one; the logistic regression to ascertain female

participation in urban areas.

logit (yt) = ln 1

=

D

D .β0 + β0 + β1 ageyrs1 + β2 marstat + β3 religion + β4 lhhsize + β5

pov + β6 lit + β7 state + β7 pcexp + β7 lowage + .............................................................(20)

Yt in this case is the female labour participation in rural areas.

3.4 Estimation Methods

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Iweagu H. E., (2012)

We address the first, objective by estimating the model for female labour force

participation and in so doing; we translate the theoretical model into an empirical logit

model. Labour supply or labour force participation in our case, measured at the time of

the survey is entered as a dependent variable in our model. The main objective of

estimating this model is to establish the factors that are more likely to influence a

woman’s decision to participate in the labour market.

3.5 Justification of the model

Since the main aim of this study is to find out the factors which affect the decision

making status of female as it concerns labour force participation, it becomes necessary to

use the Logit model analysis. This is due to the fact that our dependent variable is a

qualitative choice variable with 1 being female participation and 0 non-female

participation. According to Gujarati 2004, in such equations neither OLS nor weighted

least squares (WLS) are helpful. We have to resort to nonlinear estimating procedures

like the logit regression.

Logit analysis produces statistically sound results, by allowing the transformation of

dichotomous variable such as the female labour participation rate to a continuous

variable. Thus, the problem of out of range estimate is avoided. It provides results which

can be easily interpreted and it also gives parameter estimates which are asymptotically

consistent, efficient and normal.

We will use the logistic command so that we see the odds ratios instead of the

coefficients. In this example, we will simplify our model so that we have only one

predictor

3.6 Source of data

The data for the analysis would be the house hold survey employment data for

2010/2011. The data contains 57,372 observations from 37 states and 774 local

governments. The data set contains relevant information such as individual’s

demographic and social characteristics, characteristics of main occupation, total earnings,

sector of employment, number of hours worked and educational attainment. The survey

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covers both urban and rural areas and portrays a fair share of the national scope based on

the fact that samples were gotten from all the 37 states of the Federal Republic of

Nigeria. This will help to analyse the role of location on labour force participation.

CHAPTER FOUR

4.0 EMPIRICAL RESULTS

4.1 Presentation of Results

4.11 Logit results for female participation in rural areas

The logit regression result that is aimed at examining the determinants of female labour

participation in the rural sector as stated in objective 1 is presented below;

Logistic regression Number of obs = 781

LR chi2(9) = 45.53 Prob > chi

2 = 0.0000

Log likelihood = -35.044563 Pseudo R2 = 0.3938

Table 1: logit regression for rural female participation

Rural female labour part. Coef. Std. Err. z P>|z|

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Age>18 -.0127553 .0215002 -0.59 0.553

Marital status .5660326 .1872876 3.02* 0.003

religion -3.020461 1.190427 -2.54* 0.011

Household size -.6809934 .687956 0.99 0.322

Poverty rate 2.177998 1.00529 2.17* 0.030

Literacy rate -1.036897 1.145607 -0.91 0.364

state -.0139326 .2045547 -0.43 0.666

Per-capita exp. -3.482486 1.145607 -3.04* 0.002

Lowest wage willing to start

up work with

.0155558 .2045547 0.08 0.939

_cons 30.47918 10.06343 3.03 0.002

Coefficients with * denote significance at 95% confidence interval.

Prob > chi2 gives the probability that the null hypothesis is true and as we can see, Prob >

chi2 = 0.0000 shows that we should reject the null hypothesis as there is no statistical

probability that the null hypothesis occurred. Hence the model is statistically significant.

From the coefficients we see that age coefficient is negative with the value -.0127553.

This means that for a one-unit increase in age, we expect a 0.0127553 decrease in the log-

odds of the female participation in urban areas holding all other independent variables

constant. In other words, the exponential of 0.0127553 (e0.0127553 = 1.012836996) gives us

the odds ratio of female labour participation with respect to age, that is a unit increase in

age decreases the odds or probability that a female would participate by about 1.013. This

suggests that the older a female who lives in the urban area is, the less likely is she to

participate in the labour force and the female labour force is likely to increase with the

younger generation. We note however that the age coefficient is not significant with a z-

value of -0.59.

This could be attributed to the fact that women could work at whatever age in rural areas

and therefore would not play a significant role in determining whether women work,

rather other factors could be able to determine this such as marital status. Marital status

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has a strong positive effect in determining whether women in rural areas decision to take

up paid jobs. Marital status a coefficient of 0.5660326 that suggest that a unit increase in

every woman that gets married increases the probability that she takes up paid jobs by

about 1.76 (e0.5660326

). This is very surprising as we expect that due to the cultural beliefs

in Africa which is stronger in the villages, marriage should prevent women from taking

up paid jobs as the case maybe. However we understand equally that these rural sectors

are characterised by relatively poor families that the men may not have a choice than to

let their spouses take up paid jobs in order to increase the total household income to meet

the challenges of this new age.

Religion also appears to be one of the significant determinants of female labour

participation as portrayed by our findings, though it suggests a negative relationship. The

results show that a unit increase in women becoming Muslims or traditionalists reduces

the probability that a woman would take up paid jobs by 20.5 (e3.020461

= 20.50074035).

This also implies that regions with more muslims and traditionalists would have a lower

probability for women to participate in the labour force which is expected as these

religious groups give priority to men than women in most aspects of life.

Equally surprising is the fact that household size is not significant given the p-value of

0.322 which is higher than 0.05 considering a two-tailed test at 5% level of significance.

Therefore a unit increase in household size reduces rural female labour participation with

the log-odds ratio of -0.6809934, or the odds or probability of 1.976 (= e0.6809934

). The

negative relationship between household size and female labour participation is however

expected, given that the higher the household the higher the domestic responsibilities for

the woman. Nevertheless, the household size coefficient is insignificant and could be

attributed to the fact that rural areas tend to practice child labour such that even very

young children participate in paid jobs and thereby reducing the number of people

dependent on the woman’s assistance.

The poverty rate has a significant positive impact on female labour participation. The

higher the poverty rate the higher the probability that a woman would take up paid jobs.

In fact our results suggest that for a unit increase in poverty level the probability that a

rural woman would participate in active labour force increases by about 8.829 (e 2.177998

).

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This is expected a priori based on the fact that the poorer one is, the more he is compelled

to take up paid jobs, and in fact it becomes more a matter of obligation than choice.

However what is most surprising is that literacy rate has an insignificant impact on

female labour participation. Our results show that a unit increase in literacy rate decreases

the probability that a woman would participate in labour force by about 2.82. This could

only be explained by the fact that most people may not really work according to their

educational qualifications due to the scarcity of available jobs, and on the other hand

some of the jobs do not even necessary need educational qualifications, so at the end of

the day it is no longer a question of being educated or not but other factors could

contribute to female labour participation as we have discussed. The inverse relationship

could be attributed to the fact that if you are too qualified then you may be come

overqualified for the jobs in the rural areas.

Per-capita expenditure was seen as a very strong determined of female labour

participation in rural areas with a z-value of /-3.04/>2 and a low p-value of 0.002.

However what was surprising about this is that it had a negative relationship with female

labour participation. The results show that a unit increase in per-capita expenditure would

reduce the probability that a female participates by the probability of 32.5 (e 3.482486).

While the lowest wage they were willing to start up paid jobs with, was not significant

according to the findings. A unit increase in the amount of wage willing to start up paid

jobs with increases the probability that a female would participate by 1.0157 (e.0155558

).

This is definitely expected a priori given that economic theory projects remuneration as

an incentive to work. So wage willing to start up paid jobs and female labour

participation have a positive direction though it’s not a significant determine in the rural

areas.

The expected value of the log-odds of female participation in rural areas when all of the

predictor variables equal zero is 30.47918, with a very strong significant level. On a

general note we therefore state that the significant determinants of female labour

participation in rural areas at 5% level of significance are; marital status, religion, poverty

rate and per capita income, as has been discussed above.

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4.12 Logit results for female participation in urban areas

The logit regression result that is aimed at examining the determinants of female labour

participation as stated in objective 2 is presented below;

Logistic regression Number of obs = 781

LR chi2(10) = 24.62 Prob > chi

2 = 0.0034

Log likelihood = -22.877447 Pseudo R2 = 0.3499

Figure 2: logit regression for urban female participation

Urban female labour part. Coef. Std. Err. z P>|z|

Age>18 .1023051 .0483931 2.11* 0.035

Marital status .686181 .3156097 0.85 0.395

religion .0860819 .9740589 0.09 0.930

Household size -1.000363 .9489482 -1.05 0.292

Poverty rate -2.280907 1.983212 -1.15 0.250

Literacy rate 3.119392 1.222911 2.55* 0.011

state .0368884 .079485 0.46 0.643

Per-capita exp. .5510093 1.761261 0.31 0.754

Lowest wage willing to start

up work with

-.0854893 .2519644 -0.34 0.734

_cons -14.89962 15.52144 -0.96 0.337

Coefficients with * denote significance at 95% confidence interval.

Just like in the regression result for rural we see that Prob > chi2 = 0.0034, this shows us

that we should reject the null hypothesis as there is no statistical probability that the null

hypothesis occurred. We note that there are so many differences in urban female

determination of labour force from the rural. Strangely, while the factors that prove to be

the determinants of female labour participation in rural areas are not those that determine

those in the urban areas. In the urban areas age proves to be a very serious determinant of

female labour participation according to our results which was not the case in the urban

areas. Age has a coefficient of 0.1023051 that suggest that as a woman’s age increases

per unit the log of odds that a woman participates in the labour force is 0.1023051. That

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Iweagu H. E., (2012)

is for a unit increase in age, the probability that a female would participate is 1.108

(=e0.1023051

). The fact that there is a positive relationship between age and female labour

participation is what is expected a priori, because the older one gets all things being

equal, the more educated/qualified she becomes. It is not surprising however that this is

more apparent in urban areas or cities considering their level of exposure and

development.

On the other hand, marriage which was significant in the rural areas appears not to be

significant in the urban areas, which is expected given their level of exposure. A unit

increase in women getting married increases the probability that a woman participates in

labour force by 1.99 (=e0.686181

) but note that this is not significant so we can’t count on it.

However there exist a positive relationship between marriage women and her decision to

participate in the labour force just like in that of the rural sector. This is in line with the

age factor as women tend to get marry as they grow old so we expect a positive

relationship for age and marital status. Just like marital status, Religion and poverty rate

appears not to be significant in the urban regions unlike in the rural areas. However, just

like we explained for rural areas, some of these factors are influenced more in rural areas

by their customs and traditions while something like religion would no longer count in

the urban areas due to their level of westernisation and development, this might not be the

case with the rural sectors. We however expect poverty rate not to be a significant

determinant of female labour participation, as a majority of the inhabitants of urban areas

live above the poverty threshold value, so poverty might not really be the major force of

inducing a woman to work or not.

Household size is not significant in both cases which is rather strange and different from

many other works that show that household size is a determinant of female labour

participation. The fact that it is insignificant in both urban and rural according to our

results only guides us to suggest that household is not a determinant of female labour

participation, so policy makers should take note and pursue more serious determinants.

However the negative coefficient of household size still aligns with a priori expectation

due to the fact that the more the household is the higher would be the woman’s domestic

responsibilities and consequently might hinder her from taking up paid jobs.

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Iweagu H. E., (2012)

Literacy rate shows a significant positive relationship with female labour participation

which is highly expected more importantly on urban areas. Our result indicates that for a

unit increase in women becoming literates or learned, the log of odds that a woman

participates is 3.119392. That is a unit increase in literacy rate increases the probability

that women participate in labour force by 22.633 (e3.119392

). This is very high and makes

sense as the z-value is 2.55 with a very low p-value of 0.011at 5% level of significance.

The state of residence and lowest wage willing to work do not really appear to be female

labour determinants according to our results as they both have a z-value of 0.46 and -0.34

respectively, which is very low compared to the reference point magnitude of 2. In the

urban regions this could be explained by the fact that most urban areas tend to be the

same as development and competition increases, which may expose the women to the

same experiences such that women in different states turn to think alike with respect to

participating in female labour force. While the lowest wage willing to start up with might

not also b significant in urban regions because most employers rather look for those who

can deliver based on their level of qualification, and once they have that, how much one

is ready to start up with becomes a smaller issue to tackle.

Per-capita expenditure just like the other determinants in rural areas doesn’t seem to be a

determinant according to our result. The per-capita variable records a z-value of 0.31 and

a high p-value at 0.734 suggest that it is not a significant determinant of female labour

participation. An increase in per-capita expenditure increases the probability that females

participates by 1.735 (e0.5510093

) which is not significant. On the other hand, the fact that

the coefficient is positive also aligns with expected outcome as per-capita expenditure

might provoke a woman to take up paid jobs. The expected value of the log-odds ratio of

female participation in urban areas when all of the predictor variables equal zero is -

14.89962, however this appears to be insignificant with evidence in the z-value = -0.96

and a high p-value at 0.337. On a general note we therefore state that the significant

determinants of female labour participation in rural areas at 5% level of significance are;

age and literacy rate while the insignificant determinants are marital status, religion,

household size, poverty rate, state, per capita expenditure and lowest wage willing to start

up work with.

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Iweagu H. E., (2012)

CHAPTER FIVE

SUMMARY, POLICY IMPLICATIONS AND CONCLUSION

5.1 Summary

The study on the determinants of labour force participation was motivated by the interest

to boast female labour participation in rural and urban sectors of Nigeria. This has been a

global fight over the past decade and it is even more significant in developing countries

like Nigeria. The female sensitivity in the supply of labour has been attributed to cultural

and religious beliefs and traditions as most men prefer to keep their spouses home to take

care of domestic activities and children upkeep, while they pay the bills. This study

therefore determines the female labour participation in rural and urban areas separately so

as to understand if this notion of female participation differs in their determinants in the

different sectors.

This therefore leads us to the use of logistic regression that permits us to take advantage

of the log of odds ratio and probability designations of each of these variables. Our

finding aligns with those of existing literature as the determinants in both sectors have

been discussed by other authors as well. However the major surprise is that the

determinants in the rural areas are different from those in the urban regions. According to

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Iweagu H. E., (2012)

the results, marital status, religion, poverty rate and per capita income are significant

determinants in the rural sectors. While poverty rate and marital status have a positive

relationship with female labour participation, religion and per-capita income have a

negative relationship. On the other hand; age, household size, literacy rate, state, and

lowest wage willing to start up with are all not significant in the rural regions of Nigeria.

In the urban regions, age and literacy rate are significant positive determinants of female

labour participation which of course is expected as explained in the previous chapter.

However, marital status, religion, household size, state, per-capita expenditure, poverty

rate and lowest wage willing to start up paid work is not significant. Most of these are

significant in the rural sectors and the only reason for which it might not be significant in

the urban sectors is based on the level of exposure, development and westernisation. This

could not have been noticed if we did a general regression for both urban and rural areas.

5.2 Policy implications

The relevance of this study cannot be overemphasized as it uses more recent data from a

logistic perspective to ascertain the determinants of labour participation in Nigeria, which

is in line with the government’s objective to minimise the marginalisation of the female

population. The fact that marital status is significant in rural areas and not in urban areas

is rather unlike what we expected a priori. The motivation of this study was to crosscheck

the influence marriage has on female labour participation, and our results show that it is

very significant and interestingly, has a direct relationship with female labour

participation. This however maybe associated to the fact that rural families have awoken

to the reality of combining efforts to cover household expenditure and children upkeep,

which is therefore encouraging and means that sensitisation could also be improved on

the unmarried females to take up paid jobs and not only wait for marriage to start work.

According to our findings age is highly significant in the urban sectors and not in the

rural sectors which suggest that age is somehow proportionately related with qualification

of women in the urban sectors which is expected, however the reverse is the case in the

rural sector which suggest that residents in rural areas should keep up improving on their

educational and professional qualifications as they grow old. This can be done through

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Iweagu H. E., (2012)

setting up institutions that could offer such qualifications that may adapt to their

household-duty schedule, so as to induce them to improve on their qualifications even as

they grow old.

Religion appears to have a negative significant effect on female labour participation in

rural areas which suggest that some religious cultures seriously restrict some women into

participating in gainful employment. This is very important when we consider the

government’s objective to improve female participation in labour force. Policy

instrumentalists should therefore find a way of sorting out these religions that negatively

influence participation, to sensitise them and expose them to the benefits of women

participating in gainful employment amongst their negative ones. On the other hand the

fact that religion is not significant only show that these residents have been able to look at

the relevance of a female participating in female labour beyond the religion which further

strengthens our recommendation on the exposure and sensitisation of rural residents to

participate. However based on the dummy regressor for religion the significance for

religion was from the Muslim religion which is not very surprising following their

underlying principles for a female Muslim faithful.

What is most surprising is that household size had an insignificant effect in both rural and

urban sectors that leads us to suggest that most households have found ways of

contending their responsibilities without this affecting the labour force participation of

the woman. However though not significant, household still has a negative relationship

with labour force participation meaning that the higher the household size the lower the

participation in some few cases.

Poverty rate has a significant positive relationship with female labour force participation,

which is expected a priori though it insinuates a very sad situation, stating that the higher

the poverty rate the higher the participation in rural sectors. Though we expect to

improve on female labour participation we cannot infer that we should expect women to

become poor so that they participate, rather it shows us that poverty rate is very high in

rural regions such that they are compelled to work and not under choice. Policy makers

should therefore ameliorate that standards of living in these areas and encourage the poor.

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Iweagu H. E., (2012)

This however is not the case in the urban regions where poverty rate appears to be

insignificant.

Literacy rate further strengthens our argument on age in urban sectors, implying that on

the general sphere as women grow old they get more qualified and hence have access to

jobs, which is not the case with rural areas who are relatively lees qualified in terms of

educational attainment. This only suggests that the government can create a special fund

only for female scholarships in diverse fields in order to boast female labour participation

and set them a par with the men. State also appears to be insignificant in determining

female labour participation in both rural and urban sectors. Per-capita expenditure

however is significant in determining female labour participation in rural areas and this is

expected a priori. Nevertheless we note that there exists a negative relationship between

per-capita expenditure and female labour participation in the rural sectors which show

that richer individuals are unlikely to participate in the labour force as we can assume that

individuals with high per-capita expenditure are mostly relatively richer.

On the other hand per-capita expenditure is not significant in urban regions as most

people are rich and motivated to work not only for the income, but for other factors like

health, growth and development. In rural and urban areas the lowest wage an individual is

willing to work is not significant, which suggest that there are many other factors that

determine if a female would participate in the labour force but her choice of “starting

income” is not a determinant factor.

5.3 Limitations of the study

This research on female labour force participation has been very enriching, however we

encountered some limitations. The household survey data was not easy to come by. It

appears that time series data is made available in most of the data banks like the World

Bank indicators and Nigerian bureau of statistics, but micro data is rare. We however

recommend that all surveys carried out by non-governmental associations and

government associations should be published, the most accessible today is the National

living standard survey which sometimes very long as it occurs every 4 years and most

times not released on time.

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Iweagu H. E., (2012)

5.4 Suggestions for further Research

The logistic investigation that separated the sectors into urban and rural gave us very

interesting results and sets the stage for further research on this topic. The main

suggestion is for other researchers to explore the rural sector determinants, given that our

findings suggest that the determinants of rural female labour force participation differ

from that of urban women. Therefore other methods should be employed with more

national data if possible, to investigate further the determinants in rural sectors of

Nigeria, as their level of participation seem to be lower than in urban sectors.

The significance of marital status in rural areas and not in urban areas, helps to identify

with the hypothesis that married women’s decisions might be influenced by their

husbands. The positive relationship shows that marital status rather favours female labour

participation which contradicts previous research (at least a higher proportion of the

empirical findings), so further studies of this nature should be made to ascertain if the old

ideology of husbands influencing their wife’s participation is a myth today. The study

notes that religion has a negative significant relationship with female labour participation

and therefore earmarks a reference point upon which more research should be carried out

to identify those religions that discourage or restricts women from participating in labour

force.

5.5 Conclusion

In conclusion, we note that the finding of this study is very enriching and contributes to

knowledge significantly. The Nigerian government has as objective to, improve on

female representation nationally and primarily this impact must be felt in the labour

market. The Nigerian government has done a lot over the years to improve female labour

participation but a lot more still needs to be done. The determinants of female labour

participation in the rural sector is mainly marital status, religion, poverty rate and per

capita income are significant determinants in the rural sector, while in the urban sector is

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Iweagu H. E., (2012)

age and literacy rate. This therefore connotes that the determinants in urban sectors are

completely different from that of rural sectors. Researchers, policy analysers, policy

makers, and policy implementers should take this into consideration when designing

policies to improve labour force participation, thereby reducing unemployment rate in the

country.

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