Female Labour Force Participation and Economic Growth in Kenya, 2020

This research project, submitted to Rongo University in February 2020, investigates the relationship between Female Labour Force Participation (FLFP) and economic growth in Kenya from 2004 to 2019. The study, authored by Karanja Nancy Mugure, aims to determine the impact of factors like capital and educational attainment on this relationship. Using time series data from the World Development Indicators and employing E-Views for data analysis, the project contributes to the existing literature by providing insights into the significance of FLFP in Kenya's economic development. The introduction provides background on rising FLFP in developing countries, highlighting its connection to economic growth measured by GDP. The project covers theoretical frameworks such as the Labour-Leisure, Household Production, and Human Capital theories, along with empirical literature. The methodology includes details on the target population, data collection methods, data analysis, and model specification. The project underscores the increasing importance of women's participation in the labor force for sustainable economic growth and the need to address gender gaps in the Kenyan labor market.

FEMALE LABOUR FORCE PARTICIPATION AND ECONOMIC GROWTH IN KENYA
BY KARANJA NANCY MUGURE
ECO/012/2016
A RESEARCH PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENT FOR THE AWARD OF A DEGREE IN BACHELOR OF ARTS
ECONOMICS
SCHOOL OF ARTS AND SOCIAL SCIENCES
RONGO UNIVERSITY, KENYA
FEBRUARY 2020
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DECLARATION
I Nancy Mugure Karanja declare that this project is my own personal work and has been done
to the best of my knowledge and ability. I hereby declare that all information on this document
has been obtained and presented in accordance with academic rules and ethical conduct.
Name: Nancy Mugure Karanja Registration No.: ECO/012/2016
Signature:
Supervisor’s name: Mr Moses Obama Position: Lecturer
Signature:
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Table of Contents
DECLARATION........................................................................................................................................iii
LIST OF FIGURES.....................................................................................................................................v
ABBREVIATIONS....................................................................................................................................vi
ABSTRACT..............................................................................................................................................vii
1 CHAPTER ONE: INTRODUCTION...........................................................................................................1
1.1 BACKGROUND TO THE STUDY.....................................................................................................1
1.2 STATEMENT OF THE PROBLEM....................................................................................................4
1.3 RESEARCH OBJECTIVES................................................................................................................5
1.4 RESEARCH QUESTIONS................................................................................................................6
1.5 SIGNIFICANCE OF THE STUDY......................................................................................................6
1.6 SCOPE OF THE STUDY..................................................................................................................6
1.7 LIMITATIONS OF THE STUDY........................................................................................................6
1.8 CONCEPTUAL FRAMEWORK........................................................................................................7
1.9 OPERATIONAL DEFINITION OF TERMS.........................................................................................7
2 CHAPTER TWO: LITERATURE REVIEW.................................................................................................8
2.1 INTRODUCTION............................................................................................................................8
2.2 THEORETICAL LITERATURE...........................................................................................................8
2.2.1 Labor-Leisure Theory...........................................................................................................8
2.2.2 Household Production Theory.............................................................................................9
2.2.3 Human Capital Theory.......................................................................................................10
2.2.4 The U-Shape Hypothesis....................................................................................................11
2.3 EMPIRICAL LITERATURE.............................................................................................................11
2.4 SUMMARY OF LITERATURE REVIEW..........................................................................................18
3 CHAPTER THREE: RESEARCH METHODOLOGY...................................................................................19
3.1 INTRODUCTION..........................................................................................................................19
3.2 TARGET POPULATION................................................................................................................19
3.3 DATA COLLECTION.....................................................................................................................19
3.4 METHOD OF DATA ANALYSIS.....................................................................................................19
3.5 MODEL SPECIFICATION..............................................................................................................19
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LIST OF FIGURES
Figure 1; Conceptual framework.....................................................................................................6
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ABBREVIATIONS
FLFP – Female Labour Force Participation
SSA – Sub-Saharan Africa
GDP – Gross Domestic Product
FLFPR – Female Labour Force Participation Rate
ICLS - International Conference of Labour Statisticians
KNBS – Kenya National Bureau of Statistics
EU – European Union
ILO – International Labour Organization
UNDP – United Nations Development Programme
EAMAT – East African Multidisciplinary Advisory Team
WDI – World Development Indicators
OLS – Ordinary Least Squares
GDPpc – Gross Domestic Product Per Capita
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ABSTRACT
This paper contributes by providing new insights into the relationship between female labour
force participation and economic growth in Kenya for over a period of the last fitteen years,
2004-2019. The paper seeks to find answers for the research questions provided by using capital
and educational attainment as the explanatory variables. To examine this relationship, data on
female labour force participation and per capita income will be extracted from the World
Development Indicators database, and the relationship will be examined by using time series data
and E-Views as the method for data analysis. This paper contributes to the literature analyzing
the importance of female labour force participation in economic growth.
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1 CHAPTER ONE: INTRODUCTION
1.1 BACKGROUND TO THE STUDY
Since the 1970s, female labour force participation in developing countries has been rising
( World Bank data ,2017). As economies remain primarily agricultural , research reveals that
female labour force participation in many developing countries remains high. Gaddis and Klasen,
(2014) notes that female labour force participation declines as an economy moves from mainly
an agricultural sector to an industrial one.
Economic growth measured by the change in per capita GDP is the primary measure of the
welfare of an economy. Among the determinants of economic growth, women employment has
become a central issue for maintaining sustainable economic growth in the new global economy.
The labour force participation rate is a measure of the proportion of a country’s working-age
population that engages actively in the labour market, employed plus unemployed who are
actively seeking employment. As the sum of the employed and (searching) unemployed, this
indicator signals the relative size of the supply of labour available to engage in the production of
goods and services. Individuals who are counted as a part of the labour force are those who are
engaged in activities that are included in the System of National Accounts or are available and
searching for work in such activities. Individuals who do not make part of the labour force are
those who are attending an educational institution, engaged in household duties, retired, or infirm
or disabled (and other reasons). Female Labor Force Participation Rate (FLFPR) is the measure
of the female population of a country who are employed or unemployed but actively seeking
employment.
In 2013, the 19th International Conference of Labor Statisticians (ICLS) adopted a broader
definition of work, which encompasses “employment work” but also includes own-use
production work comprising production of goods and services for own final use, unpaid trainee
work, volunteer work, and other forms of work. Countries have been gradually aligning their
labour force surveys with the Resolution of the 19th ICLS, which will impact the measurement
of the labour force and other indicators.
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Female Labor Force Participation has become a topic of discussion for the last few decades. For
quite some time it has been argued that the division of labour between genders in family and the
society gives rise to relations of dominance and subordination between men and women.
Towards the end of the nineteenth century, Engels (1972) argued that it was not possible for
women to achieve equality with men as long as they did not partake in production, instead of
domestic labour. In the last 30-40 years, this argument has been advanced by female scholars
claiming that women emancipation is preconditioned by a “right to be commodified” (Orloff
1993) and the formation of the dual-earner model( Garnick and Meyers 2008).
The participation of women in the labour force has demanded the attention of economist analysts
such as Tansel(2002) and Boserup(2007). female participation in the labour force is key in the
examination of female labour behaviour in the household. According to Killingsworth and
Heckman(1986),” the behaviour of female labour supply has important implications for many
other phenomena are, including fertility, marriage, divorce, the distribution of family earnings
and female-male differentials”.
Female Labor Force Participation has recently become an important element in the determination
of the performance of economic growth in developed and developing countries. there is a strong
connection between FLFP and economic growth, and also between FLFP and aggregate
efficiency. Wherein, FLFP leads to increases in aggregate efficiency as well as the growth and
development in a country. The rising involvement of women in development and the economy is
central to economic growth (World Bank, 1995). Women, therefore, play a significant role in the
reduction of poverty because of their role in assuring the welfare of households. The most widely
studied dimension is the U-Shaped relationship between economic growth and women labour
force participation.
The integration of women in the labour market has been linked to the question of social equality
and women independence. Some economists have justified the increase of women in the labour
force in economic terms: more women in the labour market will increase the number of
taxpayers, thereby ensuring the sustainability of the welfare state (Esping-Andersen et. al 2002).
This justification for the increase in FLFP has connections to the European Union (EU)
concerning the social investment state, which resulted in Lisbon in 2000 in the EU objective to
increase the employment rate for women to more than 60% by 2010.
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The increasing trend toward women participation in jobs in developing countries has drawn both
social and academic attention. However, the participation rate of females in jobs is much lower
than that of men in many countries. FLFP varies greatly across countries, reflecting differences
in economic growth, social norms, education levels, fertility rates and access to childcare and
other supportive services. The relationship between FLFP and these factors is complex.
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. 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.
Despite substantial increases in female labour force participation across the world in the last
century, the global labour force participation for women stands at 49% in 2018, 27 percentage
points below that of men. This percentage has decreased from 51% in 2000. The slower decline
in women’s participation rate than that of men has slightly narrowed the gender gap since 1990.
However, the rate of improvement, which has already been slowing since 2009, is expected to
halt or even reverse during 2018-2021 (ILO 2018). This is in part due to the growing number of
young women in emerging countries that are enrolled in formal education and delaying their
entry to the labour market. The traditional economic rationale for increasing female labour force
participation is that it benefits women directly and society indirectly. However, a recent study on
the allocation of talent and economic growth (Hsieh et al. 2019) demonstrates how increased
female labour force participation has directly boosted aggregate economic growth.
A large and growing body of evidence demonstrates FLFP is directly related to economic
development. Booz & Company estimates that raising female employment to male levels could
have a direct impact on GDP, increasing it by 34 per cent in Egypt, 12 per cent in the United
Arab Emirates, 10 per cent in South Africa, and 9 per cent in Japan, taking into account losses in
economy-wide labour productivity that could occur as new workers entered the labour force.
almost half of women’s productive potential globally is unutilized, compared to 22 per cent of
men’s, according to the International Labor Organization(ILO). In places where women’s paid
work has increased, as in Latin America and the Caribbean, gains have made significant
contributions to overall poverty reduction.
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The Kenyan population is at 47.5 million with a working population of about 25 million. The
female labour force in Kenya is at 48.71% of the total labour force in 2019. The labour market in
Kenya has a wide range of gender gaps that most often favour men: men have lower
unemployment, higher employment as well as waged workers rates than women. Only 29% of
those earning a formal wage are women, leaving a huge percentage of women to work under
vulnerable conditions in the informal economy(Labor market profile of Kenya 2016). In Kenya,
workplaces have been traditionally dominated by men.
In Kenya, just like in many developing nations, FLFP has been steadily on the rise but Kenyan
women still remain disadvantaged economically, socially and politically. Traditional ideas and
roles assigned to girls and women restrict them from taking part in areas that are key in both
economic and social development. These ideas hold women back from contributing to important
development goals; especially in the areas of economic growth, nutrition and food security.
Women in Kenya are underrepresented in decision-making positions. They also have less access
to education at a higher level, land and employment. (Economic Survey, KNBS 2017).
Overview of Female Employment in Kenya
There is a general inequality in access to opportunities between men and women spilling over to
female employment. Social-cultural and economic factors in Kenya have combined to
disadvantage women with respect to employment opportunities. Inequalities between men and
women in assets, earnings, education and employment still dominate the workplace in Kenya.
Men mostly control productive assets, like land and real estate, which prevent women from
seeking bank loans for investments. Men largely control decision making on household
expenditure, thus constraining women’s ability to make strategic investments. These affect
women’s ability to improve their human capital status and hence their advancement (ILO 2004).
Women are more likely to be unemployed than men, with the average income being lower for
women than men, resulting in more women being poor than men. Although the participation rate
for women in the labour force has increased over the years, there is still gender inequality in
employment (UNDP 2002).
Female employment in the modern wage sector accounts for only 30% of the total wage
employment (Republic of Kenya 2002). In rural areas, labour force participation for women is
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much higher than for men. It is estimated that women form a strong 70% of the total labour force
in agriculture. Because of limited opportunities and access to formal employment, the avenue
open to them other than agriculture and domestic work is self-employment in the informal
sector. The 1997 WMS II data shows that for both rural and urban areas, the proportion of
female-headed households at higher incomes is lower than men. This reflects the prevalence of
poverty among female-headed households (UNDP 2002).
A number of factors also make women’s participation in the informal sector important.
Women’s share informal sector employment is proportionately less than that of their male
counterparts, while the participation of females in wage employment has remained low
compared to men’s. The share of women in the labour force also shows that they are
disproportionately concentrated in community, social and personal services. Although the
women’s share in total wage employment has increased to 29.5% in 2001, their share in the
traditionally male-dominated industriesstill remains low, while their share in community, social
and personal services stands at 42.8% (Republic of Kenya, 1998, 1999, 2002).
There are fewer women than men among the regular employees and skilled workers. Women, on
the other hand, outnumber men in the categories of unskilled workers and dominate among
unpaid family workers. Regionally, unemployment levels are higher in both rural and urban
areas for women than for men. The main characteristics of women-owned enterprises in the
informal sector are also important for poverty reduction. They start small, grow slowly, and end
smaller than the men-owned enterprises (McCormick and Mitullah, 1995). They locate more in
the home, rely more on less skilled and unpaid workers, and are less likely to diversify into other
activities. In addition, women’s activities tend to be less remunerative than men’s.
Women face a number of obstacles in entering the business, which mostly condemns them to
low-income occupations. Surveys on the labour force participation in both the formal and
informal sectors show that women are disproportionately concentrated in certain activities, with
limited access to more remunerative enterprises. This is mainly because the choice of occupation
depends on factors like education, training, capital requirements, premises and expected
earnings. These factors combine to restrict women to trade and other service activities in the
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informal sector and bar them from other activities. This exclusion from certain activities limits
their incomes since male-dominated activities are better paid than the female-dominated ones.
The 1999 ILO report also notes that women’s participation in specific sub-sectors and activities
of the informal sector is quite low (ILO/EAMAT 1999). Household budget surveys have shown
that female-headed households are more vulnerable to falling into poverty than the male-headed
ones because of women’s limited access to productive assets and education.
1.2 STATEMENT OF THE PROBLEM
Women constitute half of any country’s population. In most countries, however, women
contribute less than men towards the value of recorded production. The underutilization of
female labour has obvious implications for economic welfare and growth. In kenya women seen
to occupy more of the service sector and low paying jobs. According to previous works and
researches, FLFP has been found out to have a U-shaped relationship with economic
development.
The long term relationship between economic development and FLFP follows a
Ushape( Sinha,1967; Boserup, 1990; and Durand, 1975). The u-hypothesis states that during the
early stages of economic development, FLFP tends to decline due to the structural changes in the
economy from an agricultural to an industrialized economy,and in later stages of development,
FLFP increases as countries undergo the transition into modern economies, fertility rates decline
and female education level increases. Studies have revealed that female labour force
participation is high in low-income countries and high-income countries and relatively low in
middle-income ones. However, Gaddis and Klasen have questioned the U-shaped hypothesis
using cross-country data for the period 1980-2005(2014). They concluded that results are very
sensitive to the data sources and estimation methods used. Most empirical research confirmimg
the U-hypothesis have,however, involved widespread international comparisons of countries.
Time-series evidence for world regional areas have found similar results but are still scarce.A
In Kenya, the relationship between FLFP and economic development has not yet been
extensively studied. In an article by Sustainability (2019) for EU countries, all developing
countries exhibited the U-shaped relationship between FLFP and economic development. The
aim of this paper is to determine the relationship between FLFP and economic development in
Kenya while testing the U-shaped hypothesis.
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