Agenda 2030’s Sustainable Development Goals’ Impact on Female Labor Force

An Evaluation


Scientific Study, 2020

21 Pages


Excerpt

Table of contents

ABSTRACT

1. INTRODUCTION

2. LITERATURE REVIEW

3. DATA METHODOLOGY
3.1. DATA
3.2. DATA ANALYSIS

4. EMPIRICAL RESULTS AND DISCUSSION
4.1. DESCRIPTIVE STATISTICS
4.2. RESULT ANALYSIS

5. CONCLUSION AND POLICY IMPLICATIONS

REFERENCES

APPENDIX 1

ABSTRACT

The progress made regarding the implementation of SDGs specifically the objective five regarding gender equality is not known. The purpose of this study is to evaluate, and compare the performance made by low middle income, and upp middle income countries regarding increasing female labor force participation, from 2015 to 2019. Data related to 43 low middle income, and 59 upp middle income were collected.Using paired sample t-test, repeated measures ANOVA and post hoc test, the findings reveals that low middle income countries made statistically significant progress regarding increasing female labor force participation from 2015 to 2019. However, the findings show also that upper middle income countries did not make statistically significant progress regarding increasing female labor force participation between 2015 to 2019. The conclusion is that some countries are implementing the agenda 2030 on Sustainable Development Goals. The study shows finally that the COVID-19 pandemic narrowed employment as there is no statisticaly significant difference between 2018 and 2019. The implementation of the agenda 2030 on SDGs is a world wide concerns. All contries should engage in gender equality,and no country should lag behind as the study demonstrated it for upp middle countries. A clear mechanism of evaluating the implementation of the Agenda 2030 shoud extend at all objectives to find deviation at take corrective measures.

Keys Words: Female, Labor, participation, Evalution, Sustainable, Development.

1. INTRODUCTION

The world is engaged in the process of sustainable development trough the adoption of the agenda 2030 on Sustainable Development Goals (SDGs). Ending poverty, ending hunger, improving health and well-being, improving quality education, ending gender based discrimination, creating decent work and economic growth, reducing inequality,etc. are among the agenda 2030’s objectives. After five years of implementation of the agenda, some questions may be asked. Is the world making process in achivieving the objectives of the agenda? Did economic growth increase since the implementation of the agenda?Is there any progress in gender work discrimination?Did female vulnerable employment declin since the implementation of the agenda? Such questions remain without answer, since no performance evaluation has been made to identify achievements from 2015 to 2019. The main benefit of evaluating the performance reached is to allow adjusting the initial objectives. The evaluation allows detecting any deviation from the initial plan, and correction of the problem is done to improve performance.

The existing literature supports gender discrimination that exists all over the world especially in work place. There remain gross inequalities in work and wages, lots of unpaid women’s work such as child care and domestic work, and discrimination in public decision-making (UNDP, 2015). International Labor Force (2016) indicated that inequality between women and men persists in global labour markets, regarding opportunities, treatment and outcomes. We hypothesize that there cannot be a sustainable development without ending gender inequality in all its forms, as laid out by the UN sustainability agenda with SDGs five earmarked for addressing gender inequality concerns. Gender equality has been mentioned in Sustainable Development Goals as one of the pillars that will contribute to the development of the world.

Gender work discrimination leads to underinvesting in the human capital that countries need to assure sustainability. The World Economic Forum (2018) indicated that if current rates continue in the future, the overall global gender gap will close in 61 years in Western Europe, 70 years in South Asia, 74 years in Latin America and the Caribbean, 135 years in Sub-Saharan Africa, 124 years in Eastern Europe and Central Asia, 153 years in the Middle East and North Africa, 171 years in East Asia and the Pacific, and 165 years in North America. In this regard, the sustainable development goals assume importance, especially, SDGs5, which is envisaged to achieve gender equality by 2030.

The benefit of reducing gender inequality has been demonstrated by reaches conducted previously. The debate on the impact of gender equality on economic growth has attracted many researchers, and many found a positive link between gender equality and economic growth. For instance, Pierre, Jan and Piritta (2015) concluded that raising female labour force participation with a package of pro-growth and pro-women policies could boost the growth rate by about two percentage points over time in India. Laura, Esther and Mery (2018) concluded that, despite the negative effects of high fertility in women on economic growth, greater access to secondary education and the labor market in conditions of equality, and active political participation have significant effects on economic growth in 127 countries analyzed. Jinyoung, Jong-Wha and Kwanho (2016) found that improving gender equality can contribute significantly to economic growth by changing females’ time allocation and promoting accumulation of human capital. Moreover their results showed that if gender inequality is completely removed, aggregate income will be about 6.6% and 14.5% higher than the benchmark economy after one and two generations, respectively, while corresponding per capita income will be higher by 30.6% and 71.1% in a hypothetical ‘gender-equality achieved economy’ in the Asian context. John, et al., (2010) indicated that better-educated women can undertake higher-value economic activity. Increasing gender equality can make labour markets more competitive.

The progress made regarding the implementation of SDGs specifically the objective five regarding gender equality is not known specifically the the achievements regarding the implementation of SDGs objective five on gender equality. The purpose of this study is to fill this gap by evaluating, and comparing performance made by low middle income (LMI), and upp middle income (UMI) countries regarding increasing female labor force participation (FLFP), from 2015 to 2019.This topic is an underexplored area of research. The present paper is an attempt in this direction and it is expected that this study will be useful for scholars engaged in research on the critical aspects of gender inequality and overall inequalities that persist within and among the poor countries in particular. From a policy angle, the findings emerge from the study would help policy makers to adopt appropriate corrective measures to mitigate gender-based discrimination. An improvement in gender equality status in reality would lead to a rise in earnings of women, besides increase in employment opportunities, political representation and better access to resources, etc. The result being that the reduction in gender inequalities in opportunities and earnings will have positive impact on economic growth and per-capita income of the poor in low middle income (LMI), and upper middle income (UMI) countries.

2. LITERATURE REVIEW

This literature review shows the benefit the world can get when woman is well considered. Women are less consided than men in workplace. According to International Labour Organization (2018) when women have chance to be employed, they are confined in work with low-quality jobs in vulnerable conditions. According to Derek, Amy and Farooq (2015), the different goals and targets of the sustainable goals will constitute different degrees of challenge and ambition for different countries depending on their present state of development and the other national circumstances. So when it comes to implementation, different countries will need to give different degrees of attention and efforts to the different goals and targets, depending on where they stand regarding to them at present, their differentiated responsibilities and their different capabilities and resources. According to the statement, there is a gap of knowing who will achieve what in the proposed SDGs by 2030. Whether the developed and developing countries will fulfill the targeted SDGs, especially, those goals related to inclusive development is a moot question. Equality and Human Rights Commission (2017) stated that the gender pay gap is a longstanding phenomenon and its causes are complex. Some of the reasons given are that social pressures and norms that influence gender roles and often shape the types of occupations and career paths which men and women follow, and therefore their level of pay. In addition, women are also more likely than men to work part-time and to take time out from their careers for family reasons.

Globally, it is held that sustainable development cannot be achieved without eradicating gender inequality. The World Economic Report (2015) confirmed a positive correlation between gender equality and GDP per capita, the level of competitiveness and human development. The report recognized that correlation does not prove causality, but it is consistent with the theory and growing evidence that empowering women means a more efficient use of a nation’s human capital available and that reducing gender inequality enhances productivity and economic growth. There is a mutual reinforcement between gender equality and sustainable development (United Nations, 2014). The Council of Economic Advisers (2019) indicated that increasing female labor force participation rates creates an opportunity for countries to increase the size of their workforce and achieve additional economic growth. Sher (2018) affirmed that the relationship between women’s participation in the labor force and development is complex and reflects changes in the pattern of economic growth, educational attainment, fertility rates, social norms, and other factors. Emmanuel (2019) after the analysis of 21 African countries between 1991 and 2017, concluded that a ten percent increase in female labor participation increases on average gross domestic product by 2.7 percent. Female labor participation in the service sector had the largest impact on economic growth. Ayfer and Tanses (2017) after analyzing data from 1990 to 2015 for Turkey found a strong correlation between the rate of female labor force participation in industry and services sectors and economic development.

Literature also shows ambiguous relationship between female labor force participation and economic growth. Ewa (2014), used data from 162 countries over the period 1990-2012, and found U-shaped relationship between female labor force participation and economic growth, with high cross-country variability. Angela (2015) using econometric analysis confirmed the hypothesis of a ‘feminisation U’, and indicated that it is not sufficient in the short-term to rely on the equalizing effects of economic growth to rise the entry of women into the labour force. Elizabeth (2018) after examining 139 countries found that the female labor participation has a positive impact on economic growth, in developing countries, and in sub-Saharan Africa countries only. Leanne (2016) explained the feminization U theory claiming that women’s labor force participation drops during the initial phase of industrialization and rises once a certain level of development is reached. Buhari and Mürsel (2017) supported the feminization U theory by indicating that as the economy grows, women have easier and better jobs and are therefore encouraged to be more economically active, which in turn, increases women's participation in production activities. They also indicated the factors affecting women's participation in the labor force such as education level, family and community structure, number of children and the level of economic development of the country. Accordingly, women with many children will not participate in labor force.

The World Bank (2020) defines the cleary low middle income, upp middle income, and female labor force participation. Low middle income refers to economies whose 2010’s gross national income per capita was between $1,006 and $3,975. Upp middle income refers to countries whose 2010’s gross national income per capita was between $3,976 and $12,275. Female labor force participation rate is the proportion of the female population ages 15 and older that is economically active: all female people who supply labor for the production of services and good for market during a specified period.

3. DATA METHODOLOGY

3.1. DATA

To investigate the performance made regarding female labor force participation (FLFP), secondary data from 2015 to 2019 were collected from Word Bank Development Indicator for low middle income, and upp middle income countries. Descriptive statistics were presented. Normality test was performed using Shapiro test to decide on parametric or nonparametric test to use. The list of the countries analyzed is give in appendix one.

3.2. DATA ANALYSIS

Collected data were analyzed using R software, and JASP. Normality test were performed to analyze whether data are normally distributed. Shapiro-Wilk normality test was used to test the null hypothesis of data normal distribution . To test the equality of FLFP in low middle income (LMI), and upper middle income (UMI) coutries, the Mann Whitney Wilcoxon test was used. The test was used because data are not normally distributed. Paired sample t-test was performed to compare the means. The aim of this test is to evaluate if the mean median of FLFP is stat istically different from one year to another. In case of progress made in implementing the agenda 2030 on SDGs, the compared means must be statistically different. If the means are equal it means that there is no improvement. Normal distribution of the difference was tested for compared years. Paired sample t-test was first performed to identify the the significance of the progress made from 2015 to 2019. Wilcoxon rank test was used because difference distribution (2019-2015) is not normally distributed.

However, paired sample t-test does not indicate where dose differeces occurred between 2015 to 2019. With the paired t-test, the null hypothesis (Ho) stated that the pairwise difference between the two groups is zero. Repeated measures ANOVA was combined with post hoc tests to investigate during which year significant progress was made regarding female labor force participation.In other words, post hoc tests identify where significant group differeces occurred. The null hypothesis tested is that there is no significant difference between the means of all the groups. Specifically, post hot test compares FLFP for each year to the following yeaars to find differences in mean, for instance it compares 2015 to 2016,2017,2018 and 2019.

4. EMPIRICAL RESULTS AND DISCUSSION

4.1. DESCRIPTIVE STATISTICS

Descriptives statistics allow to understand the data under analysis. Central tendency was analysed by calculating the mean, and the median. To measure the variabily of the data, the standard deviation, the variance, the minimum and maximum variables, and the skewness were calculated. The median is considered to be the best measure of centrality in case of skewed data (George, 2005). The analysis shows data are skewed as skewness is greather than .5. The mean and median are also different.

Table 1: Descriptive statistics of female labor force participation 2015

Abbildung in dieser Leseprobe nicht enthalten

Source: Author’s computation

Table 2: Descriptive statistics of female labor force participation 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Author’s computation

Table 3: Descriptive statistics of female labor force participation 2017

Abbildung in dieser Leseprobe nicht enthalten

Source: Author’s computation

Table 4: Descriptive statistics of female labor force participation 2018

Abbildung in dieser Leseprobe nicht enthalten

Source: Author’s computation

Table 5: Descriptive statistics of female labor force participation 2019

Abbildung in dieser Leseprobe nicht enthalten

Source: Author’s computation

4.2. RESULT ANALYSIS

4.2.1. Comparing low income and upper income countries

The normality test performed using Shapiro-Wilk normality test indicates that data are not normally distributed with p <.001. The result is not suprising because data are sewed, and there is difference between mean, and median.That implies parametric tests cannot be used in the analysis. Nonparametric tests are suitbe.

Tableau 6: Normality test results

Source: Author’s computation

To test the equality of median FLFP in low income, and upper middle income, Wilcoxon signed rank test was performed. The resut indicates that there is statistically significant difference between low middle income (LMI), and upper middle income. (UMI) The same test confirms that the median of LMI is greater than UMI countries (V = 5253, p =1) for all years. UMI countries are expected to increase female labor force participation (FLFP) to reduce working gender gap.

Tableau 7: Wilcoxon signed rank test results

Source: Author’s computation

4.2.2. Analysing female labor force participation in low income and upper income countries

To analyse progress made regarding increasing female labor force participation, paired samples t-test was performed using Wilcoxon signed rank test. The resut of the comparison of 2015 to 2019 on low middle income goup shows that the effect of the implementation of the agenda 2030 is significant in 2019 (median = 46.5 sd= 5.99) compared to 2015 (median = 46.3 sd =6.39); (W =104, p < .001).

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Details

Title
Agenda 2030’s Sustainable Development Goals’ Impact on Female Labor Force
Subtitle
An Evaluation
Author
Year
2020
Pages
21
Catalog Number
V918690
ISBN (eBook)
9783346227942
ISBN (Book)
9783346227959
Language
English
Tags
Female Labor participation Evaluation Sustainable Development, Agenda2030
Quote paper
Master Antoine Niyungeko (Author), 2020, Agenda 2030’s Sustainable Development Goals’ Impact on Female Labor Force, Munich, GRIN Verlag, https://www.grin.com/document/918690

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