Religion and labour force participation in Nigeria: is there any inequality among women?
IntroductionSince Beijing Declaration in 1995, emphasis has been placed on equal involvement of both men and women in all spheres of life including moneymaking activities. Although several measures have been implemented all over the world to enhance women's participation and ensure their access to labour market, women's participation in the labour market has not been commensurate with wages, job stability and social protection. It has been observed with dismay, that occupational apartheids and wage discrimination still affect women who are often exposed to the vagaries of unpaid work as compared to men (1). Addressing this debilitating factor of women's economic disparity remains unalloyed focus of the Millennium Development Goals (MDGs) in most countries of the world. This was also included in the Sustainable Development Goals by the UN in August 2015 as goal 5 "Achieve gender equality and empower all women and girls". However, the barriers which alienate women from participating significantly in economic activities are deeply rooted in traditional beliefs, customs and low level of female involvement in decision making. This act has contributed immensely to the prolongation of robust gender disparity among developing countries. Inequality has been identified as a clog in the wheel of development which hampers social cohesion, trust and also marginalize the poor including the exclusion of women from political involvement especially in Africa (2). This inequality in the labour force participation is created by the colonial systems of education which was designed to meet the manpower needs that estranged women from economic and educational opportunities (3). In the same vein, a previous study (4) has posited that men are better than women in the economic arena, as a result of women's segregation from access to education and wealth-creating assets. This elimination is borne out of the fact that women lack required capital to participate in large scale economic activities. Also, inadequate skills and information prevent their full initiation into the labour market, thereby creating vicious circle of female poverty which is common in practically all sectors of the Nigerian economy. It has also been established that unequal participation in labour force costs women nearly twice the total GDP of Africa and the Middle East (5). The gender inequality in the labour force participation has also been argued to be responsible for the gap in the growth disparities of different counties in the world (6,7). The restriction of women's' access to job opportunities slow economic development and their capability in decision making as obtainable in developing countries like Nigeria (8).
It was also revealed that the nature of women empowerment depends on the income employment away from the home--particularly in non-familial organisations; fruitful and remunerative jobs in the formal rather than in the informal economy and regular and full-time jobs that are permanent and secure. There is mounting evidence that women's ability to fully enjoy human rights--indeed, even to demand such rights --is integrally linked to their economic empowerment. The ability to take such decisions requires a sense of personal autonomy, which develops in tandem with the knowledge that women can provide for themselves and their children. Their sense of personhood is sparked by motherhood and nurtured by participation in organized groups, but fundamentally depends on having incomes of their own" (9).
To most of the women in Nigeria, the means of support remains uncertain and economic empowerment is beyond their control due to the rising cost of caring and lack of social services that can alleviate their burden. Coupled with this is their religious belief that debar them from standing up against their husbands, partners and in-laws. This does not allow them to assert their rights on issues relating to child bearing, child spacing, sexual matters and to resist intimate partner violence. Study of women's sexual control within conjugal union in Lagos metropolitan city in Nigeria discovered that only few women could negotiate safe sex practices with their husbands/partners (10). Women empowerment through participation in economic activities does not only have consequences for women, it also has effect on the wider economy. Proper value and reward of women's work both at home and away are the key to poverty alleviation and prosperity for all (11). They estimated that worldwide, an additional US$1.6 trillion in output could be generated by reducing the gap in employment between women and men It is therefore pertinent at this juncture to ask the following questions: Does religion influence female inequality in labour force participation in Nigeria?, are there any regional differences in female labour force participation in Nigeria? are there any occupational differences among religious women?.
While studies have shown the effect of religion on female labour force in different countries and among Muslim countries (H'madoun 2010), there are no significant studies on Christian women regarding labour participation in predominant Christian countries. Unfortunately, existing studies on religion and female labour force have often merged all the countries together and have not been able to specify the effect of different religious groups on the labour force participation in each of the countries (12,13,14,15). Also in Nigeria, most of the studies were based on determinants of labour force participation (16,17,18a,18b) labour force and fertility (19 20). The above studies reveal that there is little or nothing documented on religion and the inequality in the female labour force participation. This study therefore, examines the influence of religion on female inequality in labour force participation in Nigeria using demographic data.
Methodology
This study was based on both quantitative and qualitative review of data and documents. For the quantitative data, Nigeria Demographic and Health Survey (NDHS) data sets were used. Three data sets (2003, 2008 & 2013) were used for this study. This is to provide a longitudinal trend for the past fifteen years. The data sets for women in age 1549 years were downloaded after approval from Measures DHS, these represent the active population (See Table 1). The data were weighted for national representation.
From the data set, variables related to the study were identified: these are religion, highest level of education, regions, age at first marriage, place of residence, current marital status, partners' education, total number of children (CEB), number of living children and proximate variables for participation in decision making (who has final say on your health?, who has final say on large purchases? and who has final say on family visits?). For labour force participation, three variables were used. These are; type of earnings, (this was recoded into two values 1 paid and 2 unpaid), work away or at home and whom the respondent work for (this was also recoded into self-employed and employee.)?
Three levels of analysis were used in this paper, the univariate analysis is used to explain the socio-demographic variables, while bivariate relationships between the religion, sociodemographic variables of women and participation in labour force were examined using the cross tabulations and Chi-square test for significant association. Binary logistic regression was then used to estimate pseudo maximum likelihood of logistic regression models in order to examine the combined effect of religion on the indicators of labour force. Three models were developed based on the variables of labour participation that were identified in the data. These models were also adjusted with the co-found variables (CEB, partners' education, number of living children, current marital status, age at first marriage, participation in decision making, level of education and place of residence). The models were developed sequentially so that the effect of different combinations of factors on the labour force participation could be examined in detail. Other secondary data used are the employment, unemployment and labour force participation rate that were derived from National Bureau of Statistics and International Labour Organisation.
Results
The percentage distribution in Table 1 reveals that Muslim women remain the highest in all the three data sets even with the pooled data while other Christian women increased from 17.1% in 2003 to 40.6% in 2013. Women with earnings increased from 77.2% in 2008 to 89.5% in 2013, while there was a slight proportional decrease among women working at home.
From Table 2, Whom the women worked for (employee) increased from 57.8% in 2003 to 68.5% in 2013 in urban area while it decreased from 42.2% in 2003 to 31.5% in 2013 in rural area. It is good to note that whom the women worked for increased with the level of education in 2008 and 2013 even with the pooled data while women with higher education are less likely to work away from home in 2008 (10.4%) and 2013 (11.9%). The types of earning (cash) decreased with the level of education for pooled data while there was no consistent pattern in all the three data sets with the level of education. The wealth index reveals that more than two thirds of the women who are employees were in good status in all the three data sets. Except for 2003 all the three variables for labour participation increased with age up to 34 years before it started decreasing even with the pooled data. It is important to note that there is a significant relationship between the place of residence, wealth index, age at first marriage, CEB and whom she worked for (employee) P<.001 in all the three data sets. Table 3 shows significant inverse relationship between level of education and types of earnings with the pooled data while the reverse was the case for whom she worked with (employee) when the data were pooled together. The higher the level of education the lower the cash earnings among women in the study area. This may not be unlikely with the level of unemployment and religious beliefs of the respondents.
Respondents in age group 20-34years are those that received highest cash earnings when the data were pooled together while those whose age at first marriage were between 16-20years received highest cash earnings. The pooled data also confirmed the significant relationship between CEB and labour force participation, this implies that the higher the total number of children ever born the lower the tendency from working away from home and receiving cash earnings in the study area.
The binary logistic regression as indicated in table 4 revealed the indicators of labour force participation and religion. The objective is to test the relationship between religion and labour force participation using the three different variables (Whom she worked for, where she worked and types of earnings). Whom she worked for (employee) was significant with Catholic women and other Christian women in 2003 ([beta]= 7.375, P<.001, [beta]= 8.189, P<.001) and 2008 ([beta]= 3.412, P<.001, [beta]= 3.281, P<.001) respectively even with the adjusted data. While Islam was significant only with the adjusted data in 2008 ([beta] = 0.461, P<.005). It was also established in the study that Islam was significantly related with where she worked (away from home) in 2003 ([beta]=.214, P <.001) and 2008 ([beta]=.164, P <.001) while it was only significant with other Christians in 2008 ([beta]=.667, P <.001).
Types of earning was significant with Islam in 2008 for both adjusted ([beta]=4.215, P <.001) and unadjusted ([beta]=4.670, P <.001) while it was only significant with Catholic with the adjusted data in 2008 ([beta]=.341, P <.005). However, in relation to the pooled data (See Table 5), whom she worked for (employee) was significantly related to all the religious groups with the unadjusted data but only significant with Islam when the data were adjusted. Women who worked away from home were significant for all the three religions even when adjusted with the co-found variables while the types of earning was only significant with Islam for unadjusted data.
Discussion
The objective of this study is to examine whether there is inequality in the female labour force participations among different religious groups. Three models were developed to test the hypothesis. Regional variations in the female labour force participation was established (Figure 1), North-West has the highest women working at home followed by North-east in 2003 and 2008 while the North-central had the lowest in 2003 and South-east in 2008 respectively. Among female employees, South-east has the highest in 2003 and 2013 while North-central had the highest in 2008.
The variation in these labour force participation will not be unconnected with the level of education of women in these regions. The two regions with the highest number of women working at home have the highest number of women with no education (North-west 69.4%, North-east 64.4% (21). Women employment position enhancing their ability over income, resources and gives them voice in family decision-making. Studies confirmed that women who earn wages have negotiating power within the household because their earnings affect their well-being at their threat point (22,23). The economic status of the household head may also determine female participation in the labour market and higher household economic needs drive women to participate in the economic activities. Study conducted in Pakistan emphasized the level of partner's education, employment status, patriarchal family structures and values as important factors for the female participation in the labour force (24). The participation in the labour force was one of the reasons why women in the south-west Nigerian are more empowered economically when compared with other women in the country (25).
A study reveals that modern roles are emerging as a result of increasing urbanization and improved technologies, more women are holding more consumer purchasing power. Women now have improved status and earning power than ever before alongside juggling responsibilities of managing a household and raising children which enable them to make decisions in the household. Female occupation and religion (Figure 2) show that Muslim women are more likely not to engage in any economic activities in the country in all the three data sets, while other Christians and Catholic women tended to engage in professional/ technical/managerial jobs when compared with other religions. The binary logistic regression also confirms that Catholic and other Christian women were more likely to engage in paid employments when compared with Muslim women. The Purdah system practiced by Muslims is a likely factor that prevents women from engaging in professional jobs. The 'Purdah' system also prohibits women from holding noticeable social roles. This makes Muslims women not able to participate in visible work force when compared with women in other religions. Studies also confirmed that any country or region where there are higher proportions of Muslim, women may likely have lower labour force participation rate (8;26). Where women participation is very low especially in the Northwest and Northeast, they normally use the traditional Islamic law the Shari'a, as the reason for the discrimination against women.
With respect to commercial interactions, rights, and obligations, there are no differences between women and men by Shari'a law while there are barriers to women's economic activities through Shari' a laws that govern the family (27,28). For instance, a woman must have the permission of her husband before leaving the house. This restricts women's participation in tangible economic activities. A situation like this predicts violence as husbands will be operating through threat, deceptions and socio-cultural expectations as a result of the economic disadvantage. Social norms and institutions also play a vital role in the women participation in either paid or unpaid work. These norms include early marriage, son's preference, inheritances and culturally accepted Draconian laws that affect women and girl child. This can also be the reason for the inverse relationship between level of education and types of earning among women as being observed in the study area. While increase in the level of education is supposed to improve the employment and earning outcomes the reverse is the case in the study area. It was also established in the study that Muslim women are more likely to work at home and involved in sales activities. They deal in petty trading which may not be enough to sustain them, just to keep their souls and bodies together. In Asia, majority of Muslim women in formal jobs are single and unmarried which by cultural practice are expected to turn the majority of the earnings to their parents (29). Increase in the female labour force participation will lead to economic growth and also reduce the household poverty. The engagement of women in non-household work varies with their age, and age at first marriage in this study. This may be as a result of delay in age at marriage. The increase in the labour force participation among women is as a result of delay in age at marriage. It is 'marriage, not childbirth, which is unsuited with women's employment outside the home (30,31,32,33,34). It is of the people's opinion that delayed age at marriage will enhance the women's labour force participation and increase years of schooling and eventually reduce the family size.
[FIGURE 1 OMITTED]
[FIGURE 2 OMITTED]
Recommendation and Conclusion
The study confirms the influence of religion on female labour force participation. The belief system has impacted on the work entry and promotes occupational inequality among women. Despite the decrease in unpaid work, inequalities still exist among women of different religious groups in Nigeria. While the United Nations have renewed their commitment towards achieving gender equality and empowerment for all women and girls as indicated in the goal 5 of the Sustainable Development Goals. It is clear that there are under currents that still widen the gender gap not only between males and females but also within the women fold. The socio-cultural factors that are fuelling the inequality need to be addressed especially among developing nations in Asian and African continents. Although, there is little or no policy on interventions to prevent discrimination against women from social norms and institution in Nigeria, there is need to promote female education especially among Muslims. This will empower and emancipate them from the trap of poverty and give them a voice in decision making. It will also improve the human capital development and increase the economic growth of the nation.
Acknowledgements
The author appreciates MEASUREDHS for permission to access their dataset that was used in this study.
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Oluwagbemiga E. Adeyem [1], Kolawole E Odusina [1] andAkinwole E Akintoye [2]
Dept of Demography & Social Statistics, Federal University, Oye-Ekiti [1]; Dept of Sociology, University of Ibadan [2]
* For correspondence: Email: [email protected]; Phone: 08037118931
Table 1
Survey Year Female (Sample Size)
2003 7,620
2008 33,385
2013 38,948
Table 1: Percentage Distribution of Selected Variables.
Variables 2003 2008 2013 Pooled Data
N= 7620 N=33,385 = 38,948
% % %
Religion
Catholic 15.3 10.8 10.5 11.0
Other Christians 17.1 40.9 40.6 40.1
Islam 47.3 46.5 47.9 42.6
Traditionalist 1.7 1.6 1.9 5.1
Total 100 100 100 100
Types of Earning
Not Paid/ in Kind 17.5 22.8 10.5 16.2
Cash 82.5 77.2 89.5 83.8
Total 100 100 100 100
Where She Worked
At Home 41.3 41.7 41.6
Away from Home 58.7 58.3 58.4
Total 100 100 100
Whom she worked for
Employee 12.8 11.3 11.8 11.7
Self-employed 87.2 88.7 88.2 88.3
Total 100 100 100 100
Table 2: Selected Socio-Demographic Variables of Women and Labour
Force Participation in Nigeria (2003-2013)
Variables Whom she Worked for Where she worked
(Employee) (Away from Home)
2003 2008 2013 2003 2008 2013
Place of
Residence
Urban 57.8 58.6 68.5 42.9 32.9
Rural 42.2 41.4 31.5 57.1 67.1
Total 100 100 100 100 100
[X.sup.2]PValue .000 .000 .000 .000 .000
Highest Level
of Education
No Education 6.5 9.2 4.6 29.9 27.9
Primary 13.9 11.5 7.5 28.5 25.6
Secondary 40.5 37.5 39.1 31.5 34.6
Higher 39.6 41.8 48.8 10.4 11.9
Total 100 100 100 100 100
[X.sup.2]PValue .000 .000 .000 .000 .000
Wealth Index
Poor 11.8 11.9 6.5 38.8 37.5
Middle 10.0 12.3 12.1 14.8 19.9
Richer 22.0 25.5 26.8 18.4 20.4
Richest 56.2 50.2 54,7 28.0 22.4
Total 100 100 100 100 100
[X.sup.2]PValue .,000 .000 .000 .000 .000
Age-group
15-24 36.5 29.1 28.5 26.2 24.2
25-34 34.1 37.7 36.4 34.7 37.0
35-44 21.3 25.0 28.9 27.3 27.0
45+ 8.2 8.2 10.1 11.9 11.8
Total 100 100 100 100.0 100
[X.sup.2]PValue .000 .000 .000 .032 .418
Age at First
Marriage
< 15 years 18.9 17.9 12.8 31.7 28.3
16-20 34.1 27.2 27.7 40.1 39.6
21-25 26.5 31.4 32.3 20.1 21.8
26+ 20.4 23.8 27.2 8.0 10.3
Total 100 100 100 100 100
[X.sup.2]PValue .000 .000 .000 .000 .000
CEB
0-4 79.1 74.1 34.7 64.5 74.1
5-9 18.9 24.1 33.6 31.0 24.1
10+ 2.0 1.7 31.6 4.5 1.7
Total 100 100 100 100 100
[X.sup.2]PValue .000 .000 .000 .000 .000
Variables Types of Earning
(Cash)
2003 2008 2013
Place of
Residence
Urban 26.1 34.2 32.1
Rural 73.9 65.8 67.9
Total 100 100 100
[X.sup.2]PValue .46 .000 .062
Highest Level
of Education
No Education 35.7 41.0 35.3
Primary 36.3 22.3 31.0
Secondary 26.7 26.0 29.2
Higher 1.2 9.9 4.4
Total 100 100 100
[X.sup.2]PValue .047 .000 .000
Wealth Index
Poor 63.2 39.4 44.4
Middle 16.1 19.0 25.7
Richer 12.6 20.3 17.8
Richest 8.1 21.3 12.1
Total 100 100 100
[X.sup.2]PValue .071 .000 .000
Age-group
15-24 36.5 22.0 22.1
25-34 34.1 38.5 35.1
35-44 21.3 27.7 27.1
45+ 8.2 11.8 13.6
Total 100 100 100
[X.sup.2]PValue .000 .000 .000
Age at First
Marriage
< 15 years 35.9 39.5 35.4
16-20 44.5 35.4 40.2
21-25 15.2 17.0 17.5
26+ 4.4 8.1 7.0
Total 100 100 100
[X.sup.2]PValue .090 .001 .435
CEB
0-4 62.5 74.1 55.3
5-9 32.4 24.1 39.4
10+ 5.1 1.7 5.3
Total 100 100 100
[X.sup.2]PValue .006 .000 .000
Table 3: Selected Socio-Demographic Variables of Women and Labour
Force Participation in Nigeria (Pooled Data).
Variables Whom she Worked Where she worked Types of
for (Employee) (Away from Home) Earning (Cash)
Place of
Residence
Urban 64.0 34.6 25.7
Rural 36.0 65.4 74.3
Total 100 100 100
[X.sup.2]PValue .000 .000 .000
Highest Level
of Education
No Education 6.6 28.3 40.9
Primary 9.9 26.1 30.0
Secondary 38.7 34.0 25.6
Higher 44.7 11.6 3.5
Total 100 100 100
[X.sup.2]PValue .000 .000 .000
Wealth Index
Poor 9.1 37.8 49.8
Middle 12.0 19.0 24.2
Richer 25.8 20.0 16.0
Richest 53.0 23.0 10.0
Total 100 100 100
[X.sup.2]PValue .000 .000 .152
Age-group
15-24 29.5 24.6 21.5
25-34 36.7 36.6 34.9
35-44 24.7 27.1 29.5
45+ 12.1 11.8 14.1
Total 100 100 100
[X.sup.2]PValue .000 .109 .000
Age at First
Marriage
< 15 years 15.3 28.9 36.7
16-20 28.1 39.7 40.3
21-25 31.4 21.5 16.6
26+ 25.0 9.9 6.4
Total 100 100 100
[X.sup.2]PValue .000 .13
CEB
0-4 83.0 65.6 55.3
5-9 15.0 30.7 39.4
10+ 1.1 3.7 5.3
Total 100 100 100
[X.sup.2]PValue .000 .000 .000
Table 4: Logistics Regression of Religion and Labour Force
Participation (2003-2013).
Variables Unadjusted)
Whom She Worked for (Employee)
2003 2008 2013
Religion
Catholic 7.375 ** 3.412 ** .899
Other Christians 8.189 ** 3.281 ** .840
Islam 2.107 .778 ..829
Traditionalist RC
Where she worked (Away from Home)
Catholic 1.78 1.212
Other Christians 1.198 .965
Islam .214 ** .069
Traditionalist RC
Types of Earning
Catholic 1.574 .747 .473
Other Christians 1.403 1.507 .395
Islam 1.292 4.215 ** .482
Traditionalist RC
Variables Adjusted
Whom She Worked for (Employee)
2003 2008 2013
Religion
Catholic .785 .636 8.556 **
Other Christians .785 .520 8.627 **
Islam .796 .461 * 1.975
Traditionalist
Where she worked (Away from Home)
Catholic 1.014 .879
Other Christians 1.006 .667 **
Islam .246 ** .164 **
Traditionalist
Types of Earning
Catholic 1.771 .341 * .878
Other Christians 1.799 .626 .419
Islam 1.491 4..670 ** .538
Traditionalist
** P<.001 * P<.005
Table 5: Logistics Regression of Religion and Labour Force
Participation (Pool Data).
Variables Unadjusted)
Whom She Where she Types of
for Worked worked (Away Earning
(Employee) from Home)
Religion
Catholic 3.482 ** 4.441 * .858
Other Christians 3.462 ** 3.725 * .788
Islam .799 ** .647 ** .728 **
Traditionalist RC
Variables Adjusted
Whom She Where She Types of
Worked for worked (Away Earning
(Employee) from Home)
Religion
Catholic .894 3.293 ** 1.220
Other Christians .788 2.633 ** .920
Islam .725 ** .639 ** 1.257
Traditionalist
** P<.001 * P<.005
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| Author: | Adeyem, Oluwagbemiga E.; Odusina, Kolawole E.; Akintoye, Akinwole E. |
|---|---|
| Publication: | African Journal of Reproductive Health |
| Article Type: | Report |
| Geographic Code: | 6NIGR |
| Date: | Sep 1, 2016 |
| Words: | 5147 |
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