WP-Education & Women Empowerment-Working Paper-N Kamal

7/30/2019 WP-Education & Women Empowerment-Working Paper-N Kamal

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Education and Womens Empowerment in Bangladesh

Nashid Kamal *and K.M Zunaid**

*Professor and Head, Department of Population-Environment

Independent University, Bangladesh

**Graduate student, Sydney

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Abstract:

In Bangladesh the latest BDHS, 2004 finds that only twenty percent women work

for cash. Among them only 48 percent are able to spend their money on their own,the rest are dependant upon spouses or other family members to take joint decisions

on spending. Defining this variable as a measure of empowerment, this analysis

investigates correlates of empowerment using logistic regression analysis. The model

finds that marital status is the most significant predictor of empowerment in

Bangladesh. Unmarried women are six times more likely to be empowered.

Secondary education is another major determinant of empowerment, along with the

womans mobility and decision making scores. The paper recommends

strengthening womens secondary education in Bangladesh and also taking

measures to encourage late marriage for women.

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INTRODUCTION

The participation of women in the labour market in Bangladesh has increased in therecent years. One of the major areas where women have found employment has been thegarment sector. This industry employs around 10 million persons directly or indirectly, of

which ninety percent are women workers. In the 1993-94 BDHS the percentage ofwomen who reported cash income was only 14.4 percent. After the garment industrieswere set up in Bangladesh, in 1996-97 a major increase is documented in the percentageof women employed for cash (Figure 1). However, this percentage fails to increase, infact it decreases to 19.2 percent in 1999-2000 DHS and finally the most recent BDHS(NIPORT, 2005) reports only 17.5 percent women working for cash.

The rise and fall of women cash earners in Bangladesh has been simultaneous with thechanges in the garment industries. After 12 percent growth in the year 2000, economistsnoticed a significant decline in garment exports in the year 2001. More than half of thefactories had no orders. According to Ward et al. (2004) `Declines in garment orders

accelerated rapidly after September 11,2001. By November 2001, two thirds of thefactories had no work orders .The changes in 2004 due to Multi-Fiber Agreement (Green,1998) resulted in throwing 800,000 to 1,000,000 of the workers out of jobs. This isreflected in the national survey where the current number of women workers form only17.5 percent, resulting in only 21 percent increase since 1993-94. Table 1 presents thedata from successive surveys and finds that women with no education and those withtertiary education are the ones who have highest percentages of employment for cash.The case of the uneducated women is self explanatory as they are representatives of thelowest wealth quintile and are forced to work for a living, accepting whatever form ofwork is available. Similarly, the high rates of employment among women with tertiaryeducation is self explanatory. Cash employment statistics for women with primary andsecondary education has either increased insignificantly or has decreased (BDHS,2004-secondary level). Kamal and Haider (2006) have found that in the recent years more andmore women with primary and secondary education have accepted sex work asemployment and in fact their study show that out of other categories, the sex workershave the highest levels of literacy !

The HDI has soared from 147 in 1993 to 138 in 2004. One of the major sources ofcontribution has been the increase in the womens participation in the labour force. Thegarment sector has had a lion share in contributing to the same. However, in other sectorstoo, the government has tried to increase womens participation and has introduced some`womens only jobs to encourage womens participation. For example, in the ministry ofagriculture, some positions for poultry farmers and vegetable croppers have beenreserved for women only. Much earlier in the National Health and Family WelfareMinistry, female family planning workers were recruited to serve as `change agents(Kamal,1994). Both in the government and private sector, primary and secondary schoolteachers have been recruited from amongst women. Laudable NGOs have exemplifiedother kinds of work which were earlier inconceivable as womens work. Road building,guarding tree plantations, microcredit loan for small time enterprise etc have created

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further avenues of employment for women, specially with marginal resources as well aseducational qualifications.

In Bangladesh, educational levels have also increased among women. From a mere 25.8

percent in 1991, the current literacy rate is 43.4 (BBS,2002). It is expected that aseducational levels are enhanced, women will have increased agency as well asnegotiating powers both at home and at the work place. Other covariates ofempowerment for example socioeconomic status, regional variations, religiousaffiliation may also have an effect on the empowerment status of women. In Bangladesh,womens empowerment variable has been included in the DHS surveys since 1993 whenthe number of female workers had just started increasing. Successive surveys havedocumented this variable regarding womens empowerment, recording her ability tospend her own income on her own or by taking joint decisions with husband or otherfamily members. This variable has been considered as major indicator of a womansempowerment. However, there has not been any study which looks at the influence of

womens educational levels on her empowerment status.This article examines the effectof education on womens empowerment in Bangladesh net of other socio-economiccovariates which could determine womens empowerment in Bangladesh.

METHODS AND MATERIALS

The study uses data from the 2004 Bangladesh Demographic and Health Survey (BDHS).This is a two stage nationally representative survey. The 2004 BDHS sample is astratified, multistaged cluster sample consisting of 361 primary sampling units (PSU),122 in the urban area and 239 in the rural area. The PSUs were borrowed from asampling frame created for the 2001 census of Bangladesh and which was termedenumeration areas (EA).All eligible woman aged 10-49, from the selected householdswere eligible respondents for this survey. This resulted in a total of 11440 womencompleted the female questionnaire. Further details are available in Mitra et al (2005).

Among the 11440 women were interviewed in the BDHS,2004, 2282 women reportedworking for cash or cash and kind. This variable was screened for missing data and atotal of 2279 women were used in this present analysis.

In this analysis, logistic regression results are presented using the software SPSS. Thedependant variable here is the answer to the question, whether she is able to spend herincome alone or makes joint decision with husband or any other member of the family.This variable is coded 1 , if she decides alone and 0 otherwise. A total of 2279 workingwomen were selected from the BDHS, 2005 file. Of them, 48% decided alone on thespending and the rest had joint decisions.

In the BDHS, there were many variables available for decision making and for themobility of the woman. Following a technique used earlier by the author (Kamal andSloggett,1993), a Principal Component Analysis (PCA) was conducted to reduce thenumber of variables and a decision making score and a mobility score was constructedfor each woman. The method is explained in details in Appendix 1.The socioeconomic

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index was already calculated in the BDHS, they were regrouped to form two categoriesone termed Low SES and the other High. Other variables such as religion of therespondent, her membership with any NGO, division to which she belonged, hereducational levels, marital status, husbands education and type of residence wereentered as independent ones in the model. These independent variables were tested for

significance using bivariate techniques such as chi -square tests.

RESULTS

The logistic regression was conducted with the dependant variable as the womansdecision regarding spending. It is coded as 1 if she decides alone,0 otherwise (meaningjoint with husband or some other member of the family).The distribution of the variablesconsidered here are presented in Table 2. The final parsimonious logistic regressionmodel is presented in Table 3.

The regression was conducted by using stepwise regression, including and excludingvariables at various stages according to their relative importance in the model (using

loglikelihood values as the decisive indicator). The first variable that was entered was thewomans own education. For this variable, `no education was the reference category andwomen with primary education differed significantly from the reference category,otherwise all other categories were insignificant. Women with primary education showedlower probability of being empowered, compared to women with no education.

As a second variable, mobility score was entered into the model. This variable was highlysignificant as a predictor of empowerment in this model. As mobility increased, womansempowerment increased significantly at all levels.

Decision making score was entered in the next stage. Those with low decision makingscore showed significantly lower levels of empowerment.

Socioeconomic score (SES) was entered into the model. Those in high socioeconomicstatus had 70% higher probability of being empowered.

Division of residence was entered into the model. Women from Rajshahi hadsignificantly lower probability of being empowered. However, the SES variable lost itssignificance. Hence, the interaction term between SES score and Division of residencewas entered into the model. It was found that those from Barisal and high SES showedsignificantly lower probability of being empowered (62% less), compared to those fromDhaka division and in SES score high. The term SES on its own loses its significance,indicating that the interaction term was a more significant predictor variable than SESalone.

Type of residence was entered into the model and its effect was insignificant, same forthe age of the woman. Both these variables were deleted from the model.Religion was entered into the model. Those from Islamic faith had lower probabilities ofbeing empowered, compared to those from `Others religion. They had 62% lowerprobability of being empowered.

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Marital status was now entered into the model. When this variable enters, it producesmost significant changes in the model The odds ratio is highest compared to othervariables. Women who are unmarried have almost 6 times higher probability of beingempowered. It is interesting to note that the role of womans education changes. The

primary group loses its significance and the secondary group is now significantly higherthan the `uneducated reference category. Husbands education was entered in the nextstep, interaction term of husbands education with marital status showed no significance.

DISCUSSIONS AND CONCLUSION

This model finds that a womans marital status is the most significant predictor of herempowerment. Unmarried women are much more likely to spend the income on theirown. The results match another study by the author where only around 300 women fromfour different categories of employment were asked about their control on spending.Rural urban differences and divisional differences could not be studied in the small

sample which was also involved women from the same wealth quintile. In this studywhen many more covariates have been made available and the sample size is nationallyrepresentative, exactly same findings are observed as the earlier small sample study(Kamal and Haider, 2006).

In this BDHS data (NIPORT,2005) used for the analysis the mean age at marriage wasreported to be 14.8 years ! Marriage is universal in Bangladesh. The age at marriage inBangladesh remains unusually low, in spite of various efforts to educate women andensure their workforce participation. In comparison with neighbours like India, where themean age at marriage is currently 20 or with Muslim states such as Pakistan (age 22), themean age at marriage is remarkably low (see paper on Age at marriage). In fact, it hasdeclined slightly since the BDHS 1999-2000 (reported 15). However, on detailedexamination, it is found that amongst those who have attained secondary education orhigher the mean age at marriage is 19.8 years for a cohort currently aged 25-49 whichis very encouraging in the sense that it indicates that education may work in delayingmarriage (NIPORT,2005).

Additionally the proportion of employed women who work for cash only is markedlyhigher for those who have completed secondary education, although the numbers werevery small (ibid). The multivariate analysis used in this paper also finds that aftercontrolling for other covariates, the effect of secondary education is extremely significanton her status of empowerment. This result supports us to strengthen pathways towomens education and also supports the proposition that educated women are morelikely to marry later and also more likely to have higher agency in their lives.

In the current years, aided by various policies and incentives introduced by theGovernment of Bangladesh since 1993, Bangladesh has witnessed a rising rate in girlsenrollment at school. In fact, school attendance is higher for girls compared to boys forages 6-10 and 11-15.For those aged 16-20, school attendance drops sharply from levelsseen at younger ages, and attendance is higher for males than for females (ibid). The

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major reason for school drop out at these ages for girls has been `to get married andpolicy makers have argued how the society could work towards shifting the ages ofmarriage in order for the woman to complete her secondary schooling (Amin et. al,2006).Creation of greater employment opportunities for women, social movement againstthe dowry system, strengthening the value of the girl child in the society and increasing

incentives for completing secondary education for women have been identified as majorpathways towards attaining this goal (ibid).

In support of the girls secondary education, the GOB has already introduced policies forfree education at the secondary level. These policies have been introduced in 2005 andthere will be a time lag for the policies to produce more women with higher thansecondary education, which in turn may produce a later age at marriage and more womenin the employment sector. In the meantime, other correlated factors, for examplepublication of textbooks on time, provision for girls hostel in various remote locations,increasing teachers remuneration, problems with supply of electricity need to be dealtwith.

In support of a social movement against the dowry, the Prime Minister of Bangladesh hasissued a memorandum in late 2003 urging all government officials to work towardsabolishing the practice of dowry. However, reports of dowry deaths are still common andevidence is presented in everyday coverage of the news. Even though the parents realizethe importance of continuing education, Amin et al (2006) explains that `the motives formarrying daughters off at an early age in order to save on dowry costs remain strong.Amin et al. (2006) further state that `Early marriage among females typically results inlarge age differences between spouses because male age at marriage is considerablyhigher. In a setting such as Bangladesh, where age confers authority and status, it isreasonable to argue that large age differences contribute to womens subservient status inconjugal life (2006). In this paper, truly enough, the detailed logistic regression analysis,controlling for other covariates of empowerment finds the `marital status of the womanto be the most significant predictor of her empowerment, unmarried women more atliberty to spend their own income.If we assume that this single variable `whether the woman is allowed to spend her cashincome according to her sole decision completely captures the womans empowermentstatus, then the subservient status of married women is obvious from the resultsrepresenting national level data.

This is further strengthened in the model by a variable which defines `religious affiliationand finds that women from Islamic faith have lower probabilities of being empowered.The `subservient role of women is much publicized in Islam and in this connection, thepolicy makers need to involve the religious leaders in their awareness campaigns. MoreBCC needs to be designed to support the working womans role and encourage her to bea valued partner. Bangladesh has already overcome vehement opposition fromfundamentalists who have been rampant against some womens employment schemesintroduced by various NGOs in the early 90s () . However, with years of fruitful BCCand consistent campaigns these barriers have now been removed. It is therefore hoped,

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that the womens status within the family and her working women image can also beestablished in Bangladesh in a similar manner.

In this connection, the media has a very important role in portraying the woman to anaverage viewer. More attention on promoting working women images through dramas,

advertisements, interviews and feature films is recommended. Many women have beensuccessful entrepreneurs and their successes and feats need to be shared nationwide inbuilding up positive images not only for women from the elite group but also inportraying how women can contribute from grassroots level. Creation of female iconsby highlighting success of garment worker, female worker in agriculture, politics, healthcare etc are also some ways in which the traditional gender roles need to be addressed. AsBasu (1996) writes `direct intervention from the mass media, for example, as is alreadybeing fostered by the rapid globalization of the economy and the culture in this region(even illiterate villagers now know about the benefits of Ariel washing powder, whicheven educated Indians had not heard a few years ago) can be appropriately put into thecontext of Bangladesh as well.

The employment of female workers in the garment sector has already created anenhanced image for working women, further employment opportunities need to beintroduced. As garment work is facing challenges of post multifibre agreement, furtherareas of female employment need to be evolved. The Government should consideradditional employment facilities for women in areas such as drug industries , processedfood and the like. Apart from training for traditional skills of sewing and cooking, thegovernment can think of developing other skills for women. One organization titled Sathihas had positive results in training women for computers and car driving in BangladeshWard et al.(2004).These experiences may be replicated. The women workers in the healthsector have also been a successful addition to the work force (Kamal,1994). Theircontribution should be acknowledged and institutes should be set up for further training,which should prepare them for jobs in the local as well as international markets .Womenfrom Phillipines , Indonesia, Srilanka and India have additional qualifications of knowingthe English language and other languages apart from their skill training. The GOB hasalready planned to set up computer and language centres in various subdivisions.Womens participation, enrollment and continuation needs to be supported in thisdirection. Additionally, introduction ofcreche facilities, maternal and paternal leave,flexi hours are some of the ways in which countries like Singapore and Malaysia haveencouraged their women to face the challenges of the job market.

Bangladesh is essentially a Muslim society and freedom of movement outside thehomestead is of special interest because of its association with purdah which may be adeterrent from women seeking jobs outside their homestead. This paper finds that womenwho are more mobile ie they are able to shop alone, go outside village alone, visit healthcentre alone without being accompanied by a male relative; have higher odds of beingempowered. The odds of being empowered increases with her degree of mobility. AsCleland et al. (1996) explains, these variables and what they capture may `also have aprofound influence on mentality and outlook by severely circumscribing interactions with

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the outside world and exposure to new ideas and models of behaviour. Decision makingalso emerges as an important predictor of empowerment.

The education of the woman, her autonomy and her decision making role all add up inthe same direction. As Basu (1996) argues `..female schooling does seem to increase

several aspects of female autonomy which (again, besides being good in themselves) arealso useful ways to strengthen the role of women, in this case her levels of empowerment.

The data finds that women from Barisal division, who are from high socioeconomicsubgroup have lower probabilities of empowerment compared to women from Dhakadivision and same SES status. This indicates that being from higher socioeconomic groupdoes not indicate that the woman will be more empowered. There exists divisionaldifferences, perhaps to be captured further by other variables such as level of femaleliteracy in the division, number of women in the work force, employment opportunitiesfor women in that division, the period of exposure to womens full time employment,religiosity of the community.(variables at the community level). The urbanization in

Bangladesh can be called the `primate type where growth has been centred around onecity and division alone (Afsar,2000). By year 2020 Dhaka city is expected to be thesecond most populous city in the world, Tokyo being the first (). All the industrial andinfrastructural growth has been centered around Dhaka city. This paper indicates thatthere is a strong need for decentralization, with special attention given to Barisaldivision, which is closest to the Bay of Bengal and most frequently suffers theconsequences of environmental disasters.

The major implication from this paper is therefore that female education is a necessarygoal, and it needs to be pushed even more vigorously to cross the threshold of secondaryeducation beyond which the net effects on female autonomy are all positive.

Finally, as secondary education is being strengthened, Bangladesh would like to see morewomen speak out like Rupali, that they are able to sustain themselves from their ownwork. Rupali has worked ever since her parents moved to Dhaka from their nativevillage. As a child she collected wood and paper, she started garments work at 10, but

lost her job when the foreign inspector came. Instead of school, she returned to flower

sales in the streets, until her parents married her at a young age and she returned back to

garments work. Her wages improved her situation at home with her husband, because `I

did not have to rely on my husband because I had my own income. I could live with that.

Husbands do not give any importance if we do not work (Ward et al. 2004).

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Fig. 1 Distribut ion of women in cash

employment in Bangladesh DHS,1993-

2004.

14.4

25.5

19.217.5

0

5

10

15

20

25

30

1993-94 1996-97 1999-00 2004

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Table 1: Distribution of women in employment by their educational levels,

Bangladesh DHS 1993,1996-7,1999-00,2004.

Education % in cash employment

1993 None

PrimarySecondaryTertiary

16.4

12.57.925.4

Total 14.4

1996-1997 NonePrimarySecondaryTertiary

26.120.515.632.4

Total 23.2

1999-2000 NonePrimarySecondaryTertiary

23.916.613.827.7

Total 19.8

2004 NonePrimarySecondaryTertiary

25.917.312.922.3

Total 20.0

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Table 2: Distribution of women who earn cash for a living according to various

covariates of empowerment, Bangladesh DHS 2004.Variable Frequency Percent

Spends her own incomeAlone

Jointly with others

Her education

NonePrimarySecondaryHigher

Mobility scoreNoneLowModerateHigh

Decision making scoreLowHigh

SES*LowHigh

Type of residenceRuralUrban

Geographical locationDhakaChittagongRajshahiKhulnaBarisalSylhet

Marital statusUnmarriedMarried

ReligionIslamOthers

1095

1186

1157595376153

786577446472

11581123

1373908

1361920

542322667374187189

4071874

1997284

48

52

50.726.116.56.

34.525.319.620.7

50.849.2

60.040.0

59.740.3

23.814.129.216.48.28.3

17.882.2

87.512.5

*From the original SES the first three values poorest, second and middle were merged to form the group`low SES andthe other two groups fourth and richest were merged to form `high SES.

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Table 3 Logistic regression of Empowerment of woman on various covariates,

BDHS 2004

Variables Odds ratio Significance

Womans education

Nonea

PrimarySecondaryHigher

Womans mobility score

Nonea

LowModerateHigh

Womans decision making score

Lowa

High

SES

Lowa

High

Geographical location (division)

Dhaka a

BarisalChittagongKhulnaRajshahiSylhet

Religion

Islama

Others

Marital status

Marrieda

Unmarried

Interaction term

Barisal*High SESDhaka*High SESa

1.00.831

1.408.945

1.001.2991.4932.324

1.003.613

1.001.223

1.001.0291.006.962.616

1.207

.3871.000

1.005.731

.3881.00

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Appendix APrincipal Component Analysis (PCA) is a statistical technique which can be applied to a setof highly correlated variables in order to construct a smaller set of uncorrelated components.These components can be used in place of the original variables in the interests of efficiencyand parsimony. The technique identifies groups of variables which are highly correlated witheach other, and constructs components based on these groups. The method can extract asmany components as there are variables. That does not serve the purpose of variablereduction, and only components which explain a good proportion of overall variance and havean intuitive interpretation, are usually extracted for subsequent use in regression analysis(Kamal and Sloggett,1993).Variables that could be possible indicators of decision making and mobility status weresubjected to two separate PCAs and the results are presented in Table A.1 and A. 2Table A. 1 Component scores following PCA with varimax rotation for decision makingvariables*Variables CommunalityDecisions on womans health careDecisions on large hh purchasesDecisions on purchases for daily needDecisions on visits to relativesDecision on menu everydayDecision on FP mattersDecision on child health care

.664.764.607.712.068.002.665A weighted average was constructed for each woman, using the communalities as weights.The variable was then regrouped into four quartiles. In the final regression model , this wasregrouped into two categories, low decision making, and highTable A.2 Component scores following PCA with varimax rotation for mobility variables*Variables CommunalityGoes shopping aloneGoes outside village aloneGoes to health centre alone

.496.587.568These three variables from Table A.2 were used to construct the mobility index which wasregrouped into two categories 0,1 for low mobility, 2 for moderate and 3 for high. This wasentered as an independent variable in the final regression model.

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REFERENCES

Afsar, R. (2000)Rural Urban Migration in Bangladesh The University Press Limited,Bangladesh

Amin, S. N. Selim and N.Kamal (2006) `Causes and Consequences of early marriage inBangladesh Population Council, Dhaka, Bangladesh

Basu, A. (1996) `Girls Schooling, Autonomy and Fertility Change: What do these wordsmean in South Asia?, in R. Jeffery and A. Basu (eds) Girls Schooling, WomensAutonomy and Fertility Change in South Asia, pp. 48-71.Sage Publications, India.

Cleland, J. ; N. Kamal and A. Sloggett (1996) `Links between Fertility Regulation andthe Schooling and Autonomy of Women in Bangladesh, in R. Jeffery and A. Basu (eds)Girls Schooling, Womens Autonomy and Fertility Change in South Asia, pp. 205-

217.Sage Publications, India.

Green, C. (1998) `The Asia connection: The US-Caribbean apparel circuit and a newmodel of industrial relations inLatin American Research Review 33:7-47.

Kamal, N. (1994) `Role of Government Family Planning Workers and Health Centres asdeterminants of contraceptive use in Bangladesh', Asia-Pacific Population Journal. 9 :59-65.

Kamal, N. and Haider, S. (2006) `Role of education in enabling womens empowerment inBangladesh working paper in Centre for Health, Population and Development(HPD),Independent University, Bangladesh (IUB).

Kamal, N. and A. Sloggett (1993) `The influence of religiosity, mobility and decisionmaking on contraceptive use in . Secondary Analysis of BFS 1989 data. NationalInstitute of Population Research & Training (NIPORT),Dhaka, Bangladesh.

-------------------------------(1996)`The effects of female family planning workers on use ofmodern contraception in Bangladesh, Asia-Pacific Population Journal 11:15-25.

National Institute of Population Research and Training (NIPORT) (2005).BangladeshDemographic and Health Survey 2005. Dhaka and Calverton: NIPORT,MA, and ORCMacro

Ward, Kathryn, F. Rahman, A.K.M.S.Islam,R. Akhter and N. Kamal (2004). ` TheEffects of Global Economic Restructuring in BangladeshCritical Sociology 30 (1): 63-102.

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WP-Education & Women Empowerment-Working Paper-N Kamal