European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org
RURAL WOMEN’S CONTRIBUTION IN FAMILY BUDGET: A CASE STUDY OF DISTRICT LAYYAH Ms. Shakila Bano M.Phil Economics, B.Z. university, Multan Muhammad Zahir Faridi Assistant professor of economics, B. Z. University, Multan, Pakistan Furrukh Bashir (corresponding author) Ph.D Scholar of Economics, University of the Punjab, Lahore, Pakistan. INTRODUCTION Most of the rural areas in Pakistan are economically depressed and rural women are, in fact, one of the poorest populations in Pakistan because rural women earn substantially less than rural men. The development of a rural area in developing countries is of considerable interest among many scholars. Many of the studies however have focused on the urban informal sector. Only few studies have focused on the role of women in the contribution of household budget in rural areas. The aim of this work is to investigate rural women's contribution in economic activities, and how they contribute to the household economy. In Pakistan, female labour force participation is very low. Women’s fragile social status is a real obstacle to the pivot role she plays in human and economic development. So there is a need to give the equal access of women and men to education, skills, and improvement of professional aptitudes. The incidence of poverty among women is higher than men. Women are largely neglected in the social, economic, political and legal spheres. Women’s access to money-earning activities is an important means to improve their position (Polachek and Robst, 1997). Children‘s well being, particularly of daughters is positively affected by the mother’s access to income-generating opportunities (Thomas, 1990; Haddad and Haddinot, 1995). How much women are contributing in their household’s incomes and GDP is still unexplored, along with determinants of their contribution. Informal sector employment is generally a larger source of employment for women than for men in the developing world. Most informal workers are deprived of secure work, workers’ benefits and social protection. The factors such as: educational, technical employment opportunities and vocational opportunities availed by women, wage rate, availability of credit, state of technology in the country and its implementation and cultural attitudes towards working women greatly affect the contribution of women in economic activity. Socioeconomic background of working women is the main determinant of female labour force participation at household level. Husband’s employment status also affects their contribution. Women’s productive work and level of development are positively related. The participation of women has critical importance in determining the rates of savings, investment and production. Empirical evidences suggest that women are the most disadvantaged creature in society. The provision of sufficient opportunities to female workers is associated to improve their productivity and their children enjoy more income by achieving higher educational level, low mortality rates and better health and they seem to be valued within the household. The issue of woman’s recognition as a productive member is the issue of recent times and the development of women is the issue of concern to Government. So there is a need of accurate data about women workers. This study would discuss certain factors that are responsible for women’s contribution in household budget. The rest of the paper is organized as follows: section II describes the review of literature. Section III discusses the data and methodological issues. Results are produced in section IV, while conclusions and policy recommendations are given in section V. II. Literature Review The purpose of this chapter is to review some studies related to women’s contribution in economic activities and female labor force participation. Bell (1974) estimated the contribution of working women in family income. The study found that median income of the families who held some employment had income 23 percent higher than in families with nonworking wives. Employed women contributed only 16 percent of total family. The study concluded that professional and managerial workers contributed more than the service workers.
European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org Cancian et al. (1991a) focused on changes in the level and distribution of earnings of men and women and their impacts on the distribution of family income among married couples, and among all households. The wives’ income increases substantially due to increase in the working married women and due to increase in the weakly income. The study concluded that without wives’ earnings, 9.2 percent of families would have been below the poverty line, and 26.4 percent would have income between one and two times of the poverty line. Nasreen et al. (1994) analyzed the role of rural women in decision making in various family affairs. Samples were drawn randomly. The chi square test was used. The study concluded that a large majority of the respondents believed that their husbands play a dominant role in making important family decisions concerning family affairs and they were satisfied with their position as housewives. The study concluded that education, caste, income, family type (nuclear or joint) and age of the respondents had no significant association with the decision making process in family affairs. A large majority of the respondents agreed that they were satisfied with their position as housewives. Of 115 respondents, only eight were found to be the working ladies. Azid, et al. (2001) estimated the degree of female participation in cottage industry of Pakistan by collected the primary set of data. The study analyzed the economic behavior of female workers involved in the business of embroidery in Multan. The study concluded that female members were engaged in economic activity in informal labor market due to poverty. The study concluded that number of children less than 5 years of age distance from market and Purdah played a significant role in the participation of female in work. Cameron et al. (2001) estimated the determinants of married women in five countries, Philpines, Korea, Sirilanka, and Thialand by using Probit model. The results showed that determinants of women labor force in Asia vary across countries. Woman’s education was positively related with the probability of working. In Korea, only 3 percent of women were likely to participate in economic activities, but the earned income of women as percentage of men was high in Korea. But in Philippines, women were 25 percent more likely to participate in economic activities. The study indicated that although in Korea, women got high wage rate, yet they participated less in economic activities. This showed the fact that household’s bargaining power is important in determining women’s labor force participation in Asian countries. Coady et al. (2001) analyzed the effects of Community program on participation of women in China by using the probit regression model. Multivariate regression Technique was used to see the effect of program on income level of participants and non participants. The results indicated that program increased total household income by 27 percent in treatment villages and the probability of participation by 25 percent. The probability to join the labor market and education had positive relationship. Naqvi and Shahnaz (2002) examined the effects of various demographic, socioeconomic and human capitals’ related factors on women participation in economic activities by using multi logit and probit models on data by Pakistan Integrated Household Survey 1998-99. The results indicated that women who were older, better educated, head of the household, or come from smaller, better off urban families were more empowered to take employment decisions on their own. The study concluded that women living in nuclear families and in rural areas were less likely to participate in the economic activities. Sultana and Kamal (2002) estimated the impact of Open and Distance Learning to empower rural women in Bangladesh. The study concluded that most of the rural poor women were not involved in marketable production activities due to illiteracy and lack of access to modern technology. The study concluded that the attitude, skill and knowledge level of the rural poor women, ability to prepare budget, ability to plan, ability to collect business-related information, ability to open network, ability to assess right and wrong of the rural women were enhanced after the training and they were able to contribute more in their family budget. Khan et al. (2005) investigated the contribution of women and children involved in home-based work in family income by using the primary set of data. They also analyzed the impact of increased earnings of women on household nutrition, health and education by using Binary logistic model. Household size was positively and significantly related with the decision of household to engage in home based work, while the living condition index had shown a negative significant relationship with the decision of household to engage in home based work. Khan and Khan (2006) estimated how much women were struggling for family survival in urban informal sector by applying the OLS model on 937 observations. It was found that women as head of household, women’s education, and ownership of assets by woman, family size, household poverty, women’s marital status (married women), women living in nuclear families and loan availed by the household had positive effect on contribution of women in their household budget. The study concluded that due to increase in the age of the woman, first of all the contribution increases and then decreases. Married women and women living in nuclear families contributed more to household budget. However, number of adult males in the household had decreased the volume of contribution of
European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org woman. The husband’s employment status would be a critical variable for a woman’s contribution in household budget. Khan and Khan (2007) highlighted the characteristics of informally employed women and their contribution in household budget by applying the OLS model. The results showed that woman’s education, women as head of household, ownership of assets by women had positive effect on their contribution. The study concluded that in the informal employment, married women contributed more towards family budget. The age of the woman had a non linear effect on their contribution. Khan and Khan (2009) highlighted the factors that influence the decision of married women to participate in labor force activities by applying the Probit model on 3911 observations. The study concluded that women’s age, household poverty, family size, women as head of the household, women’s education, number of girls (5-15 years), number of daughters over 15 years of age, husband’s unemployment and rural locality had a significant positive affect on labor force participation of married women. Ownership of assets by the household, household’s per capita income, nuclear family status of household, number of infants, number of sons over 15 years of age, and husband’s education negatively affect labor force participation of married women. Poverty was found to be the major determinant of the labor force participation of married women. Poverty was found to be the major determinant of the labor force participation of married women. The study concluded that increasing the income and productivity of working mothers had trickle down effects on the reduction of household poverty. Harkness (2010) analyzed the contribution of women’s employment and earnings to household income inequality. The source of the data was Luxembourg Income Survey (LIS) for 17 industrialized countries with countries grouped into three ‘regime’ types according to Esping-Anderson’s (1990) welfare state typology. The study concluded that for all countries, raising female Employment and earning, and reducing employment inequality between women would had a substantial impact on reducing household income inequality. The female earnings were an important factor in reducing household income inequality in all countries. Among couples, female earnings shares were largest in Denmark (34%). Pay was much more unevenly distributed for wives than husbands everywhere. III. DATA, METHODOLOGY AND SELECTION OF VARIABLES A. Profile of the Study Area and collection of data The area of our study is Layyah. Layyah was founded in 1550 A.D by Kmal Khan Mirani Baloch. There are three Tehsils of Layyah namely: Layyah, Choubara and Karor Lal Esan. The famous towns of district Layyah are Fateh Pur, Chock Azam and Kot Sultan. The area of district Layyah is 6291 km². Sariaki is the local language of district Layyah, while Urdu and English are just the medium of education. Major crops of Layyah are wheat, gram, cotton, and sugarcane. The women in the villages are highly involved in cultivation, harvesting, sowing of seeds, cotton picking, and rearing of animals. Agriculture sector is the main source of their livelihood. The women in these areas are very hardworking but they are getting very low wages. Even children in these areas are doing different tasks of child labor. Five villages of Layyah are selected namely Khokhar Abad, Kot Sultan, Sirai, Jaman Shah, and Ladhiana. These five villages of district Layyah are situated at North, East, West, South and center of the city. B. Model Specification Different researchers have used different models to estimate the contribution of women in their family budget. For example, Mehrotra and Biggeri (2002), Khan and Khan (2006), and Khan and Khan (2007) have used the OLS technique to see the effect of various factors on the women’s contribution to their family budget. We have also used the OLS model to determine the contribution of rural women in their family budget. The following multiple regression model is: Y= α + ß1X1 + ß2 X2 + ……. + ßkXk + ui The coefficients ß1… ßk are called partial regression coefficients. We have made three models. Our first model explains how the contribution of rural woman is affected by the core variables such as: age of the woman, family size, number of children, poverty status etc. WCB = f [AGEW,AGSQ,FSIZ,NCHI.MARD,FST,OWRP,FTMI, WMEX, WMWA, REDU,DRAT,POVS,HDMI,WHOH] ……(1) In our second model, some new important variables such as work experience of the women, education of the women, number of earners in the family, children between different age groups etc. are included. WCB=f[WEXP,EDUW,EXSQ,NEAR,WMWA,WMEX,HWHO,DRAT,POVS, REDU, CHAA,CHAB,CHAC,FST,OWRP,FTMI,WORH,WHOH] …..(2)
European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org Our third model explains how various education levels of females affects their contribution in family budget. The functional form of the model is: WCB=[FSIZ,MARD,NCHI,FST,NEAR,POVS,OWRP,REDU,WMWA, WMEX,FTMIPEDU,SEDU, BEDU,HED,WRKS,WSPN,WHOH] …….. C. Description of the Variables The description of the variables is as follow. Variables Definitions Dependent variable WCB (woman contribution to family budget) Ratio of woman income to total family income Independent variables AGEW (woman’s age) Her age in years AGSQ (woman’s age square) Square of woman’s age FSIZ(family size) Number of family members NCHI(number of children) Total number of children MARD (marital status) If she is married ,0 otherwise FST (family set up) If nuclear , ‘0’ otherwise OWRP(outside work permission) If she is permitted to work outside, ‘0’ otherwise FTMI (family’s total monthly income) Family’s total monthly income in rupees WMEX (woman’s monthly expenditures) Amount of money which she spends on herself WMWA (woman’s monthly wage ) Woman’s monthly wage in rupees REDU ( restrictions to achieve education) If restrictions to achieve education, ‘0’otherwise Ratio of number of dependents in the family to DRAT (Dependency ratio) total members of the family The people living below the poverty line are considered poor, ‘0’otherwise, where poverty POVS (poverty status) line is 1276 HDMI (Head’s monthly income) Monthly income of head of household in rupees If head of household is woman, ‘0’otherwise WHOH (woman as head of household) WEXP(work experience) Woman’s work experience ( in years) EXSQ (experience square) Square of woman’s work experience) NEAR(number of earners) Total numbers of earners in the family EDUW (woman’s education) Woman’s education in completed years HWHO (husband’s working hours) Working hours of husband If female has children between the age of zero CHAA (category A for child age) and three years, ‘0’ otherwise If female has children between the age of four CHAB(category B for child age) to seven years If female has children between the age of seven CHAC (category C for child age) to eleven years WORH (working hours) Woman’s working hours If Woman have education between 0 and 5 PEDU (primary education) years, ‘0’ otherwise. If Woman have education between 5 and 12 SEDU (secondary education) years ‘0’ otherwise. If Woman have education between 12 to 14 BEDU years ‘0’ otherwise If Woman have education between 14 years and HED (Higher education) up to M.Phil, ‘0’ otherwise. WRKS ( work satisfaction) If she is satisfied from her work, ‘0’ otherwise If she can spend most part of her income on WSPN (woman’s spending on herself) herself , ‘0’ otherwise After the data is collected, it is organized to put it into the computer to obtain the results. OLS model was applied to get the results by using the E-Views.
European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org IV. RURAL WOMEN CONTRIBUTION IN FAMILY BUDGET: RESULTS AND DISCUSSION Estimation of the OLS Models (i). Econometrics Estimates of the OLS Model 1 Table 1 explains the results of the OLS model 1 of rural women contribution in family budget. The results show the estimated coefficients and their standard errors. The two tailed t – statistics has been applied. 1%, 5 %, and 10 % level of significance are used. The intercept term is negative and insignificant which shows that intercept value is less valued. The intercept shows the average effect of the all omitted variables which affect the dependent variable. Age of the woman has a positive relationship with the contribution of women in family budget, while the coefficient of AGSQ (age square) is negative and is significant. Increase in age increases the family size, awareness and experience. Older women have also more and relaxed social contacts as compared to younger women. Our results are consistent with Naqvi and Shahnaz (2002), La Ferrrara (2002), Khan and Khan (2006), Khan and Khan (2007), and Khan and Khan (2009). Our results are also consistent with the life cycle hypothesis presented by Ando and Modigilani (1963). The variable family size has negative relationship with the contribution of woman in family budget larger family size increases the labor supply. So due to surplus labor supply, financial status of the family increases and there is less need for the woman to contribute in family budget. In our analysis, family size has no significant relationship with the contribution of women in economic activities. This shows the fact that in rural areas; contribution of woman doesn’t depend upon whether the family size is large or small. It is found during the survey that some women, having larger family size or smaller family size, are contributing towards their family budget. So the contribution of rural women in their family budget depends upon various other factors. Our results match with the findings of (Lokshin et al. (2000): Coady (2001). The coefficient of number of children is negative and insignificant. The effect of the number of the children on the contribution of women depends upon the age of the children and also on the activities of the children. For infants, the explanation may be that women are involved in child caring activities so that their contribution remains low because the birth child reduces time for economic activities and increases the work load at home (see also, Kozel and Alderman 1989, 1990). For school age children, the contribution of rural women in family budget and the number of children is negatively related because the income of woman is substituted by children’s income as the children between these ages are usually involved in economic activities. Our results are consistent with Levine and Moock (1984), Alderman and Chistie (1991), Duncan et al. (1993). The insignificant results show that number of children is not very important to determine the contribution of woman in family budget because the area where we have collected data is purely rural. And the people in rural areas doesn’t care that woman is over burdened. Due to poverty, women in rural areas are highly involved both in child caring and economic activities. But for rich families, the opposite is true. Another variable is marital status which affects the contribution of women. In our study, the coefficient of MARD is negative and insignificant. This result shows that if the marital status increases by one unit, contribution of woman in family budget decreases by .049453 rupees. Our results are consistent with the findings of Naqvi and Shahnaz (2002). Due to increasing responsibilities of married women, they are less likely to contribute in economic activities. The insignificant results show that in rural area under study married as well as single women are contributing in economic activities, so marital status is less important for rural women to participate in economic activities. Another variable which affects the contribution of women in their family budget is family set up. Women belonging to nuclear families contribute more as the coefficient of FST is positive and insignificant. The reason is interpreted in this sense that women living in joint family system face different constraints imposed by her in –laws because usually in this type of family, mother – in – law has the authority in decision making regarding income, employment and expenditures. So women’s decision to participate in economic activities is strongly affected by their coresidents. Earning members in the family are also more in combined family system, so women contribute less. On the other hand, in nuclear family system; husband is the only source of income, so woman contributes more. Our findings are consistent with the findings of Sather and Desai (1996). In our analysis, we find heterogeneous characteristics. So family set up has no any significant relationship with the contribution of rural women in household budget. The other important variable is outside work permission which affects the contribution of women. Women that are permitted to work outside the home contribute more as compared to women who have no permission to go outside the home for work. The significant results show that permission to women to work outside is the main factor which increases the contribution of women in family budget because now they can easily go to cities for work and earn high wages.
European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org The coefficients of FTMI and WMEX are negative and insignificant. It means that due to increase in family‘s total monthly income, contribution of women in family budget decreases because families having more income need less contribution of women in economic activities. Rich families don’t force women to participate in economic activities. But the coefficient of women’s monthly expenditures doesn’t make sense. Theoretically, women having more expenditure should contribute more. Our results are inconsistent with the theory. Our results show that women having more monthly expenditures contribute less. This depends upon family structure. As woman belonging to rich families spend more income on herself because she has good standard of living and at the same time she has no need to participate in economic activities because the jobs in rural areas are of low standard and husband’s income is enough for survival of the family. On the other hand, the women belonging to poor families have less income to spend on theirselves; they usually contribute more in income earning activities for the survival of their family. In our analysis, these two variables are not important to affect the contribution of rural women. Woman’s monthly wage has a positive effect on the contribution of woman. The coefficient of WMWA is positive and highly significant. This is the fact that woman earning more monthly wage rate are able to contribute more in family budget. This is the very important variable which affects the contribution of women in family budget. The coefficient shows that if the woman’s monthly wage increases by one rupee, the contribution of woman in family budget increases by 1.73 rupees, holding the effect of other variables constant. Restrictions to achieve education are the main cause of low earning and similarly women’s contribution decreases. Naqvi and Shahnaz (2002) estimated that more educated women are more likely to participate in labor market. Sackey (2005) estimated that female education exerted a positive impact on female labor market decision. The coefficient of REDU shows that if the restrictions to achieve education increases by 1 unit then on the average holding the effect of other variable constant, the contribution of women decreases by .034118 rupees. The highly significant result shows that this variable is very important to determine the contribution of women in family budget because uneducated women have low productivity and they achieve low wages. Mostly in the areas, where we have collected data, women are involved in agriculture sector, in rearing of animals, and in making cot sewing material. These types of activities give very low earnings. Empirical evidences suggest that education increases the productivity, skills, and job opportunities for workers. For example, Naqvi and Shahnaz (2002), Sackey (2005) supported this view. The variable DRAT which is the ratio of number of dependents to total family members is positive and insignificant. It means that if the dependency ratio increases by 1 unit, on the average contribution of women to family budget increase by .0601 rupees. Household poverty status is the most important variable that affects the distribution of women’s time to labor market and non market work. In our analysis, we have used the household’s poverty status as the binary variable. For this purpose, we have used the national poverty line. The families living below the national poverty line are considered poor and the women belonging to these families contribute more in their family budget. The positive results show that burden of poverty forces women to work in economic activities and generate income for their family. Our results are matched with Azid et al. (2001), Khan and Khan (2006), Khan and Khan (2009). Another variables included in our analysis are monthly income of the head of the household. The coefficient of HDMI is positive which shows that as the head’s monthly income increases by 1 rupee the contribution of women in family budget decreases by 1.76 rupees, holding the effect of other variables constant. The explanation may be that as the head of household provides most of the needs of the family there is less need for the women to contribute in family budget. Women as head of household contribute more in their family budget because the whole responsibility of the family is on the women. The female- heads decisions are different from male heads decisions because the female headed households are more vulnerable to poverty than male headed household. As a result there is more need for women to contribute in their family budget. The positive coefficient of WHOH shows that women as head of household contribute more in their family budget as compared to women where the head of household is male. Our positive results are consistent with Khan and Khan (2006), Khan and Khan (2007). Table 1 .OLS results for the rural women contribution in family budget Std. Variable Coefficient Error t-Statistic -0.017 Constant 0.093677 -0.1907 0.008*** AGEW 0.004335 1.860017 -8.32EAGSQ 05*** 4.85E-05 -1.717841 -0.004 FSIZ 0.003999 -1.114717 -0.004 NCHI 0.004952 -0.970062 -0.049 MARD 0.032076 -1.541737
European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org 0.017 FST 0.021281 0.814785 0.051* OWRP 0.020794 2.45895 -4.93E-07 FTMI 5.21E-07 -0.947468 -8.02E-06 WMEX 6.24E-06 -1.286162 1.73E-05* WMWA 2.38E-06 7.259921 -0.034*** REDU 0.020137 -1.694273 0.060 DRAT 0.049258 1.21993 0.074* POVS 0.022924 3.257359 -1.67E-06 HDMI 1.08E-06 -1.547313 0.059 WHOH 0.047538 1.243563 No of observations 200 R-squared 0.412928 Adjusted R-squared 0.412928 Prob 0.000 *significant at 1percent,**significant at 5 percent and *** significant at 10 percent (ii). Econometrics estimates of the OLS model 2 The econometrics estimates of OLS model 2 are given in table 2. In this model, we have estimated the contribution of rural women in their family budget by including some new explanatory variables, such as education of women, her work experience, number of earners in the family, different categories of the child age, and working hours of the women. The results of some variables such as family size, family set up, outside work permission, poverty status, dependency ratio, women’s monthly wage rate, women as head of household, and restrictions to achieve education, are almost the same as we have estimated them in our previous model. The coefficient of woman’s experience (WEXP) is positive and significant but the coefficient of experience square (EXSQ) is negative and insignificant. The positive coefficient of working experience of women shows that if the woman’s experience increases by 1 year, on the average the contribution of woman increases by .006172 rupees, holding the effect of other variables constant. Experience increases women’s productivity and skill. Due to specialization in their work, they become expert by doing the same job again and again, and they give more output and achieve high wage rate and are able to contribute more in family income. The significant results show that woman’s experience is the most important variable which affects the contribution of women in family budget because experienced women are better trained and they work more efficiently as compared to inexperienced women. Our positive results are also consistent with Mehrotra and Biggeri (2002) although their results are non-significant. Whereas, the coefficient of EXSQ gives the explanation that as the women becomes older, she becomes physically weak although she has better experience. We have included the variable, the education of woman in our model, her completed years of education. As education is the one of the major individual characteristics of the women. We have found a positive and significant relationship between the number of years of woman’s education and her contribution in family budget. The variable EDUW is significant. This shows that as the education of rural woman increases by 1 year, contribution of rural woman in family budget increases by .005271 rupees. Our results show that education increases the productivity by increasing the skill through training and they contribute more in their family budget. Another explanation may be that education increases women’s efficiency in household tasks and reduces the time in home production and increases the time in market activities. So our results justify the theory. Our results are consistent with the findings of Naqvi and Shahnaz (2002), Khan and Khan (2006), Khan and Khan (2009), and Faridi et al. (2009). The variable NEAR (number of earners in the family) has negative coefficient and is insignificant. As the earning members in the family are more, family is well off and there is less need for women to involve and participate in economic activities. We have found a negative and significant relationship between the woman’s monthly expenditures and her contribution in family budget. The woman belonging to richer families and living in rural areas spend more income on herself but contributes less in economic activities because the job in rural areas are of low standard and rich families don’t permit woman to work in these activities. So woman with more monthly expenditures contributes less in economic activities. We have found a positive relationship between women’s contribution in family budget and the husband’s working hours. The reason may be that as the working hours of husband increase, he spends less time at home and more time in work outside the home, so woman feels herself free to participate in income earning activities. . The number of children between the various age groups also differently affects the contribution of rural women in their family budget. The coefficient of CHAA (presence of children between the age group of 0 to 3 years) and CHAC (presence of children between the age group of 7 to 11 years) are negative and insignificant. The negative
European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org relationship supports the fact that children under the age of 3 years need care of their mothers, while the children between the ages of 7 to 11 years are involved in different tasks of child labor, so woman contributes less. Child category CHAB (presence of children within the age group of 4 to 7 years) have shown positive and insignificant relationship with the contribution of women in family budget. The reason may be that children within this age group are school going and the do not need care of their mothers, so women have time to contribute in income generating activities. In our study these variables are not very important to affect the contribution of women in income generating activities because during the collection of data, it is observed that most of the women are illiterate and belong to poor families, so they do not care for their children and are involved in various economic activities. The women’s contribution in their family budget is also greatly affected by the family’s total monthly income. So the coefficient of family total monthly income is positive and significant, supporting the fact that richer families do not permit women to work in low standard jobs. The positive sign of the coefficient of WORH shows that as the working hours of woman increase by 1 hour, the contribution of woman decreases by .000725 rupees holding the effect of other variables constant. The insignificant results show that this variable is not very important for women’s employment decision because in rural area under study, most of the women are working long hours, but achieving low wages, yet contributing less in income generating activities.
Variable Constant FSIZ WEXP EDUW EXSQ NEAR WMWA WMEX HWHO DRAT POVS REDU CHAA CHAB CHAC FST OWRP FTMI WORH WHOH
Table 2 OLS results of OLS model 2. Coefficient Std. Error t-Statistic 0.052 -0.001 0.006*** 0.005** -0.0001 -0.003 0.00001* 0.00001*** 0.0002 0.039 0.075* -0.041** -0.031 0.009 -0.025 0.006 0.058* -8.54E07** 0.0007 0.062 0.457351
0.04355 0.004275 0.003324 0.002647 0.0000872 0.007146 2.59E-06
1.203777 -0.348243 1.856677 1.991794 -1.377442 -0.484631 5.411163
6.51E-06 0.00223 0.060226 0.023844 0.022153 0.027045 0.026338 0.025415 0.021436 0.021416
-1.764127 0.090574 0.660243 3.147395 -1.89411 -1.15157 0.344307 -0.995387 0.324313 2.71535
4.89E-07 0.003248 0.048811 Adjusted R-squared
-1.746253 0.223243 1.287403
R-squared 0.399751 No of observations 200 *significant at 1percent,**significant at 5 percent and *** significant at 10 percent (iii). Econometric estimates of the OLS Model 3 In model 3, some variables are those which we have used in the previous models and their results are almost same but some variables such as: various education levels of woman, satisfaction from work, woman’s spending on herself, are new. In tabel 3, econometric results show that how various education levels of woman (primary, F.A, B.A, M.A, M.Sc, M.Com, M. phil, P.H.D) affects the contribution of women in their family budget. The results show that intercept is positive and significant which shows that some other variables which we have not included in this model also affect the contribution of women.
European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org We have included four categories of women’s education level. The coefficient of PEDU (education up to primary level), SEDU (education up to secondary level), and BEDU (education up to graduation level), are positive and insignificant, while the coefficient of higher level of education (HED) is negative and insignificant. Our positive results are supported by Azid et.al (2001) and Coady (2001); they have also estimated the positive relationship between women’s education and women’s labor force participation . Education enhances the productivity and skill of the people. The coefficient of (SEDU) is positive and non significant. This shows the fact that women having education above primary and up to secondary level contribute more in their family budget. The coefficient shows if the level of education increases by 1 year the contribution of women in their family budget increases by .006872 rupees holding the effect of other variables fix. our results are supported by Pangestu and Hendytio 1997; Azid et.al 2001). Coady (2001) have also estimated the positive relationship between the women’s education and woman’s labor force participation. The negative coefficient of HED shows that contribution of rural women in their family budget decreases by .001746 rupee due to an increase in the one unit of higher level of education. The explanation may be that jobs in the rural areas are of low standard and higher level of education of women shows that they come from the families who want that their women at least get better job otherwise no job. These women increase their productivity in making of fashionable clothes for them and spend most of their time in their make up rather than in economic activity. Another variable is satisfaction from work. The coefficient of WRKS is positive and non significant. The coefficient shows that if the work satisfaction increases by one unit, the contribution of rural women in family budget increase by .007698 rupee holding the effect of other variables constant. The insignificant results show that satisfaction from work is not an important variable to determine the contribution of rural women in family budget. During our field trip, we have observed that women were participating in economic activities because they were forced to work though they were not looking satisfied from their work. Some women were forced by their in- laws and husband to work in these tough and hard activities and some of them were forced to work due to the burden of the poverty. The coefficient of women’s spending on herself (WSPN) is positive and non significant. We have used the binary variable showing that whether the women can spend most of her income on herself or not. During the survey, we have observed that some women want to spend income on their personal needs but they are forced not to spend major part of their income on their own requirements due to family burden or because their husband don’t allow them to spend their income according to their own desire. Mostly, in rural area, men control whole income of the women and don’t give them money to spend them freely. Table 3.OLS results of model 3 Std. Variable Coefficient Error t-Statistic C FSIZ MARD NCHI FST NEAR POVS OWRP REDU WMWA WMEX FTMI PEDU SEDU BEDU HED WRKS WSPN WHOH No of observations R-squared
0.108 -0.002 -0.023 -0.0007 0.013 0.0002 0.086* 0.056* -0.033 1.67E-05* -1.02E-05 -1.01E06** 0.010 0.006 0.051 -0.001 0.006 0.007 0.061 200 0.442673
0.051835 0.00409 0.031069 0.004583 0.021933 0.006317 0.023911 0.02125 0.02133 2.68E-06 6.80E-06
2.094847 -0.653619 -0.7449 -0.16635 0.611452 0.038138 3.61513 2.670809 -1.565703 6.227568 -1.493934
5.01E-07 0.031753 0.029193 0.04726 0.065204 0.021149 0.025344 0.048742 probability Adjusted
-2.02004 0.316797 0.235407 1.079131 -0.026783 0.309813 0.303733 1.270819 0.00 R-squared
European Journal of Developing Country Studies, Vol.8 2010 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org 0.387248 *significant at 1 percent, and **significant at 5 percent
(V). CONCLUSION AND POLICY IMPLICATIONS (i). Conclusion The main findings of our results are that age of the woman has shown a nonlinear effect on the contribution of women in her family budget. We have found that outside work permission, women’s monthly wage rate, education of women, burden of poverty, positively effect the contribution of rural women in their family budget. Family size, number of children, total monthly income of the women, and women’s monthly expenditure has negative effect on the contribution of woman. Poorer the household, greater will be the contribution of women in household budget. The permission to woman to work outside the home greatly affects the contribution of women in her family budget. The important variables in our analysis are education of the women, age of the women, poverty status, outside work permission, women’ monthly wage rate, total monthly income of the family, women’s monthly expenditures, restrictions to achieve education, and work experience of the woman. (ii). Policy Recommendation To enhance the contribution of working women to family budget Government should take the following measure. Poverty is the main problem in rural areas. Low contribution of women in rural areas is due to low wage rate. To increase the wage rate of women proper technical training, marketing facilities, minimum wage implementation should be given to women. This action would increase their productivity and income. Education is the most important factor that increases the contribution of rural women in their family budget. As our results show that education increases the contribution of rural women in their family budget. Women in rural areas are deprived of the right to education due to unavailability of school and due to rural culture and ideology. They are restricted to not go to school due to rural culture and ideology financial problems also prevent women to achieve education. Financial incentives can be provided to make adult education schools more relevant to the needs of women workers. High qualified teachers should be appointed in schools so that they can give proper education to the rural females. Credit facilities should be given to poor household because women have limited access to financial institution which provides credit facilities. Bank should provide loan to poor women. Invisibility of work of rural women to policy maker is main characteristic of rural areas. Because of mostly in the rural areas, women work in their home. Reliable and comparable data on the extent and nature of working women is a key element in the effort to combat problems. Statistically sound methodological surveys of female labor force would be undertaken. The wage gap between man and women is another cause of low contribution of rural women. This gap should be eliminated by government. Government should implement economic policy that would promote employment among working women. Cost of girl’s education should be reduced. Rural girls from low income families should be supported for admission in universities. “Double burden” born by working women should be eliminated by teaching family and house keeping skills to male members of the family. Woman’s economic dependence also affects her contribution. Women economic independence in the society and their participation in economic life should be promoted. Information about family planning should be provided to rural women because the burden of more infants also decreases her contribution
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