Women s Efforts for Family Subsistence: A Rural Study

Similar documents
The Socio-Economic and Demographic Determinants of Women Work Participation in Pakistan: Evidence from Bahawalpur District

URBAN INFORMAL SECTOR: HOW MUCH WOMEN ARE STRUGGLING FOR FAMILY SURVIVAL

Female Labor Force Participation in Pakistan: A Case of Punjab

Determinants of Household Savings in Pakistan: Evidence from Micro Data

Rural-Urban Saving Differentials in Pakistan: Investigation from Primary Data

Determinants of Poverty in Pakistan: A Multinomial Logit Approach. Umer Khalid, Lubna Shahnaz and Hajira Bibi *

Factors That Affect the Participation of Female in Labor Force: A Macro Level Study of Pakistan

Employment Status and Workforce in the Formal and Informal Sector: A Case Study of district Lahore. Durdana Qaiser Gillani and Muhammad Zahid Naeem*

Socioeconomic and Demographic Factors Affecting Labor Force Participation in Pakistan

Married Women s Labor Supply Decision and Husband s Work Status: The Experience of Taiwan

Saving Behavior among Different Income Groups in Pakistan: A Micro Study

ISSN: International Journal of Advances in Management and Economics Available online at

Labor Participation and Gender Inequality in Indonesia. Preliminary Draft DO NOT QUOTE

Urban Informal Sector: How Much Women Are Struggling for Family Survival

Labour Supply and Earning Functions of Educated Married Women: A Case Study of Northern Punjab

How Do Women Decide to Work in Pakistan?

The Influence of Demographic Factors on the Investment Objectives of Retail Investors in the Nigerian Capital Market

An Analysis of the Determinants of Male Labor Force Participation and Employment Status in Pakistan: The Case of Bahawalpur District

FactorsAffectingWomenContributioninHouseholdBudgetinUrbanInformalSectorAnAnalysis

FEMALE PARTICIPATION IN LABOR FORCE AND ITS IMPACT ON HOUSEHOLD AND NATIONAL INCOME: EVIDENCE FROM PAKISTAN

Empowerment and Microfinance: A socioeconomic study of female garment workers in Dhaka City

MONEY, PRICES, INCOME AND CAUSALITY: A CASE STUDY OF PAKISTAN

Revisiting The Household s Savings Function in Karak, Pakistan

ASSESSING THE SAVING PATTERN OF DIFFERENT INCOME GROUP HOUSEHOLDS IN DISTRICT DAUSA, RAJASTHAN

MAHATMA GANDHI NATIONAL RURAL EMPLOYMENT GUARANTEE ACT (MGNREGA): A TOOL FOR EMPLOYMENT GENERATION

Determinants of Revenue Generation Capacity in the Economy of Pakistan

ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS AUGUST 2012 VOL 4, NO 4

Factor Affecting Yields for Treasury Bills In Pakistan?

www. epratrust.com Impact Factor : p- ISSN : e-issn : January 2015 Vol - 3 Issue- 1

Impact of Micro finance in Raising the Living Standard of People of D.I.Khan

A Case Study on Socio - Economic Conditions of Agricultural Labourers in Idaikal Village in Tirunelveli District. Dr. T.

HOW DO WOMEN DECIDE TO WORK IN PAKISTAN? Zareen F. Naqvi and Lubna Shahnaz 1

SECTION- III RESULTS. Married Widowed Divorced Total

DETERMINANTS OF HOUSEHOLD SAVING BEHAVIOUR A SPECIAL REFERENCE IN VELLAVELY DIVISIONAL SECRETARIAT DIVISION OF BATTICALOA DISTRICT.

AN EMPIRICAL ANALYSIS OF GENDER WAGE DIFFERENTIALS IN URBAN CHINA

Equality and Fertility: Evidence from China

WOMEN EMPOWERMENT THROUGH SELF HELP GROUPS : A STUDY IN COIMBATORE DISTRICT

Analysis on Determinants of Micro-Credit Borrowings Rural SHG Women in North Coastal Andhra Pradesh

Education and Employment Status of Dalit women

Women in the Labor Force: A Databook

Women in the Labor Force: A Databook

WOMEN PARTICIPATION IN LABOR FORCE: AN ATTEMPT OF POVERTY ALLEVIATION

Determiants of Credi Gap and Financial Inclusion among the Borrowers of Tribal Farmers. * Sudha. S ** Dr. S. Gandhimathi

Exiting Poverty: Does Sex Matter?

Exiting poverty : Does gender matter?

Asian Journal of Empirical Research

A STUDY ON FACTORS INFLUENCING OF WOMEN POLICYHOLDER S INVESTMENT DECISION TOWARDS LIFE INSURANCE CORPORATION OF INDIA POLICIES IN CHENNAI

Female labor force participation and its influencing factors in the urban areas of Afghanistan - a case study of Herat City

MOTIVATIONAL FACTORS AMONG TRIBAL WOMEN FOR JOINING SELF HELP GROUPS IN DHARMAPURI DISTRICT

Women in the Labor Force: A Databook

Returns to education in Australia

Ministry of Health, Labour and Welfare Statistics and Information Department

IMPACT OF MACROECONOMIC VARIABLES ON ECONOMIC GROWTH: EVIDENCE FROM PAKISTAN

Macroeconomic variables; ROA; ROE; GPM; GMM

2000 HOUSING AND POPULATION CENSUS

Differentials in pension prospects for minority ethnic groups in the UK

WOMEN ENTREPRENEURSHIP IN UNORGANISED SECTOR

the effect of microcredit on standards of living in bangladesh shafin fattah, princeton university (2014)

The labour force participation of older men in Canada

Women in the Labor Force: A Databook

A STUDY OF INVESTMENT AWARENESS AND PREFERENCE OF WORKING WOMEN IN JAFFNA DISTRICT IN SRI LANKA

Socio-Economic Determinants of Household Food Expenditure in a Low Income Township in South Africa

Cross- Country Effects of Inflation on National Savings

CONVERGENCES IN MEN S AND WOMEN S LIFE PATTERNS: LIFETIME WORK, LIFETIME EARNINGS, AND HUMAN CAPITAL INVESTMENT $

The BEAC Central Bank and Wealth Creation in Cameroon Economy

Married Women s Labor Force Participation and The Role of Human Capital Evidence from the United States

HOW DOES WOMEN WORKING AFFECT SOCIAL SECURITY REPLACEMENT RATES?

Socio-Economic Status Of Rural Families: With Special Reference To BPL Households Of Pauri District Of Uttarakhand

Liquidity Risk Management: A Comparative Study between Domestic and Foreign Banks in Pakistan Asim Abdullah & Abdul Qayyum Khan

An Analysis Of Determinants Of Private Investment In Pakistan

Gender Inequality in Labour Force Participation: An empirical Investigation. Labour Market Discrimination (J7, J15, J16, J42)

Impact of Capital Market Expansion on Company s Capital Structure

Gender wage gaps in formal and informal jobs, evidence from Brazil.

Southern Punjab Poverty Alleviation Project (SPPAP)

DEVELOPMENT OF FINANCIAL SECTOR AN EMPIRICAL EVIDENCE FROM SAARC COUNTRIES

Exchange Rate Regimes and Trade Deficit A case of Pakistan

Gender Based Utilization of Microfinance: An Empirical Evidence from District Quetta, Pakistan

SOCIO-ECONOMIC STATUS OF MUSLIM MAJORITY DISTRICT OF KERALA: AN ANALYSIS

POPULATION, ECONOMIC GROWTH AND DEVELOPMENT IN THE EMERGING ECONOMIES

Impact of Characteristics on Outreach and Profitability of Microfinance Institution in India

Vulnerability to Poverty and Risk Management of Rural Farm Household in Northeastern of Thailand

[32] Determinants of Educated Women s Low Labour Force Participation in Sri Lanka. Jayathunge, I.S.

Structure and Dynamics of Labour Market in Bangladesh

Correlation of Personal Factors on Unemployment, Severity of Poverty and Migration in the Northeastern Region of Thailand

Factors Affecting Rural Household Saving (In Case of Wolayita Zone Ofa Woreda)

Aging in India: Its Socioeconomic. Implications

A Study On Socio-Economic Condition Of Self Help Group Members At Village Warishpur, West Bengal

Demographic Dividend or Demographic Threat in Pakistan?

ESTIMATING THE RISK PREMIUM OF LAW ENFORCEMENT OFFICERS. Brandon Payne East Carolina University Department of Economics Thesis Paper November 27, 2002

Program on Retirement Policy Number 1, February 2011

METHODOLOGICAL ISSUES IN POVERTY RESEARCH

A case study of Cointegration relationship between Tax Revenue and Foreign Direct Investment: Evidence from Sri Lanka

THE ANALYSIS OF FACTORS INFLUENCING THE DEVELOPMENT OF SMALL AND MEDIUM SIZE ENTERPRISES ACTIVITIES

SATISFACTION OF WORKING WOMEN POLICYHOLDERS ON THE SERVICES OF LIC

Fundamental Determinants affecting Equity Share Prices of BSE- 200 Companies in India

A Study On Micro Finance And Women Empowerment In Thanjavur District

Awareness and Willingness to Pay for Health Insurance: A Study of Darjeeling District

EFFECTS OF ECONOMIC FACTORS ON FOREIGN DIRECT INVESTMENT INFLOW: EVIDENCE FROM PAKISTAN ( )

a. Explain why the coefficients change in the observed direction when switching from OLS to Tobit estimation.

Saving for Retirement: Household Bargaining and Household Net Worth

Transcription:

Pakistan Journal of Social Sciences (PJSS) Vol. 31, No. 2 (December 2011), pp. 319-330 Women s Efforts for Family Subsistence: A Rural Study Muhammad Zahir Faridi Assistant Professor of Economics, Bahauddin Zakariya University, Multan. Email: zahirfaridi@bzu.edu.pk Abstract The present study provides the analysis of the women s efforts for family survival especially in rural areas. The study is based on the primary source of data collected by author. Ordinary Least Square method is employed for obtaining estimates. We have found that age of the women, women hourly wage rate, poverty status and women s permission to work outside. Women living in joint family system, with more poverty and high dependency have positive and significant effect on women s contribution in Household budget make more efforts for household survival. Marital status, more number of children in early age group and larger family size retard the women s efforts for family in the rural areas. The study suggests that the size of the family should keep short and women should be given permission to get education and to work outside the home. Keywords: Women s budget contribution; OLS method; Hourly wage rate; Poverty status; District Multan; Family Size. I. Introduction The economy of Pakistan, being an under developed is passing through the stabilization phase. In order to achieve the macroeconomic stability, it is necessary to provide the platform for generating economic growth, employment and raising the human quality. Economic growth is the main source of poverty alleviation, an increase in real wage rate and reduction in unemployment. Pakistan is the 6 th most populous country of the world. The estimated population of Pakistan is 177.10 million by end June 2011. The annual growth rate of population is 2.05 percent per year. According to the world s ranking of size of the labor force, Pakistan is ranked as the 9 th largest country with 54.92 million labor force in the year 2009-10. As compared with previous, 1020 million more people are added in the labor force. The increase of male and female proportion is 0.53 and 0.67 million respectively. The unemployment rate is marginally higher than the last year i.e. 5.6 in 2009-10 and 5.5 in 2008-09 1. Female labor force participation rate is very low in Pakistan as compared with others countries in the region. According to refined activity rate (RAR), the male participation rate is 68.8 percent and female participation rate is 21.5 percent in the year 2009-10. In the same year, the rural female participation rate is 27.6 percent and urban 1 These informations are taken from Economic Survey of Pakistan (various issues).

320 Pakistan Journal of Social Sciences Vol. 31, No. 2 female participation rate is 10.3 percent 2. According to these facts and figures, female s participation in economic activities is increasing gradually in Pakistan albeit low as compared with other developed and under developed economies. The rural female labor force participation in different activities like harvesting sowing seeds, maize and rice husking, picking of cotton and other farming activities has increased. But it is not still explored the factors that determine the females contribution in family income. A very few studies 3 are made to analyze the factors that contribute in family budget by females. A bulk of studies has attempted to analyze the factors of female labor force participation. The present study is focused on analyzing the factors or efforts that are made by rural females for survival of their families. The efforts of females are measured by the factors that influence females earnings in rural areas. The rest of the study is arranged as follows. The section two provides the review of literature. Data sources and brief profile of the study area is mentioned in the section third. Fourth section describes the methodological issues and variables interpretation. Results and discussion is made in the section fifth. Last section concludes the study. II. Review of Literature The present section reviews some related studies. A bulk of research is conducted on female labor market participation but few studies relate to the problem discussed up to some extent. Bell (1974) provided the estimate of working women s contribution in household income. Findings of the study indicated that only 16 percent of total family income was contributed by some employed women and average income of working women s family was almost 23 percent more than non working women. The full time working ladies contributed in family income about 39 percent. In addition, study concluded that there was a significant difference of women s share in their family income due to working in different occupation. The professional skill workers contributed more in their household income as compared with those females employed in service sector. Cancian et al. (1991a) analyzed the male female earning differentials and observed their influence on the distribution of family income among married couple and all households. It was found that there was a substantial rise in wives incomes during the period 1968 1988 as compared with husbands earnings. The study provided the influence of wives income on family earnings that almost 9.2 percent households were below poverty line whose women were not earning and almost 26.4 percent families has income two times more than poverty line, whose women were working. Cancian et al. (1991b) discovered that almost 20 percent income inequality has been reduced by wives earnings. A similar study made by Machin and Waldfogel (1994) for Britain economy. The results concluded that 27 percent inequality has decreased due to the earnings of wives. Shaw (2005) studies direct and indirect contribution of working women to increase in trend productivity. Luo (2005) explored the influence of rural urban migration on rural female workers earnings. The study analyzed that female migrants has positive impact on household s material well being. 2 Govt. of Pakistan, Economic Survey (2009 10). 3 See in the section of Literature Review.

Muhammad Zahir Faridi 321 Khan et al. (2005) explored the contribution of women and children in family income who are involved in home based activities. The study also provided the influence of increased incomes of the females on family education, health and nutrition. The analysis was based on micro study or primary source of data. Logistic Regression technique was employed for estimation. The findings showed that household size had positive and significant impact on household decision to participate in home based activities but living condition index had inverse effect. Caruana (2006) investigated the factors that influence female work force participation in Malta. The results of the study concluded that female labor force participation was positively influenced by wage rate and availability of part time work while crude birth had negative impact on female work participation. Ogbimi et al. (2006) studied the factors that minimized financial management problems among rural women for sustainable economic empowerment. The sources of financial resources of women were identified in analysis. The analysis showed that rural women played a dynamic and essential role in rural economic life. Khan and Khan (2007) discussed the properties of women employed in informal sector and evaluated their contribution in family budget. The study was based on primary source of data. In order to analyze the impact of socioeconomic and demographic factors on females contribution, the study employed ordinary least square method. The findings indicated that women s education, as a head of household, ownership of assets had positive and significant influence on their contribution in family budget. It was also observed that informally employed married women had more contribution in household budget. Arif and Hamid (2009) analyzed the effect of urbanization on city growth and quality of life in Pakistan. The analysis of the study was based on both qualitative and quantitative approaches. It was found that more jobs opportunities were increased for women due to rural urban migration. The study concluded that the migration improved the average income of migrants and their consumption level. Khan and Khan (2009) highlighted the factors that contribute in family budget of informally employed women in urban sector. The study was based on primary source of data. The ordinary least square method was used in order to obtain the estimates. The study concluded tat the factors like head of household status, education and ownership of assets by women, family size, poverty status of the family positively contributed in the family budget. In addition to, there are numerous studies that mainly focused on the factors affecting females work participation s decision, and employment in all sectors of the economy. These may be associated with females contribution in family budget and become useful in identifying the factors to observe the determinants of the share of females income in the total family income. Azid et al. (2001) studied the economic behavior of female labor force in the business of embroidery in Multan. Naqvi and Shahnaz (2002), Hamid (1991), Faridi et al. (2009) etc analyzed the factors which force the women to participate in the labor market for raising the family income.

322 Pakistan Journal of Social Sciences Vol. 31, No. 2 III. Data Sources The main objective of the present study is to examine the factors that become the cause of economic contribution in their family budget. The present study is based on primary source of data conducted in Southern Punjab which is under developed part of Punjab province. We have selected rural areas of district Multan for analysis because Multan is representative district of South Punjab. Five villages of Multan district are selected at random which are situated at north, East, West and South of district. The total area of district Multan is 3721 sq. km. the women in these villages are highly involved in cultivation, harvesting, sowing of seeds, cotton picking and rearing of animals. The data in this study is collected through field survey; a sample of 200 women is randomly drawn from rural area of the district from selected villages. Simple random sampling technique is employed. Data is collected by interviewing the females directly and information are recorded at the spot. Personal contracts are used for collecting the data. IV. Model Specification and Methodology We have observed in the literature that different researchers have used various techniques to estimate the contribution of females in their family budget. But most of studies have employed ordinary least square method in their analysis. Following Mehrotra and Biggeri (2002), Khan and Khan (2007, 2008, 2009), we have also used OLS method to estimate the contribution of rural women in their household budget. The general form of multiple regression models is given as; Y = f (X 1, X 2,., X N ).. (i) Where Y = dependent variable (Women s budget contribution), X 1, X 2,.., X N are explanatory variables. The multiple regression equation is given as follows; Y = α + β X + β X +... + β + µ X 1 1 2 2 k k i.. (ii) Where β, β,... 1 2..., β k are called partial regression coefficients and µ i is called error term which satisfies is OLS assumptions. Relying on OLS techniques, our specified model is given in the following equation. α + β1agw + β 2 AGS + β 3EDW + β 4MAS + β 5NCH + β 6FSP + β7 FSZ + β8red WBC = + β9whw + β10whd + β11hwh + β12hme + β13pos + β14ddr + β15owp + e i.. (iii) Table 1 represents the definitions and measurement of the selected variables.

Muhammad Zahir Faridi 323 Table 1 Definition and Hypothesized relationships of the variables VARIABLES DEFINITIONS WBC Women s Budget contribution Ratio of women s monthly income in the family to the total monthly income of the family and expressed as a percentage. EXPLANATORY VARIABLES AGW Age of woman Woman s age in completed years AGS Woman s age squared Square of the woman s age EDW Woman s Education Woman s education in completed years MAS Woman s marital status 1 If woman is married 0 Otherwise NCH Number of children in family Total number of children up to 15 years in the family FSP Family Setup 1 if woman belongs to joint family setup 0 Otherwise FSZ Family Size Total number of family members RED Restriction to achieve education 1 if she is not given permission to get education 0 Otherwise WHW Woman s Hourly Woman per hour wage (in Rs.) wages WHD Women as a head of Household 1 if woman is head of household 0 Otherwise HWH Husband s working Hours A continuous variable which includes husband s daily working hours HME Household s Household s expenditures (in Thousand POS DDR OWP Monthly expenditure Poverty Status of Household Dependency Ratio Outside work Permission Rupees) per month 1 if household s per month, per capita income is Rs. 3375 or below 0 Otherwise Ratio of the person below 16 years and above 65 to total size of the family. 1 if a woman is given permission to work outside the home 0 Otherwise V. Results and Discussion The present study is analyzed at two stage level. At the first stage, we have provided preliminary and descriptive analysis of the study and econometric analysis is described in the second stage. a. Elementary data analysis In elementary data analysis, we have provided socio economic profile of females who are making efforts for their family survival, reasons to participate in economic activities, marital status, educational status, employment status.

324 Pakistan Journal of Social Sciences Vol. 31, No. 2 Socio economic Profile of women The present study shows that 74 percent females are participating in rural economic activities to support their families and 26 percent women are not involved in economic activities. Table 2 Characteristics Characteristics Percentages Working women 74 percent Non working Women 26 percent Average monthly income of women 2618.50 Rupees Household average monthly income 19656.00 Rupees Average Household Size 6.80 persons Average number of children 4.56 children Household residing below poverty line 29 percent Women who are forced to work 53 percent Source: Sample survey conducted by author We have found that 29 percent households are residing below poverty line and 53 percent women are forced to work to face the poverty. The working women are living in large household with average household size of 6.8 persons. Table 3 Causes of females participation in economic activities for family survival Causes of work Percentage Poverty 21.00 Non working Husband 4.00 Family Presence 53.50 Absence of male head 6.00 Source: Sample survey conducted by author Table 3 reports reasons of females participation in rural economic activities for family survival. It is found that 21 percent females are participating in rural economic activities due to poverty because family income is not sufficient to meet the basic necessities of the family. Preliminary analysis indicates that 4 percent women are making efforts for subsistence of their family because their husbands are not working. In addition, we have observed that almost 53.5 percent women are working due to their family presence and 6 percent women are participating in rural labor market because they are head of household. Table 4 Married status of working women Marital Status Percentage Single 22.5 Married 68.5 Widowed 6.0 Divorced 3.0 Source: Sample survey conducted by author Marital status of the working women is presented in table 4. Majority of the women (68.5 percent) are married and 22.5 percent working women are single. The study shows that 6 percent women are widowed and only 3 percent working women are divorced.

Muhammad Zahir Faridi 325 Educational Status of Rural working women Table 5 interprets the educational status of rural working women. The analysis has indicated that majority of working women in rural areas are uneducated or illiterate i.e. 61.5 percent. Only 13 percent women have primary education and 7.5 percent rural working ladies are educated up to middle level. We have observed that only few women are highly educated i.e. 3 percent. Table 5 Educational Status Educational Status Percentages Illiterate 61.5 Primary 13 Middle 7.5 Matric 5.5 Intermediate 5.0 BA/ B.Sc 4.5 MA/ M.Sc and Professional 3.0 Source: Sample survey conducted by author Working women by occupation There is a variety of jobs in rural areas. Table 6 provides the nature of different jobs or occupation and percentage distribution of working women by occupation. We have observed during the survey that mostly women are involved in more than one activity due to illiteracy, low skill, low wages or income and family pressure. Our elementary data analysis shows that 33.5 percent females are performing more than one activity, 13 percent are making farming and 4.5 percent are involved in live stock activities. It is also found in the present study that almost 7.5 women are preparing cot knitting material and 4.0 percent is knitting Fan by leaf of dates while 5.5 percent women are sewing clothes. Table 6 Distribution of working women by occupation Nature of Jobs/ Occupation Percentages Farming 13 Livestock 4.5 Cot Sewing Material 7.5 Fan Knitting by Leaf of dates 4.0 Teacher/ LHVs/ Nursing 10.0 Casual wage worker 22.0 Cloth Sewing 5.5 Involved in more than one activities/ occupation 33.5 Source: Sample survey conducted by author b. Correlation Analysis We have presented the pair wise correlation coefficients in table 7, in order to examine the degree of association among the explanatory variables. It is found that all the variables have some degree of relationships. We have also observed in correlation analysis that the variables used in the model are not exactly related. So the present analysis is free from Multicollinearity problem.

326 Pakistan Journal of Social Sciences Vol. 31, No. 2 Table 7 Pairwise coefficient of correlation matrix VARIABLES AGW AGS EDW MAS NCH FSP FSZ RED WHW WHD HWH HME POS DDR OWP AGW 1.00 AGS 0.98 1.00 EDW -0.22-0.17 1.00 MAS 0.48 0.40-0.31 1.00 NCH 0.50 0.40-0.41 0.57 1.00 FSP 0.18 0.18-0.03 0.17 0.11 1.00 FSZ -0.15-0.16-0.06-0.58 0.251-0.41 1.00 RED -0.05-0.04-0.33-0.05 0.05 0.04 0.08 1.00 WHW 0.07 0.07 0.53-0.07-0.14 0.06 0.01-0.19 1.00 WHD 0.12 0.10 0.17 0.07-0.01 0.07-0.13-0.19 0.33 1.00 HWH 0.26 0.19-0.32.70 0.48 0.17-0.15 0.09-0.17-0.04 1.00 HME 0.12 0.14 0.46-0.12-0.12-0.15 0.18-0.27 0.43 0.03-0.13 1.00 POS 0.08 0.05-0.36 0.21 0.37 0.12 0.05 0.14-0.07 0.01 0.19-0.33 1.00 DDR -0.12-0.14-0.29 0.18 0.23-0.03 0.33 0.02-0.20-0.11 0.23-0.22 0.31 1.00 OWP -0.02 0.00 0.18-0.25-0.08 0.13-0.05 0.15 0.19 0.16-0.13-0.01-0.01-0.04 1.00 Source: Calculated by author from sample using EViews-7 c. Estimation Analysis The table 8 provides the estimates of females efforts for family subsistence model. The solidity of our model mainly consists of specification of model, measurement of variables, consistency of data, economic and statistical significance of variables included in the analysis. The overall significance of the model is judged with F-statistics which is significant at one percent level of significance albeit low value of R 2 and adjusted R 2 (0.45 and 0.40) which is typical phenomenon in cross section studies. The problem of Heteroskedasticity is removed by applying white Heteroskedasticity test. There is no existence of Multicollinearity among explanatory variables. The intercept term is negative and insignificant. The age of women plays a significant role in women labor market participation and income raising activities. We have found that the coefficient of age of woman (AGW) is positive and highly significant. Female s contribution in family budget rises by an increase of age. The present study shows that rural females contribute in family budget by about 1.1 percent due to an increase of one year in females age. The coefficient of age squared is negative and statistically significant at one percent level of significance. It indicates that females contribution diminishes after prime age (35 45) and shows a non linear relationship. The economic reason may be that skill, experience and expertise increase with rising age and females income and employment opportunities has also increased. Our results are stay in line with Hartog and Theevwes (1986), Kozel and Alderman (1990), Azid et al. (2001), La Ferra (2002), Khan and Khan (2007, 2008 and 2009) s findings. Education has a strong effect on females income and they contribute more in household budget. In order to observe the impact of females education on their contribution, study incorporates the completed years of females education as an explanatory variable. We have noted that there exists positive relationship between females years of education and contribution of rural females to family income. An additional year of education raises rural women s contribution to household budget by about 0.229 percent. Findings of the research validate neo-classical hypothesis (see Becker 1980) that education level and women s work participation are directly correlated. Further, our results maintain the structuralists views regarding women s labor supply in economic activities and its return and an increase of educational level (Benham, 1980). The reason may be that the females become more productive, skilled, better trained and have technological know how as a result of increasing level of education. All these

Muhammad Zahir Faridi 327 raise the women s wages and earnings and ultimately women s share in household s expenditure has increased. We have found that the coefficient of marital status is negative and statistically significant at 5 percent level of significance. Rural married females are sharing less in their family expenditure with comparison of unmarried females. Married rural women reduce their contribution in family budget by 8.52 percent. We have observed during survey that mostly women belong to Purdah observing families and are not given per mission to work outside home. The same results are found in Naqvi and Shahnaz s study (2002) that married females are less likely to participate in economic activities. Supporting to previous results, the study has concluded that the number of children up to 15 years of age exert negative effect on females contribution in family budget. The women s contribution in household s budget diminishes by 0.82 percent as a result of more number of children in the family. The reason may be that the females allocate more time inside the home for children caring which reduces their contribution. Another interpretation may be that there is no concept of day care centers in rural areas. Our results are consistent with the findings of khan and khan (2008, 2009). We have observed that the coefficient of family setup (FSP) is positive and statistically insignificant. Females belonging to joint family setup are more contributing in family expenditure. The interpretation may be that females allocates more time outside the home activities because her inside home activities like cooking food, washing clothes, rearing child etc are shared or performed by other numbers of the family. So her contribution in family budget has increased. Our findings contradict with the result of khan and khan (2009) and reconciliate with the findings of Naqvi and Shah (2002) and Faridi et al. (2009). Further it is noted in the present study that larger size of family puts negative impact on females income and their contribution in household budget. But, the family size has no significance effect on females contribution. We have incorporated an additional variables i.e. restriction on females in attaining education (RED) in our model in order to observe the efforts for family survival through contributing in household budget. The finding indicates that the females efforts for family subsistence become fruitless and are spoiled, when they are not given permission to attain education. The study revealed that the coefficient of women s hourly wage rate (WHM) is not only positive but also significant at one percent level of significance. An increase of one rupee in women s wage raises the female s contribution in family budget by 0.303 percent. The study supports the neo-classical theory of labor supply that workers supply more working hours as hourly wage rate increases. It is also observed those women s efforts for family subsistence has increased significantly if she is household head. The women s contribution in family budget boosts up by 7.66 percent being a head of household. The reason may be that the household s responsibility like education of children, expenditure management and budget preparation, caring of old age people in the family etc are fulfilled by household head only. So her contribution in family has increased by working more. Our findings supports Khan and Khan (2009) s results and differs from the results of Naqvi and Shahnaz s study (2002).

328 Pakistan Journal of Social Sciences Vol. 31, No. 2 Table 8 OLS Regresion Estimates of Females Contribution Model VARIABLES COEFFICIENTS STANDARD T STATISTIC ERROR CONSTANT -10.38 9.68-1.07 AGW 1.09* 0.438 2.49 AGS -0.012* 0.005-2.40 EDW 0.229 0.247 0.93 MAS -8.517** 3.818-2.23 NCH -0.816*** 0.439-1.86 FSP 2.43 1.95 1.25 FSZ -0.263 0.409-0.64 RED -3.54*** 2.11-1.68 WHW 0.303* 0.047 6.45 WHD 7.66*** 4.621 1.66 HWH -0.452*** 0.262-1.73 HME -0.00018* 0.0000711-2.59 POS 8.97* 2.289 3.92 DDR 5.15 4.481 1.15 OWP 4.91* 2.06 2.38 R Squared 0.45 F Statistic 9.26783 Adj. R Squared 0.41 Prob. (F Stat) 0.0000 Sample Size 200 Source: Estimates are obtained by Authors using E-Views 7 Software *,**,*** depicts the significant level at 1, 5 and 10 percent respectively VI. Conclusion and Policy Recommendation This study mainly discusses the females efforts regarding family survival especially in rural areas. The main aim of the study is to explore the factors which are responsible for determining the women s contribution in their family budget. The analysis is based on primary source of data collected through survey. We have observed that 74 percent women are working whose monthly average income is Rs. 2618.50. The analysis provides the information that 29 percent households are living below poverty line, 53 percent women are forced to work and 68.5 percent women are married. Moreover, we have found that 61.5 percent women are uneducated and 33.5 percent women are involved in more than one activity. The findings of the study has indicated that the age of the working women, women s hourly wage, women as a head of household, poverty status and outside work permission are positively and significantly influencing women s contribution in family budget. In addition, it is noted in the present study that married women, more number of children, restriction to attain education and more working hours of husband significantly reduce females contribution in their household budget. In the light of the above findings, the study concludes that women s participation in earnings and economic activities for contributing in their household budget has become a vital and necessary in the present era. The household s expenditure has been increased due to high inflation rate, substitution of luxuries into necessities, high expenditure on children education and health etc. It is suggested that size of family should be kept short. Government should control population growth rate and should provide the best health facilities. In addition, it is suggested that women should be given permission for getting education and provide employment opportunities outside the

Muhammad Zahir Faridi 329 home. Women should be given proper wage rate especially in rural areas. The minimum wage legislation should be maintained. Moreover, the study concludes that the women s contribution in family budget increases as age increases but declines after some years. So, it is suggested that government should provide social security benefits and old age benefits to the women. Government should provide child care facilities through subsidization. References Azid, T., Aslam, M. and Omer, M. (2001). Poverty, Female labor force participation, and Cottage Industry: A Case Study of Cloth Embroidery in Rural Multan. Pakistan Development Review, 40(4), 1105 1118. Becker, G. (1980). The theory of the Allocation of Time, in Aliech Amsden (eds.). The Economics and Women and work, Penguin Books, England. Bell, C. H. (1974). Working Women s contribution to family income. Eastern Economic Journal, 17, 185 201. Benham, L. (1980). Benefits of women education within marriage. Journal of political Economy, 82(2). Cancian, M., Danziger, S. and Gottschalk, (1991a). The changing contribution of Men and Women to the level and distribution of family income (1968 1988). Working Paper No. 62. Jerome Levy Economics Institute of Bard College. Cancian, M., Danziger, S. and Gottschalk, (1991a). Working Wives and the distribution of family income, ln S. Danziger and P. Gottschalk (eds.) Increasing Income Ineqality: What Matters and what does not. Russel Sage Foundation, New York. Faridi, M. Z., Chaudhry, I. S. and Anwar, M. (2009). The Socioeconomic and demographic determinants of Women work participation in Pakistan: Evidence from District Bahawalpure. A Research Journal of South Asian Studies, 24(2), 351 367. Govt. of Pakistan. (2010-11). Pakistan Economic Survey, Federal Bureau of Statistics, Pakistan. Hamid, S. (1991). Determinants of the Supply of Women in the Labour Market: A Micro Analysis. The Pakistan Development Review, 345(4), 755 766. Hartog, J. and Theevwes, J. (1986). Participation and Hours of Work: Two Stages in the Life-Cycle of Married Women. European Economic Review, 30(4), 833 857.

330 Pakistan Journal of Social Sciences Vol. 31, No. 2 Khan, R. E. A. and Khan, T. (2007). Informally Employed Women: Their Characteristics and Contribution in Household Budget. Journal of Applied Sciences, 7(14), 1901 1907. Khan, S. R., Khattak, S. G. and Kazmi, S. (2005). Hazardous Home Based Subcontracted Work: A Study of Multiple Tiered Exploitation. Sustainable Development Policy Institute (SDPI). Oxford University Press. Khan, T. and Khan, R. E. A. (2008). Household Characteristics: How much They Affect Women s Contribution in Household Budget. Indian Journal of Labour Economics. Khan, T. and Khan, R. E. A. (2009). Urban Informal Sector: How Much Women Are Struggling for Family Survival. Pakistan Development Review, 48(1), 67 95. Kozel, V. and Alderman, H. (1990). Factors Determining Work Participation and Labour Supply Decisions in Pakistan s Urban Areas. The Pakistan Development Review, 29(1), 1 18. La Ferrara, E. (2002). Self Help Groups and Income Generations in the Informal Settlements of Nairobi. Journal of African Economies, 11(1), 61 89. Luo, G. (2005). Effects of Rural Urban Migration on rural female workers: A case study of Chinese rural women, Paper for NACS Conference Helsinki, 7 9. Machin, S. and Waldfogel, J. (1994). The Decline of the Male Breadwinner. London School of Economics. Discussion Paper No. 10. Mehrotra, S. and Biggeri, M. (2002). Social Protection in the Informal Economy: Home Based Women Workers and Outsourced Manufacturing in Asia. Innocenti Research Centre, UNICEF, Florence. Working Paper No. 97. Naqvi, Z. F. and Shahnaz, L. (2002). How Do Women Decide to Work in Pakistan. The Pakistan Development Review, 41(2), 495 513. Ogbimi, G. E., Soyebo, I. K. O. and Alahi, D. L. (2006). Minimizing Financial Management problems among rural women for sustainable economic empowerment: Case of Osun State, Nigeria Research Journal of social sciences, 1(1), 51 55. Shaw, K. (2005). Women s Contribution to Productivity. Regional Review, 1, 45 48.