Abstract

This paper overviews socio-economic factors as determinants of working women earnings in education department of district Peshawar Khyber Pakhtunkhwa. For this purpose, a primary data was collected through a structured questionnaire from 126 working females in September, 2017. Multinomial logistic regression technique has been used for the estimation of results. The main findings of the study are that education, experience, family income, and locality of job area showed positive relationship with working women earnings. However, marital status remained insignificant. Based on the findings of this study the researchers recommended that females are significantly contributing in family expenditures. Therefore, government should invest more in female's education and prioritize it.

Keywords

Multinomial Logistic Model, Education Sector, Working Women Earnings

Introduction

Nearly half of the population of Pakistan is female and they are playing a vital role in the economic development of the country. In modern ages, world is concerned about the trend and structure of the female labor force participation (FLFP). The issue is getting attention in Pakistan as well. Although, during 2003 to 2004 the annual average growth rate of females' participation rate was 15.9% which increased to 18.9% during 2005-2006, still female's participation rate is very low in Pakistan against other Asian countries (Faridi, Chaudhry & Anwar, 2009)

Like other countries of the world, the dynamic and vibrant character of women cannot be under estimated in Pakistan as they play a prolonged constructive and productive role in the social and economic development of the country. Women are playing their role in almost all spheres of the life including health, education, law, administration, sports, infrastructure, agriculture, defense, NGOs along with many other walks of life. So it can be concluded that there is hardly any field of life where female part, role and contribution is missing. Unfortunately, women in Pakistan have to play a dual role of labor inside and outside their homes. Due to domestic responsibilities, women in Pakistan are deprived of receiving proper education and ultimately getting a decent job. Low female literacy rate is a big issue in Pakistan and government is trying to make better the situation. But the situation is changing rapidly and now-a-days, because of high population growth and rising cost of living, family members are sending female members to educational institutions and allow them to do jobs in public or private sectors for earnings and household income generating activities. (Maan, Tanveer, Saboor, Asghar & Ali, 2006)

In spite of women active play of their role in the uplift of socio-economic status of their household's along men from the stone age, the recent wave of terrorism and political instability in the country has largely affected their share. It has become difficult for a middle class family to survive in a reasonable style and to lead a reasonable and peaceful life. In Pakistan, women have a higher risk of exposure to bad experiences, non-recognition of duties and prejudiced thinking even from their family members at the place of their job. Due to the fact, women job participation and ultimately their earnings are less than men in the job market in Pakistan. To meet the basic needs of daily life, women have to work in various public and private institutions in Pakistan. For this purpose, they remain absent from their homes for long hours and have to face many problems outside and inside their homes. They have to run the affairs of the household properly through kitchen responsibilities, cleaning of their homes, taking care of the children, husbands, elders and other members of the families beside their office responsibilities. Although men perform their outdoor responsibilities, their part in household activities is minimal and women are the major share-holders of inside and outside events. This affects their role in economic development of the country, status, earnings, and skills of working women in Pakistan (Avais, Wassan & Shah, 2014).

• Problem Statement

As discussed above, women in Pakistan are facing a lot of problems and issues while performing their duties in public or private institutions and organizations. In Khyber Pakhtunkhwa (KPK), the situation is harsher for the working women because of the traditional life style of the people of KPK. Specially district Peshawar where the society of the city is traditional mixed society of different social classes due to the migration of the people from all over Khyber Pakhtunkhwa to district Peshawar. Therefore, the life of working women in such a situation is hard. All these circumstances affect earnings, status, performance, skills, behaviors and efficiency of the working women. Therefore, the study is organized to provide insight into the issues and factors like socio-economic factors that affect earnings of working women. A reasonable amount of literature (Qureshi, 2000; Maqsood, and Chaudhry, Zia and Cheema, 2006; Maan et al., 2006; Avais et al., 2014) is available that highlights the problems of working women in Punjab and Sindh provinces of Pakistan however, research is inadequate on the issue of earnings and socio-economic factors in district Peshawar.

Objectives of the Study

The study examines the socio-economic factors involved in women earnings in education sector of district Peshawar Khyber Pakhtunkhwa.

Hypothesis of the Study

The following hypothesis is tested:

H₀: Socio-economic factors do not affect working women earnings in education sector

H₁: Socio-economic factors do affect working women earnings in education sector

Literature Review

Qureshi (2000) in her study explored different problems faced by working women belonging to different professional categories in Faisalabad. Results showed that majority of working women were unable to give proper time to their family members, health care and family functions.

Naqvi and Shahnaz (2002) investigated the factors determining female participation in the economic activities in Pakistan. They have collected cross sectional data from Household Integrated Survey (1998 to 1999). Multinomial logistic model has been used for the computation of the study results. The results showed age, marital status, education, family size, financial status, presence of children and residential area played an important role in determination of female participation in economic activities. Morrisson and Jutting (2005) also studied the determinants of female's participation in the economic activities. They have collected data for 66 developing countries. Ordinary least squares method has been used for estimating results.

Maqsood et al. (2005) analyzed the problems of employed women in the urban area of Faisalabad district. Primary data were collected from a sample of 150 employed women. Study concluded that most of the employed women have joined their jobs for raising living standard of the family. But employed women face conflict with their husbands and in-laws, difficulty in attending family functions, undesirable working conditions, insufficient pay and allowances and prejudiced behavior of the society members.

Ahmad and Aminah (2007) in a study investigated social support, strategies and work family interference in two hundred and thirty-nine married female production operators in Malaysia. Results showed that work interference with family was greater than family interference with work. Women were inclined to leave job upon having another child. Social support of supervisors towards working women was found to be least while performing their job.

Din and Khan (2008) analyzed socio-economic and cultural role, and constraints faced by rural women in their different activities in Mardan district, North West Frontier Province (NWFP). Primary data and descriptive statistics revealed a very limited socioeconomic and cultural role of women along with a low status in the study area. Different cultural constraints like young age marriage, restriction of women to indoor activities, low access to health facilities, and no choice of selecting a life partner are prevailing in the study area. The development of training institutions and cottage industries in research area are suggested necessary for changing the existing scenario.

Faridi et al., (2009) examined the relationship of FLFP and various factors in Bahawalpur District-Punjab province. Cross sectional data were collected through field survey. Results of the logistic regression technique showed that education level has positively and number of children negatively affected women work participation. Study recommended higher education, skill development opportunities and rural market participation for women to grab employment opportunities in the society.

Whitehead (2011) analyzed the impact of cultural factors on female labor force participation in 45 countries. Specifically, the role of cultural factors like fertility rate, religion, government type, government spending, citizen views of work and women in the workforce. The study concluded that cultural factors played vital role in affecting the female labor force participation.

Nawaz et al., (2013) examined social and domestic problems of working women in formal sector of Bahawalnagar district of Punjab, Pakistan. Descriptive statistics analysis revealed that working women in formal sector are facing problems like long working hours, job insecurity, low allowance and wages, gender discrimination, unscheduled working hours, low social status and non-recognition of their jobs. Study recommended protective and security laws for formally employed women in Pakistan for policy perspectives.

Avais et al., (2014) in their research study traced different problems of working women in Sukkur city, Sindh province of Pakistan. Respondents from various public and private sector, and Non-Governmental Organizations (NGOs) were selected for the study. Results in descriptive statistics showed that working women face difficulties in looking after their homes, physical and mental stress, work place discrimination, having less number of leaves and sexual harassment during their mobility to work place with no control on utilization of their salaries.

Malelu (2015) examined the impact of institutional factors on career advancement of working women in Kenyatta University, Kenya. It was concluded that institutional factors like university physical set up, financial constraints, insufficient mentorship, scant awareness of opportunities and rules regulations have negative influence on career development of working women. Study recommended that women should be provided equal opportunities of participation in trainings, conferences, and research and publication activities.

The above review indicates that a lot of work has been conducted to high light the influence of socio-economic and cultural factors on female labor force participation, determinants of gender inequalities in participation in economic activity, gender gap in earnings, access to resources for women, career advancement policies, problems of working women in formal and informal sectors, work family conflict, while little attention has been given to explore the impact of socio-economic factors which are affecting working women earnings. Current study will investigate the impact of socio-economic factors on the earnings of employed women in education sector in district Peshawar KPK.

Data and Methodology

This section shows information about the data, sample size and methodology.

Sample Size

This study is based on primary data collected from women working in the various departments of education in district Peshawar. All the data has been collected through a field survey by using questionnaire during 2017. Questionnaire was pre tested and important corrections were made after the pilot study. A sample size of one hundred and twenty-six respondents was selected through random sampling technique from the rural and urban areas of district Peshawar. Employed women earnings are examined by studying the various household socio-economic factors. The analysis of the study is carried out through Multinomial logistic regression because the dependent variable is in categories. The earnings function in economic activities is modeled by using the Multinomial logistic estimation technique.

Empirical Model

The following is the empirical model of the study:

Women Earnings= f (Education, Experience, Family Income, Marital Status, Locality) ...................................................... (1)

Equation (1) shows the empirical model of the study. The definitions of the variables are given as follows.

Employed women annual earnings: This variable is measured by the monthly salary of the employed women multiplied by twelve. The annual earnings are categorized into five categories starting with the lowest through 20000, 21000 through 40000, 41000 through 60000, 61000 through 80000, and 81000 through highest earnings.

Education: Education is considered an important determinant of working women earnings. To investigate its role in females' earnings it has been categorized in different categories i.e. primary, middle, high, higher secondary, bachelor, master and higher level of education. It is expected that education with show a positive relationship with female's earnings.

Experience: Experience is measured by total number of years of service in a department.it is expected that there exists a positive relationship between earnings and experience of the employed women.

Family Income: Family income is the annual income of the family members excluding employed women income. Family income is measured in thousands of Pakistani rupees. Family income causes higher education of employed women therefore a positive relationship is expected.

Place of Job: A dummy variable D is equal to zero if woman is employed in rural area and equal to one if employed in urban area. Earnings in urban area is expected to be high than rural areas.

Marital Status: The marital status of the respondents has been divided into two groups i.e. married and unmarried. The expected signs of the relationship between the marital status and women earnings can be both positive and negative.

Estimation Techniques

The dependent variable is employed women earnings which will be taken in categories so Multinomial Logistic Regression Model can be used for analysis. This model is used by Khattak, Tariq and Khan (2010) for analyzing the demand for electricity for different categories of income groups.

Results and Discussion

The present study leads to the discussion and results which are described in detail as follows:

Descriptive Analysis

Table 1 shows that on the average 15.21 years of schooling female workers have education with an average of 7.88 years of experience. The average annual family income remains Rs.725983.47.

Table 1. Descriptive Statistics

Variables	N	Minimum	Maximum	Mean	Std. Deviation
Years of Schooling	126	10	21	15.21	1.922
Experience in Years	126	1	22	7.88	5.509
Family annual Income	126	36000	3600000	725983.47	458690.321

Table 2 shows the place of job of the respondents. It is clear from the table that 51% of the respondents are doing job in rural areas and 49 % perform their duties in urban areas.

Locality of Job	Frequency	Percent
Rural Area	370	51.0
Urban Area	356	49.0
Total	126	100.0

Table 3 shows the percentage distribution of the employed women with respect to their marital status. Table shows that 35.8 percent are unmarried, whereas 64.2% are married employed women.

Status	Frequency	Percent
Un-Married	260	35.8
Married	466	64.2
Total	126	100.0

Estimation of the Multinomial Logistic Model

The dependent variable employed women average annual earning, lowest through 20000 with rural area and un-married employed woman is the reference category.

Table 4. Estimation results of Multinomial Logistic regression Salary Groups BStd. ErrorSig.

-40000

Intercept -11.833 2.923 .000

SCHOOLING .366 .078 .000

Log_Annual_FI 1.009 .515 .050

Exp_Years .557 .077 .000

Rural Area -.593 .286 .038

Un-married -.059 .279 .833

-60000

Intercept -30.728 3.805 .000

SCHOOLING .585 .101 .000

Log_Annual_FI 3.429 .635 .000

Exp_Years .750 .081 .000

Rural Area -1.480 .337 .000

Un-married .058 .339 .865

-80000

Intercept -46.798 4.913 .000

SCHOOLING .556 .120 .000

Log_Annual_FI 6.049 .804 .000

Exp_Years .785 .083 .000

Rural Area -1.942 .396 .000

Un-married .247 .401 .537

and above

Intercept -59.824 6.521 .000

SCHOOLING 1.217 .141 .000

Log_Annual_FI 6.109 1.051 .000

Exp_Years .903 .089 .000

Rural Area -2.429 .516 .000

Un-married -.008 .543 .988

Current study uses Multinomial logistic regression technique to assess the nexus of employed women earnings and socio-economic factors. Results are obtained by using statistical package for social sciences package (SPSS). Regression results indicate that education, experience, household annual income, locality of job are important factors determining employed women earnings in education sector of district Peshawar KPK. Results show that for all categories of dependent variable, a one-year increase in education has a positive impact on earnings. The impact of education increases as the category of income increases. This shows a positive and upward sloping relationship between education and earnings.

Similarly result shows that annual family income excluding employed women earnings and experience of the employed women have a positive effect on all of the categories of the earning groups and has a significant impact on earnings. Results also confirmed that women doing their duties in urban areas are earning more than rural areas employed women for all the categories of employed women.

Marital status of the employed women showed insignificant results for all the categories of earning groups which shows that marital status in the study area has not much impact on the earnings of employed women in the study area.

Conclusion

The current study investigated the relation of socio-economic factors and employed women earnings in education sector of district Peshawar in KPK using Multi Nominal Logistic regression technique. Results revealed that employed women earnings are largely affected by factors like education, family income, experience and locality of job in the study area, and marital status of the women has insignificant impact on earnings of the employed women. A number of policy initiatives could be used to increase earnings of female labor force. These efforts may include increasing labor market flexibility to allow more women in employment in the formal sector and help them in moving from the informal sector. Also the improvement of infrastructure need addressing so other constraints are removed to job creation for women. Conducive environment for women at workplace is needed. Facilitation for women to enter the labor force and earn money for their families need to incorporated into existing and future policies. Finally, higher investment in education, can also lead to higher earnings by enhancing female stocks of human capital.1

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