Zahoor Hussain Javed*, **Aysha
Asif
* Assistant Professor, ** M.Phil Scholar
Department of Economics, GC University, Faisalabad ,
Email:
zahoorhj64@yahoo.com
Cell# 0092-3006501785
Fax # 0092-41-9200671
Abstract:
The study investigates relationship
between poverty and role of feminine headed families. The binary Logistic
regression and mean techniques are used to find the factors that influence the
level of poverty. Even though, mean variables
analysis shows that total monthly income and consumption of the family are
insignificant but there is no differentiation sandwiched between means of both
variables of guy headed families and feminine headed families. Total value of assets
own by family for feminine headed families and guy headed families are
significant and there difference between means of both variables of guy headed families
and feminine headed families. In
addition, the consequences of binary logistic regression model demonstrate that
education has the accurate predictable sign but is not significant. The probabilities
of the household show that poverty increase with boost of family size and consumption
expenditures and decrease with increase of income and employment. Furthermore
study explores that there is negative and significant relation between head of family
and poverty. Feminine headed families are more liable toward poverty than guy
headed families, this is so because feminine head families
support more dependants and have better propensity to kids compared to another sort
of families.
Key words: Feminine family, headship, poverty, Faisalabad , Pakistan
Introduction:
This research investigates that women
are poor as compare to men, owing to raise of feminine headed families, inequality
of sexual characteristics, and restriction to access of land ownership, restriction
to get education and in other productive activities. Furthermore, the raise of
involvement of women in the in formalized economomics activities, create conflicts
among the families and other relatives. Consequently, well-being of females is
affected negatively and they sustain poor (Chant 1997; Bridge 2001; Moghadam,
2005).
Globally, it is acknowledged that feminine heads of families are on the
increase and higher poverty rates among these families (Buvinic et. aI., 1978;
Folbre, 1991; Fields and Casper, 2001). The greater parts of the women are
faced the problems of poverty and they can not settle down their problems
individually. In the Asia over the past two
decades, the poverty among women has been increased at large scale in spite of
economic pay back by developing countries. The same level of nutrition,
satisfactions, pleasure, health, education, employment and access to productive
resources are not enjoyed by women as men do. The policies regarding alleviation
of poverty and infrastructures programmes are repeatedly formulated on the
foundation of the household as the unit of assessment; therefore, the analysis
of poverty in feminine headed families focuses on the household level, rather
than the individual level. Thus feminine headed families do not exclude the men
living in these families (Fuwa 1999; Judithand Lloyd 1992; Quisumbing et al.
1995).
In Pakistan ,
the information regarding poverty of women is quite inadequate and not much explores
the status about feminine-headed families. Pakistan is generally a patriarchal
society. Nonetheless, feminine headship has also acquired some visibility,
apparently, as a residual category. In Pakistan
percentage distribution of families
by gender headship is 6.4% feminine headed and 93.6% guy headed in the year of
2006-07 and 9% feminine headed families and 91% guy headed families in the year
of 2007-8[1]. Total labour force participation is 70.2%
from which 70.2% men and 22.8% women in the year of 2007-08. Total 8.14 million
people in Punjab employed from which 7.20 million
guys and only 0.94 million feminine are employed[2]. Total 56.6 % respondents had no personal
income from which 33.3 % are guys and 78.7 % are feminine; in Punjab
total 62.2% respondents had no personal income from which 37.5% were guys and
84.9% were feminine.[3]
Few research
questions regarding feminine headed families and guy headed families are
constructed as.
H1= what
are the reasons for the pervasiveness of feminine headed families;
H2 = what
are the reasons of the poverty of families;
H3 = Why
feminine headed families are poor
then gentleman headed families;
H4 = are feminine headed families poorer because
their low level of education, occupation, income, physical infrastructures,
dependence ratio or any other reason.
The answers
of these research questions are examined the status of poverty in feminine
headed families and guy headed families.
In this research
investigation feminine headed families are defined as those feminine of families
where no adult guys are present owing to separation, disconnection, immigration,
non exodus or widow or any other grounds and facts. This research defines head of families in
economic rather than cultural terms. That is why a person is regard as head of families
if he or she has major economic responsibility for his family because use of the
typical UN description describes the unacceptable consequences that there are
no feminine heads of families among married women at all. More clearly, the
four types of economic household tasks, which qualifies women as head of the families.
They are described as below:
Category 1. In this type feminine has the full
economic responsibility for her family due to non availability of adult guy
members;
Category 2. Only the
women in the family are wage earner;
Category 3. In the family feminine earnings is more than
that of any other guy or feminine;
Category 4. Wages of
every one feminine in the family go over the joint earnings of all guys in the
family. (Mohiuddin. Y, 1989)
The foremost purpose of this paper is to find that; either there is any remarkable
relation between feminine headed families and poverty or not.
Review of Literature:
Feminine
headed families have been a foremost unit of analysis in the literature. The
research investigates that guy-headed household are rich as compare to feminine-headed
families.
This is so because guy-headed families as superior
access to employment and having higher earning capabilities, by professional
segregation, sexual characteristics, wages discrepancy and job oppturtunities. Moreover, females have a greater tendency to encompass
children as well as the burden of more dependents to support. (Roosenhouse1989,
ILO 1996, Bridge1997, Fuwa1999). Previous study in this regard depicts that
women more or less everywhere are deprived relative to men in their access to resources,
credit, employment, and education. These disadvantages are primarily caused by
their low qualifications which lead them to be segregated into unskilled and
low paid job as well as lower economic status. Additionally, the heads of feminine-headed
household in certain categories, namely, widowed, separated or divorced are
unable to provide significant economic support to their household and therefore
it is more difficult to attain the identical height of wellbeing as achieved in
guy-headed families Consequently, it is often supposed that feminine-headed families
are poorer than guy-headed families, (Folbre, 1991; United Nations, 1996; World
Bank, 2001; Busapathumrong, 2006; Joshi, 2004).
Poverty: both in terms of returns and everyday expenditure have amplified
in Pakistan .
The frequency of poverty has increased amongst the feminine headed families as match
up to to guy headed families The foremost grounds for present boost in poverty owing to slight assembly of human capital, less
approach to manual labor market and resources, injustice inside and outside dwelling,
socio-cultural manners, and egotism of macroeconomic strategies to sexual
characteristics issues. This research investigates that education above the
primary level is significantly influenced worth, returns and reduced poverty
level of the family. The results of logit regression model demonstrate that
poverty is considerably associated with the schooling, level of employment,
asset possession and professional selection Siddiqui, and Hamid, (2003).
As mentioned above, most studies concluded that
feminine headed families are poor when compare with guy-headed families. Nevertheless,
some studies shows that feminine headed families are not at all times worse off
than guy headed families. For instance, a study in Vietnam found that feminine-headed families
are not worse off economically than guy-headed families. The case of Vietnam
suggests that feminine headship families are not the poorest families (Loi,
1996).
Chaudhry (2003) measured education variable
with the help of education codes. Education codes were in the farm of 0, 5 and
10 where 0 was assigned to illiterate members, 5 for educated up to secondary
level and 10 up to college university level. Sum of these points was divided by
the household size. This may lead to measurement bias. There existed a wide gap
between illiteracy and secondary education. It would be better to approximate
education in educational years. However, findings revealed that education codes
were also negatively related with poverty.
Data
and Methodology:
The central point of this study is to
detect the association between poverty and role of feminine headed families. Owing
to lack of resources like money and valuable resources, the investigation of
research is focused only and only to District Faisalabad. Regarding the nature
of study primary data source is utilized. There are five Thesils in District
Faisalabad, which is based on five Thesils. From these tehsils, two Tehsil
namely Faisalabad
and Tehsil Jaranwala are selected for investigation. Data is collected by
simple random method. A complete interview agenda is organized to attain its
objectives and goals. The randomly data is collected by survey of household of 80
feminine headed and guy headed families from recommended thesils. The investigator
gets interview of every one of the respondents personally. The researcher togetherness
information of all households as a whole, such as personal profile, education,
marital status, family size, occupation, health facilities, employment, family
income, consumption, status of house, and saving activities. In this regards Logistic
Regression Analysis technique is used to find the required results.
Level of age of the family head, sexual
characteristics of the family head, schooling, and dependency ratio, level of
family income and level of family spending are taken as exogenous variables. The
level of age of family head is calculated on year's basis. The family head's sexual characteristics is
determined as qualitative variable that is gender (guy =
1, feminine = 0). Education is taken in
form two dummies. Endogenous and earners variables are calculated on basis of the
number of persons who earn in a family.
In the framework of logistic regression assessment, endogenous variables
have the value of zero for not deprived families and 1 for deprived families. As a result, O.L.S. cannot use to estimate the
analysis of parameters thus; the maximum likelihood method is used for
estimation. Conventionally, qualitative models are used to detect the results:
They are based on: (1) logit technique (b) probability approach (c) probit approach.
The Linear probability approach provides heteroscedasticity trouble and there
is no assurance that probability will lie sandwiched between 0 and 1. The most significant
thing is that in this representation probability is linearly associated with exogenous
variables. Logit and probit techniques are used to shun from this problem. In
these techniques probability remained between 0 and 1. However, probability is not linearly associated
with exogenous variables. Probit model is more sensitive for normality
assumption whereas logit model supposes that it has logistic sharing. In nut
shell, logit technique is employed in the this research to get required results_(Javed.et.al, 2011).
The Logistic Model:
The logistic model relates the independent variable, X,
to the rolling mean of the dependent variable Y. The
formula may be written as;
Y = e c
+ d X / 1+ e c + d
or
Y = 1/ 1+ e -
c +
d X
Where P is the probability of a 1, the
mean of Y), e is the base of the natural logarithm c and d are called the
parameters. The value of c provides Y when X is zero and d shows
adjustment when one unit changes take place in X and b weights in logistic
regression. Because the relation between X and Y is nonlinear, therefore d
does not have a clear-cut explanation in this model.
In logistic regression, the dependent variable is a logit,
which is the natural log of the odds, that is,
Ln (odds) = logit ( Y) = Log( Y/1-Y)
So a logit is a log of odds and odds are a function of P,
the probability of a 1. In logistic regression, it can be found out
Logit (Y) = c + dX
logit(P) = a + bX,
This is supposed to be linear, that is, the logit is
guessed to be linearly related to X,. As a result there is an ordinary
regression hidden in there. Nevertheless, in theory ordinary regression with
logits as dependent variable,
Ln (Y/1-Y) = c + d X
Y/ 1-Y = e
c +
d X
Y = e c + d X/
1 + e c + d X
The
simple probability is this unattractive equation. If log logits are linearly
related to X, then the relation between X and Y is nonlinear (Gujarati, 2004).
Results and
Discussion:
Table 1 revealed the
test for comparison of means of total income of the family per month (Rs.), consumption
of the family per month (Rs.), worth of property possess by family (Rs.), gold 's worth hold by family (Rs.), vehicle's
worth possess by family (Rs.), equipment's worth own by family (Rs.) for feminine headed families
and guy headed families.
Table 1: Comparison of Means of Selected
Variables for Female Headed Families and Male- Headed Families.
|
Variables
|
Mean
|
t-stat
|
Sig.
|
|
|
Monthly income of the family (Rs.)
|
feminine headed
|
15590.00
|
-1.991**
|
.051
|
|
Guy headed
|
24442.50
|
|||
|
Consumption of the family per month(Rs.)
|
feminine headed
|
13476.00
|
-1.457
|
.150
|
|
Guy headed
|
16355.00
|
|||
|
Property worth possessby family
(Rs.)
|
feminine headed
|
605800.00
|
1.497
|
.139
|
|
Guy headed
|
377500.00
|
|||
|
Worth of gold possess by family(Rs.)
|
feminine headed
|
40590.00
|
-2.525***
|
.014
|
|
Guy headed
|
127050.00
|
|||
|
Worth of vehicle possess by family(Rs.)
|
feminine headed
|
37640.00
|
-2.025**
|
.047
|
|
Guy headed
|
147950.08
|
|||
|
Total worth of piece of equipments possess by family(Rs.)
|
feminine headed
|
28656.00
|
-2.118**
|
.038
|
|
Guy headed
|
46005.00
|
|||
***=1 percent level of significance, **=5
percent level of significance*=10 percent level of significance
Test of Hypothesis:
Assumption No.1
Ho = There is no difference of means of family’s monthly income for guy headed
families against feminine headed families
H1 = There is difference of means of family’s monthly income for
guy headed families versus feminine headed families
The proposition is examined through the family’s monthly income of the
family heads. It is found that the mean value of monthly income of the family
of feminine headed families is higher and significant, so there is significant
difference between means family’s total monthly income of feminine headed and guy
headed families.
Assumption No.2
Ho = There is no difference of means of monthly consumption expenditure of
guy headed families against feminine headed families.
H1 = There is difference of means of monthly consumption
expenditure of guy headed families against feminine headed families.
The proposition is examined through the monthly consumption expenditure
of the heads. It is found that the mean value of monthly consumption of the
family of guy headed families is higher than female headed families but not
significant, so there is no difference between means of total monthly family
consumption expenditure of guy headed and feminine headed families.
Assumption No.3
Ho = There is no difference of means of total family’s worth of property of
feminine headed families against guy headed families.
H1 = There is difference of means of total family’s worth of
property of feminine headed families against guy headed families.
The proposition is tested through the total family’s worth of property of
the heads. It is found that the mean of total value of property own by family
of the family of feminine headed families is higher and insignificant, so there
is no difference between means of total value of property own by family of feminine
headed and guy headed families.
Assumption No.4
Ho = There is no difference of means of total family’s worth of gold of guy
headed families against feminine headed families.
H1 = There is difference of means of total family’s worth of
gold of feminine headed families versus guy headed families.
The proposition is tested through the total family’s worth of gold of the
heads. It is found that the mean of total value of property own by family of guy
headed families is higher and significant, so there is difference between means
of value of gold own by family of feminine headed and guy headed families.
Assumption No.5
Ho = There is no
difference of means of total family’s worth of automobile equipments of guy headed
families versus feminine headed families.
H1 = There is difference of means of total family’s worth of
automobile equipments of guy headed families against feminine headed families.
The hypothesis is tested through the total family’s worth of automobile
equipments of the heads. It is investigated that gay headed families have
higher mean of total value of automobiles
equipments than female headed families and significant, so there is difference
exist between means of total worth of automobiles equipments own by family of guy
headed and feminine headed families.
Assumption No.6
Ho = There is no
difference of means of whole family’s worth of appliances of guy headed families
against feminine headed families.
H1 = There is difference of means of total family’s worth of appliances
of feminine headed families against guy headed families.
The proposition is tested through the means of total value of price of
equipments hold by family of the heads. It is found that the mean of total
family’s electrical devices value of guy headed families is higher and
significant, so there is difference between means total family’s worth of
appliances of guy headed and feminine headed families.
Binary Logistic Regression Analysis:
The results of Logistic Regression in the
regard of the Poverty are presented for feminine and guy-headed families in
Table 2.
The exogenous
variables are:
X1= Head of the family's age (in years)
X2 = Head of the family's education (in years);
X3 = Level family income
X4 = Level of consumption
X5 =Location (=town, 0
= otherwise)
X6 = Level of family size
X7 = status of headship
(= 1 if guy headed, 0 = otherwise).
Table 2: Determinants
of Poverty: A family Analysis
Results of Binary Logistic Regression
Analysis
|
Variables
|
Coefficients
|
S.E
|
Sig.
|
Exp(B)
|
|
Age
|
0.056
|
0.051
|
0.274
|
1.057
|
|
Education
|
- 0.014
|
0.095
|
0.884
|
0.986
|
|
Place
|
-0.948
|
1.064
|
0.373
|
0.388
|
|
Log of Family Income
|
-26.72**
|
8.713
|
0.002
|
0
|
|
Log of consumption
|
23.759***
|
8.317
|
0.005
|
2.08E+10
|
|
Family Size
|
1.86***
|
0.554
|
0.001
|
6.427
|
|
Headship
|
2.539**
|
1.203
|
0.035
|
12.667
|
Endogenous
Variable = assumed the value of 1 if poor and 0 otherwise.
***Indicates that the coefficients were
significant at 1 percent level.
**Indicates that the coefficients were
significant at 5 percent level.
*
Indicates that the coefficients were significant at 10 percent level.
Endogenous variable has
the value of 1 for a family who lives below poverty line and 0 otherwise. In this research family head’s age of the family
head’s sexual characteristics, the family head’s education level, size of family,
returns of family and spending of family are used as exogenous variables. Outcomes
indicated that family returns, spending, education, dependency ratio and
headship status are significant in determination of poverty. The research
analysis reports show that schooling and family returns are negatively related
with the probability of poverty.
There is negative relationship between
dependency ratio and poverty as the dependency ratio increase the poverty decreases. There was negative relationship between volume of family returns
and poverty as family returns increase the poverty decrease. This study shows positive
relationship between level of consumption of the family and poverty. As well as
monthly consumption of the family increases the probability of poverty also
increases.
Education attainment
of the household head asserted negative relationship with the probability of
poverty. Probability of poverty among sampled families decreased with the
increase in educational years of household heads. Thus poverty is less in a household
where the head completes primary education or above than in one where he or she
is illiterate. The results of this study match up with the findings of
The variable age
possessed the correct expected sign but is not significant. In many families
there was more than 1 earner so age of the household head may not matter so
much.
It was concluded that families with guy head,
educated heads, higher dependency ratio, sufficient family income and
controlled consumption were less likely to be poor.
Conclusion:
The study is based on feminine
headed families and their association with poverty. Compare mean analysis and logistic
model are used to detect the association. Compare mean is used for difference
variables to compare their means. Significance level is checked by T-test. The
factors that affect the probability of poverty are tested by the binary the
logistic regression. In compare mean analysis the family’s whole monthly
returns (Rs.), the family’s whole monthly consumption (Rs.) are insignificant
and there is no disparity between means of both variables of feminine headed families
and guy headed families. Family’s total value of property (Rs.), family’s whole
worth of gold (Rs.), family’s whole worth of automobile equipments (Rs.), family’s whole worth of electronics equipments
(Rs.) for feminine headed families and guy
headed families were significant and there is
disparity exist between means of both variables of guy headed families
and feminine headed families.
The outcome of binary logistic model demonstrated
that the level of age and level of education variables have the accurate predictable
sign but these are not significant. In abundant families there is more than 1
earner. The probabilities of the family on the subject of the poverty increase with
size of family, and level of consumption. The probability of the family regarding
with the decrease of poverty is associated with augment of income and
employment. There is negative and significant relation between worth of head of
household and poverty. Feminine headed families are extra vulnerable in the
direction of poverty than guy headed families. Feminine headed families are not
as good as because they prop up more dependants, i.e. have a upper ratio of unemployed
persons and a larger propensity to have children. Furthermore, feminine heads
have fewer assets, inferior access to remunerative jobs a lower earning
capacity possibly caused by occupational isolation, gender earnings discrepancy
and unemployment, and productive resources than guy-headed ones.
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