Page 1 of 5
Journal for Studies in Management and Planning
Available at
http://edupediapublications.org/journals/index.php/JSMaP/
e-ISSN: 2395-0463
Volume 02 Issue 8
August 2016
Available online: http://edupediapublications.org/journals/index.php/JSMaP/ P a g e | 505
The Relationship between Income and Fertility in Manmunai
North Divisional Secretariat
Kajenthini Ganeshamoorthy ; Mr.Panchadsharam Vinoth
Department of Economics, Faculty of Commerce and Management, Eastern University of Sri Lanka
Department of Geography, Faculty of Arts and Culture, Eastern University of Sri Lanka
vpkaji@gmail.com ;vinotharan.89@gmail.com
Abstract
Increasing income should lead to not only
the increase the quality of children but
also increase the quantity of children. In
this context, the main objective of the
present study is to examine the impact of
family income on fertility. This study
utilized the primary data, which were
collected through a survey of mothers in
the area of Manmunai North divisional
secretariat, Batticaloa District. The
survey was conducted among 100 mothers
who were selected by using random
sampling method. To examine the impact
of family income on fertility, number of
children were taken as an indicator of
fertility of mothers. The data were
analyzed by the multiple regression model.
The results found that family income do
not associate with fertility. Further, other
factors namely family Plane, primary
education of husband, secondary
education of husband, husband’s age and
husband’s occupation impacted positively
on fertility. Conversely, mother’s
occupation negatively related with fertility.
Moreover, the study found that other
variables are not significant with fertility.
Entirely, the study revealed that there is no
relationship between family income and
fertility and family income is not impact on
fertility in Manmunai North Divisional
Secretariat.
Key words: Fertility, Family income,
mothers, children
1. Introduction
“Most of the increased expenditures on
children would consist of an increase in
the quality of children. Economic theory
does not guarantee that the quantity of
children would increase at all, although a
decrease in quantity would be an exception
to the usual case” (Becker, 1960).
Increase in income should lead to not only
the increase the quality of children but also
increase the quantity of children. Anyhow,
according to Becker (1960), increase in
income would increase both the quality of
children and quantity of children though,
quantity elasticity should be small than the
quality elasticity. In order to Becker
(1960), we can point out that family
income induce to enhance the quality of
children than quantity of children. Increase
in income should lead to increase the
family size. People are induced to marry
earlier by an increasing in income
(Maithus in Becker, 1960). “Fertility is
often higher in poorer families within a
society and across countries those with
higher average fertility tend to have lower
average income” (Paul, 2005). Similar to
Paul, Scholz and Ananth (2009) state
Page 2 of 5
Journal for Studies in Management and Planning
Available at
http://edupediapublications.org/journals/index.php/JSMaP/
e-ISSN: 2395-0463
Volume 02 Issue 8
August 2016
Available online: http://edupediapublications.org/journals/index.php/JSMaP/ P a g e | 506
“Low-income families have more children
than high-income families”, According to
this finding when family income occur
lower level, which would lead to higher
fertility than higher income earnings
family.
Thus in this background, a question arise
that do family income induce the fertility
or not? Hence, this study tries to examine
the relationship between family income
and fertility. In this context, the objective
of the present study is to examine the
impact of family income on fertility.
Literature on fertility had revealed that not
only family income but also another
factors also determine the fertility. For
instance, the study mentioned that the both
frequency of coition and age at marriage
determine the fertility (Becker, 1960 in
Mithus). It argued also abortion or
abstinence delayed marriage lead to
societies to be control the number of births
and deficient knowledge of contraception.
Wife’s potential income negatively related
with fertility, in contrast husband’s
potential income insignificant with fertility
(Eileen and Phyllies, 1982). Like that Paul
(2005) revealed that whereas women’s
family has own assets and land, there
fertility is higher. Conversely lower
fertility prevails when women has become
educated. In addition, his study found out
also higher fertility prevail among poorer
families, they have lower average income.
Source, which associated with earning
family income, it alters the economic
opportunities of parents. Then parents can
ensure their sacrifice to have another child
or not. It impacts on fertility in different
ways that either through stimulate the
fertility or discourage the fertility. Some
sources of income guide to increase
fertility conversely some source of income
lead to control the fertility among
societies. Further lower fertility can be
achieved through higher values of
women’s time (Paul, 2005 in Mincer,
1963).
Vijay et al (2009) conducted a study on
significant determinants of fertility and
incomes of households. They found out
that the fertility, age of the women, age of
the husband, schooling of parents
determines the incomes of household when
fertility is treated as endogenous. Further
they identified that non- farm self- employed and agriculture households
impact negatively and significant on
fertility. Similarly, background
characteristics like place of residence,
ethnicity and religion affect the fertility of
household. Thus previous studies have
revealed that most of the factors namely
age, education, valuable time, etc
determine the fertility.
2. Methodology
This study relies on primary data, which
were collected through a survey of
mothers in the area of Manmunai North
divisional secretariat, Batticaloa District.
A Structured questionnaire was used to
collect data. The survey was conducted
based on simple random sampling method.
Among the total population size of 92,753
which comprising 25,546 numbers of
families. This study involved 100
respondents among mothers who reside in
Manmunai North divisional secretariat,
Batticaloa District. Sample were selected
from twenty Girama Niladari Division
comprising most of population compare to
other twenty-eight G.N Division. To
examine the impact of family income on
fertility, number of children were taken as
an indicator of fertility of mothers. To
examine the objective of this study, it has
tried to analyze via the multiple regression
model, and assumed as follows
Page 3 of 5
Journal for Studies in Management and Planning
Available at
http://edupediapublications.org/journals/index.php/JSMaP/
e-ISSN: 2395-0463
Volume 02 Issue 8
August 2016
Available online: http://edupediapublications.org/journals/index.php/JSMaP/ P a g e | 507
Y = β0+ β1 lnFI+ β2MO + β3MMA+
β4HMA + β4lnMW + β5EH + β6HO+
β7SA+ β8 D4+ β9FP + μi
Where,
Y: Number of children which can expect
to have over mother’s lifetime specific
fertility.
FI: Family Income (Rs)
MO: dummy for mother’s occupation (1 =
if she is working, 0 = otherwise)
MMA: Mother’s age when she married
HMA: Husband’s age when he married
MW: Mother’s Level of Education
EH: Husband’s Level of Education
HO: Husband’s occupation
SA: Dummy for Saving of Household
FP: Dummy for Family Plan
3. Results and Discussion
The following table represents the results of this study.
Table 6.1: Results of Multiple Regression Analysis
Variables Coefficient t statistics p statistics
Family income 0.038286 0.10 0.918
Mother’s Occupation -0.291933*** -2.42 0.018
Mother ’s age when she married -0.50345 0.15 0.878
Husband’s age when he married 0.002978*** 2.62 0.010
Mother’s Level of Education
(Primaryeducation)
-0.280067 -0.88 0.383
Mother’s Level of Education (Secondary
education)
- 0.501156 -2.22 0.29
Mother’s Level of Education (Higher
education)
-0.296468 -1.05 2.98
Husband’s Level of Education (primary) 0.704790** 2.13 0.036
Husband’s Level of Education (secondary) 0.474604** 2.06 0.043
Husband’s Level of Education (Higher) 0.284613 1.25 0.216
Husband’s occupation: Agriculture 0.408949 1.73 0.88
Husband’s occupation: Government 1.3257 2.42 0.18
