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ABSTRACT
Migration has long been an important livelihood
strategy for the people of Bangladesh. Choice
of destination and levels of benefits and risks,
however, vary significantly, according to the
economic and social power of the migrant. The
aim of this study is to identify the various influential
factors on monthly income of male migrants. Therefore,
the data of this study was collected from 420
respondents by purposive sampling technique and
interview method in Chapai-Nawabgonj Pourasava,
Bangladesh. Multiple Classification Analysis (MCA)
has been used in this study. It was observed that
people migrate to certain places due to economic
reasons and to improve their life style. The results
showed that the effect of occupation has been
found to be the strongest factor and educational
level is the second strongest and is a positively
significant influence for explaining the variation
on monthly income for male migrants among the
selected demographic and socio-economic variables
in both cases. So, people migrate to new places
with the hope of improving their social and economic
status.
Key Words: Socio-economic and demographic
variables of Migrants, Multiple Classification
Analysis (MCA), Bangladesh.
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INTRODUCTION
Migration is the third basic
factor affecting change in the population of an area:
the other two factors are births and deaths. The importance
of migration in affecting the growth and decline of
populations and in modifying the demographic characteristics
of the areas of origin and the areas of destination
has long been recognized. It is also an important element
in the growth of population and the labor force of an
area. It has long been an important livelihood strategy
for the people of Bangladesh. Whenever the population
rose to such an extent that people could no longer secure
a livelihood, they are obliged to migrate elsewhere.
Even today, both poor and better off people pursue migration
as a livelihood strategy in Bangladesh.
Migration stands out among the
fundamental topics of demography both in the number
of ways it is manifested and defined. Two crucial dimensions
of migration are space and time. In order to separate
migration from other spatial movement, operational definitions
invariably set lower limits. The most frequently imposed
lower limits are geo-political boundaries. Moves within
prescribed boundaries are not migration while moves
across boundaries are. These boundaries are often chosen
as proxies for spatial distance.
However, very long distance
moves may fall within established boundaries. Short
distance moves may involve crossing national boundaries.
Migration is a form of geographical
or spatial mobility involving a change of usual residence
between clearly defined geographical units. According
to the UN Multilingual Demographic Dictionary "Migration
is a form of geographical mobility or spatial mobility
between one geographic unit and another generally involving
a change in residence from the place of origin or place
of departure to the place of destination or place of
arrival".
Johnston et al (2000:504) define
migration as permanent or semi-permanent change of residence
by an individual or group of people. Migration means
physical movement of people from one place to another
for the betterment of life. Rural-urban migration is
the migration of people from rural areas into cities.
It is one of the vital events that alter the size of
the population of sub-regions in a country.
Migration can occur as result
of push and pull factors. Push factors are those, which
force a person to move. These can include drought, famine,
lack of jobs, over population and civil war. Pull factors
are those, which encourage a person to move to leave
the place of origin. These include a chance of a better
job, better education, better standard of living, good
physical facilities etc. Furthermore, urban pull factors
- conditions encouraging people to move to the cities
- tend to be similar worldwide, and include prospects
of earning higher wages, a perceived demand for labor
and better social services. Push factors - conditions
encouraging people to leave the origin - vary considerably
among regions and countries, as well as among social
groups, and between men and women.
No one will ordinarily like
to leave the place of his birth; friends as well as
kind, unless that is absolutely necessary. Some factors
influence the causes which affect the migration such
as- Economic factors, Geographical factors, Social factors,
Demographic factors, Political factors, Religious factors,
Industrialization.
Many studies have been carried
out on migration by individuals as well as by organizations.
They studied migration pattern and socio-economic structure
in different times. Recent research strongly emphasizes
the role of social contacts, social networks, and social
capital in perpetuating the flow of migration within
spatial settings, social groupings, or identity groups
(Massey et al., 1987; Boyd, 1989; Portes and Bach, 1985;
Shah, 1998).
People migrated to cities and
towns because they are attracted by livelihood opportunities.
Studies on migration have established a positive association
between levels of infrastructural development of a region
and the magnitude of out-migration (CUS, 1990). Regardless
of skill, the migrated population can find diversified
livelihood opportunities with various incomes in the
towns and cities.
Therefore the main objectives
of this study are:
i) to study the living status, that is, the socio-economic
and demographic characteristics of the migrants and
ii) to assess the contribution of some demographic and
socio-economic factors on monthly income before and
after migration, for male migrants.
This paper is structured as
follows: Sources of data are included in section 2.
Section 3 contains methodology of this study. Results
and discussion are described in Section 4. Section 5
provides the conclusion and lastly, recommendations
are in Section 6.
DATA AND METHODOLOGY
Sources of Data
To fulfill the aforementioned objectives, the data of
this study was collected from the Pourasava of Chapai-Nawabganj
district of Bangladesh by purposive sampling technique
and direct interview method. The socio-economic and
demographic characteristics are considered at the time
of data collection.
Methodology of this Study
In 1934, Yates developed the multiple classification
analysis (MCA). It was later expanded and detailed by
Anderson and Bancroft in 1952. In 1963, the computerized
MCA programme was prepared by a group of researchers
at the Survey Research Center of the University of Michigan.
Multiple classification analysis requires one dependent
variable and two or more independent variables. The
dependent variable can be either a continuous or a categorical
variable but all the independent variables must be categorical
variable.
The MCA model can be written
as
Yijk
=  +
ai + bj +ck+ ..................+
eij
Where,Yijk
= The value or score on the dependent variable
=
Grand mean of the dependent variable
ai = The effect of the membership in the
ith category of predictor A
bj = The effect of the membership in the
jth category of predictor B
ck = The effect of the membership in the
jth category of predictor C
eijk = The error term related with Yijk score
of the individuals
In this model, monthly income
(before and after migration) is considered as a dependent
variable and age , religion, education, occupation,
type of family and number of family members are treated
as independent variables.
RESULTS AND DISCUSSION
Age is the most important variable
not only in the study of demographic analysis but also
in social research. It was found from Table 1 that maximum
number of migrants has age more than 35 that is 68.5%.
It noticed that 86.2% migrants are Muslims and 13.8%
are Non-Muslims. It was also found that 19% completed
secondary education and 80.2% had higher secondary and
above education. The occupation established that 57.4%
of migrants had involved in service and 32.1% had engaged
in business and the rest being in another category.
Most of the migrants, 81% and 19%, had lived with a
single and joint family respectively. It also observed
that 82.6% and 15% of migrants had been living with
less than 4 and 4-5 family members respectively.
Table
1
In this research, we investigated the intensity of influence
of all explanatory variables with our selected dependent
variable in different cases. For this investigation,
Multiple Classification Analysis (MCA) is used, which
is made for the contribution of independent variables
with our selected dependent variables. The dependent
variables are monthly income of migrants before and
after migration. Age, an important factor, influences
on monthly income.
Before migration, a migrant's
age belongs to the age between 30 to 35 years which
we have adjusted as mean of monthly income at TK. 10235.79.
The results show that migrants who belong to the age
interval 30 to 35 years have higher monthly income than
migrant's age that belong to less than 30 years and
more than 35 years respectively. It is found that the
monthly income for Muslims and Non-Muslims family has
a very small difference.
The adjusted mean of monthly
income of migrants who have attained more than higher
secondary education is TK. 10111.46. It is observed
that monthly income of higher secondary and above is
more than that of other categories of education. The
adjusted mean of monthly income for service, business
and other occupations are TK. 9295.26, TK. 11465.14,
and TK. 8613.43 respectively. It is seen that monthly
income is higher for those who are engaged in business.
It shows that monthly incomes
of single family and joint family are not much difference.
The adjusted mean of monthly income is TK. 9955.60 for
those who have less than four family members.
The proportion of variance of
monthly income explained by occupation is the highest
(unadjusted value,  2=0.259
and adjusted value, ß2=0.266) among
all other variables while the proportion of variance
explained by type of family is the lowest (unadjusted
value, 2
=0.035 and adjusted value, ß2 =0.001).
It is observed that the significance of educational
level has been found to be the second strongest influence
for explaining the variations on monthly income among
the included variables in the case of before migration.
The proportion of variance explained by migrant's education
is 2
=0.086 and ß2=0.092.
Table
2
Education
of migrants has directly affected monthly income. The
indirect effects of education on monthly income through
occupation and numbers of family members are 0.100 and
0.001 respectively. Occupation has a direct affect on
monthly income. Migrant's age has the direct effect
on monthly income and also has an indirect effect through
occupation, at 0.058. Migrant's age and occupation has
a positive association. Type of family is directly affected
on monthly income.
Table
3.
Again in the case of after migration,
migrants age belonging to the age between 30 to 35 years,
have a mean adjusted monthly income of TK. 10189.24.
We detect that the mean adjusted monthly incomes are
TK. 9987.49 and TK. 9868.18 for Muslim family and Non-Muslim
family respectively. Migrants who have achieved more
than higher secondary education have a mean adjusted
monthly income of TK. 10155.47.
Occupation is an important factor
that affects monthly income of migrants. It is found
that those who are engaged in business have the highest
adjusted mean of monthly income of TK. 11465.14. Among
the socio economic factors, type of family is another
influential factor that is differentiating migration.
The adjusted mean of monthly
incomes are TK. 9921.30 and TK.10180.59 who are living
in a single and joint family, correspondingly. The mean
adjusted monthly income is TK. 10030.45 for those who
has less than four family members. On the other hand,
the adjusted mean of monthly incomes are TK. 9676.57
and TK. 9644.47 for families that have four to five
and more than five family members respectively.
The proportion of variance in
monthly income explained by occupation is the highest
(unadjusted value, 2
=0.262 and adjusted value, ß2=0.269) among all
other variables while the proportion of variance explained
by type of family is the lowest (unadjusted value, 2
=0.013 and adjusted value, ß2=0.025). Educational
level is found to have a very strong and positive influence
on migration. The strength in explaining the variability
by this variable is 2
=0.091 and ß2=0.091.
In this study there are various
variables that have a direct and indirect effect on
monthly income. Educational level has been found to
be one of the strongest factors that have a direct and
indirect effect on migrant's monthly income. Education
has indirect consequences on monthly income through
occupation status and numbers of family members are
0.1014 and 0.0022 correspondingly. Migrant's age has
a direct effect on monthly income. The indirect effect
on monthly income through occupation is 0.0584.
Type of family is one of the
influential factors on monthly income. It has a direct
influence on monthly income. The indirect influence
of type of family on monthly income through occupation
and numbers of family member are 0.0078 and 0.0012 respectively.
Table
4.
Table
5.
CONCLUSSIONS
Migration is an important factor
to change the population of a region or a country. In
MCA, the result suggests that occupation of male migrants
has found to be the first strongest influential factor
for explaining the variation of monthly income both
before and after migration. On the other hand, educational
level of male migrants also has the second strongest
factor.
The MCA result shows that grand
average monthly income of a migrant is TK. 9650.84 before
migration and TK. 9678.13 after migration. So, a migrant's
income level has increased after migration.
The fact shows that the academic
qualifications of the migrants have a positive factor
for the increase of salary structure after migration.
It is taken to be the strongest factor. The MCA result
shows that migrant's occupation is a positive factor
for explaining the variation of monthly salary structure.
Before migration, a migrant
earned mean adjusted TK. 11465.14 per month. But after
migration, the migrant's income reached mean adjusted
TK. 11505.81 per month and the income is getting reached
gradually.
These migrants are doing business.
Migrants have to migrate to improve their life status.
So they are obliged to migrate to earn money. It is
noted that the variation of monthly income (before and
after migration) could not be shown actually due to
lack of proper information of income. It is tradition
that none can provide actual information of income.
RECOMMENDATIONS
Bangladesh is characterized
by rapid urbanization, backed by a huge base population
with accelerated growth rate. So, it is very difficult
to give any solution to reduce this problem. The following
policies are suggested in the present study:
i) Government should adopt
decentralized policies and programmers to create employment
opportunities in the rural areas to reduce unemployment
and hence rural to urban migration might be discouraged.
Consequently, the pressure of urbanization should be
abated.
ii) Government may invest resources for the improvement
of rural economies through different rural development
projects and by creating job opportunities in the rural
areas.
iii) Alleviate urban poverty by income-enhancing methods,
improve productivity of the informal sector. The role
of NGOs should be encouraged and enhance their activities
at grass root levels in rural areas of Bangladesh.
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