Abstract: The aim of this study is to identify the impact of socio-economic and demographic factors on migration. Using data in this study was collected by purposive sampling technique at Meherpur Sadar Thana at Meherpur district, Bangladesh. The logistic regression analysis has been used to identify the influential factors of migration. The logistic regression analysis has focused that respondent’s age, education, monthly income and number of family member have significant effects on causes of migration among the selected variables. The results of logistic regression analysis indicate that the risk of migration for secondary and above education is higher than that of illiterate.

INTRODUCTION

Bangladesh is one of the most densely populated countries in the world. Bangladesh is a small country of 147570 km² area with a population of around 148 million people (938 people km^-2). The populations of Bangladesh are mostly poor and maximum (91.2 and 8.8%) of them lives in rural areas. Migration is a process that occurs between two places of people with many objectives. People migrated to cities and towns because they are attracted by livelihood opportunities. Studies on migration have been established with positive association between levels of infrastructure development of a region and the magnitude of out-migrations (CUS, 1990).

Regardless of skill, the migrated population can find diversified livelihood opportunities with various incomes in the cities and towns. Thus, the poor rural population considers migration a livelihood coping strategy. On the other hand, a considerable number of the population migrates to urban areas from villages for higher/better education, employment and investment opportunities. Analysis of migration differential is impacted by rural-urban migration on socio-economic and demography structures at both the places of destination and origin.

The accelerating rate of rural-urban migration (urbanization) is high among the least developed countries of Asia. Hugo (1981) estimated the loss of young adults through migration from village leads to undermining of agricultural production by way of agricultural laborer. United Nation found that the urban growth rate has dominated by rural-urban migration and its contributes between three-fifth to two-third of this growth. Long rural development efforts neither could reverse the trend in rural-urban migration nor could it minimize uneven economic opportunities such as off-farm employment and earning. Migration by has been found to be more or less similar for developed as well as developing countries. It established that adult males are more inclined to migrate than other people of the community (Singh and Yadava, 1981). Migration is a process that occurs between two places of people with many objectives. The differentials migration has been studied mainly by age, sex, marital status, education, occupation and economic status. Several studies reported that determinants of migration vary from country to country and even within a country, it varies depending on the socio-economic, demographic and cultural factors. High unemployment rate, low income, high population growth, unequal distribution of land, demand for higher schooling, prior migration patterns and dissatisfaction with housing have been identified as some of the prominent determinants of rural out migration (Bilsborrow et al., 1987; Kadioglu, 1994; Nabi, 1992; Sekhar, 1993; Yadava, 1988; Singh and Yadava, 1981) finds that out migration of young male leads to decline in fertility at the place of origin. The existing micro-level studies mostly investigate the characteristics of migrants at destination places mainly Dhaka city (CUS, 1988, 1990, 1996), giving a little attention to the causes of out-migration from villages (Afsar, 1995; Chowdhury, 1978). Mazumder et al. (1989) and Amin (1986) studied the economic consequences of migration based on sample surveys conducted in Dhaka city. Chowdhury (1980) found that out-migration is generally higher from the villages characterized by land scarcity, unequal distribution of land and high proportion of agricultural laborer. Afsar (1995) argued that migrants often benefited more than non-migrants because of their innovative, risk taking and desperate nature.

The importance emerges not only form the movement of people but also from its influence on the lives of individuals and urban growth. Generally, rural to urban migration domain of research and planning as its role in changing the lives of migrants families both at the place of origin and destination. It is important to give attention to micro-level studies, based on sample surveys which have advantage to identifying regional heterogeneity.

The socio-economic and demographic characteristics of migrants can give some idea about type of people involved in the process of migration. The main objective of this study is to identify the impact of socio-economic and demographic factors on migrants. This studies carried out in Bangladesh are mainly destination based and attention on causes and consequences of migration and socio-economic characteristics of migrants at individual or household level of a particular origin.

MATERIALS AND METHODS

Generally, data can be collected through censes or survey method for analytical purposes. This research has been performed by primary data. The data was collected from Meherpur district at Sadar Thana by purposive sampling technique. Methodologies used in applied research are equally important as the data. Every methodology is not suitable for analyzing every set of data. So, here use various statistical techniques. The logistic regression model can be used not only to identify risk factors but also to predict the probability of success. Multiple regression analysis and discriminate analysis are two related techniques but these techniques are applicable, only when the dependent and independent variables are measured in interval scale under the assumption that they are normally distributed normally with equal variances. This regression is useful when the dependent variable is dichotomous.

The interpretation of the parameters in logistic regression has another interesting aspect. In fact, this is the proper interpretation for the parameters of qualitative variable coefficient. To describe this, researchers first consider that the independent variable (X_j) is dichotomous.

Table 1:	Logistic regression estimates for the effect on causes of migration with demographic and socio-economic variables
R means reference category, *significant at p<0.01, **significant at p<0.05

The logistic regression model may be described as follows:

Where: β₀, β₁, ..., β_k are parameters and X₁, X₂, ... , X_k are explanatory variables. The dependent variables considered in this study are as follows. For model 1:

The independent variables used in this model and analytical results are shown in Table 1.

RESULTS AND DISCUSSION

Research is a systematic search for knowledge. It is a sincerely attempt for actual finding as well as a careful inquiry to expand and to verify existing knowledge. In this connection, researcher tried to find out socio-economic and demographic characteristics of the migrants.

Table 2:	Percentage distribution of the female migrants based on background characteristics

The background characteristics of the respondents are shown in Table 2. In Table 2, it is shown that maximum number of female migrants (22.4%) are belongs to age group 30-34 years. Most of the female migrants (28.0%) are primary level educated. It is also observed that maximum number of female migrants (73.6%) is housewife and 78.8% of female migrants are married who belong to the age 18+ years.

The result of logistic regression model is shown in Table 1 shows that four variables are statistically significant at 5% level among the selected variables. The age is the most important demographic factor that influences migration. Table 1 shows that the estimated regression coefficient for age groups 20-25 and 25+ years are 0.824 and 0.754 which means that positive effects on migration for female migrants. The odds ratio for the age group 20-25 and 25+ years are 2.279 and 2.125. It is shown that 2.279 and 2.125 times higher risks of migration than that of age <20 years. Education is also influencing factor of migration. From Table 1, it is observed that the estimated regression co-efficient of education for primary and secondary and above are -1.287 which means has negative effects and 0.60 means positive effects on migration. The odd ratio of primary education is 0.276 which means 0.276 times lower risk of migration and secondary and above is 1.173 means 1.173 times higher risk of migration than that of illiterate. Monthly income plays an important role of influencing migration. From Table 1, it is shown that the estimated regression co-efficient of monthly income are 0.887 and 0.747 which means positive effects on migration. The odds ratio of monthly income 1001-5000 and 5000+ are 2.428 and 2.735 which means 2.428 and 2.735 times higher risk of migration than income 1000.

Member of family is an important factor of migration. Maximum time migration decision depends on family member. The estimated regression co-efficient of family member is -0.718 and -0.79 which has negative effects on migration. The odds ratio of family member is 0.488 and 0.924. It is shown that the risks of migration for family member are 0.488 and 0.924 times lower than that of <3 members.

CONCLUSION

From the this study, it may be concluded that people generally migrate in order to gain something better between two places like as betterment of life and others opportunities (educational facilities, income and better health services, etc.). This study focuses some important features of internal migrants based on the collected data. The logistic regression analysis suggested that respondent’s age, educational qualification, monthly income and family member have been found to be the significant influence on causes of migration. The main reason’s of migration is the lack of opportunities in his/her own place or origin.

RECOMMENDATIONS

For this reason, it should take some policy to reduce migration process. The policy are need to reduce imbalances in urban rural employment opportunities, need to reduce indiscriminate educational expanses, need to programs of integrated rural development should be encouraged.