American Journal of Economics 2013, 3(6): 273277 DOI: 10.5923/j.economics.20130306.05 Factors Affecting on Migration to ChapaiNawabganj Rafiqul Islam 1,*, Nurullah 1, Obaidur Rahman 1, Sabbir Hossain 2 1 Department of Population Science and Human Resource Development, University of Rajshahi, Bangladesh 2 Department of Business Administration, Bangladesh Islami University, Dhaka, Bangladesh Abstract The purpose of this study is to identify the socioeconomic and demographic factors affecting on migration to ChapaiNawabganj city in Bangladesh. To this, frequency distribution and logistic regression analysis are employed to the data extracted from 750 respondents of the Pouroshava of ChapaiNawabganj district in Bangladesh through purposive sampling technique. The findings of this study reveal that most of the respondents are migrants (56%) with a monthly income of more than Tk.7000 (73.6%), and belongs to single type of family (82.7%). The risk of migration to the cities increases with the increase in age of the respondents where as it also bears an inverse relation to the level of education, monthly income and numbers of family members. Also, nonmuslim respondents engaged in business or other types of occupation and having place of birth in rural areas are more vulnerable to higher risk of migration to the cities as compared to their counterparts. From the broader perspective of growth, equity and distributive justice this unrestrained migration to the cities will impinge serious and far reaching sociopolitical and economic implications for the mass people in this country leading ultimately to an unavoidable crisis. Hence, adoption of balanced development strategy, monotonic and stable increase in the level of income, creation of all types of urban facilities in rural areas, and ensuring a better quality of life etc. is strongly recommended for reducing migration to the cities as well as for sustainable development. Keywords Sociodemographic Characteristics, Migration, Logistic Regression Analysis 1. Introduction Migration is one of the three population process (along with fertility and mortality) which refers to the movement of people from one geographical location to another, either a temporary or permanent basis i.e., the change of residence for a substantial period[1]. It is a direct component in the growth of the population and the labor force in an area. Migration has immense role to play in the modern societies being controlled by some characteristics of human societies or communities. For demographic purposes, two broad types of migration are identified, international and internal migration. The former refers to movement across national boundaries and the later term refers to migration within the national boundaries. A common observation all over the world is ru ralurban migration v irtually, a dominant pattern of internal migration. Generally, in developing countries like Bangladesh, people migrate from rural to urban areas in response to prevailing conditions. Obviously, the cogent reason for it differs from one individual to another. Studies on migration in different regions of developing countries * Corresponding author: rafique_pops@yahoo.com (Rafiqul Islam) Published online at http://journal.sapub.org/economics Copyright 2013 Scientific & Academic Publishing. All Rights Reserved have commonly dealt with the economic aspects of migration. Evidence shows that a remarkable number migrates to urban from rural areas for better education, health, employment and investment opportunities. However, migrants also transfer their skills, ideas and knowledge; and establish interpersonal relationships among origin and destination countries and their people. Therefore, migration has socioeconomic and environmental implications, both positive and negative. A great impact on rural life has been felt and observed as a result of rural urban migration. Many communities are constantly losing their economically and socially most active people. Ofuoku and Chukwaji (2012) noted that ruralurban migration significantly and positively correlates with labor shortage, incomplete harvesting and forgone revenue, but it has negative impacts on plantation agriculture[2]. So, from the viewpoint of sustainability, in agriculturebased countries across the world and, especially in a country like Bangladesh, it plays a pivotal role indeed. At present, the agriculture dependent Bangladesh is the 8th most populous country in the world, and if the current growth pattern continues, its population would reach to 22.6 million by 2050[3]. In recent years, rapid urbanization occurs in most of the cities in Bangladesh and rural to urban migration is the most important factor behind it. According to UN projection, the size of the urban population in Bangladesh will be near to 100 million by the year 2025[4].
274 Rafiqul Islam et al.: Factors Affecting on Migration to ChapaiNawabganj Like many other countries, the rate of urban growth in Bangladesh is increasing and people are migrating more to urban areas for various reasons. Ruralurban migration is predominantly a part of family based poverty alleviation strategy in Bangladesh[5]. Despite the unfavorable living conditions of most of the migrants in Bangladesh, the migration happens, and strong urban pull factors keep the migrants from leaving the city while weak pull factors of the country s rural area fail to bring the migrants back to village[6]. Nevertheless, the poverty argument in this country is strong, where many poor and land less migrants are forced to migrate to support themselves or their families[7]. Farhana et al. (2012) found that the underlying cause of migration is mainly economic and social factors i.e., unemployment, poverty, political and ethnic conflicts, religious etc.[8]. In the migration process, the push factors are more active than pull factors as poverty, and unemployment always push the poor villagers to change their residence to the cities[8]. After migration, the majority of them comparatively improve their livelihoods in the city [8]. M icrolevel research finds the change in consumption patterns (especially access to better education and health care services) in migrant families than nonmigrant families[9]. But due to ruralurban migration rapid urbanization has created severe pressure on existing infrastructures and its absorption capacities[10]. Therefore, improvement of urban management in Bangladesh is highly desired for a sustainable future of the city[10]. If the right implementation of policies are in place, agriculture based Bangladesh can drive the benefit from migration. Reminding further, this study is an attempt in which the migration issues have been considered. Therefore, the specific objective of this study is to identify the socioeconomic and demographic factors influencing on migration to ChapiNawabganj city in Bangladesh and ma ke some recommendations which would be much useful for the policy makers in designing an effective p rogram and its implementation. 2. Sources of Data This is a cross sectional study involving 750 respondents at all ages extracted from the pourasava ofchapainawabga nj district (by purposive sampling technique) in Bangladesh. Data on some selected important socioeconomic, demographic and migration related characteristics have been collected using direct interview method at the time of the survey. 3. Methodology In this study, descriptive statistics and logistic regression analysis have been employed. Descriptive statistics has been used to explore the patterns of important socioeconomic, demographic and migration related characteristics, and the logistic regression analysis has been employed for identifying risk factors of migration to the cities in Bangladesh. This logistic model was developed by Walker and Duncun (1967)[11] and Co x (1970)[12]. The logistic regression model can be used not only to identify risk factor but also to predict the probability of success. The model is now widely used in research work to assess the influence of various socioeconomic and demographic characteristics for controlling the effect variables on the likelihood of the occurrence of the event of interest. In logistic model, migrant is considered as dependent variable which is dummy variable and it is classified in the following way: 1, if the respondents are migrant Y = 0, if the respondents are non migrant The explanatory variables that are used in this model are presented in the respective table. 4. Results of the Study Table 1 represents the distribution of socioeconomic, demographic and migration related characteristics of respondents. It is observed from Table 1 that more than half of the total respondents (56%) are migrants and the rest of them are nonmigrants. Among all respondents, 57.5% has born in urban area and 42.5% has born in rural area. The majorities (80.5%) are in 35+ years of age group and in <30 and 3035 years of age group, 9.9% and 9.6% respondents are belonged respectively. There are 89.3% and 10.7% respondents who are Muslims and nonmuslims respectively. Of all respondents, only 2% have primary level of education, 20.9% have completed secondary level of education and the majorities (77.1%) have higher secondary and above level of education. In case of occupation, most of the respondents (60.4%) are involved in service, 30.8% has engaged in business and the rest are belonged to other category of occupation. About half of the respondents (47.9%) have earned more than 9000 TK per month, and 7.1%, 19.3% and 25.7% have earned monthly <5000 TK, 50007000 TK and 70009000 TK respectively. There are 80.4%, 18.5% and 1.1% respondents who have <4, 45 and >5 number of family members respectively. Again, the majority (82.7%) of the respondents has been lived with single type of family and the rest (17.3%) of them are lived with joint type of family. In Table 2, the effect of various types of explanatory variable on dependent variable named migration has been presented where regression coefficients with their corresponding standard error (S. E.), significance level and odds ratio are disclosed. According to the fitted model, all explanatory variables except types of family are appeared as the significant predictors of migration to cities. In accordance with their importance, place of birth, age of the respondents, religion, educational level, occupation, monthly income and number of family members have statistically significant effect on migration to cities in this study.
American Journal of Economics 2013, 3(6): 273277 275 Place of birth is an important significant factor for migration to cities. The regression coefficient for the respondents whose place of birth is in rural areas is 0.342 with odds ratio 1.408 which implies that the risk of migration to cities for the respondents whose place of birth is in rural areas is 1.408 times higher than that of the respondents whose place of birth is in urban areas. The regression coefficients of 3035 years and >35 years aged respondents are 0.621 and 0.826 respectively and the corresponding odds ratios are 0.537 and 2.285. These results indicate that people with 3035 years of age group has 0.537 times lower risks of migration to cities and people aged >35 years has 2.285 times higher risks of migration to cities than that of the people aged <30 years respectively. In case of religion, it has been found that the regression coefficient for the nonmuslim respondents is 0.683 and the corresponding odds ratio is 1.980. It explains that nonmuslims have 98% higher risks of migration to cities than that of the Muslims. It has been demonstrated from Table 2 that the regression coefficients for the respondents whose have secondary and higher secondary & above level of education are 3.716 and 0.313 respectively and the corresponding odds ratios are 0.024 and 0.731 which implies that respondents having secondary and higher secondary & above level of education have 97.6% and 26.9% lower risks of migration to cities than that of the respondents having primary level of education respectively. Again, the regression coefficients for the respondents engaged with business and other types of occupation are 0.571 and 1.071 with odds ratios 1.769 and 2.919 respectively. These results imply that the risks of migration to cities for the respondents who are engaged with business and other types of occupation are 1.769 and 2.919 times higher than that of the respondents who are engaged in service respectively. Monthly income plays significant role in case of migration to cities. The regression coefficients for the respondents whose monthly income is 50017000 TK, 70019000 TK and >9000 TK are 1.073, 0.045 and 0.610 respectively and the corresponding odds ratios are 0.342, 0.956 and 0.543 which indicates that respondents having monthly income of 50017000 TK, 70019000 TK and >9000 TK have 65.8%, 4.4% and 45.7% lower risks of migration to cities than that of the reference category respectively. The regression coefficients for the respondents who have 45 and >5 numbers of family members are 2.410 and 3.135 respectively and the corresponding odds ratios are 0.090 and 0.044 which imp lies that the respondents having 45 and >5 numbers of family members have 91% and 95.6% lower risks of migration to cities than that of the respondents having <4 numbers of family members respectively. Ta ble 1. Distribution of respondents based on socioeconomic and demographic characteristics Name of socioeconomic and demographic characteristics Numbe r of respon dents Percentage (%) Type of respon dents: NonMigrants Migrants 330 420 44.0 56.0 Place of birth: Urban Rural Age of respondents: <30 years 3035 years 35+ years Religion: Muslims NonMuslims Educational level: Primary Secondary Higher Secondary & above Occu pation: Service Business others Monthly income (in TK): <5000 50007000 70009000 9000+ Number of family member: <4 45 5+ Type of family: Single Joint 431 319 74 72 604 670 80 15 157 578 453 231 66 53 145 193 359 603 139 8 620 130 57.5 42.5 9.9 9.6 80.5 89.3 10.7 2.0 20.9 77.1 60.4 30.8 8.8 7.1 19.3 25.7 47.9 80.4 18.5 1.1 82.7 17.3
276 Rafiqul Islam et al.: Factors Affecting on Migration to ChapaiNawabganj Ta ble 2. Logistic regression estimates for the effect on migrants and nonmigrants with demographic and socioeconomic variables Characte risti cs Place of birth: Urban Rural Age of respondents: <30 years 3035 years 35+ years Religion: Muslims NonMuslims Educational level: Primary Secondary Higher secondary & above Occu pation: Service Business Others Monthly income (in TK): <5000 50017000 70019000 9000+ Number of family members: <4 45 5+ Type of family: Single Joint Coefficient (β) 0.342 0.621 0.826 0.683 3.716 0.313 0.571 1.071 1.073.045.610 2.410 3.135 0.119 S.E of estimate (β) 0.170 0.283 0.287 0.278 1.248 0.203 0.189 0.343 0.414 0.408 0.390 1.353 1.361 0.221 Wald 4.070 4.814 8.262 6.017 8.867 2.368 9.155 9.775 6.721.012 2.444 3.171 5.304 0.288 Significant (ρ) 0.044 0.028 0.004.014 0.003 0.124 0.002 0.002 0.010 0.913 0.118 0.075 0.021 0.592 Odds ratio 1.408 0.537 2.285 1.980 0.024 0.731 1.769 2.919 0.342 0.956 0.543 0.090 0.044 1.126 Constant 2.882 1.420 4.120.042 17.854 5. Discussion A common regularities in developing countries like Bangladesh across the world is migration to cities. In this study, most of the respondents in this city are migrants (56%); belong to 35+ years of age group (80.5%); have higher secondary and above level of education (77.1%) and involve in service (60.4%). The majorities (73.6%) have earned more than 7000 TK per month and the single type of family (82.7%) is observed more in this city. These results are supported by many studies. Afsar (2003a) has noted that all types of migration have recently increased significantly[13]. Twothirds of all migration is from rural areas to urban areas and migration plays an important role in the reduction of rural poverty[14]. In fact, Ru ralurban migration is predominantly a part of family based poverty alleviation strategy in Bangladesh[5]. A recent study shows that the majority of them have comparatively improved their livelihoods in the city after migration[8], although Afsar (2005) has identified that there is a strong positive and negative povertymigration nexus[15]. Though the incidence of ruralurban migration in any developing country is higher, a distinct selectivity with respect to age, sex caste, marital status, education, occupation etc. occurs and the propensity of migration differs significantly among these socioeconomic groups[16]. In this study, it has been found that place of birth, age of the respondents, religion, educational level, occupation, monthly income and number of family members are statistically significant factors affecting on migration to cities. The risk of migration to cities for the respondents who are nonmuslim and whose place of birth is in rural areas is higher than their counterparts. With growing the level of education, monthly income and numbers of family members, this risk is decreasing; but it increases with increasing the age of the respondents. The respondents who are engaged with business and other types of occupation have higher risks of migration to this city than that of service personnel. These results are supported by Rahman et al. (2007) because they have identified that education, monthly income, type of family and land property significantly affect on causes of migration[17]. In another study, it has been noted that people migrate to certain places due to economic reasons and migration can alter the life style of individuals and families[18]. Clearly, people migrate to new places with the hope of improving their social and economic status[18]. But rapid migration to cities in developing countries like Bangladesh occur unplanned growth of cities across the world, which creates severe pressure on existing infrastructures[10]. So, improvement of urban management of Bangladesh is essential for a
American Journal of Economics 2013, 3(6): 273277 277 sustainable future of the city[10]. 6. Recommendations Since rapid urbanization creates more hazards on existing environment and its absorbing capacities, the agriculture based Bangladesh can get the benefit from migration to cities by taking the right kinds of policies. The above discussion rightly suggests that it is very important to identify the contributing factors of migration to the cities and take necessary steps in this regard. In the light of the study, the following policies are suggested which would be very helpful for policy maker to existing program. i. Since the risk of migration to the cities for the respondents whose place of birth is in rural areas is higher, a balanced development regional pact should be needed. ii. Ensuring the quality of life for urban residence as well as enhancing all types of facilities in rural areas which one gets in urban areas. iii. Creating more income sources and increasing the level of inco me in rural areas. REFERENCES [1] Ekong, E. (2003) An Introduction to Rural Sociology. Uyo, Nigeria: Dove Educational Publishers. [2] Ofuoku, A. U. & Chukwuji, C. O. (2012) The Impact of RuralUrban Migration on Plantation Agriculture in the Niger Delta Region, Nigeria. Journal of Rural Social Sciences 27(1), 137 151. [3] PRB (2012) World Population Data Sheet of the Population Reference Bureau. Demographic Data and Estimate for the Countries and Region of the World, Washington, DC. [4] UNESCO (2009) Final Report of Regional Seminar on Policy Response to the Challenge of Rural Urban Migration, held on January 1516 in Beijing, China by UNESCO International research & training centre for rural education. [5] Afsar, R. (2000) RuralUrban Migration in Bangladesh: Causes, Consequences and Challenges, University Press Limited, Dhaka. [6] Ishtiaque, A. & Mahmud, M. S. (2011) Migration Objectives and their Fulfillment: A Micro Study of the RuralUrban Migration of the Slums of Dhaka City. Malaysian Journal of Society and Space 7(4), 2429. [7] Ahmed, A. & Uddin, M. (2005) Weber s Perspective on the City and Culture, Contemporary Urbanization and Bangladesh. http//www.bangladeshsociology.org/max%20w eber%20%20ahmed.htm (acceded on 11 July 2006). [8] Farhana, K. M., Rahman, S. A. & Rahman, M. (2012) Factors of Migration in Urban Bangladesh: An Empirical Study of Poor Migrants in Rajshahi City. Bangladesh ejournal of Sociology 9(1), 105117. [9] Siddiqui, T. (2011) Impact of Migration on Poverty and Development, (unpublished) commissioned by the Research Programme Consortium on Migrating Out of Poverty based at the University of Sussex, UK. [10] Jahan, M. (2012) Impact of Rural Urban Migration on Physical and Social Environment: The Case of Dhaka City. International Journal of Development and Sustainability 1(2), (In Press). [11] Walker, S. H. and D. B. Duncan (1967) Estimation of the Probability of an Event as a Function of Several Independent Variables, Biometrica, Vol. 54, pp. 167179. [12] Cox, D. R. (1970) The Analysis of Binary Data, London: Methuen, Chapman and Hall Ltd. [13] Afsar, R. (2003a) Internal Migration and the Development Nexus: The Case of Bangladesh. Paper Presented at the Regional Conference on Migration and ProPoor Policy Choices in Asia, Organized by the DFID, Sonargaon Hotel, Dhaka, Bangladesh, 2224 June. [14] Afsar, R. (2003b) Dynamics of Poverty, Development and Population Mobility: The Bangladesh Case. Paper Prepared for Ad Hoc Expert Group Meeting on Migration and Development, Organized by Economic and Social Commission for Asia and the Pacific, Bangkok 2729 August. [15] Afsar, R. (2005) Internal Migration and Propoor Policy, Country Paper, Bangladesh. Paper Prepared for Regional Conference on Migration and Development in Asia, Sponsored by the Department for International Development, UK, Lanzhou China, 1416 March. [16] Yadava, K. N. S. (1988) Volume and Pattern of RuralUrban Migration in India. Seminar Paper Presented in the Department of Demography, Australian National University, Canbera. [17] Rahman, M., Islam, M. R. & Rahman, M. (2007) Causes and Consequences of InMigration at Rajshahi City Corporation, Bangladesh. Journal of Engineering and Applied Sciences 2(2), 305308. [18] Islam, R., Faruk, A. O., Mostofa, M. G. & Haque, M. E. (2007) Living Standards of Migrants: A Study of Katakhali Pourusova in Rajshahi District, Bangladesh. Middle East Journal of Family Medicine.