175 Regression Model Approach for Out-Migration on Demographic Aspects of Rural Areas of Pauri Garhwal Pankaj Bahuguna, Research Scholar, Department of Statistics, H.N.B.G.U., Srinagar (Garhwal) Uttarakhand Prof. O.K. Belwal, Department of Statistics, H.N.B.G.U., Srinagar (Garhwal) Uttarakhand ABSTRACT Creation of separate state Uttarakhand is also becoming the base of migration in Garhwal from different parts of India and in foreign countries. Another way of migration is Garhwalis fleeing from Garhwal and establishing themselves in various cities and villages of other parts of India. It is estimated that approximately, one fifth population of Garhwalis is scattered here and there in India and other countries. Migration is the third component of population change, the other two being mortality and fertility. As compared to birth rate and death rate, migration affects the size of population differently. Migration is not a biological event like birth rate and death rate, but is influenced by the social, cultural, economic and political factors. This paper is an attempt to analyse the out-migration with reference to various demographic indicators like age, marriage, family nature, facilities in the rural areas of Pauri Garhwal. The data is collected through a survey with the help of questionnaire. The multiple regression model is used to show the impact of out-migration from the study area. The analysis shows that highest responsible indicator is income after migration for the study area. Keywords: Multiple regression, migration indicators, push factors, unemployment. INTRODUCTION Migration is the movement of people from one place in the world to another for the purpose of taking up permanent or semi permanent residence. One of the most significant migration patterns has been rural to urban migration - the movement of people from the countryside to cities in search of opportunities. In the rural areas, sluggish agricultural growth and limited development of the rural non-farm sector raises the incidence of rural poverty, unemployment and underemployment. The fact that most of the high productivity activities are located in the urban areas, the rural-urban income differentials, particularly for the poor and unemployed, are enormous. Thus, many of them migrate to the urban areas in search of jobs. Even when jobs in the high productivity activities are limited in number relative to the supply, and often they are not accessible, population still flows to the urban areas in search of opportunities. In the face of a high natural growth of population, rural-urban migration aggravates the situation of excess supplies of labour in the urban areas. Within the urban informal sector this tends to reduce the level of earnings and get manifested in a high incidence of urban poverty. The 2011 Census reveals migration from all hill districts of the State. Excepting two Hill Districts, all others hover around a population growth rate of 5 % with Almora and Pauri Districts showing a negative population growth of - 1.73 % and -1.51 % respectively against a national average of 17 %. This reflects the absence of livelihood opportunities in the Hills and yearning for a better quality of life. Migration is one of the major contributors to urban growth in Uttarakhand. Migration accounts for about two-thirds of the urban growth seen in Pauri Garhwal since Creation of separate state. This paper focuses on rural - urban migration, which involves both permanent and temporary moves in search of employment and livelihoods. Push and pull factors are responsible for the migration of people from the place of origin to the place of destination. In this study multiple regression model approach is suitable for all the independent indicators to show the variation in dependent variable that is migration. Recently released provisional decadal Census results (2011) have been called a mixture of the expected and the unexpected. Some of the results could perhaps also be called alarming. The latest decadal growth of 19.17 %, much higher than the all-india decadal growth of 17.64%, is somewhat lower than the previous (1991-2001) growth rate of 20.41 %. The decline in the population growth rate during 2001-2011 is much slower in Uttarakhand (1.24 percentage points) than at the national level (3.90 percentage points) and in the neighbouring mountain state of Himachal Pradesh (4.73 percentage points). This is said to correspond with the evidence of natural rate of population increase which has been more or less stable over the years 2005 to 2009.
176 Population Growth Rate Overall Sex Ratio Child (0 6) Sex Ratio District 2001 2011 2001 2011 2001 2011 Uttarkashi 23.07 11.75 941 959 942 915 Chamoli 13.87 5.60 1016 1021 953 889 Rudraprayag 13.43 4.14 1115 1120 953 899 Tehri Garhwal 16.24 1.93 1049 1078 927 888 Dehradun 25.00 32.48 887 902 894 890 Pauri Garhwal 3.91-1.51 1106 1103 930 899 Pithoragarh 10.95 5.13 1031 1021 902 812 Bageshwar 9.28 5.13 1106 1093 930 901 Almora 3.67-1.73 1145 1142 933 921 Champawat 17.60 15.49 1021 981 934 870 Nainital 32.72 25.20 906 933 910 891 U. Singh Nagar 33.60 33.40 902 919 913 896 Hardwar 28.70 33.16 865 879 862 869 Uttarakhand 20.41 19.17 962 963 908 886 Source: Population Census Provisional Data-2011 The Table very tellingly shows how the decadal rate of population growth has been exceptionally high in four districts: over 30 % in Dehradun, Hardwar and Udham Singh Nagar and over 25% in Nainital, and moderately high in Champawat (14.5 %) and Uttarkashi (about 12 %). In the remaining seven districts, population growth has been rather low, being about 5% or less. In two of these districts, Pauri Garhwal and Almora, it is negative. Except Nainital and Uttarakashi, the high population growth districts are either fully situated in the plains (Udham Singh Nagar and Hardwar). In simpler terms, even though the mountain districts of Uttarakhand were already well known for male-out migration in search of employment the rate of out migration has accelerated to such an extent that while all mountain districts exhibit substantial decline in population growth, two erstwhile 'capital ' districts of Pauri Garhwal and Almora have shown a negative growth rate. The only mitigating factor seems to be that the migration has taken place to the plains regions of the state itself. The other indicators suggest that not only there is considerable migration from the mountain districts, in contrast to the earlier pattern of only men going out, now whole families are migrating. The other disturbing area of concern, which emerges from these early results, relates to a rather sharp decline in the child sex ration, in the mountain districts. To what extent it mirrors the phenomenon of 'women drudgery', feminization of agriculture and increased poverty levels of mountain regions, deserves to be investigated through micro-investigations. Picture: After migration the condition of villages in rural areas of Pauri Garhwal
177 METHODOLOGY In this study, the analysis of spatial concentrated location is based on migration effectiveness statistics while the statistical processing of migration stream is based on multiple regression analysis. For determining the most responsible factor for migration in rural areas, we selected randomly 24 villages from over all villages of Pauri Garhwal and from each village we select 10 households for investigation by questionnaire. Dependent variables are number of migrants moved into destination areas and from original areas. We will try to examine the associations between number of migrants and other independent variables by regression model approach in the study area. Various diagrammatic representations are used to show the migration with reference to different factors. OBJECTIVES 1. To fit the multiple regression model for migration on different independent variables. 2. To show the status of rural areas of Pauri Garhwal with reference to different indicators. MULTIPLE REGRESSION MODEL To show the functional relationship between one dependent variable to another independent variable, multiple regression approach is very useful tool. In this study number of migrants is our dependent variable and nature of family, age at migration time, Income after migration, facilities available in villages, female marriage(number of females moved to their in-laws home), & marital status at migration time are the independent variables. The data collected from 24 villages of rural areas of Pauri Garhwal by conducting field survey and 240 households were interviewed. The following multiple regression equation is obtained Number of Migrants = X 1 + X 2 (Nature of Family) + X 3 (Age at Migration Time) + X 4 (Income) + X 5 (Facilities) + X 6 (Female Marriage) + X 7 (Marital Status) Where number of migration is dependent variable, nature of family, age at migration time, Income after migration, marital status, facilities & educational status are independent variables respectively. Table 1-Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1.693 a.480.466 1.96754 a. Predictors: (Constant), Marital status at migration time, Nature of family, No. of females moved to their inlaws home, Facilities in Villages, Age of Migrants, Income after migration b. Dependent Variable: No. of migrants Table 2-ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 831.988 6 138.665 35.819.000 a Residual 901.995 233 3.871 Total 1733.983 239 a. Predictors: (Constant), Marital status at migration time, Nature of family, No. of females moved to their inlaws home, Facilities in Villages, Age of Migrants, Income after migration b. Dependent Variable: No. of migrants Table 3-Residuals Statistics Minimum Maximum Mean Std. Deviation N Predicted Value -1.1022 5.5018 1.7583 1.86578 240 Residual -3.61650 14.62004.00000 1.94269 240 Std. Predicted Value -1.533 2.006.000 1.000 240 Std. Residual -1.838 7.431.000.987 240 a. Dependent Variable: No. of migrants
178 Table 4-Coefficients Model Unstandardized Coefficients Standardized Coefficients B Std. Error Beta 1 (Constant) 6.000.883 6.797.000 Nature of family -.083.149 -.027 -.560.576 Age of Migrants.112.090.076 1.244.215 Income after migration.451.100.292 4.507.000 Facilities in Villages -.258.068 -.185-3.790.000 No. of females moved to their in-laws home Marital status at migration time a. Dependent Variable: No. of migrants t Sig..053.102.025.520.604-2.540.325 -.461-7.817.000 The fitted multiple regression model for the dependent over the various independent variables is given below by the equation: Number of Migrants = 6.000 0.083 (Nature of Family) + 0.112 (Age at Migration Time) + 0.451 (Income) 0.258 (Facilities) + 0.053 (Female Marriage) 2.540 (Marital Status) The Standardised regression equation is given below: Z (Number of Migrants) = 0.027 Z (Nature of Family) + 0.076 Z (Age at Migration Time) + 0.292 Z (Income) 0.185 Z (Facilities) + 0.025 Z (Female Marriage) 0.461 Z (Marital Status)
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181 The above figures show the condition of migration in rural areas of Pauri Garhwal. CONCLUSIONS & DISCUSSIONS In Pauri Garhwal migration is due to underdevelopment. It is one of the few districts of Uttarakhand, which shows practically no trend of in-migration, but a growing tendency of out-migration. A large number of able-bodied men have to migrate to earn their living, employment opportunities in this area being negligible. The multiple regression model is used for out migration on different independent variables. The model summary shows the adjusted R square 0.466 by which 46.6 % variations can be specified. Model show the highly associated variable is Income after migration (45.1%) and Age at migration time (11.2%), Female marriage (5.3%). Income after migration is highly responsible for pulling the persons from the rural areas by the attraction of cities. The secondly responsible factor is age of migrants at migration time and the thirdly responsible factor is female marriage means a female of a family is permanently migrated to her in-laws home. Also after marriage of migrated person his family move with him in the cities. To show the status of rural areas of Pauri Garhwal with reference to different indicators the second figure is the representation of type of villages. In the hill areas, the region is divided into three types of villages: road side, valley and high elevation villages. There are 37.50% road side, 37.50% valley and 25% high elevation villages in this study area. Condition of a village (distance from road) play a significant role in the development, there finding imbalances between rural and urban areas in the context of social, economical, cultural and political activities. The third figure shows the number of persons migrated from these three type of villages. The fourth figure represents the number of persons migrated due to lack of facilities available in the villages. Fifth figure represents the main source of income for the livelihood for their families. The main source of income in the study area is highly depends upon government service (30.83%) followed by agriculture (28.75%) and private service (23.75%). The Sixth figure represents that temporary and permanent (31.67%) both the types of migration highly associated with the household levels. Migrants are predominantly young adults from low income families. But the traditional picture of young males leaving their villages to find work to support their families is changing as more and more women join their ranks and, increasingly, migrants are more informed about job opportunities at work destinations. The effect of factors at the place of destination on migration is interesting. Prospects for better job opportunities are a major determinant of migration. Low castes and minority groups tend to pull migration through network effects. Thus the study area requires some new policies specially concern with rural areas of Pauri Garhwal.
182 REFERENCES [1] Government of India (2011): Census of India, Uttarakhand Provisional Population Figure, Uttarakhand. [2] Belwal, O.K., Bhatt N. & Panwar Pushpa (2011): Role of Socio-Economic Factors which affect the Out-migration in Rural Areas of Uttarakhand: A case study, Arya Bhatta Journal of Mathematics & Informatics Vol. 3, No.1 [3] Belwal, O.K., Bhatt N. & Todaria, N. P. (2005): Pattern of Land Holdings and consequences of migration on Culture & Economy in Garhwal Himalaya. MUHA-2005, Vol.5 [4] Belwal, O.K. & Bhatt N. (2004): Effect of Socio- Economic characteristics on out-migration; A case study of Garhwal Himalayan Villages, Bio-Science Research Bulletin, 2004. [5] Srivastava, S.C. (2004): Studies in Demography, Anmol Publications Pvt. Ltd. [6] Belwal, O.K. & Bhatt N. (2003): Trend and pattern of migration in Uttaranchal: A Statistical perspective. Bio-Science Research Bulletin Vol.19 (No.2) [7] Datta, A. (2003): Human Migration: A Social Phenomenon, Mittal Publication, Delhi. [8] Joshi, G.V. & Lobo, N. (2003): Rural Urban Migration and Rural Unemployment in India. New Delhi, Mohit Publication. [9] Kumar, K. & Agarwal, S.C. (2003): An Econometric Analysis of Causes of Migration in Assam. Demography India, Vol. 32, No. 1. [10] Mahendra, K.P. (2001): Who Migrates To Delhi? Demography India, Vol. 30, No. 1. [11] Singh, D.P. (1998): Internal Migration in India; 1961-91. Demography India, Vol. 27, No. 1. [12] Bora, R.S. (1998): Himalayan Migration: A Study of Hill Region of Uttar Pradesh. [13] Semwal, G.N. (1993): Uttarakhand Ki Parasthitiyan and Palayan. [14] Mehta, G.S. (1991): Socio-Economic Aspects of Migration, Deep & Deep Publications, New Delhi. [15] Singh, S.C. (1985): A Study of Out Migration from Rural Garhwal, Demography India Vol. 14. [16] Rawat, R. & Rawat P.S. (1986): Rural Urban Migration: Impact of Villages. The Eastern Anthropologists, Vol 39. [17] Mehta, B.H. (1946): Village in City, A Study of Rural-Urban Relationships. Indian Journal of Social Work, Vol. 1