Do natural resources and social networks matter in rural-urban migration? Evidence from punjab

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1 Scientia Agriculturae E-ISSN: X / P-ISSN: DOI: /PSCP.SA Sci. Agri. 15 (2), 2016: PSCI Publications Do natural resources and social networks matter in rural-urban migration? Evidence from punjab Muhammad Imran 1, Khuda Bakhsh 2, Sarfraz Hassan 3 1. Department of Agricultural Economics, Agriculture Faculty, Akdeniz University Antalya 07058, Turkey 2. Department of Management Sciences, COMSATS Institute of Information Technology, Vehari, Pakistan 3. Institute of Agricultural and Resource Economics, University of Agriculture Faisalabad, Pakistan Corresponding Author maniuaf@yahoo.com Paper Information A B S T R A C T The present study was designed to estimate the impact of resource Received: 8 February, 2016 degradation and networks on rural-urban migration. Cross-sectional data were collected from Muzaffargarh, Punjab province of Pakistan. Accepted: 19 April, 2016 Households with migrant family member and non-migrant households were selected randomly from various villages. We used logit model to Published: 1 June, 2016 determine factors affecting rural-urban migration. Results showed that family and social networks had significantly positive impact on rural-urban migration, in addition to socioeconomic factors, implying that households having strong family and social networks would contribute substantially in rural to urban migration. Availability of transport facility and higher land holdings were negatively related with rural-urban migration. Improving infrastructure, consolidation of landholdings, bettering health and education facilities and creating employment opportunities at village level would reduce rural to urban migration in the study area PSCI Publisher All rights reserved. Key words: Logit model; Migration; Natural resources; Punjab; Social networks. Introduction An increase in population and urbanization is the concern of many countries in the world. Historical increase in urban population is attributed to rural-urban migration. There are various reasons for rural to urban migration. Share of the agriculture sector continues declining while that of industrial sector rises in Gross Domestic Product (GDP) as a result of the structural transformation led by economic development. Migration to urban areas has been viewed as a vehicle for change and as a factor in redistribution of population from rural to urban centers. There is a wide range of evidences that economic factors have more importance in migration as compared to other social and political factors. Similarly, environmental (Myers, 2005) and social factors also affect rural to urban migration. Rural-urban migration can lead to sub-optimal use of land and further land degradation (Scherr and Yadav, 1998). Further, the presence of established contacts attracts new migrants. Pakistan is among the least developed countries, facing low economic development and high poverty. This results in huge rural-urban migration. Although studies are available on international migration in Pakistan, very little work has emphasized on internal migration. Population Census, Labor Force Surveys, and special migration and labor force surveys have been the major source of data for these migration studies. These studies include a wide range of issues. Close observation at them reveals that they have mostly focused on the rate of migration, direction of migration flows, gender dimension, factors involved in decision to move and earning of migrants and non-migrants. An individual having any network at urban centers can avail much information and ease in migration and also in searching job. But we do not find any study emphasizing issues like impacts of natural resources on migration, or contribution of social networks in migration. The present study addresses these issues. The findings of the study would help to design policies to reduce rural-urban migration thereby a reduction in burden on resources in urban centers. Review Of Literature Huge literature is available on migration. However, this section considers some important migration studies relating to rural-urban migration and its causes. Lack of agricultural land and the excess of household labor are the important factors of labor migration because of a decrease in the relative marginal income in agriculture. But the prevailing landownership system is barrier to further increases

2 in labor productivity in farming (Zhao, 1999). Brauw et al. (1999) find that differences in income of rural and urban areas motivate rural households to migrate from agriculture sector to industrial sector. Ullah (2004) also argues that the difference in rural-urban income, employment opportunities and absorptive capacity play important role in rural-urban migration. Some studies (Paris et al., 2009) also conclude that labor outmigration is mostly high and would continue to increase as long as it is beneficial to move and as long as the farm income is not predominant source of income. In spite of rising migration rate, farming is still the mainstay in rural areas. Among rural households, those with higher opportunity cost tend to migrate and the old, uneducated households are left behind to manage farm operations. Sidiqi (2004) show role of economic factors in migration than non-economic factors. Muhamud et al., (2010) indicate that when a migrant individual does not consider social amenities and the main motivational force is to improve economic status. In case of individuals with low income, the possibility of earning higher income in urban centers is more crucial than public utilities and better-off individuals migrate due to quality health and education services in urban areas. So generally importance of economic consideration was more than social in a decision to migrate. Availability and quality of natural resources plays a very vital role in decision relating to rural-urban migration. Land deprivation particularly landlessness or small landholdings have a positive impact on rural-urban migration. Small farmers are more inclined to rural-urban migration while large farmers have less tendency of migration. Mullan et al., (2011) found that tenure insecurity reduced migration. Secure land tenure have a positive impacts on rural to urban migration. This is due to an increase in the incentive to migrate due to less risk of land expropriation. Quality of resources also matters in migration decision (Farooq et al., 2005). In such circumstances, rich households have higher probability to migration than the poorest households (Shah, 2005). High degree of deforestation, soil erosion and land degradation strongly influence the migration decision (Alscher, 2010). Family and social networks at destination help in many ways. Pre-established networks at urban centers help rural migrants in searching job, providing shelter and sometime financing their migration from rural to urban areas. Households with higher number of family and social networks have a greater tendency to migrate (Dolfin et al., 2011). Heering et al., (2004) argue that family networks and migration culture are important factors affecting migration decision. However, women are found using social networks frequently in rural-urban migration decision (Zhang, 2006). Social networks help in finding jobs and reducing in risk and costs associated with migration. Methodology We used logit model to determine probability of having migrant family member in a household. This regression analysis is fitted to the situation when we have dichotomous dependent variable. Logit model takes the value of one when the household has a migrant and zero if the household does not has a migrant member. The probability that a given household has a migrant member can be expressed as a function of X as follow P( Y 1) P( X X ) P[ X ( ) ( )] P( X ) F( X ) where P is a probability function, is a random disturbance term, ), a vector ( of unknown parameters to be estimated and it is interpreted as the net influence of the vector of independent variables on migrant households (), stands for households having no migrant members and F( X ) is the cumulative distribution for evaluated at X. We employed the maximum likelihood approach to estimate the Logit model 1. The empirical Logit model used to estimate the impacts of various factors on rural to urban migration is given as under: The relative odds of versus households are given by: By taking the logarithms on both sides, we get: The logit regression of rural-urban migration is thus specified as a function of various socioeconomic variables as 1 For more details about the Logit model, see Greene (2000) and Wooldridge (2000) 357

3 Where is the log of odds of adoption of rural-urban migration. It is equal to 1 if the household has at least one member outside native village for more than three months and 0 otherwise. X s are independent variables having impact on dependent variable. Descriptive statistics and definition of explanatory variables is given in Table 1. ß 0 is constant andß s are the unknown parameters to be estimated.ɛ is usual error term with zero mean and constant variance. Results of Table 1 show that, 2.59 male members in the household have age more than 15 years. Households with more male members have higher probability of being migrant households. Married males in the selected households constitute 1.59 in number. Out of the selected households, around 38 percent have non-farm income, in addition to farm income and such households are expected to have uncertain outcome relating to migrant member. Landholding is an important nature resource having impact on decision relating to migration. The mean area of the respondents was 4.86 acres. Another important factor determining rural-urban migration is quality of land owned by the households. Transport facility available to the rural households also contributes in rural-urban migration. Out of total respondents, 43 percent reported that they have access to transport facilities in the village. Family and social networks have a positive impact on probability of migration from rural to urban areas and 33 percent have networks at urban centers. Income earned by household by selling milk was Rs4961. On average distance from the main city was above 17 km. The present study was conducted in the Punjab province, being the largest province in term of population in Pakistan. Major part of population of the Southern Punjab lives in rural areas and their livelihood depends on agriculture and agriculture related activities. Form this part of province district Muzaffargarh was selected. This district was selected due to many reasons. Muzaffargarh district is among the district where migration of peoples occurs many time due to natural disasters mainly flood and sometimes for search of job as land holdings of rural people is mostly small. A total of 120 respondents were interviewed from two tehsils of district. From each tehsil 5 villages were selected randomly, farmers were selected from each village randomly. A well-defined and pre-tested questionnaire was used for data collection. Only those respondents engaged fully or partially in farming were considered. Households with at least one migrant member were taken as migrant households. Individuals with more than three month away from the native village were considered as a migrant (Paris et al., 2009). The study also included a comparison group of non-migrant households. Empirical Findings Motives of migration vary among individuals. Different factors induce migration from rural to urban areas. They include networks, availability of natural resources and socioeconomic factors. We used logit model to determine contribution of these factors on rural to urban migration in the study area. Results of logit regression model are given in Table 2. We considered ten independent variables to determine impact on probability of rural-urban migration. Five independent variables have a statistically significant and positive impact on migration, two have significant and negative effect on migration. Adult family members contribute significantly in household income we considered adult who were in the age bracket of years. Coefficient of adult male variable has positive sign and it is statistically different from zero. This result indicate that family with high number of male members is more probable (0.049) of having migrant member. Studies such as Zhu and Luo (2009), Goldsmith et al., (2004), Ikramullah and Shair (2011) and Zahonogo (2011) show the similar findings. Such households may have more tendency of diversifying source of income, so they may send the young and skilled members to urban centers for improving family earnings. Positive and significant coefficient of married members in the family shows that one percent increase in married male would increase probability of rural to urban migration by It may be due to the fact that married malesare assumed to have relatively more responsibilities as compared to non-married. Such individuals have to feed their children, educate them and also have to spend amount on their medication. Thus married individuals are expected to have higher probability of rural to urban migration for bettering living standard as migrants expect to have better employment opportunities at urban centers. Income of the household is expected to have an important role in decision making regarding rural-urban migration. Here we consider non-farm income and we find that coefficient of the variable is positive and statistically significant. This result implies that an increase in non-farm income has probability of a rise in rural to urban migration by This result is different from Ikramullah and Shair (2011) who showed that households with non-farm income were less probable to migrate from rural to urban areas. However, the findings of the present study can be valid because migration needs some cost initially. A household having non-farm income can easily fund the migration process of a member from rural to urban areas. Land is also a source of income. Area owned by the household has a significant and negative impact on rural-urban migration, implying that households with more farm area have low probability of rural-urban migration. Zhu and Lu (2009) and Zhao (1999) also showed the same outcome of land ownership. 358

4 Quality of land has significant and positive impacts on migration. As quality of land goes to be degraded, the ruralurban migration increases. Households with poor quality of land have a probability of rural-urban migration. It is due to the fact that when quality of land degrades, agriculture production also declines and household tend to diversify income generating activities. They compensate this decrease in income by migration, being one option. Availability of transport facilities to main city has significant and negative impact on rural-urban migration. Findings are supported by Sidiqi (2004). Having access to transport facilities to main city, households have less probability of rural-urban migration as the household members can return back to home daily after earning livelihood if there are better transport facilities available from city to their homes. Family and social networks at destination have significant and positive impact on rural-urban migration. These observations confirm the results of earlier studies, which show that networks have positive impact on migration (Feng and Heerink (2005), Dolfin and Genicot (2010)). Family and social networks facilitate new migrants in providing information about destination, shelter and helping in search of jobs. So chances of migration for those households who have networks are higher. Table 1: Summary statistics of variables used in logit model Variables Mean Standard Dev. Min Max Male above 15 years Married male (no.) Non-farm income (0= no, 1= yes) Area owned (acres) Quality of land (0= very good, 1= good, 2= fair, 3= poor, 4= very poor) Transport facility (0= no, 1= yes) Networks (0=no, 1= yes) Quality of ground water ( 0= very poor, 1= poor, 2= fair, 3= good, 4=very good) Income from milk (Rs) Distance from main city (km) Table 2: Results of Logit Regression Model Variables Coefficients t-ratio Change in probability Constant -6.41*(1.77) Male above 15 years 0.55**(0.29) Married male 0.73***(0.44) Non-farm income 1.35**(0.67) Area owned -0.18***(0.10) Quality of land 1.40**(0.47) Distance from main city 0.06(0.05) Transport facility -1.35***(0.81) Networks 1.55**(0.70) Quality of ground water 0.76(0.52) Income from milk -0.00(0.00) Lr Chi Prob 0.00 Pseudo R *** Significant at 10%, ** significant at 5%, * significant at 1%, figures in parentheses are standard deviation Conclusion The present study provides important findings relating to rural-urban migration. Availability of natural resources in the rural areas is found as an important determinant of rural-urban migration. Less availability and low quality of natural resources affect households decision to migrate from rural to urban areas, being an alternative strategy for bettering livelihood. Shortage of farmland in the study area is among the most important factors of labor migration to urban areas because this factor reduces the relative marginal income from labor in farming. Conservation of land resources and consolidation of landholdings can improve livelihood of rural masses thereby declining migration from rural to urban areas. Composition of household members is another important determinant of rural-urban migration. Male members, married male and non-farm income are significantly related with rural-urban migration. Family and social networks also played significant role in rural-urban migration in the study area. Individuals having strong connections at the destination are more probable to migrate in the urban areas to earn livelihood and or to have better health and education facilities compared to rural areas. The networks are important in finding jobs, providing shelter, assisting in migration process to migrants, etc. Provision of quality health and education facilities coupled with employment opportunities in the rural areas could induce little rural-urban migration. 359

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