Predicting Rural Migration in India using Socio-Demographic Information

Project Details

Term: 

2011

Students: 

Akshad Viswanathan, Anjali Kumari, Imran Ali Richa Gupta, Varun Sayal

University: 

ISB

Presentation: 

Report: 

India as a nation has seen a high migration rate in recent years. Over 98 million people migrated from one place to another in 1990s, the highest for any decade since independence according to the 2001 census details. However in 1970s migration was slowing down. The number of migrants during 1991-2001 increased by about 22% over the previous decade an increase since 1951. Apart from women migrating due to marriage, employment is the biggest reason for migration. The number of job seekers among all migrants has increased by 45% over the previous decade. Nearly 14 million people migrated from their place of birth in search of jobs. The overwhelming majority of these-12 million was men.

Migrants have created pressure on others who are in same job market. While freedom to migrate within the country is an enshrined right the uneven development, levels of desperation and other factors have created friction points. Most people migrate because of a combination of push and pull factors. Lack of rural employment, fragmentation of land holdings and declining public investment in agriculture create a crisis for rural Indians. Urban areas and some rural areas with industrial development or high agricultural production offer better prospects for jobs or self-employment.

The above issue led to our study, through which we wanted to understand if migration could be predicted depending on parameters associated with an individual. And if it can be predicted beforehand then it will provide the government and regulatory authorities with a very strong tool. The tool could then be used to identify the reasons of migration and take pro-active measures to ensure that rural Indians do not migrate. It will also enable state and central governments to provide region-wise incentives to rural Indians to check migration and hence prevent excessive pressure on urban cities.

Application Area: