The Role of Highly Skilled Diaspora and Returnees in India’s Development: Data Collection Strategies and Survey Methods

  • Umesh L. Bharte
Part of the Dynamics of Asian Development book series (DAD)


Research into different aspects of migration has expanded significantly over the last few decades paving the way for dialogue of a more interdisciplinary nature. This has not only resulted in a diversity of migration-related topics but it has also seen migration scholars adhering to a diverse range of methods. Today, we can see how issues related to the return of highly skilled migrants to their countries of origin and the ways in which they can contribute to the development process have become the subject of many studies. Likewise, scholars have been attracted to the study of diasporas and their potential contributions to development. In the case of Indian skilled migration, it has become important to deliberate upon the strategies and the specific methods that are used to assess the role played both by the diaspora and by returnees in home country development. This chapter provides an overview of the methods that were used for carrying out a recent research study on Indian skilled migration. Given the technical nature of this chapter on Method, we have restricted our discussion to the sampling procedure, the tools employed in the study, the operational definition of the target group and the data collection procedure used. Information is also provided on the key sample characteristics in order to supplement the discussion. Three questionnaires were developed for the study which allowed us to observe three sets of highly skilled Indians at the same time, diaspora, returnees and non-migrants, and to compare their perceptions about returning to India after international exposure. In terms of practical application, our hope is that the study will inform policy-making bodies in both the host and the source countries concerned.


Host Country Home Country Destination Country Pilot Survey Indian Student 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The author would like to express his thanks to Dr. Zakaria Siddiqui for his critical comments on an earlier version of this manuscript. Likewise, he would like to acknowledge the various suggestions he received time to time from Dr. Gabriela Tejada and Metka Hercog. The author is also indebted to Professor Binod Khadria, Professor Uttam Bhattacharya and other members of the teams at JNU and IDSK for the fruitful discussions he had with them.


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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Zakir Husain Centre for Educational StudiesSchool of Social Sciences, Jawaharlal Nehru UniversityNew DelhiIndia

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