Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
156 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

An Agent-Based Modelling Approach to Brain Drain (2103.03234v2)

Published 4 Mar 2021 in physics.soc-ph, cs.MA, econ.GN, and q-fin.EC

Abstract: The phenomenon of brain drain, that is the emigration of highly skilled people, has many undesirable effects, particularly for developing countries. In this study, an agent-based model is developed to understand the dynamics of such emigration. We hypothesise that skilled people's emigration decisions are based on several factors including the overall economic and social difference between the home and host countries, people's ability and capacity to obtain good jobs and start a life abroad, and the barriers of moving abroad. Furthermore, the social network of individuals also plays a significant role. The model is validated using qualitative and quantitative pattern matching with real-world observations. Sensitivity and uncertainty analyses are performed in addition to several scenario analyses. Linear and random forest response surface models are created to provide quick predictions on the number of emigrants as well as to understand the effect sizes of individual parameters. Overall, the study provides an abstract model where brain drain dynamics can be explored. Findings from the simulation outputs show that future socioeconomic state of the country is more important than the current state, lack of barriers results in a large number of emigrants, and network effects ensue compounding effects on emigration. Upon further development and customisation, future versions can assist in the decision-making of social policymakers regarding brain drain.

Citations (6)

Summary

We haven't generated a summary for this paper yet.