Return Migration After Brain Drain: A Simulation Approach

The Brain Drain phenomenon is particularly heterogeneous and is characterized by peculiar specifications. It influences the economic fundamentals of both the country of origin and the host one in terms of human capital accumulation. Here, the brain drain is considered from a microeconomic perspective: more precisely we focus on the individual rational decision to return, referring it to the social capital owned by the worker. The presented model compares utility levels to justify agent migration conduct and to simulate several scenarios within a computational environment. In particular, we developed a simulation framework based on two fundamental individual features, i.e. risk aversion and initial expectation, which characterize the dynamics of different agents according to the evolution of their social contacts. Our main result is that, according to the value of risk aversion and initial expectation, the probability of return migration depends on their ratio, with a certain degree of approximation: when risk aversion is much bigger than the initial expectation, the probability of returns is maximal, while, in the opposite case, the probability for the agents to remain abroad is very high. In between, when the two values are comparable, it does exist a broad intertwined region where it is very difficult to draw any analytical forecast.

💡 Research Summary

The paper tackles the phenomenon of brain drain from a micro‑economic perspective, focusing on the individual’s rational decision to return to the country of origin after having migrated abroad. Rather than treating brain drain solely as a macro‑level loss of human capital, the authors model each migrant as an agent who possesses a stock of “social capital” – the strength of ties to family, friends, and professional contacts both at home and in the host country. The agent’s utility at any point in time is a function of three components: (1) the current level of social capital, (2) a penalty proportional to the agent’s risk‑aversion coefficient (ρ) multiplied by the variance of expected future earnings, and (3) an “initial expectation” term (E₀) that captures the migrant’s anticipated income, career prospects, and status when first moving abroad. The expectation term decays over time, reflecting the diminishing optimism as the migrant’s experience unfolds.

The decision rule is simple: at each discrete time step the agent compares the utility of staying abroad with the utility of returning home. If the utility of returning exceeds that of staying, the agent migrates back; otherwise, the agent remains abroad. The dynamics of social capital are modeled probabilistically: while abroad, the agent builds new connections (increasing social capital) with probability p₁ and simultaneously loses ties to the home network (decreasing social capital) with probability p₂. This stochastic evolution captures the realistic fact that migrants’ networks evolve in both directions.

To explore the aggregate implications of these micro‑behaviors, the authors construct a computational simulation. They generate 10,000 synthetic agents, drawing each agent’s risk‑aversion coefficient ρ and initial expectation E₀ from independent uniform distributions on the interval